ALBERT

Description: At present, inspection systems process visual data captured by cameras, with deep learning approaches applied to detect defects. Defect detection results usually have an accuracy higher than 94%. Real-life applications, however, are not very common. In this paper, we describe the development of a tire inspection system for the tire industry. We provide methods for processing tire sidewall data obtained from a camera and a laser sensor. The captured data comprise visual and geometric data characterizing the tire surface, providing a real representation of the captured tire sidewall. We use an unfolding process, that is, a polar transform, to further process the camera-obtained data. The principles and automation of the designed polar transform, based on polynomial regression (i.e., supervised learning), are presented. Based on the data from the laser sensor, the detection of abnormalities is performed using an unsupervised clustering method, followed by the classification of defects using the VGG-16 neural network. The inspection system aims to detect trained and untrained abnormalities, namely defects, as opposed to using only supervised learning methods.

Description: Synthetic polypeptides prepared from N-carboxyanhydrides (NCAs) of α-amino acids are useful for elucidating the relationship between the primary structure of natural peptides and their immunogenicity. In this study, complex copolypeptide sequences were prepared using a recently developed technique; specifically, the random copolymerization of l-alanine NCA with NCAs of l-glutamic acid 5-benzylester (Bn-Glu NCA), S-benzyl-cysteine (Bn-Cys NCA), O-benzyl-l-serine (Bn-Ser NCA), and l-phenylalanine (Phe NCA) was performed using N-heterocyclic carbene (NHC) catalysts. The NHC-initiated Ala NCA/Bn-Glu NCA and Ala NCA/Bn-Cys NCA copolymerization reactions achieved 90% conversion within 30 min. The reactivity ratio values estimated using the Kelen and Tüdos method show that poly(Bn-Glu-co-Ala) and poly(Bn-Cys-co-Ala) have random repeating units with rich alternating sequences, whereas poly(Bn-Ser-co-Ala) and poly(Phe-co-Ala) contain a larger proportion of Ala-repeating units than Bn-Ser and Phe in random placement.

Description: For an industry to succeed in a competitive market, it should continuously take care of not only its stakeholders but also its technical efficiency and productivity. In this paper, data envelopment analysis was combined with Malmquist productivity analysis to investigate the pattern of multifactor productivity changes in the European energy industry over the period from 2005–2016. The results showed that the whole industry was technically inefficient and had large potential for improvement. A slight average increase in productivity that was observed over the studied period proved to be sensitive to the financial and economic situation and equally sensitive to technological and efficiency advances. As for efficiency gains, they reflected the nature of the energy industry, implying that they were due to scale efficiencies rather than human resource improvements. Although technological innovation and the optimal scale of production increased productivity, the slow pace at which this occurred and the negative outlook highlighted by the observed trends call for more serious consideration of the future productivity deployment of the European energy industry, particularly in the context of its decarbonisation, diversification, and modernisation.

Description: This paper presents the results of an experimental program aimed at the assessment of the freeze–thaw (F–T) resistance of concrete based on the evaluation of fracture tests accompanied by acoustic emission measurements. Two concretes of similar mechanical characteristics were manufactured for the experiment. The main difference between the C1 and C2 concrete was in the total number of air voids and in the A300 parameter, where both parameters were higher for C1 by about 35% and 52%, respectively. The evaluation of the fracture characteristics was performed on the basis of experimentally recorded load–deflection and load–crack mouth opening displacement diagrams using two different approaches: linear fracture mechanics completed with the effective crack model and the double-K model. The results show that both approaches gave similar results, especially if the nonlinear behavior before the peak load was considered. According to the results, it can be stated that continuous AE measurement is beneficial for the assessment of the extent of concrete deterioration, and it suitably supplements the fracture test evaluation. A comparison of the results of fracture tests with the resonance method and splitting tensile strength test shows that all testing methods led to the same conclusion, i.e., the C1 concrete was more F–T-resistant than C2. However, the fracture test evaluation provided more detailed information about the internal structure deterioration due to the F–T exposure.

Description: The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempts to damage and disrupt the network, often leading to serious consequences. Network attack detection is an active area of research in the community of cybersecurity. In the literature, there are various descriptions of network attack detection systems involving various intelligent-based techniques including machine learning (ML) and deep learning (DL) models. However, although such techniques have proved useful within specific domains, no technique has proved useful in mitigating all kinds of network attacks. This is because some intelligent-based approaches lack essential capabilities that render them reliable systems that are able to confront different types of network attacks. This was the main motivation behind this research, which evaluates contemporary intelligent-based research directions to address the gap that still exists in the field. The main components of any intelligent-based system are the training datasets, the algorithms, and the evaluation metrics; these were the main benchmark criteria used to assess the intelligent-based systems included in this research article. This research provides a rich source of references for scholars seeking to determine their scope of research in this field. Furthermore, although the paper does present a set of suggestions about future inductive directions, it leaves the reader free to derive additional insights about how to develop intelligent-based systems to counter current and future network attacks.

Description: The Y Balance Test (YBT) is a dynamic balance assessment typically used in sports medicine. This work proposes a deep learning approach to automatically score this YBT by estimating the normalized reach distance (NRD) using a wearable sensor to register inertial signals during the movement. This paper evaluates several signal processing techniques to extract relevant information to feed the deep neural network. This evaluation was performed using a state-of-the-art human activity recognition system based on recurrent neural networks (RNNs). This deep neural network includes long short-term memory (LSTM) layers to learn features from time series by modeling temporal patterns and an additional fully connected layer to estimate the NRD (normalized by the leg length). All analyses were carried out using a dataset with YBT assessments from 407 subjects, including young and middle-aged volunteers and athletes from different sports. This dataset allowed developing a global and robust solution for scoring the YBT in a wide range of applications. The experimentation setup considered a 10-fold subject-wise cross-validation using training, validation, and testing subsets. The mean absolute percentage error (MAPE) obtained was 7.88 ± 0.20%. Moreover, this work proposes specific regression systems to estimate the NRD for each direction separately, obtaining an average MAPE of 7.33 ± 0.26%. This deep learning approach was compared to a previous work using dynamic time warping and k-NN algorithms, obtaining a relative MAPE reduction of 10%.

Description: The influence of four naturally occurring mineral additives (zeolite, diatomite, trass and bentonite) on the hydration and properties of cement pastes and mortars was investigated. The materials change the phase composition, heat of hydration (determined by calorimetry) and mechanical properties of composites. After 28 days, the amount of Ca(OH)2 was reduced by up to 23% and up to 35% more C-S-H was formed, as proved by TG measurements. Differences were observed in the kinetics of heat release, especially for 25% of the addition. In the calorimetric curves, an additional exothermic effect is observed, related to the alteration in the hydration of C3A in cement. From the point of view of beneficial influence on mechanical properties of mortars, the additives could be ranked as follows: bentonite 〈 diatomite, zeolite 〈 trass after 2 days and bentonite 〈 diatomite 〈 trass 〈 zeolite after 28 days of curing. The highest compressive strength (58.5 MPa) was observed for the sample with a 10% addition of zeolite. Zeolite, trass, bentonite and diatomite are all pozzolanic materials; however, their activity varies to an extent due to the differences in their specific surface area and the content of the amorphous phase, responsible for the pozzolanic reaction.

Description: Traffic congestion and the occurrence of traffic accidents are problems that can be mitigated by applying cooperative adaptive cruise control (CACC). In this work, we used deep reinforcement learning for CACC and assessed its potential to outperform model-based methods. The trade-off between distance-error minimization and energy consumption minimization whilst still ensuring operational safety was investigated. Alongside a string stability condition, robustness against burst errors in communication also was incorporated, and the effect of preview information was assessed. The controllers were trained using the proximal policy optimization algorithm. A validation by comparison with a model-based controller was performed. The performance of the trained controllers was verified with respect to the mean energy consumption and the root mean squared distance error. In our evaluation scenarios, the learning-based controllers reduced energy consumption in comparison to the model-based controller by 17.9% on average.

Description: In this paper, a robust observer-based control strategy for n-DOF uncertain robot manipulators with fixed-time stability was developed. The novel fixed-time nonsingular sliding mode surface enables control errors to converge to the equilibrium point quickly within fixed time without singularity. The development of the novel fixed-time disturbance observer based on a uniform robust exact differentiator also allows uncertain terms and exterior disturbances to be proactively addressed. The designed observer can accurately approximate uncertain terms within a fixed time and contribute to significant chattering reduction in the traditional sliding mode control. A robust observer-based control strategy was formulated, according to a combination of the fixed-time nonsingular terminal sliding mode control method and the designed observer, to yield global fixed time stability for n-DOF uncertain robot manipulators. The proposed controller proved definitively that it was able to obtain global stabilization in fixed time. The approximation capability of the proposed observer, the convergence of the proposed sliding surface, and the effectiveness of the proposed control strategy in fixed time were fully confirmed by simulation performance on an industrial robot manipulator.

Description: The simple act of walking can occasionally cause ankle sprains. Traditionally, the rehabilitation of a sprained ankle involves physical therapy. Physical therapy is one of the health professions that help regain mobility through manual exercises. Aquatic therapy is one of the most potent water-based anti-inflammatory methods currently employed that increases local blood circulation, decreases pain and swelling, and promotes speedy healing. Several studies have demonstrated that ankle rehabilitation robots have immense potential in patients’ rehabilitation and recovery; however, these robots cannot be used underwater. This paper introduces the design, development, and control of a therapeutic robot incorporating aquatic therapy for ankle rehabilitation. Its primary objective is to design and control a one degree of freedom ankle rehabilitation robot that can be used in water and can recirculate hot water to simultaneously perform physical therapy and aquatic therapy. To conduct this study, an ankle rehabilitation robot was designed, modeled, developed, and controlled. The design and control techniques were evaluated by means of simulation and experimental results.

Description: Community-based rehabilitation (CBR) is a multi-sectorial community strategy for guaranteeing that people with disabilities enjoy the same rights and opportunities as all other community members. CBR is organized in a five-component matrix—namely, health, education, social, livelihood, and empowerment. To measure the effectiveness of CBR, the World Health Organization (WHO) has developed standardized indicators. The objective of the present study is to translate and validate the CBR indicators (CBR-Is), providing preliminary evidence of their use for disability in Italy. After obtaining permission from the WHO, the CBR-Is followed a process of translation and cross-cultural adaptation according to international guidelines. An examination of internal consistency and reliability was than performed. The intra-rater reliability was estimated using the Intraclass Correlation Coefficient with a 95% confidence interval. In order to measures the differences between people with and without disabilities, an independent sample t-test was used for quantitative indicators. The Italian version of the CBR-Is (IT-CBR-Is) was administered to 234 people. The internal consistency showed a good value, with a Cronbach’s alpha coefficient of 0.862, and the intra-rater reliability analysis showed solid values for each domain (range: 0.723–0.882). Statistically significant differences between people with and without disabilities were found for each domain of the CBR matrix—namely, health, social, education, livelihood, and empowerment. The IT-CBR-Is are consistent and reliable measures when used to investigate disability in a community-based inclusive development perspective. National stakeholders can now have specific indicators to implement services and actions for people with disabilities.

Description: Strong evidence from studies on primates and rodents shows that changes in pupil diameter may reflect neural activity in the locus coeruleus (LC). Pupillometry is the only available non-invasive technique that could be used as a reliable and easily accessible real-time biomarker of changes in the in vivo activity of the LC. However, the application of pupillometry to preclinical research in rodents is not yet fully standardized. A lack of consensus on the technical specifications of some of the components used for image recording or positioning of the animal and cameras have been recorded in recent scientific literature. In this study, a novel pupillometry system to indirectly assess, in real-time, the function of the LC in anesthetized rodents is presented. The system comprises a deep learning SOLOv2 instance-based fast segmentation framework and a platform designed to place the experimental subject, the video cameras for data acquisition, and the light source. The performance of the proposed setup was assessed and compared to other baseline methods using a validation and an external test set. In the latter, the calculated intersection over the union was 0.93 and the mean absolute percentage error was 1.89% for the selected method. The Bland–Altman analysis depicted an excellent agreement. The results confirmed a high accuracy that makes the system suitable for real-time pupil size tracking, regardless of the pupil’s size, light intensity, or any features typical of the recording process in sedated mice. The framework could be used in any neurophysiological study with sedated or fixed-head animals.

