ALBERT

Description: This paper presents the design of NaviPBx, an ultrasound-navigated prostate cancer biopsy system. NaviPBx is designed to support an affordable and sustainable national healthcare program in Senegal. It uses spatiotemporal navigation and multiparametric transrectal ultrasound to guide biopsies. NaviPBx integrates concepts and methods that have been independently validated previously in clinical feasibility studies and deploys them together in a practical prostate cancer biopsy system. NaviPBx is based entirely on free open-source software and will be shared as a free open-source program with no restriction on its use. NaviPBx is set to be deployed and sustained nationwide through the Senegalese Military Health Service. This paper reports on the results of the design process of NaviPBx. Our approach concentrates on “frugal technology”, intended to be affordable for low–middle income (LMIC) countries. Our project promises the wide-scale application of prostate biopsy and will foster time-efficient development and programmatic implementation of ultrasound-guided diagnostic and therapeutic interventions in Senegal and beyond.

Description: Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data. However, in the practical realm of software development, the software project that needs to be predicted is generally a brand new software project, and there is not enough labeled data to build a defect prediction model; therefore, traditional methods are no longer applicable. Cross-project defect prediction uses the labeled data of the same type of project similar to the target project to build the defect prediction model, so as to solve the problem of data loss in traditional methods. However, the difference in data distribution between the same type of project and the target project reduces the performance of defect prediction. To solve this problem, this paper proposes a cross-project defect prediction method based on manifold feature transformation. This method transforms the original feature space of the project into a manifold space, then reduces the difference in data distribution of the transformed source project and the transformed target project in the manifold space, and finally uses the transformed source project to train a naive Bayes prediction model with better performance. A comparative experiment was carried out using the Relink dataset and the AEEEM dataset. The experimental results show that compared with the benchmark method and several cross-project defect prediction methods, the proposed method effectively reduces the difference in data distribution between the source project and the target project, and obtains a higher F1 value, which is an indicator commonly used to measure the performance of the two-class model.

Description: This paper combines the interval analysis tools with the nonlinear model predictive control (NMPC). The NMPC strategy is formulated based on an uncertain dynamic model expressed as nonlinear ordinary differential equations (ODEs). All the dynamic parameters are identified in a guaranteed way considering the various uncertainties on the embedded sensors and the system’s design. The NMPC problem is solved at each time step using validated simulation and interval analysis methods to compute the optimal and safe control inputs over a finite prediction horizon. This approach considers several constraints which are crucial for the system’s safety and stability, namely the state and the control limits. The proposed controller consists of two steps: filtering and branching procedures enabling to find the input intervals that fulfill the state constraints and ensure the convergence to the reference set. Then, the optimization procedure allows for computing the optimal and punctual control input that must be sent to the system’s actuators for the pendulum stabilization. The validated NMPC capabilities are illustrated through several simulations under the DynIbex library and experiments using an inverted pendulum.

Description: Al2O3 and Al2O3-ZrO2 coatings were deposited on stainless steel using atmospheric plasma spraying. The influence of arc current and zirconia addition on the surface morphology of the coating, phase composition and tribological properties under dry sliding conditions were investigated. The addition of zirconia reduced the surface roughness of the coatings. The X-ray diffraction measurements indicated that the Al2O3 coatings were composed of β-Al2O3, α-Al2O3, and γ-Al2O3 phases. The addition of zirconia led to the formation of tetragonal and monoclinic phases of zirconia in the as-sprayed coatings. The friction coefficients of Al2O3 and Al2O3-ZrO2 coatings were similar and varied in the range of 0.72–0.75. The specific wear rates of the as-sprayed coatings were reduced with the increase of arc current. It was obtained that the wear rates of the Al2O3-ZrO2 coatings were at least three times lower compared to Al2O3 coatings.

Description: Creating a widely excepted model on the measure of intelligence became inevitable due to the existence of an abundance of different intelligent systems. Measuring intelligence would provide feedback for the developers and ultimately lead us to create better artificial systems. In the present paper, we show a solution where learning as a process is examined, aiming to detect pre-written solutions and separate them from the knowledge acquired by the system. In our approach, we examine image recognition software by executing different transformations on objects and detect if the software was resilient to it. A system with the required intelligence is supposed to become resilient to the transformation after experiencing it several times. The method is successfully tested on a simple neural network, which is not able to learn most of the transformations examined. The method can be applied to any image recognition software to test its abstraction capabilities.

Description: In this work, a single-layer TiO2–ZrO2 thin film is deposited on the AISI 316L austenitic stainless steel by the sol–gel process and the dip coating method to improve its corrosion resistance properties. For the sol preparation, titanium isopropoxide and zirconium butoxide are used as the precursors, yttrium acetate hydrate is used for the ZrO2 stabilization, i-propanol as the solvent, nitric acid as the catalyst, acetylacetone as the chelating agent, and the distilled water for the hydrolysis. The deposited films are annealed at 400 °C or 600 °C. Morphology and phase composition of the sol–gel TiO2–ZrO2 films and powders are analyzed by scanning electron microscopy (SEM) equipped with EDX detector and X-ray diffraction (XRD), respectively. The thickness of the sol–gel TiO2–ZrO2 films deposited on the stainless steel is determined by glow discharge optical emission spectrometry (GD-OES). The corrosion behavior of the stainless steel, coated by amorphous films, is evaluated in 3 wt% NaCl and 0.5 mol dm−3 HCl by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. It is found that the sol–gel TiO2–ZrO2 films with the amorphous structure, deposited by the sol–gel process, and calcined at 400 °C significantly enhance the corrosion properties of AISI 316L in both chloride media.