Description: Smoke-free pregnancies have long-term health benefits for mothers and babies. This paper quantitatively examines factors associated with smoke-free pregnancies among Aboriginal and Torres Strait Islander women (hereafter Aboriginal women) and qualitatively explores their smoking cessation (SC) experiences during pregnancy. An Aboriginal-led online cross-sectional study on SC was conducted with Aboriginal women and in partnership with Aboriginal communities, between July and October 2020. The present analysis includes participants who made a pregnancy-related quit attempt (N = 103). Chi-squared tests, logistic regression models, and thematic analysis of free-form text responses were performed. The adjusted odds of having smoke-free pregnancies were 4.54 times higher among participants who used Aboriginal Health Services (AHS) (AOR = 4.54, p-value 0.018). Participants living in urban settings had 67% lower odds of having smoke-free pregnancies compared to their regional/remote counterparts (AOR = 0.33, p-value 0.020). Qualitative data revealed strong motivations to reduce tobacco-related harms to the fetus and variability in quitting experiences at different stages of and across pregnancies. Smoking cessation care (SCC) can support Aboriginal women meaningfully if their quitting experiences are considered in SCC development and implementation. Consistent funding for AHS-led SCC is needed to garner health benefits for Aboriginal peoples. More research into urban versus regional/remote differences in maternal SC is recommended.

Description: During the last few years, attention has overwhelmingly focused on the integrated management of urban services and the demand of customers for locally-based supply. The rapid growth in developing smart measuring devices has made the underlying systems more observable and controllable. This exclusive feature has led the system designers to pursue the implementation of complex protocols to provide faster services based on data exchanges. On the other hand, the demands of consumers for locally-based supply could cause a disjunction and islanding behavior that demands to be dealt with by precise action. At first, keeping a centralization scheme was the main priority. However, the advent of distributed systems opened up new solutions. The operation of distributed systems requires the implementation of strong communication links to boost the existing infrastructure via smart control and supervision, which requires a foundation and effective investigations. Hence, necessary actions need to be taken to frustrate any disruptive penetrations into the system while simultaneously benefiting from the advantages of the proposed smart platform. This research addresses the detection of false data injection attacks (FDIA) in energy hub systems. Initially, a multi-hub system both in the presence of a microgrid (the interconnected smart energy hub-based microgrid system) and without it has been modeled for energy management in a way that allows them to cooperate toward providing energy with each other. Afterward, an FDIA is separately exerted to all three parts of the energy carrier including the thermal, water, and electric systems. In the absence of FDIA detection, the impact of FDIA is thoroughly illustrated on energy management, which considerably contributes to non-optimal operation. In the same vein, the intelligent priority selection based reinforcement learning (IPS-RL) method is proposed for FDIA detection. In order to model the uncertainty effects, the unscented transformation (UT) is applied in a stochastic framework. The results on the IEEE standard test system validate the system’s performance.

Description: Two of the main problems encountered in flexible pavements are the stripping of coarse aggregates and the formation of rut depth due to increases in the volume of road traffic and heavy vehicle loads, especially in areas where speeds are low. The existence of rut depth also affects the comfort and safety of road users due to the water accumulation on the pavement surface and reducing tire/pavement friction, which can lead to hydroplaning phenomena. In this research, it was proven that the use of fillers of different origins influences the affinity between aggregates and the binder. The effect of an adhesion promoter in the mix design (such as the amine included in cellulosic fiber pellets) was also studied. Several tests were carried out to determine the binder/aggregate adhesiveness, water sensitivity and resistance to permanent deformation, to evaluate the performance of different blends. It was found that the addition of this additive increased 10% of the aggregate surfaces covered with bitumen when compared with the aggregates without this addition. As expected, the water sensitivity tests showed that the mixture with granitic filler had the lowest indirect tensile strength ratio (ITSR) value (70%), while the mixtures with limestone filler led to the highest percentages (ranging from 83 to 93%). As for the results of the wheel tracking tests (WTT), it was confirmed that the use of limestone filler translates into an improvement in the performance against the permanent deformation of the asphalt mixtures. The mixture with higher bitumen content and adhesion promoter revealed the best average results.

Description: The aim of this study was to compare the surface roughness and gloss of polymer-infiltrated ceramics after simulated in vitro toothbrushing in different storage mediums. Four polymer- infiltrated ceramics were evaluated, Lava ultimate (LU), Vita enamic (EN), Shofu (SH), and Crystal ultra (CU). The control group was a feldspathic ceramic, Vita Mark II (VM). One hundred and twenty specimens (12 × 14 × 2.5 mm) were prepared using a precision saw. For each material (n = 24), the specimens were allocated into two groups, polished and stained. The specimens of each group were stored (for 7 days) in either citric acid (0.2N) or distilled water. Data for surface gloss (ΔE*SCE-SCI) and roughness (Ra) were evaluated before (baseline) and after simulated toothbrushing. For toothbrushing simulation, a toothpaste slurry containing a toothpaste of 100 relative dentin abrasion (RDA) and 0.3 ml distilled water was used for 3650 cycles (7300 strokes) for each specimen. Data were analyzed using t-test and ANOVA. A p-value of ≤ to 0.05 was considered significant. The highest mean value of surface gloss was identified in CU (stained—water) (4.3 (0.47)) (ΔE*) and EN (stained—acid) (4.3 (1.00)) (ΔE*) specimens, whereas the lowest mean value was shown by SH (stained—acid) (2.04 (0.42)) (ΔE*) samples. The highest mean value of surface roughness was observed in SH (0.40 (0.99)) Ra (stained—acid) whereas the lowest in VM (0.13 (0.039)) Ra (polished— water). A significant difference (p 〈 0.05) was observed in surface roughness and gloss between the materials with simulated toothbrushing, except in VM and LU, respectively. Therefore, it can be concluded that simulated toothbrushing impacts on surface roughness and gloss, irrespective of the storage medium.

Description: Recent technological developments have paved the way to the employment of Autonomous Underwater Vehicles (AUVs) for monitoring and exploration activities of marine environments. Traditionally, in information gathering scenarios for monitoring purposes, AUVs follow predefined paths that are not efficient in terms of information content and energy consumption. Informative Path Planning (IPP) represents a valid alternative, defining the path that maximises the gathered information. This work proposes a Genetic Path Planner (GPP), which consists in an IPP strategy based on a Genetic Algorithm, with the aim of generating a path that simultaneously maximises the information gathered and the coverage of the inspected area. The proposed approach has been tested offline for monitoring and inspection applications of Posidonia Oceanica (PO) in three different geographical areas. The a priori knowledge about the presence of PO, in probabilistic terms, has been modelled utilising a Gaussian Process (GP), trained on real marine data. The GP estimate has then been exploited to retrieve an information content of each position in the areas of interest. A comparison with other two IPP approaches has been carried out to assess the performance of the proposed algorithm.

Description: We report that polymerization makes a robust, practically applicable multifunctional optical device with a continuous wavelength tunable over 500 nm spectral range using UV-polymerizable cholesteric liquid crystals (CLCs). It can be used as a circular polarizer generating an extremely high degree of circularly polarized light with |g| = 1.85~2.00. It can also be used for optical notch filters, bandwidth-variable (from ~28 nm to ~93 nm) bandpass filters, mirrors, and intensity-variable beam splitters. Furthermore, this CLC device shows excellent stability owing to the polymerization of CLC cells. Its performance remains constant for a long time (~2 years) after a high-temperature exposure (170 °C for 1 h) and an extremely high laser beam intensity exposure (~143 W/cm2 of CW 532 nm diode laser and ~2.98 MW/cm2 of Nd: YAG pulse laser operation for two hours, respectively). The optical properties of polymerized CLC were theoretically analyzed by Berreman’s 4 × 4 matrix method. The characteristics of this device were significantly improved by introducing an anti-reflection layer on the device. This wavelength-tunable and multifunctional device could dramatically increase optical research efficiency in various spectroscopic works. It could be applied to many instruments using visible and near-infrared wavelengths.

Description: Climate change-related natural disasters, including wildfires and extreme weather events, such as intense storms, floods, and heatwaves, are increasing in frequency and intensity. These events are already profoundly affecting human health in the United States and globally, challenging the ability of communities to prepare, respond, and recover. The purpose of this research was to examine the peer-reviewed literature on community resilience initiatives in one of the most densely populated and economically important regions, the Northeastern United States, and to identify evidence-based interventions and metrics that had been field-tested and evaluated. This paper addresses two critical gaps in the literature: (1) what strategies or interventions have been implemented to build or enhance community resilience against climate change-related natural disasters; and (2) what metrics were used to measure community resilience as an outcome of those strategies or interventions? This review provides a succinct list of effective interventions with specific health outcomes. Community or state-level health officials can use the results to prioritize public health interventions. This review used existing database search tools to discover 205 studies related to community resilience and health outcomes. Methods set criteria to assess if interventions were able to measure and change levels of community resilience to the health impacts associated with a changing climate. Criteria included: (a) alignment with the United States’ National Preparedness Goal for reducing risks to human health and for recovering quickly from disasters; (b) derived from publicly available data sources; (c) developed for use by communities at a local scale; and (d) accessible to modestly resourced municipalities and county health agencies. Five (5) peer-reviewed, evidence-based studies met all of the selection criteria. Three of these articles described intervention frameworks and two reported on the use of standardized tools. Health-related outcomes included mental health impacts (PTSD/depression), mental stress, emergency preparedness knowledge, social capital skills, and emergency planning skills. The paper recommends the COAST project, COPEWELL Rubric for self-assessment, and Ready CDC intervention as examples of strategies that could be adapted by any community engaged in building community resilience.

Description: Education for Sustainable Development (ESD) and Entrepreneurial Education (EE) are quite abstract and demanding concepts for teacher students. Yet, Key Sustainability Competences and Entrepreneurial Competences entail important qualities of future citizens and workers, and teacher students should become prepared to accommodate education for these competencies in their teaching practice. This paper explores teacher students’ process of sense-making of sustainable development and how becoming a teacher who practices ESD connects with entrepreneurship. EE serves as a good mirroring surface to ESD as they both have their roots in Transformative Learning (TL) but pursue transformation towards different goals. The case study follows the vocational teacher education (VTE) students’ sensemaking of Sustainable Development as a part of teacher’s work during one semester which included integrated Thematic Studies of Sustainable Development. The qualitative content analysis of students’ texts focused on signs of transformative learning and was guided by the dimensions of sustainable development and learning goals set for teacher’s sustainability competences in the VTE curriculum. The results indicate that transformative learning is possible. Furthermore, they address the importance of certain entrepreneurial capabilities in the actualization of change agency.

Description: This study aimed to determine the prevalence of high levels of knowledge, positive attitude, and good practice on evidence-based medicine (EBM) and identify the associated factors for practice score on EBM among emergency medicine doctors in Kelantan, Malaysia. This cross-sectional study was conducted in government hospitals in Kelantan. The data were collected from 200 emergency physicians and medical officers in the emergency department using the Noor Evidence-Based Medicine Questionnaire. Simple and general linear regressions analyses using SPSS were performed. A total of 183 responded, making a response rate of 91.5%. Of them, 49.7% had a high level of knowledge, 39.9% had a positive attitude and 2.1% had good practice. Sex, race, the average number of patients seen per day, internet access in workplace, having online quick reference application, and attitude towards EBM were significantly associated with EBM practice scores. It is recommended that appropriate authorities provide emergency doctors with broader access to evidence resources. EBM skill training should be enhanced in the current medical school curriculums.

Description: The Poisson–Boltzmann equation (PBE) arises in various disciplines including biophysics, electrochemistry, and colloid chemistry, leading to the need for efficient and accurate simulations of PBE. However, most of the finite difference/element methods developed so far are rather complicated to implement. In this study, we develop a ResNet-based artificial neural network (ANN) to predict solutions of PBE. Our networks are robust with respect to the locations of charges and shapes of solvent–solute interfaces. To generate train and test sets, we have solved PBE using immersed finite element method (IFEM) proposed in (Kwon, I.; Kwak, D. Y. Discontinuous bubble immersed finite element method for Poisson–Boltzmann equation. Communications in Computational Physics 2019, 25, pp. 928–946). Once the proposed ANNs are trained, one can predict solutions of PBE in almost real time by a simple substitution of information of charges/interfaces into the networks. Thus, our algorithms can be used effectively in various biomolecular simulations including ion-channeling simulations and calculations of diffusion-controlled enzyme reaction rate. The performance of the ANN is reported in the result section. The comparison between IFEM-generated solutions and network-generated solutions shows that root mean squared error are below 5·10−7. Additionally, blow-ups of electrostatic potentials near the singular charge region and abrupt decreases near the interfaces are represented in a reasonable way.

Description: Many studies have found that gold nanoparticles with branched surfaces (nanoflowers) are markers for immunosensors that provide higher sensitivity gains than the commonly used spherical gold nanoparticles. Although the analytical characteristics of nanoparticle-using systems vary significantly depending on their size and shape, the question of choosing the best gold nanoflowers remains open. This work presents a comparative study of a panel of 33 preparations of gold nanoflowers formed by varying several parameters: the size of spherical nanoparticles-nuclei, the concentrations of nuclei, and tetrachloroauric acid during growth. The sizes of the resulting particles, their sorption capacity under antibody immobilization, mobility along membranes for lateral flow assays, and the effects of these parameters on the limits of detection of lateral flow immunoassay are characterized. The optimality of preparations obtained by growing a 0.2% v/v solution of nuclei with a diameter of 10 or 20 nm with tetrachloroauric acid at a concentration of 0.12 mM was shown. With their use, lateral flow immune tests were developed to determine markers of acute myocardial infarction—fatty acids binding protein and troponins I and T. The use of gold nanoflowers obtained under the proposed protocols led to significant gains in the limits of detection—3 to 10 times under visual detection and over 100 times under instrumental detection—compared to spherical gold nanoparticles. The significant increase under instrumental detection is due to the label’s low nonspecific binding.

Description: The aim of this study was to evaluate and compare the sealing ability of two calcium silicate-based sealers (TotalFill BC RRM Fast Set Putty and White ProRoot MTA) when used as apical plugs in immature teeth through nuclear medicine. Single-rooted extracted teeth (n = 34) had their crowns and root tip sectioned to obtain 14 mm long root segments to simulate an in vitro apexification model. Were created two experimental groups, namely MTA (n = 12) and BC (n = 12), and two control groups, PG (positive group, n = 5) and NG (negative group, n = 5). On the 4th day after placing the respective apical plug, the apical portions of the teeth were submerged in a solution of sodium pertechnetate (99mTcNaO4) for 3 h. Statistical analysis showed a significant difference between the MTA group and the controls (p 〈 0.05). The BC group had a significant difference regarding the negative control (p 〈 0.001) but showed no statistical significance regarding the positive control (p = 0.168). There was a statistically significant difference (p = 0.009) between the BC group (7335.8 ± 2755.5) and the MTA group (4059.1 ± 1231.1), where the last showed less infiltration. Within the limitations of this study, White ProRoot MTA had a significantly better sealing ability than TotalFill BC RRM Fast Set Putty.

Description: Enzymatic synthesis of aromatic biobased polyesters is a recent and rapidly expanding research field. However, the direct lipase-catalyzed synthesis of polyesters from ferulic acid has not yet been reported. In this work, various ferulic-based monomers were considered for their capability to undergo CALB-catalyzed polymerization. After conversion into diesters of different lengths, the CALB-catalyzed polymerization of these monomers with 1,4-butanediol resulted in short oligomers with a DPn up to 5. Hydrogenation of the double bond resulted in monomers allowing obtaining polyesters of higher molar masses with DPn up to 58 and Mw up to 33,100 g·mol−1. These polyesters presented good thermal resistance up to 350 °C and Tg up to 7 °C. Reduction of the ferulic-based diesters into diols allowed preserving the double bond and synthesizing polyesters with a DPn up to 19 and Mw up to 15,500 g·mol−1 and higher Tg (up to 21 °C). Thus, this study has shown that the monomer hydrogenation strategy proved to be the most promising route to achieve ferulic-based polyester chains of high DPn. This study also demonstrates for the first time that ferulic-based diols allow the synthesis of high Tg polyesters. Therefore, this is an important first step toward the synthesis of competitive biobased aromatic polyesters by enzymatic catalysis.

Description: In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.

Description: Background: Hemodialysis patients are suffering from depressive symptoms. Brain-derived neurotrophic factor (BDNF) levels are negatively associated with depressive symptoms and decrease during a single hemodialysis session. Resistance training (RT) might be an additional non-pharmacological tool to increase BDNF and promote mental health. Methods: Two randomized groups of hemodialysis patients: control (CTL, n = 76/F36; 66.33 ± 3.88 years) and RT (n = 81/F35; 67.27 ± 3.24 years). RT completed six months of training thrice a week under the supervision of strength and conditioning professional immediately before the dialysis session. Training loads were adjusted using the OMNI rating of perceived exertion. The total antioxidant capacity (TROLOX), glutathione (GSH), thiobarbituric acid reactive substance (TBARS), and BDNF levels were analyzed in serum samples. Quality of life (assessed through Medical Outcomes—SF36), and Beck Depression Inventory was applied. Results: RT improved handgrip strength (21.17 ± 4.38 vs. 27.17 ± 4.34; p = 0.001) but not for CTL (20.09 ± 5.19 vs. 19.75 ± 5.54; p = 0.001). Post-training, RT group had higher values as compared to CTL related to TROLOX (RT,680.8 ± 225.2 vs. CTL,589.5 ± 195.9; p = 0.001) and GSH (RT, 9.33 ± 2.09 vs. CTL,5.00 ± 2.96; p = 0.001). RT group had lower values of TBARS as compared to CTL at post-training (RT, 11.06 ± 2.95 vs. CTL, 13.66 ± 2.62; p = 0.001). BDNF increased for RT (11.66 ± 5.20 vs. 19.60 ± 7.23; p = 0.001), but decreased for CTL (14.40 ± 4.99 vs. 10.84 ± 5.94; p = 0.001). Quality of life and mental health increased (p = 0.001) for RT, but did not change for CTL (p = 0.001). BDNF levels were associated with emotional dimensions of SF36, depressive symptoms, and handgrip (p = 0.001). Conclusions: RT was effective as a non-pharmacological tool to increased BDNF levels, quality of life, temper the redox balance and decrease depressive symptoms intensity in hemodialysis patients.

Description: In this paper, a new methodology for the assessment of the so-called “acoustic capacity” of a road infrastructure is proposed. This aspect is very important in the field of transportation planning as, currently, road infrastructures are verified only in terms of physical capacity; at most, the environmental capacity due to atmospheric pollutants is taken into account, while the acoustic capacity is completely neglected. The acoustic capacity is assessed based on the Harmonoise model, which is widely recognized at the European level. The Harmonoise model, starting from traffic data, such as traffic flows, average speed, and typologies of vehicles, provides the levels of noise emissions and immissions, which can be compared to the noise limit levels established by law. The validity of the proposed methodology was assessed on a test network. The results of this analysis show that, generally, the acoustic capacity is actually a capacity constraint, which involves several traffic flows: this occurs in particular in the case of an intersection, but also in the case of a bi-directional road. Furthermore, the acoustic capacity of a road infrastructure is generally lower than its physical capacity.

Description: Lithium-ion capacitors (LICs) have gained significant attention due to the combination on the advantages of electric double-layer capacitors (EDLCs) and lithium-ion batteries (LIBs). Herein, the LIC pouch cell was fabricated by an activated carbon (AC) cathode and a Li4Ti5O12 (LTO) anode. Two organic electrolytes (1 mol L−1 LiBF4/acetonitrile (AN) and 1 mol L−1 LiPF6/ ethylene carbonate (EC) + ethyl methyl carbonate (EMC) + dimethyl carbonate (DMC)) were chosen and the gas swelling behavior was studied. Compared with the ester-based LIC, the AN-based LIC displays higher energy density of 13.31 Wh kg−1 at 11.4 W kg−1 and even provides a value of 9.1 Wh kg−1 at 1075 W kg−1. Because of the lower DC Resistance of 0.761 mΩ, the maximum power density of the AN-based LIC reaches 12.5 kW kg−1. The AN-based LIC delivers good stability with an energy retention of 88.3% after 900 cycles. It is discovered that the swelling behavior of AN-based LICs is more serious and the major component is H2. The difference of swelling behavior among the LICs, lithium nickel cobalt manganese oxide (NCM)/LTO LIB and AC/AC EDLC is proposed to be caused by the AC electrode and the interfacial reaction of LTO.

Description: In this paper, a dual-polarized four-port 2 × 2 series fed antenna array operating at 28 GHz with beam-switching capability is proposed. The antenna array uses a simple passive beamforming network to switch the main beam. The presented antenna design is suitable for 5G user equipment and high data rates applications by which it has a compact size with low cost and complexity. The size of the antenna is 37.2 × 37.2 mm2 including the ground plane, and it produces 10 different switched beams by using only two simple 3 dB/90∘ couplers which create the required amplitudes and phase excitations for the antenna elements. A one-port simple feeding mechanism including Peregrine PE42525 SPDT switch modules and a power divider is used to generate and measure the 10 switched beams. The antenna design is implemented on a two-layer 0.203 mm thick low-loss (tanδ = 0.0027) Rogers 4003C substrate, and it has a measured 10 dB impedance bandwidth of 4 GHz (14.3%, from 26 GHz to 30 GHz) for all ports. Measured peak isolation between any dual-polarized ports of the antenna is better than 30 dB. The antenna has an average measured realized gain of 8.9 dBi and around 10 dB side lobe level (SLL) for all beams. The antenna has 3-dB coverage of 80∘ to 90∘ in 2D space and it has a maximum of ±26∘ beam-steering angle. The antenna is designed and simulated using Ansys HFSS and fabricated using regular PCB processing.

Description: To respond to global climate change and achieve a “carbon peak” and “carbon neutrality” as soon as possible has become a common goal around the world. Economic growth relies heavily on financial development; indeed, low-carbon economic development is inseparable from financial support. This paper studies the impact of financial development on carbon emission intensity and its mechanism from both theoretical and empirical aspects. Based on the 2005–2018 data on Chinese cities and the Spatial Durbin Model (SDM) research results, this paper finds that: (1) Financial development has significantly reduced China’s carbon emission intensity overall. After considering spatial effects, financial development increases local carbon emission intensity, although it may lead to a more significant decrease in the surrounding area. (2) The analysis of heterogeneity shows that only the financial development in the eastern region has a substantial detrimental impact on total carbon emission intensity and the carbon emission intensity of neighboring cities. The financial development in the central and western regions has no significant effect on carbon emission intensity. (3) The mechanism test shows that financial development mainly reduces carbon emission intensity through technological innovation and structural optimization, with the effect of technological innovation being 9.5%, and the effect of structural optimization being 12.15%. The expansion of the consumption effects of financial development has no significant impact on carbon emission intensity. Accordingly, this article believes that it is necessary to further support financial development, build large-scale financial centers, continue to optimize the structure of financial products, and encourage the development of green finance.

Description: To explore the effects of thermal actions on the pore structural features of granite, scanning electron microscope (SEM) and mercury injection experiments were carried out on granite after thermal treatment (25 °C to 400 °C). The pore structure was investigated from various perspectives, including the capillary pressure curve, the pore–throat ratio, the median saturation pressure, the median pore–throat radius, the porosity, the pore volume, and the pore size distribution. Based on mercury intrusion test data, the Winland model of permeability prediction was modified for a high-temperature tight granite reservoir. The results showed that: (1) As the temperature rose, the mercury injection curve was gradually flattened, and the mercury ejection efficiency gradually increased. Meanwhile, the pore–throat ratio and the median saturation pressure decreased exponentially, and the pore connectivity was enhanced. (2) The median pore–throat radius and the porosity of granite increased exponentially as the temperature increased. Above 200 °C, the median pore–throat radius and the porosity increased substantially. (3) The pore volumes of the transitional pores, mesopores and macropores, and the total pore volume inside the granite, increased as the temperature rose. Especially above 200 °C, the transitional pores and the mesopores were prominently developed, and the pore volumes of the transitional pores and the mesopores took up a significantly greater proportion of the total pore volume. (4) As the temperature rose, the pore size distribution of granite became more extensive, the pore–throat structure was obviously developed, and the pore–throat connectivity was enhanced. (5) The relationship between the micropores’ characteristic parameters and the macro-permeability in engineering was established though a modified Winland model, and the modified Winland model had a better prediction effect. The findings provide a solid basis for rock geothermal mining projects and related geotechnical engineering.

Description: Monitoring physical activity in medical and clinical rehabilitation, in sports environments or as a wellness indicator is helpful to measure, analyze and evaluate physiological parameters involving the correct subject’s movements. Thanks to integrated circuit (IC) technologies, wearable sensors and portable devices have expanded rapidly in monitoring physical activities in sports and tele-rehabilitation. Therefore, sensors and signal acquisition devices became essential in the tele-rehabilitation path to obtain accurate and reliable information by analyzing the acquired physiological signals. In this context, this paper provides a state-of-the-art review of the recent advances in electroencephalogram (EEG), electrocardiogram (ECG) and electromyogram (EMG) signal monitoring systems and sensors that are relevant to the field of tele-rehabilitation and health monitoring. Mostly, we focused our contribution in EMG signals to highlight its importance in rehabilitation context applications. This review focuses on analyzing the implementation of sensors and biomedical applications both in literature than in commerce. Moreover, a final review discussion about the analyzed solutions is also reported at the end of this paper to highlight the advantages of physiological monitoring systems in rehabilitation and individuate future advancements in this direction. The main contributions of this paper are (i) the presentation of interesting works in the biomedical area, mainly focusing on sensors and systems for physical rehabilitation and health monitoring between 2016 and up-to-date, and (ii) the indication of the main types of commercial sensors currently being used for biomedical applications.