Description: TiAlN coatings with different Al ratios were deposited by the cathodic arc ion plating (AIP) method, and the relationship between solid particle erosion resistance and structural, mechanical properties was investigated by a micro slurry-jet erosion (MSE) test. The crystal structure of TiAlN coating changes depending on the Al ratio. The coating shows a B1 single cubic phase between the Al ratio of 0 and 0.58; above this ratio, formation of a B4 hexagonal phase is observed. The mechanical properties such as hardness and Young’s modulus of the TiAlN coating also depend on the Al ratio and the crystal structure. The erosion rate decreases by increasing the Al ratio up to 0.58, as the coating is a cubic single phase. The TiAlN coating shows the lowest erosion rate at an Al ratio of 0.58. The erosion rate increases drastically as the crystalline phase changes from the B1 cubic to B4 hexagonal phase at the Al ratio of more than 0.58. The change in erosion rate is also discussed in connection with mechanical properties such as erodent particle hardness to coating hardness ratio and coating hardness to Young’s modulus ratio.

Description: The characteristics of bridge pile-group foundation have a significant influence on the dynamic performance of the superstructure. Most of the existing analysis methods for the pile-group foundation impedance take the trait of strong specialty, which cannot be generalized in practical projects. Therefore, a project-oriented numerical solution algorithm is proposed to compute the dynamic impedance of bridge pile-group foundation. Based on the theory of viscous-spring artificial boundary, the derivation and solution of the impedance function are transferred to numerical modeling and harmonic analysis, which can be carried out through the finite element method. By taking a typical pile-group foundation as a case study, the results based on the algorithm are compared with those from existing literature. Moreover, an impact experiment of a real pile-group foundation was implemented, the results of which are also compared with those resulting from the proposed numerical algorithm. Both comparisons show that the proposed numerical algorithm satisfies engineering precision, thus showing good effectiveness in application.

Description: Medical image analysis research requires medical image datasets. Nevertheless, due to various impediments, researchers have been described as “data starved”. We hypothesize that implicit evolving community standards require researchers to use ever-growing datasets. In Phase I of this research, we scanned the MICCAI (Medical Image Computing and Computer-Assisted Intervention) conference proceedings from 2011 to 2018. We identified 907 papers involving human MRI, CT or fMRI datasets and extracted their sizes. The median dataset size had grown by 3–10 times from 2011 to 2018, depending on imaging modality. Statistical analysis revealed exponential growth of the geometric mean dataset size with an annual growth of 21% for MRI, 24% for CT and 31% for fMRI. Thereupon, we had issued a forecast for dataset sizes in MICCAI 2019 well before the conference. In Phase II of this research, we examined the MICCAI 2019 proceedings and analyzed 308 relevant papers. The MICCAI 2019 statistics compare well with the forecast. The revised annual growth rates of the geometric mean dataset size are 27% for MRI, 30% for CT and 32% for fMRI. We predict the respective dataset sizes in the MICCAI 2020 conference (that we have not yet analyzed) and the future MICCAI 2021 conference.

Description: Soil stabilization, through either physical or chemical techniques of coating-cementation development, is a commonly adopted practice in geotechnical and transportation engineering projects used to strengthen soils and mitigate negative geo-environmental impacts. This can be particularly important in enhancing the mechanical properties of soils which are prone to degradation of their response because of freezing and thawing actions. It was attempted in this research study to examine the effect of lime–zeolite stabilization on the behavior of a silt-sized natural soil of low plasticity, by performing standard compaction tests as well as unconfined compressive experiments evaluating the strength of the composite samples. The natural soil mixed with various contents of lime and zeolite partial replacement was subjected to consecutive freezing and thawing cycles. The results from the study showed significant improvement of the mechanical performance of the treated soil when mixed with lime partially replaced with zeolite in terms of strength and durability and, based on scanning electron microscopic images, additional insights were attempted to be obtained on the microstructure of the specimens subjected to temperature changes.

Description: Many smart city and society applications such as smart health (elderly care, medical applications), smart surveillance, sports, and robotics require the recognition of user activities, an important class of problems known as human activity recognition (HAR). Several issues have hindered progress in HAR research, particularly due to the emergence of fog and edge computing, which brings many new opportunities (a low latency, dynamic and real-time decision making, etc.) but comes with its challenges. This paper focuses on addressing two important research gaps in HAR research: (i) improving the HAR prediction accuracy and (ii) managing the frequent changes in the environment and data related to user activities. To address this, we propose an HAR method based on Soft-Voting and Self-Learning (SVSL). SVSL uses two strategies. First, to enhance accuracy, it combines the capabilities of Deep Learning (DL), Generalized Linear Model (GLM), Random Forest (RF), and AdaBoost classifiers using soft-voting. Second, to classify the most challenging data instances, the SVSL method is equipped with a self-training mechanism that generates training data and retrains itself. We investigate the performance of our proposed SVSL method using two publicly available datasets on six human activities related to lying, sitting, and walking positions. The first dataset consists of 562 features and the second dataset consists of five features. The data are collected using the accelerometer and gyroscope smartphone sensors. The results show that the proposed method provides 6.26%, 1.75%, 1.51%, and 4.40% better prediction accuracy (average over the two datasets) compared to GLM, DL, RF, and AdaBoost, respectively. We also analyze and compare the class-wise performance of the SVSL methods with that of DL, GLM, RF, and AdaBoost.

Description: Biomaterial surface modification represents an important approach to obtain a better integration of the material in surrounding tissues. Different techniques are focused on improving cell support as well as avoiding efficiently the development of infections, such as by modifying the biomaterial surface with amine groups (–NH2). Previous studies showed that –NH2 groups could promote cell adhesion and proliferation. Moreover, these chemical functionalities may be used to facilitate the attachment of molecules such as proteins or to endow antimicrobial properties. This mini-review gives an overview of different techniques which have been used to obtain amine-rich coatings such as plasma methods and adsorption of biomolecules. In fact, different plasma treatment methods are commonly used with ammonia gas or by polymerization of precursors such as allylamine, as well as coatings of proteins (for example, collagen) or polymers containing –NH2 groups (for example, polyethyleneimine). Moreover, this mini-review will present the methods used to characterize such coatings and, in particular, quantify the –NH2 groups present on the surface by using dyes or chemical derivatization methods.

Description: The aim of this research project is to analyze support panels that are based on aramid fabrics which are reinforced with polybenzoxazine/urethane (poly(BA-a/PU)) composites and contain multiwalled carbon nanotubes (MWCNTs). Through the measurement of mechanical properties and a series of ballistic-impact tests that used 7.62 × 51 mm2 projectiles (National Institute of Justice (NIJ), level III), the incorporated MWCNTs were found to enhance the energy-absorption (EAbs) property of the composites, improve ballistic performance, and reduce damage. The perforation process and the ballistic limit (V50) of the composite were also studied via numerical simulation, and the calculated damage patterns were correlated with the experimental results. The result indicated hard armor based on polybenzoxazine nanocomposites could completely protect the perforation of a 7.62 × 51 mm2 projectile at impact velocity range of 847 ± 9.1 m/s. The results revealed the potential for using the poly(BA-a/PU) nanocomposites as energy-absorption panels for hard armor.

Description: In this study, a femtosecond laser was used to pretreat the surface of the Al–Li alloy, the surface micromorphology, roughness, contact angle, and surface wettability of which were adjusted by changing the laser scanning speed, and the sample was bonded into a single joint with polyether ether ketone (PEEK) adhesive. The mechanism of the laser surface treatment affecting the bonding strength of the Al–Li alloy was explored through tensile and shear experiments. The results indicated that optimizing the laser surface treatment parameters could change the surface roughness and surface micromorphology of the Al–Li alloy, so as to change its surface free energy and bonding strength. Compared with the untreated sample, the bonding strength of the Al–Li alloy increased by 81%, 95%, 107%, 91%, and 78% under the treatment of laser scanning at 25, 20, 15, 10, and 5 mm/s, respectively. As a whole, femtosecond laser etching of the Al–Li alloy surface had an important influence on its wettability and bonding performance.

Description: Visual Question Generation (VQG) from images is a rising research topic in both fields of natural language processing and computer vision. Although there are some recent efforts towards generating questions from images in the open domain, the VQG task in the medical domain has not been well-studied so far due to the lack of labeled data. In this paper, we introduce a goal-driven VQG approach for radiology images called VQGRaD that generates questions targeting specific image aspects such as modality and abnormality. In particular, we study generating natural language questions based on the visual content of the image and on additional information such as the image caption and the question category. VQGRaD encodes the dense vectors of different inputs into two latent spaces, which allows generating, for a specific question category, relevant questions about the images, with or without their captions. We also explore the impact of domain knowledge incorporation (e.g., medical entities and semantic types) and data augmentation techniques on visual question generation in the medical domain. Experiments performed on the VQA-RAD dataset of clinical visual questions showed that VQGRaD achieves 61.86% BLEU score and outperforms strong baselines. We also performed a blinded human evaluation of the grammaticality, fluency, and relevance of the generated questions. The human evaluation demonstrated the better quality of VQGRaD outputs and showed that incorporating medical entities improves the quality of the generated questions. Using the test data and evaluation process of the ImageCLEF 2020 VQA-Med challenge, we found that relying on the proposed data augmentation technique to generate new training samples by applying different kinds of transformations, can mitigate the lack of data, avoid overfitting, and bring a substantial improvement in medical VQG.

Description: In this paper, we construct novel numerical algorithms to solve the heat or diffusion equation. We start with 105 different leapfrog-hopscotch algorithm combinations and narrow this selection down to five during subsequent tests. We demonstrate the performance of these top five methods in the case of large systems with random parameters and discontinuous initial conditions, by comparing them with other methods. We verify the methods by reproducing an analytical solution using a non-equidistant mesh. Then, we construct a new nontrivial analytical solution containing the Kummer functions for the heat equation with time-dependent coefficients, and also reproduce this solution. The new methods are then applied to the nonlinear Fisher equation. Finally, we analytically prove that the order of accuracy of the methods is two, and present evidence that they are unconditionally stable.

Description: The use of gradient descent training to optimize the performance of a rule-fact network expert system via updating the network’s rule weightings was previously demonstrated. Along with this, four training techniques were proposed: two used a single path for optimization and two use multiple paths. The performance of the single path techniques was previously evaluated under a variety of experimental conditions. The multiple path techniques, when compared, outperformed the single path ones; however, these techniques were not evaluated with different network types, training velocities or training levels. This paper considers the multi-path techniques under a similar variety of experimental conditions to the prior assessment of the single-path techniques and demonstrates their effectiveness under multiple operating conditions.