Description: The battery storage system (BSS) is one of the key components in many modern power applications, such as in renewable energy systems and electric vehicles. However, charge imbalance among batteries is very common in BSSs, which may impair the power efficiency, reliability, and safety. Hence, various battery equalization methods have been proposed in the literature. Among these techniques, switched-capacitor (SC)-based battery equalizers (BEs) have attracted much attention due to their low cost, small size, and controllability. In this paper, seven types of SC-based BEs are studied, including conventional, double-tiered, modularized, chain structure types I and II, series-parallel, and single SC-based BEs. Mathematical models that describe the charge–discharge behaviors are first derived. Next, a statistical analysis based on MATLAB simulation is carried out to compare the performance of these seven BEs. Finally, a summary of the circuit design complexity, balancing speed, and practical implementation options for these seven topologies is provided.

Description: High energy consumption, rising environmental concerns and depleting fossil fuels demand an increase in clean energy production. The enhanced resiliency, efficiency and reliability offered by microgrids with distributed energy resources (DERs) have shown to be a promising alternative to the conventional grid system. Large-sized commercial customers like institutional complexes have put significant efforts to promote sustainability by establishing renewable energy systems at university campuses. This paper proposes the integration of a photovoltaic (PV) system, energy storage system (ESS) and electric vehicles (EV) at a University campus. An optimal energy management system (EMS) is proposed to optimally dispatch the energy from available energy resources. The problem is mapped in a Linear optimization problem and simulations are carried out in MATLAB. Simulation results showed that the proposed EMS ensures the continuous power supply and decreases the energy consumption cost by nearly 45%. The impact of EV as a storage tool is also observed. EVs acting as a source of energy reduced the energy cost by 45.58% and as a load by 19.33%. The impact on the cost for continuous power supply in case of a power outage is also analyzed.

Description: 3D visual recognition is a prerequisite for most autonomous robotic systems operating in the real world. It empowers robots to perform a variety of tasks, such as tracking, understanding the environment, and human–robot interaction. Autonomous robots equipped with 3D recognition capability can better perform their social roles through supportive task assistance in professional jobs and effective domestic services. For active assistance, social robots must recognize their surroundings, including objects and places to perform the task more efficiently. This article first highlights the value-centric role of social robots in society by presenting recently developed robots and describes their main features. Instigated by the recognition capability of social robots, we present the analysis of data representation methods based on sensor modalities for 3D object and place recognition using deep learning models. In this direction, we delineate the research gaps that need to be addressed, summarize 3D recognition datasets, and present performance comparisons. Finally, a discussion of future research directions concludes the article. This survey is intended to show how recent developments in 3D visual recognition based on sensor modalities using deep-learning-based approaches can lay the groundwork to inspire further research and serves as a guide to those who are interested in vision-based robotics applications.

Description: “Clean water and sanitation” is listed as one of the 17 United Nations’ Sustainable Development Goals and implementing circular economy principles in the water sector has been widely regarded as an important approach in achieving this goal. In the era of Industry 4.0, research and practice in the digitalisation of the water sector to create a smart water system have attracted increasing attention. Despite the growing interest, limited research has been devoted to how digital technologies might enhance circularity. In practice, smart water systems often fail to promote circularity in such aspects as water reuse and resources recovery. This paper aims to identify the main barriers to implementing circularity in the smart water management system in Zhejiang, China. The research adopts a mixed research method that includes a literature review to identify the potential barriers from the existing studies, a case study to determine the most critical barriers in practice, and a fuzzy Delphi method to reach a consensus on the crucial barriers. The research identified 22 main barriers to implementing circular economy in smart water management. The barriers are divided into three categories: infrastructure and economic, technology, and institution and governance. The results show that the barriers related to recycling technologies, digital technology know-how, and the lack of CE awareness raise the most concern. Our findings also indicate that experts are interested in the decentralized wastewater treatment system. This research provides significant insights that practitioners, researchers, and policymakers can use in developing and implementing digital-based CE strategies to reduce water scarcity and pollution.

Description: Magnetic micro- and nanoparticles (MPs)-based composite materials are widely used in various applications in electronics, biotechnology, and medicine. This group of silicone composites have advantageous magnetic and mechanical properties as well as sufficient flexibility and biocompatibility. These composites can be applied in medicine for biological sensing, drug delivery, tissue engineering, and as remote-controlled microrobots operating in vivo. In this work, the properties of polydimethylsiloxane (PDMS)-based composites with different percentages (30 wt.%, 50 wt.%, 70 wt.%) of NdFeB microparticles as a filler were characterized. The novelty of the work was to determine the influence of the percentage of MP content and physiological conditioning on the properties of the PDMS-MP composites after in vitro incubation. An important essence of the work was a comprehensive study of the properties of materials important from the point of view of medical applications. Materials were tested before and after conditioning in 0.9 wt.% NaCl solution at a temperature of 37 °C. Several studies were carried out, including thermal, physicochemical, and rheological tests. The results show that with an increase of the incubation time, most of the measured thermal and physicochemical parameters decreased. The presence of the magnetic filler, especially at a concentration of 70 wt.%, has a positive effect on thermal stability and physicochemical and rheological properties. The performed tests provided important results, which can lead to further research for a broader application of magnetic composites in the biomedical field.

Description: It has been established in literature that the addition of nanoparticles to lubricants at an optimum concentration results in a lower coefficient of friction compared to lubricants with no nanoparticle additives. This review paper shows a comparison of different lubricants based on the COF (coefficient of friction) with nanoadditives. The effect of the addition of nanoparticles on the friction coefficient was analyzed for both synthetic and biolubricants separately. The limitations associated with the use of nanoparticles are explained. The mechanisms responsible for a reduction in friction when nanoparticles are used as an additive are also discussed. Various nanoparticles that have been most widely used in recent years showed good performance within lubricants, including CuO (copper oxide), MoS2 (molybdenum disulfide), and TiO2 (titanium dioxide). The paper also indicates some research gaps that need to be addressed.

Description: E-cigarettes utilize a wide range of flavoring chemicals with respiratory health effects that are not well understood. In this study, we used pulmonary-associated cell lines to assess the in vitro cytotoxic effects of 30 flavoring chemicals. Human bronchial epithelial cells (BEAS-2B) and both naïve and activated macrophages (THP-1) were treated with 10, 100, and 1000 µM of flavoring chemicals and analyzed for changes in viability, cell membrane damage, reactive oxygen species (ROS) production, and inflammatory cytokine release. Viability was unaffected for all chemicals at the 10 and 100 µM concentrations. At 1000 µM, the greatest reductions in viability were seen with decanal, hexanal, nonanal, cinnamaldehyde, eugenol, vanillin, alpha-pinene, and limonene. High amounts of ROS were elicited by vanillin, ethyl maltol, and the diketones (2,3-pentanedione, 2,3-heptanedione, and 2,3-hexanedione) from both cell lines. Naïve THP-1 cells produced significantly elevated levels of IL-1β, IL-8, and TNF-α when exposed to ethyl maltol and hexanal. Activated THP-1 cells released increased IL-1β and TNF-α when exposed to ethyl maltol, but many flavoring chemicals had an apparent suppressive effect on inflammatory cytokines released by activated macrophages, some with varying degrees of accompanying cytotoxicity. The diketones, L-carvone, and linalool suppressed cytokine release in the absence of cytotoxicity. These findings provide insight into lung cell cytotoxicity and inflammatory cytokine release in response to flavorings commonly used in e-cigarettes.

Description: The present paper focuses on the fabrication of coatings based on vinyltrimethoxysilane and the influence of various corrosion media on the coatings produced. Coatings were deposited on two substrate materials, namely, titanium Grade 2 and titanium alloy Ti13Nb13Zr, by immersion in a solution containing vinyltrimethoxysilane, anhydrous ethyl alcohol, acetic acid and distilled water. The obtained coatings were characterized in terms of surface morphology, adhesion to the substrate and corrosion resistance. As corrosion solutions, four different simulated physiological fluids, which differed in the contents of individual ions, and a 1 mol dm−3 NaBr solution were used. The chloride ions contained in the simulated physiological fluids did not lead to pitting corrosion of titanium Grade 2 and titanium alloy Ti13Nb13Zr. This investigation shows that titanium undergoes pitting corrosion in a bromide ion medium. It is demonstrated that the investigated coatings slow down corrosion processes in all corrosion media examined.

Description: Nanoplastics (NPs) are considered emerging pollutants, namely unregulated contaminants whose toxic effect on humans and the environment has been demonstrated or suspected. They are the result of the physical fragmentation of the plastics that over time reach smaller dimensions (

Description: Fiber-reinforced polymer (FRP) matrix materials are quickly being investigated for application in concrete construction repair, reinforcement, and refurbishment. The technology has progressed to the point that its future acceptance is mainly reliant on the availability of established design guidelines based on recognized performance criteria, as well as the cost competitiveness of these technologies in contrast to conventional rehabilitation methods. The goal of this study is to evaluate the different functional grades of adhesives throughout bond length for bonded socket joints of laminated FRP composite pipes. Damage development resistance is high with a functionally graded FRP composite socket joint, as shown. To extend the service life of the structure, the joint designer should use an FRP composite socket joint with a functionally graded adhesive (FGA).

Description: The main objective of this study was to explore the perceptions of LGBTQIA+ students regarding sexual and gender diversity in the university context by (1) identifying conceptions about a being LGBTQIA+ student in the higher education context, (2) researching perceptions of the stigma and discrimination against, and inclusion of LGBTQIA+ students and (3) to recognize discourses and scenarios identified by students in the university context regarding sexual diversity and gender diversity, distinguishing their experiences in the classroom as well as in the university, with their peers and with their professors. This research was based on a quantitative method, the sample consisted of 171 students from the School of Medicine of a public university in the United States in the state of Texas. The results showed that there is currently a greater knowledge of the subject of sexual and gender diversity and of the spaces and resources offered by the university on the subject compared to previous years, however, it is found that knowledge is still limited and that this knowledge may possibly be due to the faculty in which they study.

Description: Due to the clime change scenario, severe hydro-meteorological phenomena are having a high impact on the ecosystems of the earth. Some strategies based on the use of natural communities associated with geomorphological changes that restore the natural landscape are gaining success due the resistance and resilience against damages. All of these strategies are known as nature-based solutions (NBS). Soil and water bioengineering techniques are one of the most appreciated tools to reach effectiveness for slope stabilization. They are based on the capacity of some plants to consolidate the soil with his rooting system in special conditions (high slope, flooding impact). Slope stabilization solutions with soil and water bioengineering techniques need to be adapted to this new scenario. Crib wall is one of the most complete soil and water bioengineering technique for structural slope stabilization. It is based on a wooden box full of live plants that in the future will grow and gain stability at the same time that wood decays. The crib wall box is full of soil, and the front area is traditionally stabilized with some branches of fascines to let plants grow, maintaining the structure. Fascines are made of branches of riparian species with the capacity for vegetative propagation. Their diameter can change due to the humidity variation, so the stiffness of the system is at risk against severe hydro-meteorological phenomena. This study aims to assess that the introduction of HDCL in crib walls improves planting success and makes them more resistant to adverse weather events in Mediterranean areas. Four experiments were performed in controlled and natural conditions with this proposal. The results show that the use of natural fibers instead of branch fascine helps to maintain the humidity conditions and increase the resistance capacity. High-density coir logs (HDCL) are not affected by volume changes for humidity conditions. HDCL maintains the plant’s humidity conditions longer and makes plants grow faster, bigger and increase their survival. This method of Crib wall construction increases the associated biodiversity. The most important results are that the use of HDCL in crib walls has an effect on the growth of planted shrub, the development of roots, the colonization of native vegetation and ultimately, the resistance of the structure to the floods. The results also show that crib walls are a good technique for the stabilization of slopes with considerable gradients and high hydraulic impacts. HDCL can reduce the water stress of plantations, and they can be a good system to retain runoff and provide it to the plants. Finally, the HDCL allows the revegetation of a crib wall 30% faster than with branch fascine.