Description: This study evaluates the effects of gelatin coating enriched with ethanolic propolis extract (PE) at 1%, 2% or 3% (w/v) on the quality parameters of pork meat during storage at 2 °C. Physical (pH, weight loss, color) and chemical parameters (percentage contents of metmyoglobin (MetMb), along with thiobarbituric acid reactive substances (TBARS)) were measured, and microbiological (total aerobic plate count (TAPC)) analysis, as well as consumer evaluation, was carried out every four days during the storage period of twelve days. The results indicated that the proposed treatments affected (p 〈 0.05) the quality characteristics of meat samples. The high prevention of physicochemical alterations and maximum inhibition of microorganisms was obtained for samples stored in gelatin coatings containing 2% and 3% PE. Additionally, despite a slight deterioration in odor on Day 4 in the P3 group, no negative changes in overall acceptability of the P2 and P3 groups compared to uncoated samples were observed. The obtained results indicate a significant role of propolis extract incorporation into gelatin packaging to extend the shelf life of stored pork.

Description: Organic–inorganic nanoparticles, which can improve and modify the mechanical and chemical properties of polymers, have been used as fillers to prepare high-performance hybrid nanocomposite membranes. In this study, we explored whether the incorporation of organic nanofillers (graphene (G), graphene oxide (GO), carbon nanotubes (CNTs), or oxidized carbon nanotubes (CNTOxi)) into polysulfone (PSF) and montmorillonite (MMt)-modified PSF membranes could enhance membrane performance for the removal of heavy metal ions from contaminated solutions. These hybrid membranes were prepared by a phase inversion method using chloroform as the solvent. The surface morphologies of the membranes revealed good dispersibility of the organoclay and carbon nanomaterials in the PSF matrix. The hybrid nanocomposite membranes showed significantly improved thermal stability and mechanical properties as compared to the pristine PSF and PSF/MMt membranes. The adsorption efficiencies of these hybrid adsorptive membranes for Hg(II), Pb(II), Sr(II), Fe(III), Zn(II), Ni(II), Al(III), Co(II), Y(III), and Cr(III) were investigated. The PSF/MMt/CNTOxi and PSF/MMt/GO membranes exhibited the highest adsorption efficiencies. In particular, these adsorptive membranes showed selectivity toward Hg(II), and the Hg(II) extraction percentage was maximized at pH 2. The maximum Hg(II) adsorption capacities of PSF/MMt/CNTOxi and PSF/MMt/GO were 151.36 and 144.89 mg/g, respectively, and the adsorption isotherm was in approval with the Langmuir model. These hybrid nanocomposites can be used in water purification application.

Description: The intricate nature of congenital heart disease requires understanding of the complex, patient-specific three-dimensional dynamic anatomy of the heart, from imaging data such as three-dimensional echocardiography for successful outcomes from surgical and interventional procedures. Conventional clinical systems use flat screens, and therefore, display remains two-dimensional, which undermines the full understanding of the three-dimensional dynamic data. Additionally, the control of three-dimensional visualisation with two-dimensional tools is often difficult, so used only by imaging specialists. In this paper, we describe a virtual reality system for immersive surgery planning using dynamic three-dimensional echocardiography, which enables fast prototyping for visualisation such as volume rendering, multiplanar reformatting, flow visualisation and advanced interaction such as three-dimensional cropping, windowing, measurement, haptic feedback, automatic image orientation and multiuser interactions. The available features were evaluated by imaging and nonimaging clinicians, showing that the virtual reality system can help improve the understanding and communication of three-dimensional echocardiography imaging and potentially benefit congenital heart disease treatment.

Description: Volatile fatty acids obtained from the fermentation of the organic fraction of municipal solid waste can be used as raw materials for non-toxic ethyl ester (EE) synthesis as well as feedstock for the production of polyhydroxyalkanoates (PHAs). Taking advantage of the concept of an integrated process of a bio-refinery, in the present paper, a systematic investigation on the extraction of intracellular poly(3-hydroxybutyrate-co-3-hydroxyvalerate), produced by mixed microbial culture by using EEs was reported. Among the tested EEs, ethyl acetate (EA) was the best solvent, dissolving the copolymer at the lowest temperature. Then, extraction experiments were carried out by EA at different temperatures on two biomass samples containing PHAs with different average molecular weights. The parallel characterization of the extracted and non-extracted PHAs evidenced that at the lower temperature (100 °C) EA solubilizes preferentially the polymer fractions richer in 3HV comonomers and with the lower molecular weight. By increasing the extraction temperature from 100 °C to 125 °C, an increase of recovery from about 50 to 80 wt% and a molecular weight reduction from 48% to 65% was observed. The results highlighted that the extracted polymer purity is always above 90 wt% and that it is possible to choose the proper extraction condition to maximize the recovery yield at the expense of polymer fractionation and degradation at high temperatures or use milder conditions to maintain the original properties of a polymer.

Description: During transmission of digital images, secret messages can be embedded using data hiding techniques. Such techniques can transfer private secrets without drawing the attention of eavesdroppers. To reduce the amount of transmitted data, image compression methods are widely applied. Hiding secret data in compressed images is a hot issue recently. In this paper, we apply the de-clustering concept and the indicator-free search-order coding (IFSOC) technique to hide information into vector quantization (VQ) compressed images. Experimental results show that the proposed two-layer reversible data hiding scheme for IFSOC-encoded VQ index table can hide a large amount of secret data among state-of-the-art methods with a relatively lower bit rate and high security.

Description: We constructed a capacitively coupled plasma (CCP) source and installed various diagnostic tools to perform process diagnosis using a plasma process gas (CxFy). We obtained the energy and mass distributions of the ions and radicals from Ar, C4F8/Ar, and C4F6/Ar plasmas. The energy distribution of the ions incident on the substrate was controlled using the self-bias voltage, and the ion energy was found to be inversely proportional to the mass. The measured species and density of the ions and radicals can help understand plasma process results as they provide information about the ions and radicals incident on the substrate.

Description: In this work, we propose a mechanism for knowledge transfer between Convolutional Neural Networks via the geometric regularization of local features produced by the activations of convolutional layers. We formulate appropriate loss functions, driving a “student” model to adapt such that its local features exhibit similar geometrical characteristics to those of an “instructor” model, at corresponding layers. The investigated functions, inspired by manifold-to-manifold distance measures, are designed to compare the neighboring information inside the feature space of the involved activations without any restrictions in the features’ dimensionality, thus enabling knowledge transfer between different architectures. Experimental evidence demonstrates that the proposed technique is effective in different settings, including knowledge-transfer to smaller models, transfer between different deep architectures and harnessing knowledge from external data, producing models with increased accuracy compared to a typical training. Furthermore, results indicate that the presented method can work synergistically with methods such as knowledge distillation, further increasing the accuracy of the trained models. Finally, experiments on training with limited data show that a combined regularization scheme can achieve the same generalization as a non-regularized training with 50% of the data in the CIFAR-10 classification task.

Description: Genetic algorithms (GA’s) are mostly used as an offline optimisation method to discover a suitable solution to a complex problem prior to implementation. In this paper, we present a different application in which a GA is used to progressively adapt the collective performance of an ad hoc collection of devices that are being integrated post-deployment. Adaptive behaviour in the context of this article refers to two dynamic aspects of the problem: (a) the availability of individual devices as well as the objective functions for the performance of the entire population. We illustrate this concept in a video surveillance scenario in which already installed cameras are being retrofitted with networking capabilities to form a coherent closed-circuit television (CCTV) system. We show that this can be conceived as a multi-objective optimisation problem which can be solved at run-time, with the added benefit that solutions can be refined or modified in response to changing priorities or even unpredictable events such as faults. We present results of a detailed simulation study, the implications of which are being discussed from both a theoretical and practical viewpoint (trade-off between saving computational resources and surveillance coverage).

Description: Plasma electrolytic oxidation (PEO) has attracted increasing attention since the transportation industry adopts more lightweight metal components and requires an improved version of anodizing for surface protection. In response to the demand, researchers enrich the technical connotation of PEO through diversifying the growth paths and adopting new precursors. Foreign electrolyte additives, involving ceramic and polymeric particles, organic dye emulsions, are incorporated to accomplish various goals. On the other hand, significant progress has been made on comprehension of softening sparks; denoting the adverse trend of growing discharge intensity can be re-routed by involving cathodic current. I–V response shows the cathodic pulse current not only cools down the ensuing anodic pulse, but also twists the coating conductivity, and the residuals of twists accumulate over a long time frame, plausibly through oxide protonation. Thus, the cathodic current provides a tool to control the discharge intensity via integration of the coating conductivity deviations. So far, these cathodic current studies have been performed in the electrolytes of KOH and Na2SiO3. When exotic additives are included, for example Cr2O3, the cathodic current effect is also shifted, as manifested in remarkable changes in its current–voltage (I–V) behavior. We anticipate the future study on cathodic current influences of inclusion shall lead to a precise control of micro arc.

Description: Within the context of structure deterioration studies, we propose a new numerical method based on the use of fragility curves. In particular, the present work aims to theoretically study the degradation of concrete bridge structures subjected to aggressive environments. A simple probabilistic method based on fragility curves is presented which allows the forecasting of the lifetime of the considered structural system and the best monitoring time. The method was applied to investigate the degradation of a concrete bridge used as a case study. A Monte Carlo numerical procedure was used to simulate the variation over time of the residual resistant section and the ultimate bending moment of the deck of the case study. Within this context, fragility curves are used as reliable indicators of possible monitoring scenarios. In comparison with other methods, the main advantage of the proposed approach is the small amount of computing time required to obtain rapid assessment of reliability and deterioration level of the considered structure.

Description: In this study, nanosecond-pulse laser is used in combination with cold spraying to form a hybrid solid-state forming technology: nanosecond-pulse laser assisted cold spraying. This method successfully manufactured Al-Cu high-strength aluminum alloy coatings. The nanosecond-pulse laser reduced the porosity of the coatings. The laser-induced micro-texture on the substrate surface had the ability of improving the bonding strength of the coating-substrate interface. The bonding strength was closely related to the depth of the micro-texture. The deeper micro-texture caused an unfused interface on the bottom of the texture, which produced voids and reduced the bonding strength. The nanosecond-pulse lasers can also increase the hardness of the coatings. The assistance of the nanosecond-pulse laser has proved to be an effective method to improve the quality of cold sprayed metal coatings.