Description: For the sound field reconstruction of large conical surfaces, current statistical optimal near-field acoustic holography (SONAH) methods have relatively poor applicability and low accuracy. To overcome this problem, conical SONAH based on cylindrical SONAH is proposed in this paper. Firstly, elementary cylindrical waves are transformed into those suitable for the radiated sound field of the conical surface through cylinder-cone coordinates transformation, which forms the matrix of characteristic elementary waves in the conical spatial domain. Secondly, the sound pressure is expressed as the superposition of those characteristic elementary waves, and the superposition coefficients are solved according to the principle of superposition of wave field. Finally, the reconstructed conical pressure is expressed as a linear superposition of the holographic conical pressure. Furthermore, to overcome ill-posed problems, a regularization method combining truncated singular value decomposition (TSVD) and Tikhonov regularization is proposed. Large singular values before the truncation point of TSVD are not processed and remaining small singular values representing high-frequency noise are modified by Tikhonov regularization. Numerical and experimental case studies are carried out to validate the effectiveness of the proposed conical SONAH and the combined regularization method, which can provide reliable evidence for noise monitoring and control of mechanical systems.

Description: Monitoring gait patterns in daily life will provide a lot of biological information related to human health. At present, common gait pressure analysis systems, such as pressure platforms and in-shoe systems, adopt rigid sensors and are wired and uncomfortable. In this paper, a biomimetic porous graphene–SBR (styrene-butadiene rubber) pressure sensor (PGSPS) with high flexibility, sensitivity (1.05 kPa−1), and a wide measuring range (0–150 kPa) is designed and integrated into an insole system to collect, process, transmit, and display plantar pressure data for gait analysis in real-time via a smartphone. The system consists of 16 PGSPSs that were used to analyze different gait signals, including walking, running, and jumping, to verify its daily application range. After comparing the test results with a high-precision digital multimeter, the system is proven to be more portable and suitable for daily use, and the accuracy of the waveform meets the judgment requirements. The system can play an important role in monitoring the safety of the elderly, which is very helpful in today’s society with an increasingly aging population. Furthermore, an intelligent gait diagnosis algorithm can be added to realize a smart gait monitoring system.

Description: Voids in polymer matrix composites are one of the most common manufacturing defects, which may influence the mechanical properties and structural behavior of the final parts made of composites by various manufacturing methods. Therefore, numerous non-destructive testing (NDT) techniques were developed and applied for quality control and in-service testing of such structures. In this paper, the authors analyzed various alternatives to the reference technique, X-ray computed tomography (XCT) NDT, which is used for industrial testing of composite disks having defects in the form of the lower density areas. Different candidates, namely: vibration-based testing, infrared thermography, vibro-thermography, as well as ultrasonic testing were analyzed in terms of their sensitivity and technical feasibility. The quality of the results, the complexity of the testing procedure, time and labor consumption, and the cost of the equipment were analyzed and compared with the reference technique. Based on the conducted research the authors finally proposed a hybrid approach to quality control, using a combination of two NDT techniques–infrared thermography (for initial scanning and detection of near-surface defects) and ultrasonic testing (for a more detailed analysis of products that pass the first testing procedure). It allowed for replacing the costly XCT diagnostics with a much cheaper, but almost equally effective, alternative.

Description: Wine batch distillation in a copper pot still heated directly by combustion is unusual. It is a niche sector. Few studies are available on the subject and even fewer have studied it from a thermal point of view. In a context of ecology awareness and regularly increasing gas taxes, finding less energy consuming and more performing solutions has become necessary. Two methods already exist to recover energy for such pot stills, however improvements could be made. The present study focuses on the heating zone of an experimental pot still. First, a thermal diagnosis based on a nodal model is conducted in transient regime. The major sites of energy expenditure and waste are thus identified and quantified. Results highlight significant losses both in combustion smoke and by conduction to the environment resulting from a limited thermal performance of the system. Proposals are then made to enhance it. For instance, the preheating could be optimized and more thermal waste could be recovered.

Description: Floods are a known natural hazard in Germany, but the amount of precipitation and ensuing high death toll and damages after the events especially from 14 to 15 July 2021 came as a surprise. Almost immediately questions about failure in the early warning chains and the effectiveness of the German response emerged, also internationally. This article presents lessons to learn and argues against a blame culture. The findings are based on comparisons with findings from previous research projects carried out in the Rhein-Erft Kreis and the city of Cologne, as well as on discussions with operational relief forces after the 2021 events. The main disaster aspects of the 2021 flood are related to issuing and understanding warnings, a lack of information and data exchange, unfolding upon a situation of an ongoing pandemic and aggravated further by critical infrastructure failure. Increasing frequencies of flash floods and other extremes due to climate change are just one side of the transformation and challenge, Germany and neighbouring countries are facing. The vulnerability paradox also heavily contributes to it; German society became increasingly vulnerable to failure due to an increased dependency on its infrastructure and emergency system, and the ensuing expectations of the public for a perfect system.

Description: Disposal of municipal solid wastes (MSW) remains a challenge to minimize its impacts on the environment and human health. Landfilling, currently the most common method used for MSW disposal, occupies land space and leads to soil and air emissions. Gasification, an alternative MSW disposal method, can convert waste to energy, but can also lead to soil and air emissions and is a more extensive operation. In this study, life cycle assessments (LCA) of the two disposal methods (landfilling without energy recovery and gasification) were compared to understand impacts on environment and health. The LCA was conducted following the ISO 14040 standards with one ton of MSW as the functional unit. The life cycle inventory was obtained from published journals, technical reports, LandGEM, HELP and GREET database. The impact assessment was done using TRACI 2.1 and categorized into eight groups. The LCA revealed that landfilling is a higher contributor in global warming, acidification, smog formation, eutrophication, ecotoxicity and human health cancer and non-cancer categories. The negative environmental impacts of MSW landfilling can be primarily attributed to the fate of leachate loss and landfill gas, while those of the MSW gasification can be attributed to the disposal of its solid residues.

Description: This article aims to assess how fiscal and financial incentives and government support conditioned the profitability of Portuguese SMEs between 2010 and 2019. The high tax and financial burdens on SMEs have consequences for sustainability and business development. Thus, the study analyzes different incentives provided by the Portuguese government to ease this burden and improve business profitability. The study uses panel data with fixed effects using five different sources of information from five internal tax grant types, three different European Union program financial subventions, and three national budget-specific expenses. The results obtained suggest that tax incentives influence the profitability of SMEs; however, government incentives do not have any impact. The QREN (financial) incentives positively decide the ROA and negatively impact the ROE, contributing to sustainable performance. Portugal 2020 incentives have a weak effect on the first years, improving in the following years. However, the incentive related to R&D is not relevant. This work aims to contribute to decision making for managers, shareholders, and government entities, allowing them to choose those measures that could increase the company’s added value, and for governments, as a tool to select incentives that will most benefit SMEs’’ profitability. This work identifies the key incentives that impact companies’ profitability.

Description: The use of intelligent compaction (IC) in asphalt overlay includes the use of double-drum IC rollers, a roller measurement system, global position system (GPS) radio/receiver/base station, infrared temperature sensors, and an onboard computer reporting system. GPS based mapping and optional feedback control help to overcome the drawbacks associated with conventional compaction such as identifying soft spots, achieving consistent roller patterns, and monitoring asphalt surface temperature and levels of compaction with adequate quality control or quality assurance (QC/QA). Cost-effectiveness of both compaction types was measured in terms of initial and roadway lifecycle cost based on the cost inputs received from South Korea and other published literatures. Roadway lifecycle cost was reported based on the improvement in in-place density, smoothness, and fatigue life. The results of this study showed that: (1) with IC an approximate 4.1% initial cost reduction can be achieved compared to conventional compaction; (2) QC/QA cost is found to have the most significant effect on the higher initial cost of conventional compaction compared to other associated costs whereas intelligent roller cost is the vital cost category for IC; (3) improvement of in-place air voids and density due to the IC has shown that at 97% field density (or at 3% air void content) the State Highway Agency can save approximately 44% over a 20-year service period; and (4) agency cost is observed to be reduced by approximately 62% with the IC method based on the 25-year analysis period due to the increase in fatigue life.

Description: Lane and road marker segmentation is crucial in autonomous driving, and many related methods have been proposed in this field. However, most of them are based on single-frame prediction, which causes unstable results between frames. Some semantic multi-frame segmentation methods produce error accumulation and are not fast enough. Therefore, we propose a deep learning algorithm that takes into account the continuity information of adjacent image frames, including image sequence processing and an end-to-end trainable multi-input single-output network to jointly process the segmentation of lanes and road markers. In order to emphasize the location of the target with high probability in the adjacent frames and to refine the segmentation result of the current frame, we explicitly consider the time consistency between frames, expand the segmentation region of the previous frame, and use the optical flow of the adjacent frames to reverse the past prediction, then use it as an additional input of the network in training and reasoning, thereby improving the network’s attention to the target area of the past frame. We segmented lanes and road markers on the Baidu Apolloscape lanemark segmentation dataset and CULane dataset, and present benchmarks for different networks. The experimental results show that this method accelerates the segmentation speed of video lanes and road markers by 2.5 times, increases accuracy by 1.4%, and reduces temporal consistency by only 2.2% at most.

Description: Gait and physical fitness are related to cognitive function. A decrease in motor function and physical fitness can serve as an indicator of declining global cognitive function in older adults. This study aims to use machine learning (ML) to identify important features of gait and physical fitness to predict a decline in global cognitive function in older adults. A total of three hundred and six participants aged seventy-five years or older were included in the study, and their gait performance at various speeds and physical fitness were evaluated. Eight ML models were applied to data ranked by the p-value (LP) of linear regression and the importance gain (XI) of XGboost. Five optimal features were selected using elastic net on the LP data for men, and twenty optimal features were selected using support vector machine on the XI data for women. Thus, the important features for predicting a potential decline in global cognitive function in older adults were successfully identified herein. The proposed ML approach could inspire future studies on the early detection and prevention of cognitive function decline in older adults.

Description: The present study aimed at assessing the consequences of prolonged exposure to COVID-19 distress on mental health in non-frontline health care workers. For this purpose, we have conducted a survey on 425 Italian dermatologists, in the period February–March 2021. The psychopathological symptoms, depression, anxiety, post-traumatic stress symptoms (PTSD), as well as resilience, have been evaluated. The main factors that influence the physician’s psychological health have been also investigated. Our study showed that the physicians older than 40 years, as well as those who lived this period in company, reported more personal resources, better managing the distress. Resilience, COVID-19 belief, COVID-19 working difficulties, and age were the common predictors of the severe psychopathological symptoms. An interesting result is that the lower level of resilience was the most powerful predictor of a more severe depression, as well as of a higher severity of generalized anxiety disorder, but not of COVID-19 PTSD. The fear of COVID-19 was the most powerful predictor of COVID-19 PTSD. Home conditions and previous SARS-CoV2 infection constituted significant predictors of severe depressive symptoms, but not of anxiety and COVID-19 PTSD. These results are useful in a better understanding of protective and risk factors involved in COVID-19 long-term distress exposure.

Description: In this work, we studied the impacts of transmitting light, nonlinear thermal, and micropolar fluid mechanics on a wire surface coating utilizing non-Newtonian viscoelastic flow. Models with temperature-dependent variable viscosity were used. The boundary layer equations governing the flow and heat transport processes were solved using the Runge–Kutta fourth order method. A distinguished constituent of this study was the use of a porous matrix that acted as an insulator to reduce heat loss. In this paper we discuss the effects of numerous development parameters, including β0, Q, m, Ω, Kp, and Br (non-Newtonian parameter, heat-producing parameter, viscosity parameter, variable viscosity parameter, porosity parameter, and Brinkman number, respectively). Furthermore, the effects of two other parameters, D and M, are also discussed as they relate to velocity and temperature distributions. We observed that the velocity profiles decreased with increasing values of Kp. Fluid velocity increased as the values of M, Br, N, and D increased, while it decreased when the values of Kp, Q and D increased. For increasing values of M, the temperature profile showed increasing behavior, while Br and Q showed decreasing behavior. Furthermore, the present work is validated by comparison with HAM and previously published work, with good results.

Description: In the past few decades, biosensors have been gradually developed for the rapid detection and monitoring of human diseases. Recently, functional nucleic-acid (FNA) biosensors have attracted the attention of scholars due to a series of advantages such as high stability and strong specificity, as well as the significant progress they have made in terms of biomedical applications. However, there are few reports that systematically and comprehensively summarize its working principles, classification and application. In this review, we primarily introduce functional modes of biosensors that combine functional nucleic acids with different signal output modes. In addition, the mechanisms of action of several media of the FNA biosensor are introduced. Finally, the practical application and existing problems of FNA sensors are discussed, and the future development directions and application prospects of functional nucleic acid sensors are prospected.