Description: Using automotive smartphone applications (apps) provided by car manufacturers may offer numerous advantages to the vehicle owner, including improved safety, fuel efficiency, anytime monitoring of vehicle data, and timely over-the-air delivery of software updates. On the other hand, the continuous tracking of the vehicle data by such apps may also pose a risk to the car owner, if, say, sensitive pieces of information are leaked to third parties or the app is vulnerable to attacks. This work contributes the first to our knowledge full-fledged security assessment of all the official single-vehicle management apps offered by major car manufacturers who operate in Europe. The apps are scrutinised statically with the purpose of not only identifying surfeits, say, in terms of the permissions requested, but also from a vulnerability assessment viewpoint. On top of that, we run each app to identify possible weak security practices in the owner-to-app registration process. The results reveal a multitude of issues, ranging from an over-claim of sensitive permissions and the use of possibly privacy-invasive API calls, to numerous potentially exploitable CWE and CVE-identified weaknesses and vulnerabilities, the, in some cases, excessive employment of third-party trackers, and a number of other flaws related to the use of third-party software libraries, unsanitised input, and weak user password policies, to mention just a few.

Description: Collision between rigid three-dimensional objects is a very common modelling problem in a wide spectrum of scientific disciplines, including Computer Science and Physics. It spans from realistic animation of polyhedral shapes for computer vision to the description of thermodynamic and dynamic properties in simple and complex fluids. For instance, colloidal particles of especially exotic shapes are commonly modelled as hard-core objects, whose collision test is key to correctly determine their phase and aggregation behaviour. In this work, we propose the Oriented Cuboid Sphere Intersection (OCSI) algorithm to detect collisions between prolate or oblate cuboids and spheres. We investigate OCSI’s performance by bench-marking it against a number of algorithms commonly employed in computer graphics and colloidal science: Quick Rejection First (QRI), Quick Rejection Intertwined (QRF) and a vectorized version of the OBB-sphere collision detection algorithm that explicitly uses SIMD Streaming Extension (SSE) intrinsics, here referred to as SSE-intr. We observed that QRI and QRF significantly depend on the specific cuboid anisotropy and sphere radius, while SSE-intr and OCSI maintain their speed independently of the objects’ geometry. While OCSI and SSE-intr, both based on SIMD parallelization, show excellent and very similar performance, the former provides a more accessible coding and user-friendly implementation as it exploits OpenMP directives for automatic vectorization.

Description: This study aimed to measure and compare the shear bond strength (SBS) of a self-adhering flowable resin composite to dentin with a conventional flowable composite, and evaluate the various modes of failure. Thirty human premolar teeth (n = 30) were randomly allocated to two groups (Group I: Vertise™ Flow; Group II: Filtek Ultimate + Single Bond Universal) of 15 specimens each, and SBS was measured for specimens from each group by applying a shear load using a universal testing machine (UTM). Modes of failure were observed with an optical microscope. An independent-samples T-test was performed to test Levene’s assumption of homogeneity of variance across both groups, with the critical value set at 0.05. The results revealed, that the self-adhering flowable composite (Group I: Vertise™ Flow) resulted in a lower shear bond strength compared with the conventional adhesive system composite (Group II: Filtek Ultimate + Single Bond Universal). Moreover, group I predominantly exhibited non-cohesive failure, which reflects poor bonding to dentin. On the other hand, Group II showed mixed failure for most of the samples, which demonstrated strong adhesive bonding. Therefore, it could be concluded that the self-adhering flowable resin composite (Group I) results in lower SBS to dentin compared with a conventional adhesive system.

Description: Research on flexible unit systems (FUS) with the context of descriptive, predictive, and prescriptive analysis have remarkably progressed in recent times, being now reinforced in the current Industry 4.0 era with the increased focus on integration of distributed and digitalized systems. In the existing literature, most of the work focused on the individual contributions of the above mentioned three analyses. Moreover, the current literature is unclear with respect to the integration of degradation and upgradation models for FUS. In this paper, a systematic literature review on degradation, residual life distribution, workload adjustment strategy, upgradation, and predictive maintenance as major performance measures to investigate the performance of the FUS has been considered. In order to identify the key issues and research gaps in the existing literature, the 59 most relevant papers from 2009 to 2020 have been sorted and analyzed. Finally, we identify promising research opportunities that could expand the scope and depth of FUS.

Description: The purpose of this study was to examine the combined effects of milk intake and physical activity on bone mineral density in adolescents. This study was conducted using data from the 2009–2011 Korea National Health and Nutrition Examination Survey (KNHANES), which provided measurements of bone mineral density (BMD) in addition to basic health-related data. This study included 1061 adolescents aged 13 to 18 years (557 males and 504 females) whose data on milk intake and participation time in moderate to vigorous physical activity were available. BMD was measured by dual-energy X-ray absorptiometry (DXA). Milk intake was assessed using the 24-h recall method, and the levels of physical activity were examined using a questionnaire. The physical activity questions of 2009–2011 KNHANES were based on the Korean version of the International Physical Activity Questionnaire (IPAQ) short form. The subjects were classified into four groups according to milk intake and physical activity level: no milk intake + low-level physical activity group (MnoPlow), no milk intake + high-level physical activity group (MnoPhigh), milk intake + low-level physical activity group (MyesPlow), and milk intake + high-level physical activity group (MyesPhigh). The results of partial correlation controlling for age, body mass index (BMI), and energy intake showed that the BMD variables were associated significantly with physical activity in both males and females. Among males, the MnoPlow group had the lowest BMD in all BMD variables, showing a significant difference from the high-level physical activity groups (MnoPhigh, MyesPhigh) by multiple logistic regression analysis. Among females, the MyesPhigh group showed a significantly higher lumbar BMD value than the other groups. The MnoPlow group had approximately 0.3 to 0.5 times lower odds ratio for median or higher BMD values, compared to MyesPhigh group. These results show that milk intake and physical activity have a combined effect on BMD, and suggest that to achieve healthy bone growth, it is important to encourage both moderate to vigorous physical activity and milk intake during adolescence.