Description: The application of mathematical analysis has been an essential tool applied on Catenary Anchor Leg Mooring (CALM) buoys, Wave Energy Converters (WEC), point absorber buoys, and various single point mooring (SPM) systems. This enables having mathematical models for bonded marine hoses on SPM systems with application with CALM buoys, which are obviously a requisite for the techno-economic design and operation of these floating structures. Hose models (HM) and mooring models (MM) are utilized on a variety of applications such as SPARs, Semisubmersibles, WECs and CALM buoys. CALM buoys are an application of SPM systems. The goal of this review is to address the subject of marine hoses from mathematical modeling and operational views. To correctly reproduce the behavior of bonded marine hoses, including nonlinear dynamics, and to study their performance, accurate mathematical models are required. The paper gives an overview of the statics and dynamics of offshore/marine hoses. The reviews on marine hose behavior are conducted based on theoretical, numerical, and experimental investigations. The review also covers challenges encountered in hose installation, connection, and hang-off operations. State-of-the-art, developments and recent innovations in mooring applications for SURP (subsea umbilicals, risers, and pipelines) are presented. Finally, this study details the relevant materials that are utilized in hoses and mooring implementations. Some conclusions and recommendations are presented based on this review.

Description: This paper investigates the hybrid source localization problem using differential received signal strength (DRSS) and angle of arrival (AOA) measurements. The main advantage of hybrid measurements is to improve the localization accuracy with respect to a single sensor modality. For sufficiently short wavelengths, AOA sensors can be constructed with size, weight, power and cost (SWAP-C) requirements in mind, making the proposed hybrid DRSS-AOA sensing feasible at a low cost. Firstly the maximum likelihood estimation solution is derived, which is computationally expensive and likely to become unstable for large noise levels. Then a novel closed-form pseudolinear estimation method is developed by incorporating the AOA measurements into a linearized form of DRSS equations. This method eliminates the nuisance parameter associated with linearized DRSS equations, hence improving the estimation performance. The estimation bias arising from the injection of measurement noise into the pseudolinear data matrix is examined. The method of instrumental variables is employed to reduce this bias. As the performance of the resulting weighted instrumental variable (WIV) estimator depends on the correlation between the IV matrix and data matrix, a selected-hybrid-measurement WIV (SHM-WIV) estimator is proposed to maintain a strong correlation. The superior bias and mean-squared error performance of the new SHM-WIV estimator is illustrated with simulation examples.

Description: We present results of Large-eddy simulations (LES) modeling of steady sheet and unsteady cloud cavitation on a two-dimensional hydrofoil which are validated against Particle image velocimetry (PIV) data. The study is performed for the angle of attack of 9° and high Reynolds numbers ReC of the order of 106 providing a strong adverse pressure gradient along the surface. We employ the Schnerr–Sauer and Kunz cavitation models together with the adaptive mesh refinement in critical flow regions where intensive phase transitions occur. Comparison of the LES and visualization results confirms that the flow dynamics is adequately reproduced in the calculations. To correctly match averaged velocity distributions, we propose a new methodology based on conditional averaging of instantaneous velocity fields measured by PIV which only provides information on the liquid phase. This approach leads to an excellent overall agreement between the conditionally averaged fields of the mean velocity and turbulence intensity obtained experimentally and numerically. The benefits of second-order discretization schemes are highlighted as opposed to the lower-order TVD scheme.

Description: Despite its severe adverse effects, such as agranulocytosis, clozapine is the primary treatment for treatment-resistant schizophrenia. The established clozapine monitoring system has contributed to reducing agranulocytosis incidence and mortality rates. However, the pandemic coronavirus disease 2019 (COVID-19) has caused changes in the monitoring system. This review aimed to assess the current evidence on the neutrophil changes in the patient on clozapine treatment and infected with COVID-19. Individual cases reported various absolute neutrophil count (ANC) levels, normal, reduced, or elevated. No agranulocytosis case was reported. One case had a borderline moderate-severe ANC level, but the patient was in the 18-week period of clozapine treatment. A cumulative analysis of case the series initially reported inconclusive results. However, a more recent study with a larger sample size reported a significant reduction in the ANC during COVID-19 infection. Nevertheless, this effect is transient as no significant difference was found between the baseline and the post-infection period in ANC levels. In conclusion, COVID-19 is associated with a temporary reduction in ANC levels. The results supported the recommendation to reduce the frequency of clozapine monitoring in the eligible candidates. However, more data are required to confirm the current findings given the limitations, including study design, sample size, and statistical analysis.

Description: The construction sector is one of the main contributors to greenhouse gas emissions and consumers of energy, making it one of the most relevant sectors when planning reduction strategies and policies. The use of timber in the built environment has been identified as a key strategy to reduce the carbon footprint of the construction sector. In this paper, we use the concept of policy gap analysis to identified underlying challenges in the implementation of timber construction on three Nordic countries, Finland, Norway, and Sweden. We carried out a series of semi-structured interviews with experts from the countries of study. The interviews came from industry, government, and construction companies. The use of the gap analysis approach was useful not only to identify areas that are being targeted but also those areas that were not covered by any programme at the time of study. The results showed that the studied programmes have a large level of coverage and congruence with the identified challenges. Moreover, they also showed that challenges related to fire safety regulations and insurance policies for timber buildings still need to be addressed, whereas the challenges of high price variability and lack of promotion are being addressed by multiple programmes. With this work, we have seen how timber construction is gaining momentum and how the challenges have been addressed systematically.

Description: In the first quarter of 2020, Italy became one of the earliest hotspots of COVID-19 infection, and the government imposed a lockdown. During the lockdown, an online survey of 2053 adults was conducted that asked about health behaviors and about the psychological and overall impact of COVID-19. The present study is a secondary analysis of that data. We hypothesized that self-control, higher socio-economic status, existing health conditions, and fear of infection were all inversely related to actions (or intentions) that violated the lockdown (i.e., infractions). Using partial least squares structural equation modeling (PLS-SEM), we found that only the fear of infection significantly dissuaded people from violating lockdown rules. Since it is not practical or ethical to sow a fear of infection, our study indicates that enacting rules and enforcing them firmly and fairly are important tools for containing the infection. This may become more important as vaccines become more widely available and people lose their fear of infection.

Description: Wastewaters from the olive oil industry are a regional environmental problem. Their phenolic content provides inherent toxicity, which reduces the treatment potential of conventional biological systems. In this study, Sulfate Radical based Advanced Oxidation Processes (SRbAOPs) are compared with advanced oxidation processes (namely Fenton’s peroxidation) as a depuration alternative. Synthetic olive mill wastewaters were submitted to homogeneous and heterogeneous SRbAOPs using iron sulfate and solid catalysts (red mud and Fe-Ce-O) as the source of iron (II). The homogenous process was optimized by testing different pH values, as well as iron and persulfate loads. At the best conditions (pH 5, 300 mg/L of iron and 600 mg/L of persulfate), it was possible to achieve 39%, 63% and 37% COD, phenolic compounds and TOC removal, respectively. The catalytic potential of a waste (red mud) and a laboratory material (Fe-Ce-O) was tested using heterogenous SRbAOPs. The best performance was achieved by Fe-Ce-O, with an optimal load of 1600 mg/L. At these conditions, 27%, 55% and 5% COD, phenolic compounds and TOC removal were obtained, respectively. Toxicity tests on A. fischeri and L. sativum showed no improvements in toxicity from the treated solutions when compared with the original one. Thus, SRbAOPs use a suitable technology for synthetic OMW.

Description: The Internet of Robotic Things (IoRT) has emerged as a promising computing paradigm integrating the cloud/fog/edge computing continuum in the Internet of Things (IoT) to optimize the operations of intelligent robotic agents in factories. A single robot agent at the edge of the network can comprise hundreds of sensors and actuators; thus, the tasks performed by multiple agents can be computationally expensive, which are often possible by offloading the computing tasks to the distant computing resources in the cloud or fog computing layers. In this context, it is of paramount importance to assimilate the performance impact of different system components and parameters in an IoRT infrastructure to provide IoRT system designers with tools to assess the performance of their manufacturing projects at different stages of development. Therefore, we propose in this article a performance evaluation methodology based on the D/M/c/K/FCFS queuing network pattern and present a queuing-network-based performance model for the performance assessment of compatible IoRT systems associated with the edge, fog, and cloud computing paradigms. To find the factors that expose the highest impact on the system performance in practical scenarios, a sensitivity analysis using the Design of Experiments (DoE) was performed on the proposed performance model. On the outputs obtained by the DoE, comprehensive performance analyses were conducted to assimilate the impact of different routing strategies and the variation in the capacity of the system components. The analysis results indicated that the proposed model enables the evaluation of how different configurations of the components of the IoRT architecture impact the system performance through different performance metrics of interest including the (i) mean response time, (ii) utilization of components, (iii) number of messages, and (iv) drop rate. This study can help improve the operation and management of IoRT infrastructures associated with the cloud/fog/edge computing continuum in practice.

Description: Ontologies, and especially formal ones, have traditionally been investigated as a means to formalize an application domain so as to carry out automated reasoning on it. The union of the terminological part of an ontology and the corresponding assertional part is known as a Knowledge Graph. On the other hand, database technology has often focused on the optimal organization of data so as to boost efficiency in their storage, management and retrieval. Graph databases are a recent technology specifically focusing on element-driven data browsing rather than on batch processing. While the complementarity and connections between these technologies are patent and intuitive, little exists to bring them to full integration and cooperation. This paper aims at bridging this gap, by proposing an intermediate format that can be easily mapped onto the formal ontology on one hand, so as to allow complex reasoning, and onto the graph database on the other, so as to benefit from efficient data handling.

Description: To address the problem of ever-increasing oily wastewater management, due to its directional liquid transport property, membranes with asymmetric wettability can be effectively used for emulsion separation. This study reports the synthesis of electrospun polymer–clay nanocomposite nanofibers, using co-polyamide polymer (COPA) and halloysite nanotubes (HA) as filler. The influence of clay content on the morphological, thermal and dielectric properties of the polymer composite nanofiber was investigated comprehensively to address the material characteristics of the developed system. The surface structure analysis and contact angle measurements of the electrospun composite nanofibers confirms the change in surface roughness and wettability when the fillers are added to the polymer. The porosity of the composite electrospun nanofiber membrane was found to be 85% with an oil adsorption capacity of 97% and water permeability of 6265 L/m2 h. Furthermore, the asymmetric wettability-driven oil/water emulsion separation abilities of the as-synthesized membranes shows that the separation efficiency of the composite fiber membrane is 10% improved compared to that of the neat fiber membrane, with improved separation time.

Description: This paper presents an adaptive protection scheme (APS) for solving the coordination problem that deals with coordination directional overcurrent relays (DOCRs) and distance relays second zone time, in relation to coordination with DOCRs. The coordination problem becomes more complex with the impact of renewable energy sources (RES) when added to the distribution grid. This leads to a change in the grid topology, caused by the on/off states of the distribution generators (DG). The frequency of topological changes in distribution grids poses a challenge to the power system’s protection components. The change in the state of DGs leads to malfunction in reliability and miscoordination between protection relays, since that causes a direct effect to the short circuit currents. This paper used the school-based optimization (SBO) algorithm, which simulates the educational process, in order to deal with coordination problems. That algorithm is modified (MSBO) by modified both learning and teaching processes. The IEEE 8-bus test system and IEEE 14-bus distribution network are used to validate the proposed coordination system’s effectiveness when dealing with the coordination process between distance and DOCRs, at both the near- and far-end in the typical topological grid and with DGs in working order.

Description: There is an increasing interest in properly representing local driving patterns. The most frequent alternative to describe driving patterns is through a representative time series of speed, denominated driving cycle (DC). However, the DC duration is an important factor in achieving DC representativeness. Long DCs involve high testing costs, while short DCs tend to increase the uncertainty of the fuel consumption and tailpipe emissions results. There is not a defined methodology to establish the DC duration. This study aims to study the effect of different durations of the DCs on their representativeness. We used data of speed, time, fuel consumption, and emissions obtained by monitoring for two months the regular operation of a fleet of 15 buses running in two flat urban regions with different traffic conditions. Using the micro-trips method, we constructed DCs with a duration of 5, 10, 15, 20, 25, 30, 45, 60, and 120 min for each region. For each duration, we repeated the process 500 times in order to establish the trend and dispersion of the DC characteristic parameters. The results indicate that to obtain driving pattern representativeness, the DCs must last at least 25 min. This duration also guarantees the DC representativeness in terms of energy consumption and tailpipe emissions.

Description: The analysis of the impact of shift work on occupational health still needs further contributions. Therefore, we developed this research with the purpose of assessing the impact of shift work on occupational health indicators, namely burnout, work-engagement, occupational self-efficacy, and mental health functioning (symptoms of depression and anxiety), by comparing workers who did shift work (44.2% of participants) with workers who did not (55.8% of participants). A total of 695 Portuguese professionally active adults between 18 and 73 years of age (Mage = 37.71; SD = 12.64) participated in this study and completed a survey containing a sociodemographic questionnaire and four occupational health measures: The Burnout Assessment Tool, The Work-Engagement questionnaire (UWES), The Occupational Self-Efficacy Questionnaire, and the BSI-18 for mental health symptoms. Results showed statistically significant differences (p 〈 0.05) for all indicators, demonstrating that participants who worked shifts presented lower scores of work-engagement and occupational self-efficacy, and higher scores of burnout, depression, and anxiety when compared to participants who did not work shifts. Linear regressions showed that shift work explained significant but low percentages of anxiety symptoms, low work-engagement, depression symptoms, low occupational self-efficacy, and burnout. We concluded that non-standard working hours (by shifts) are detrimental to employee occupational health, by increasing the risk of anxiety and depression levels, and burnout, and by reducing work-engagement (as a well-being indicator) and occupational self-efficacy perceptions.

Description: The unique role of the zinc (II) cation prompted us to cut a cross-section of the large and complex topic of the stimuli-responsive coordination polymers (CPs). Due to its flexible coordination environment and geometries, easiness of coordination–decoordination equilibria, “optically innocent” ability to “clip” the ligands in emissive architectures, non-toxicity and sustainability, the zinc (II) cation is a good candidate for building supramolecular smart tools. The review summarizes the recent achievements of zinc-based CPs as stimuli-responsive materials able to provide a chromic response. An overview of the past five years has been organised, encompassing 1, 2 and 3D responsive zinc-based CPs; specifically zinc-based metallorganic frameworks and zinc-based nanosized polymeric probes. The most relevant examples were collected following a consequential and progressive approach, referring to the structure–responsiveness relationship, the sensing mechanisms, the analytes and/or parameters detected. Finally, applications of highly bioengineered Zn-CPs for advanced imaging technique have been discussed.

Description: Water Use Efficiency (WUE) is an important indicator of the carbon cycle in the hydrological and ecological system. It is of great significance to study the response of different hydrological processes to climate and to understand ecosystem carbon sink. However, little is known about the effects and mechanisms of precipitation and temperature on the WUE of different hydrological processes. Thus, three kinds of WUEs (GPP/E (eWUE), GPP/Et (tWUE), and GPP/P (pWUE)) are defined for three different hydrological indicators in semi-arid areas in this study in order to reveal the variation pattern of WUEs based on hydrological indicators and their response to climate. We found that in the past 15 years, the seasonal fluctuation of evapotranspiration in arid areas was large, and the spatial difference of WUE of different hydrological processes was obvious. In semi-arid areas, temperature had a significant effect on WUE (about 68–81%). However, precipitation had a lag effect on WUEs, and the negative impact of precipitation has a great influence (about 84–100%). Secondly, the threshold values of precipitation to WUEs (200 or 300 mm) and temperature to WUEs (2 or 7 °C) are also different from previous studies. This study advances our understanding of the influence of different hydrological processes on ecosystem carbon and climate.

Description: The present study reports on the method used to obtain the reliable outcomes for different responses in electric discharge machining (EDM) of metal matrix composites (MMCs). The analytic hierarchy process (AHP), a multiple criteria decision-making technique, was used to achieve the target outcomes. The process parameters were varied to evaluate their effect on the material erosion rate (MER), surface roughness (SR), and residual stresses (σ) following Taguchi’s experimental design. The process parameters, such as the electrode material (Cu, Gr, Cu-Gr), current, pulse duration, and dielectric medium, were selected for the analysis. The residual stresses induced due to the spark pulse temperature gradient between the electrode were of primary concern during machining. The optimum process parameters that affected the responses were selected using AHP to figure out the most suitable conditions for the machining of MMCs.

Description: In the paper, a thermodynamically consistent model of elastic damaged material in the framework of small strain theory is formulated, describing the process of deterioration in quasibrittle materials, concrete in particular. The main goal is to appropriately depict the distinction between material responses in tension and compression. A novel Helmholtz energy and a dissipation potential including three damage parameters are introduced. The Helmholtz function has a continuous first derivative with respect to strain tensor. Based on the assumed functions, the strain–stress relationship, the damage condition, the evolution laws, and the tangent stiffness tensor are derived. The model’s predictions for uniaxial tension, uniaxial compression, uniaxial cyclic compression–tension, and pure shear tests are calculated using Wolfram Mathematica in order to identify the main features of the model and to grasp the physical meaning of an isotropic damage parameter, a tensile damage parameter, and a compressive damage parameter. Their values can be directly bound to changes of secant stiffness and generalized Poisson’s ratio. An interpretation of damage parameters in association with three mechanisms of damage is given. The considered dissipation potential allows a flexible choice of a damage condition. The influence of material parameters included in dissipation function on damage mode interaction is discussed.

Description: The field of autonomous driving vehicles is growing and expanding rapidly. However, the control systems for autonomous driving vehicles still pose challenges, since vehicle speed and steering angle are always subject to strict constraints in vehicle dynamics. The optimal control action for vehicle speed and steering angular velocity can be obtained from the online objective function, subject to the dynamic constraints of the vehicle’s physical limitations, the environmental conditions, and the surrounding obstacles. This paper presents the design of a nonlinear model predictive controller subject to hard and softened constraints. Nonlinear model predictive control subject to softened constraints provides a higher probability of the controller finding the optimal control actions and maintaining system stability. Different parameters of the nonlinear model predictive controller are simulated and analyzed. Results show that nonlinear model predictive control with softened constraints can considerably improve the ability of autonomous driving vehicles to track exactly on different trajectories.

Description: In a complex underwater environment, finding a viable, collision-free path for an autonomous underwater vehicle (AUV) is a challenging task. The purpose of this paper is to establish a safe, real-time, and robust method of collision avoidance that improves the autonomy of AUVs. We propose a method based on active sonar, which utilizes a deep reinforcement learning algorithm to learn the processed sonar information to navigate the AUV in an uncertain environment. We compare the performance of double deep Q-network algorithms with that of a genetic algorithm and deep learning. We propose a line-of-sight guidance method to mitigate abrupt changes in the yaw direction and smooth the heading changes when the AUV switches trajectory. The different experimental results show that the double deep Q-network algorithms ensure excellent collision avoidance performance. The effectiveness of the algorithm proposed in this paper was verified in three environments: random static, mixed static, and complex dynamic. The results show that the proposed algorithm has significant advantages over other algorithms in terms of success rate, collision avoidance performance, and generalization ability. The double deep Q-network algorithm proposed in this paper is superior to the genetic algorithm and deep learning in terms of the running time, total path, performance in avoiding collisions with moving obstacles, and planning time for each step. After the algorithm is trained in a simulated environment, it can still perform online learning according to the information of the environment after deployment and adjust the weight of the network in real-time. These results demonstrate that the proposed approach has significant potential for practical applications.

Description: Performance in wheelchair basketball is determined by capabilities, such as strength and power. The study has two aims: first, to analyze the association between speed and acceleration variables (collected in the bench press (BP) exercise) and the distinct percentages of one-repetition maximum (1RM); second, to analyze the effect of a strength training protocol on wheelchair basketball (WB) players according to their functional impairments. Ten Spanish male WB players volunteered to participate in the study. The players did a pretest and posttest (1RM in bench press) with 6-week muscle strength intervention program. The results showed a high association between the %1RM and the mean propulsive velocity (MPV) and the maximum velocity (Vmax), both in the total of the participants, and in each separate group of athletes. After implementing the strength training program, both the players of the IWBF (International Wheelchair Basketball Federation) 〈 2.5 group and those of IWBF 〉 2.5 group improved their 1RM (p 〈 0.01, ES = 0.20 to 0.23). However, the program produced positive effects at submaximal intensities in the MPV reached with 30, 40, 70, and 80 kg and in time to maximum velocity (TVmax) with 30, 40, and 70 kg (ES = −3.24 to 1.32) only in players with greater functional impairments. The high association between %1RM and MPV and Vmax can allow for determination the %1RM of the WB players in the BP using the MPV and the Vmax. The training program was effective in improving 1RM in both groups, while improvements in submaximal values only occurred in the IWBF 〈 2.5 group.

Description: In this paper, 4,4′-diaminodiphenyl ether and 2,2′-bis (trifluoromethyl)-4,4′-diaminophenyl ether are selected for molecular structure design, and PAI materials are synthesized by acyl chloride method. 2,2′-bis (trifluoromethyl)-4,4′-diaminophenyl ether has the same main chain structure as 4,4′-diaminodiphenyl ether, but the side chain contains two trifluoromethyl groups, which has high fluorine content. PAI terpolymers were prepared by compounding two diamine monomers, and the effects of trifluoromethyl on heat resistance, friction and wear properties, hydrophobic properties and mechanical properties of PAI materials were studied. The results showed that with the increase of trifluoromethyl content, the Tg of PAI material first increased and then changed little, and the Td5% would decrease and the tensile properties would also decrease. The wear mechanism of PAI varied with the content of trifluoromethyl. With the increase of the amount of fluorinated diamine monomer, the adhesive wear degree of PAI materials gradually increased, and reached the maximum when the molar ratio of the two monomers was 5:5, and then decreased gradually. Different trifluoromethyl content had little effect on friction coefficient, and the friction coefficient increased slightly when the molar ratio of 4,4′-diaminodiphenyl ether to 2,2′-bis (trifluoromethyl)-4,4′-diaminophenyl ether is 1:9. With the increase of trifluoromethyl content, the wear of PAI material would increase. With the increase of the amount of trifluoromethyl, the water absorption of PAI material decreased and the water contact angle increased, which indicated that the hydrophobic property of PAI material was improved. To sum up, the results of this study showed that the introduction of trifluoromethyl into the side chain provided an effective way to prepare PAI materials with low water absorption. Considering the comprehensive properties such as heat resistance, friction and wear, tensile properties, etc., the appropriate addition amount is 10–30%.

Description: In early 2020, the COVID-19 pandemic revealed a faceless, non-adversarial threat that endangered Israelis and Palestinians with the same ferocity. However, the capacities of the health systems to address it were not equal, with Israel more equipped for the outbreak with infrastructure, resources, manpower and later, vaccines. The pandemic demonstrated the life-saving benefits of cooperation and the self-defeating harms brought by non-cooperation. These trends are explored here by an international team of public health and environmental scholars, including those from different sides of the Israeli–Palestinian conflict. This article explores the importance of recognizing the Israeli and Palestinian jurisdictions as a single epidemiological unit, and illustrates how doing so is a pragmatic positioning that can serve self-interest. We demonstrate how despite political shocks precipitating non-cooperation, there has been a recurrent tendency towards limited cooperation. The paper concludes with lessons over the need for reframing public health as a potential bridge, the need for structural changes creating sustainable platforms for accelerated transboundary cooperation to enable the steady management of current and future public and environmental health crises regardless of dynamic political crises, and the importance of civil society and international organizations in forging collaboration in advance of governmental engagement.

Description: A critical assessment has been performed to determine the stacking fault energy (SFE) of the austenite phase in high manganese steels using X-ray diffraction (XRD). It was found that the SFE varies substantially with the chosen elastic constants. This strong dependence induces substantial errors in the estimated values of the SFE of the austenite and, thus, the mechanical behavior of Fe-Mn-Al-C steels. The SFE of three different Fe-Mn-Al-C alloys with varying aluminum (Al) content was determined in order to establish the main plastic deformation mechanism. The aim of this work is to establish a more straightforward and reliable methodology to calculate the SFE by XRD. In this effort, it was determined that uncertainty in the elastic constants can generate errors in up to 37% of the SFE. Moreover, in the studied case, for average of elastic constant values, the predominant deformation mechanism is defined, but when considering one set of constants, these can present uncertainty of 2.7 mJ/m2 and 4.4 mJ/m2 for alloys of 0% Al and 3% Al, respectively. This would lead them to be within the following plastic deformation mechanism, while for 8% Al the uncertainty is negligible.

Description: Wave energy has great prospect among many forms of marine renewable energy for its high density and storage. This paper proposes an underwater direct drive wave energy converter (UDDWEC), which is composed of a submerged point absorbing buoy and a linear-rotating axial flux permanent magnetic generator (LR-AFPMG). In addition, a maximum energy capture control strategy, resonance control, is derived for UDDWEC, based on small amplitude oscillation and hydrodynamic analysis. The proposed control strategy assumes the availability of sea condition such as wave height and period. This control strategy has three main characteristics. Firstly, this control strategy is derived based on hydrodynamic analysis of the submerged point absorber. Added mass, radiation damping and other hydrodynamic parameters are obtained to participate in UDDWEC dynamic model. Secondly, a LR-AFPMG is applied as power take-off device to realize energy conversion, which can improve the power density. Thirdly, small amplitude oscillation can be changed into long stroke rotary motion through the LR-AFPMG. The reliability and effectiveness of the proposed control strategy are assessed at various operation conditions for a heaving system and the validity for the UDDWEC is verified.