Description: Varicocele is an age-related disease with no current medical treatments positively impacting infertility. Toll-like receptor 4 (TLR4) expression is present in normal testis with an involvement in the immunological reactions. The role of peroxisome proliferator-activated receptor-α (PPAR-α), a nuclear receptor, in fertility is still unclear. N-Palmitoylethanolamide (PEA), an emerging nutraceutical compound present in plants and animal foods, is an endogenous PPAR-α agonist with well-demonstrated anti-inflammatory and analgesics characteristics. In this model of mice varicocele, PPAR-α and TLR4 receptors’ roles were investigated through the administration of ultra-micronized PEA (PEA-um). Male wild-type (WT), PPAR-α knockout (KO), and TLR4 KO mice were used. A group underwent sham operation and administration of vehicle or PEA-um (10 mg/kg i.p.) for 21 days. Another group (WT, PPAR-α KO, and TLR4 KO) underwent surgical varicocele and was treated with vehicle or PEA-um (10 mg/kg i.p.) for 21 days. At the end of treatments, all animals were euthanized. Both operated and contralateral testes were processed for histological and morphometric assessment, for PPAR-α, TLR4, occludin, and claudin-11 immunohistochemistry and for PPAR-α, TLR4, transforming growth factor-beta3 (TGF-β3), phospho-extracellular signal-Regulated-Kinase (p-ERK) 1/2, and nucleotide-binding oligomerization domain-like receptor (NLR) family pyrin domain-containing 3 (NLRP3) Western blot analysis. Collectively, our data showed that administration of PEA-um revealed a key role of PPAR-α and TLR4 in varicocele pathophysiology, unmasking new nutraceutical therapeutic targets for future varicocele research and supporting surgical management of male infertility.

Description: The Dynamic Facility Location problem is a generalization of the classic Facility Location problem, in which the distance metric between clients and facilities changes over time. Such metrics that develop as a function of time are usually called "evolving metrics", thus Dynamic Facility Location can be alternatively interpreted as a Facility Location problem in evolving metrics. The objective in this time-dependent variant is to balance the trade-off between optimizing the classic objective function and the stability of the solution, which is modeled by charging a switching cost when a client’s assignment changes from one facility to another. In this paper, we study the online variant of Dynamic Facility Location. We present a randomized O(logm+logn)-competitive algorithm, where m is the number of facilities and n is the number of clients. In the first step, our algorithm produces a fractional solution, in each timestep, to the objective of Dynamic Facility Location involving a regularization function. This step is an adaptation of the generic algorithm proposed by Buchbinder et al. in their work "Competitive Analysis via Regularization." Then, our algorithm rounds the fractional solution of this timestep to an integral one with the use of exponential clocks. We complement our result by proving a lower bound of Ω(m) for deterministic algorithms and lower bound of Ω(logm) for randomized algorithms. To the best of our knowledge, these are the first results for the online variant of the Dynamic Facility Location problem.

Description: We study the algorithmic complexity of solving subtraction games in a fixed dimension with a finite difference set. We prove that there exists a game in this class such that solving the game is EXP-complete and requires time 2Ω(n), where n is the input size. This bound is optimal up to a polynomial speed-up. The results are based on a construction introduced by Larsson and Wästlund. It relates subtraction games and cellular automata.

Description: To date, reinforcement concrete is the main construction material worldwide. As the concentration of atmospheric CO2 is steadily increasing, carbonation of the reinforcement concrete becomes a pressing concern. In this study, novel surface protective materials (SPMs) modified with hybrid nanoSiO2 (HNS), fly ash, and slag were developed to reduce CO2 emissions and extend the service life of the reinforcement concrete. The carbonation depths were measured by phenolphthalein to reflect the carbonation resistance. X-ray diffraction (XRD), fourier-transform infrared spectroscopy (FTIR), and thermal gravimetric analysis (TGA) were conducted to analyze the chemical components of the samples after carbonation. In addition, MIP was carried out to examine the microstructures of the samples prior to carbonation. Thermodynamic modeling was employed to calculate the changes in the phase assemblages of each blends in an ideal situation. The experimental results showed that the carbonation depth and CaCO3 content of the SPM modified with HNS decreased by 79.0% and 64.6% compared with the reference, respectively. The TGA results showed that after carbonation, the CaCO3 contents were 4.40% and 12.42% in the HNS modified samples and reference samples, respectively. MIP analysis demonstrated that the incorporation of HNS in SPM led to a 48.3% and 58.5% decrease in big pores and capillary pores, respectively. Overall, the SPMs modified with HNS in this study possessed better carbonation resistance and refined pore structures.

Description: Both the statistical machine translation (SMT) model and neural machine translation (NMT) model are the representative models in Uyghur–Chinese machine translation tasks with their own merits. Thus, it will be a promising direction to combine the advantages of them to further improve the translation performance. In this paper, we present a hybrid framework of developing a system combination for a Uyghur–Chinese machine translation task that works in three layers to achieve better translation results. In the first layer, we construct various machine translation systems including SMT and NMT. In the second layer, the outputs of multiple systems are combined to leverage the advantage of SMT and NMT models by using a multi-source-based system combination approach and the voting-based system combination approaches. Moreover, instead of selecting an individual system’s combined outputs as the final results, we transmit the outputs of the first layer and the second layer into the final layer to make a better prediction. Experiment results on the Uyghur–Chinese translation task show that the proposed framework can significantly outperform the baseline systems in terms of both the accuracy and fluency, which achieves a better performance by 1.75 BLEU points compared with the best individual system and by 0.66 BLEU points compared with the conventional system combination methods, respectively.