Description: Feature Pyramid Network (FPN) is used as the neck of current popular object detection networks. Research has shown that the structure of FPN has some defects. In addition to the loss of information caused by the reduction of the channel number, the features scale of different levels are also different, and the corresponding information at different abstract levels are also different, resulting in a semantic gap between each level. We call the semantic gap level imbalance. Correlation convolution is a way to alleviate the imbalance between adjacent layers; however, how to alleviate imbalance between all levels is another problem. In this article, we propose a new simple but effective network structure called Scale-Equalizing Feature Pyramid Network (SEFPN), which generates multiple features of different scales by iteratively fusing the features of each level. SEFPN improves the overall performance of the network by balancing the semantic representation of each layer of features. The experimental results on the MS-COCO2017 dataset show that the integration of SEFPN as a standalone module into the one-stage network can further improve the performance of the detector, by ∼1AP, and improve the detection performance of Faster R-CNN, a typical two-stage network, especially for large object detection APL∼2AP.

Description: The exposure to extreme temperatures in workplaces involves physical hazards for workers. A poorly acclimated worker may have lower performance and vigilance and therefore may be more exposed to accidents and injuries. Due to the incompatibility of the existing standards implemented in some workplaces and the lack of thermoregulation in many types of protective equipment that are commonly fabricated using various types of polymeric materials, thermal stress remains one of the most frequent physical hazards in many work sectors. However, many of these problems can be overcome with the use of smart textile technologies that enable intelligent thermoregulation in personal protective equipment. Being based on conductive and functional polymeric materials, smart textiles can detect many external stimuli and react to them. Interconnected sensors and actuators that interact and react to existing risks can provide the wearer with increased safety, protection, and comfort. Thus, the skills of smart protective equipment can contribute to the reduction of errors and the number and severity of accidents in the workplace and thus promote improved performance, efficiency, and productivity. This review provides an overview and opinions of authors on the current state of knowledge on these types of technologies by reviewing and discussing the state of the art of commercially available systems and the advances made in previous research works.

Description: This paper is focused on the analysis of unfairness of random media access in Local Operating Networks (LON), which is one of the commercial platforms of the Industrial Internet of Things (IIoT). The unfairness in accessing the LON channel is introduced by a collision avoidance mechanism in the predictive p-persistent CSMA protocol adopted at the media access control layer. The study on the bandwidth share in predictive p-persistent CSMA calls for the analysis of multiple memoryless backoff. In this paper, it is shown that the channel access in LON systems is unfair in the short term for medium traffic load conditions, and in the long term for heavy loaded networks. Furthermore, it is explained that the average bandwidth allocated to a particular node is determined implicitly by the load scenario, while an actual node bandwidth fluctuates in time according to stochastic dynamics of the predictive p-persistent CSMA. Next, it is formally proven that the average bandwidth available to a node is a linear function of its backoff state and does not depend on backoff states of the other stations. Finally, it is demonstrated that possibly unfair bandwidth share in LON networks determined implicitly by load scenario is stable because, with lowering a fraction of actual network bandwidth accessible by a given station, the probability to decrease it in the future also drops.

Description: Copolymers based on 4,4′-dihydroxydiphenyl, phenolphthalein and 4,4′-dichlorodiphenyl sulfone were synthesized by the method of high temperature polycondensation. The structure of the synthesized copolymers was confirmed by IR spectroscopy. Their physical, mechanical and thermal properties were investigated. It is shown that increases in the content of carded fragments lead to higher glass transition temperatures and heat resistance of the copolymers, as well as higher elastic and strength properties.

Description: In the past few decades, ZrN thin films have been identified as wear resistant coatings for tribological applications. The mechanical and tribological properties of ZrN thin layers depend on internal stress induced by the adopted deposition techniques and deposition parameters such as pressure, temperature, and growth rate. In sputtering deposition processes, the selected target voltage waveform and the plasma characteristics also play a crucial influence on physical properties of produced coatings. In present work, ZrN thin films, obtained setting different values of duty cycle in a reactive bipolar pulsed dual magnetron sputtering plant, were investigated to evaluate their residual stress through the substrate curvature method. A considerable progressive increase of residual stress values was measured at decreasing duty cycle, attesting the significant role of voltage waveform in stress development. An evident correlation was also highlighted between the values of the duty cycle and those of wear factor. The performed analysis attested an advantageous effect of internal stress, having the samples with high compressive stress, higher wear resistance. A downward trend for wear rate with the increase of internal residual stress was observed. The choice of suitable values of duty cycle allowed to produce ceramic coatings with improved tribological performance.

Description: With a growing global population and energy demand, there is increasing concern about the world’s reliance on fossil fuels, which have a negative impact on the climate, necessitating the immediate transition to a cleaner energy resource. This effort can be initiated in the rural areas of developing countries for a sustainable, efficient and affordable energy source. This study evaluated four types of renewable energy (solar, wind, biomass, and mini-hydro energy) using the integrated Life Cycle Assessment (LCA) and Analytical Hierarchy Process (AHP) approaches to select the best renewable energy source in Tatau, Sarawak. The criteria under consideration in this study included the environment, engineering and economics. The LCA was used to assess the environmental impact of renewable energies from gate-to-grave boundaries based on 50 MJ/day of electricity generation. The AHP results showed that solar energy received the highest score of 0.299 in terms of the evaluated criteria, followed by mini-hydro, biomass and wind energy, which received scores of 0.271, 0.230 and 0.200, respectively. These findings can be used to develop a systematic procedure for determining the best form of renewable energy for rural areas. This approach could be vital for the authorities that are responsible for breaking down multi-perspective criteria for future decision making in the transition into renewable energy.

Description: Cholera remains a heavy burden worldwide, especially in Sub-Saharan African countries, which account for the majority of the reported cases on the continent. In this study, a 27-year retrospective analysis of cholera epidemics in Guinea-Bissau was performed in order to highlight major stressors fueling the trigger and dissemination of the disease. Although the role of environmental factors did not always have the same degree of importance for the onset of epidemics, a cholera seasonal pattern was clearly perceived, with most of the reported cases occurring during the wet season. The generated theoretical hypothesis indicated rainfall above climatological average, associated with a lack of WASH (water, sanitation and hygiene) infrastructure, and the occurrence of concomitant epidemics in neighboring countries as the key indicators for optimal conditions for cholera to thrive in Guinea-Bissau. Warmer air temperature, the increase in sea surface temperature, and the decrease in salinity in the coastal areas may also contribute to the emergence and/or aggravation of cholera events. Prediction of the conditions favorable for cholera growth and identification of risk pathways will allow the timely allocation of resources, and support the development of alert tools and mitigation strategies.

Description: According to the current European scenario, cultural, creative, and community-led policies play an increasingly important role in influencing local resources, systems, and infrastructures management and demand a novel approach in governing, financing, and monitoring urban regeneration processes. Therefore, cities become contexts where cultural and creative practices can be implemented, integrating social cohesion principles based on communities, shared values, and collaborative decision-making approaches, with particular attention to enhancing cultural heritage, mainly unused or underutilised. The purpose of this research is to explore how the Cultural and Creative Cities Monitor (CCCM) methodological framework, developed by the Joint Research Centre of the European Commission, can be integrated at the local scale to assess the impacts of urban regeneration processes in an interactive and dynamic way, through the data emerging from the monitoring of urban regeneration experiences activated with the communities. The paper describes the “Play ReCH (Re-use Cultural Heritage)” approach, that promotes a process of collaboration, gamification, and innovation in cultural heritage reuse, as an opportunity to test how cultural, creative, and community-led urban strategies can support the enhancement of heritage generating enabling environments and culturally vibrant contexts. The Play ReCH approach and the “Hack the City Salerno” mission, activated in the Salerno historic centre (Italy), open the reflection on some relevant issues related to how citizens become makers of cultural and creative cities’ policies, and contribute to evaluating and monitoring their implementation at diverse urban scales. The Play ReCH mission underlines how new evidence suggests declining the CCCM conceptual framework and related urban policies assessment, co-defining suitable community-based indicators.

Description: The traction power supply system of an Electrical Multiple Unit (EMU) often suffers from overvoltage impact. As an important protection device for on-board electrical equipment, the working environment of a roof arrester is worse than that of a power system. In recent years, the explosion failure of the roof arresters of an EMU has occurred from time to time, which seriously endangers the safe operation of high-speed railways. In this paper, the electrical performance test and material micro test of roof arrester in three states of normal, defect, and exploded, are carried out in order to study the internal causes of roof arrester explosion and clarify its deterioration mechanism. Using the DC reference voltage test and leakage current test, the electrical performance differences of normal, defective, and exploded arresters are obtained. By studying the disassembly of an arrester, the appearance characteristics of arrester varistor in three states are obtained. The micro morphology and chemical elements of the varistor are analyzed by Scanning Electron Microscope and Energy Dispersive Spectrometer. The deterioration mechanism of the arrester varistor is then revealed, and preventive measures for the explosion failure of the roof arrester are put forward. The obtained results show that, during the long-term operation of the roof arrester of an EMU, the varistor may be damp, and therefore the aluminum electrode layer and side insulation layer of the varistor may deteriorate. After the deterioration of the aluminum electrode layer, the content of the O element increases, and multiple film structures are formed on the surface. After the deterioration of the side insulating layer, the content of the O element increases, and the surface becomes uneven. Improving the sealing performance requirements of the roof arrester and optimizing the maintenance process can reduce its explosion failure.

Description: This article analyses the role of intermediaries’ engagements to bridge the gaps between research, education and practice in the processes of knowledge production needed for the shift to sustainable agri-food systems. It is based on an immersive study of an intermediary organization in the USA, including comprehensive interviews with the staff of the organization about their professional activities, their career paths, their close and longstanding professional relationships, and their values. Three characteristics of engaged intermediaries are identified, which can be positive add-ons for bridging activities: they consider farmers and scientists as equal contributors to the production of knowledge; they are involved in multiple life-worlds: for instance, being both a farmer and an outreach specialist or scientist; and they are closely associated with movements furthering the development of local and sustainable agri-food systems and an equitable sharing of knowledge. The article addresses topics often neglected in the innovation systems literature: the experience, social relations and political engagement of intermediary actors.

Description: Cooperative driving is an essential component of intelligent transport systems (ITSs). It promises greater safety, reduced accidents, efficient traffic flow, and fuel consumption reduction. Vehicle platooning is a representative service model for ITS. The principal sub-systems of platooning systems for connected and automated vehicles (CAVs) are cooperative adaptive cruise control (CACC) systems and platoon management systems. Based on vehicle state information received through vehicle-to-vehicle (V2V) communication, the CACC system allows platoon vehicles to maintain a narrower safety distance. In addition, the platoon management system using V2V communications allows vehicles to perform platoon maneuvers reliably and accurately. In this paper, we propose a CACC system with a variable time headway and a decentralized platoon join-in-middle maneuver protocol with a trajectory planning system considering the V2V communication delay for CAVs. The platoon join-in-middle maneuver is a challenging research subject as the research must consider the requirement of a more precise management protocol and lateral control for platoon safety and string stability. These CACC systems and protocols are implemented on a simulator for a connected and automated vehicle system, PreScan, and we validated our approach using a realistic control system and V2V communication system provided by PreScan.

Description: This study investigates a precision milling process conducted with the use of conventional end mills and a standard CNC (Computer Numerical Control) machine tool. Milling tests were performed on samples of AZ91D magnesium alloy using TiB2- and TiAlN-coated three-edge end mills measuring 16 mm in diameter. The following technological parameters were made variable: cutting speed, feed per tooth and axial depth of cut. The effects of precision milling were evaluated by analysing the scatter of dimension values obtained in successive tool passes. In addition to that, deviations from the assumed nominal depth as well as obtained ranges of dimension varation were analysed. The study also examined surface quality obtained in the precision milling process, based on the basic surface roughness parameters: Ra, Rz and RSm. Results have confirmed that the use of conventional cutting tools and a standard CNC machine tool makes it possible to manufacture components characterized by relatively small scatter of dimension values and high accuracy classes. Additionally, the results have shown that the type of tool coating and variations of individual technological parameters exert impact on the dimensional accuracy and surface quality obtained.