Description: With the flourishing development of the hotel industry, the study of customer satisfaction based on online reviews and data has become a new model. In this paper, customer reviews and ratings on Ctrip.com are used, and TF-IDF and K-means algorithms are used to extract and cluster the keywords of reviews texts. Finally, 10 first-level influencing factors of hotel customer satisfaction are determined: epidemic prevention, consumption emotion, convenience, environment, facilities, catering, target group, perceived value, price, and service. Based on backpropagation neural network and weight matrix operation, an influencing factor analysis model of hotel customer satisfaction is constructed to explore the role of these factors. The results show that consumption emotion, perceived value, epidemic prevention, target group, and convenience would significantly affect customer satisfaction, among which epidemic prevention becomes a new factor affecting customer satisfaction. Environment, facilities, catering, and service have relatively little effect on customer satisfaction, while price has the least effect. This study provides a path and method for online reviews of hotel management to improve customer satisfaction and provides a theoretical basis for the study of online reviews of hotels.

Description: Among the various polymeric options employed for the deposition of electrospun coatings, poly(vinylidene fluoride) (PVDF) has been widely investigated thanks to its excellent mechanical properties, high chemical resistance, and good thermal stability. In this work, the electrospinning technique is used for the fabrication of functional PVDF fibers in order to identify and evaluate the influence of the experimental conditions on the nanofiber properties in terms of optical transmittance, wettability, corrosion resistance, and surface morphology. Some of these properties can play a relevant role in the prevention of ice formation in aircrafts. According to this, a matrix of 4 × 4 samples of aluminum alloy AA 6061T6 was successfully coated by controlling two operational input parameters such as the resultant applied voltage (from 10 up to 17.5 KV) and the flow rate (from 800 up to 1400 µL/h) for a fixed polymeric precursor concentration (15 wt.%). The experimental results have shown a multilevel fiber-bead structure where the formation of a fiber mesh directly depends on the selected operational parameters. Several microscopy and surface analysis techniques such as confocal microscopy (CM), field emission scanning electron microscopy (FE-SEM), UV/vis spectroscopy, and water contact angle (WCA) were carried out in order to corroborate the morphology, transmittance, and hydrophobicity of the electrospun fiber composite. Finally, the corrosion behavior was also evaluated by electrochemical tests (Tafel curves measurement), showing that the presence of electrospun PVDF fibers produces a relevant improvement in the resultant corrosion resistance of the coated aluminum alloys.

Description: Product counterfeiting is a continuous problem in industry. Recently, an anti-counterfeiting protocol to address this issue via radio-frequency identification (RFID) technology was proposed by researchers. Yet, the use case of reselling the same product has not been fully addressed which might cause serious problems for the exciting and proposed schemes and transactions. This paper proposes an extended RFID-based anti-counterfeiting protocol to address the use case of the original buyer reselling the same item to a second buyer. We will follow the proposed extended scheme with a formal security analysis to prove that the proposed protocol is secure and immune against most known security attacks.

Description: The suppression of unnecessary radio-electronic noise and the protection of electronic devices from electromagnetic interference by the use of pliable highly microwave radiation absorbing composite materials based on polymers or rubbers filled with conductive and magnetic fillers have been proposed. Since the working frequency bands of electronic devices and systems are rapidly expanding up to the millimeter wave range, the capabilities of absorbing and shielding composites should be evaluated for increasing operating frequency. The point is that the absorption capacity of conductive and magnetic fillers essentially decreases as the frequency increases. Therefore, this paper is devoted to the absorbing capabilities of composites filled with high-loss dielectric fillers, in which absorption significantly increases as frequency rises, and it is possible to achieve the maximum frequency selective of absorption due to electromagnetic and electromechanical resonances.

Description: This paper proposes a model to evaluate business projects to get into an incubator, allowing to rank them in order of selection priority. The model combines the Momentum method to build prospective scenarios and the AHP-TOPSIS-2N Multiple Criteria Decision Making (MCDM) method to rank the alternatives. Six business projects were evaluated to be incubated. The Momentum method made it possible for us to create an initial core of criteria for the evaluation of incubation projects. The AHP-TOPSIS-2N method supported the decision to choose the company to be incubated by ranking the alternatives in order of relevance. Our evaluation model has improved the existing models used by incubators. This model can be used and/or adapted by any incubator to evaluate the business projects to be incubated. The set of criteria for the evaluation of incubation projects is original and the use of prospective scenarios with an MCDM method to evaluate companies to be incubated does not exist in the literature.

Description: Objective: The health effects of a supplemented Mediterranean diet (SMD) with extra-virgin olive oil (EVOO) and nuts are well documented in non-HIV-infected individuals. We hypothesised that the benefits of an SMD could be mediated by changes in the gut microbiota, even in those with an altered intestinal microbiota such as people living with HIV. Design: Individuals living with HIV (n = 102) were randomised to receive an SMD with 50 g/day of EVOO and 30 g/day of walnuts (SMD group) or continue with their regular diet (control group) for 12 weeks. Methods: Adherence to the Mediterranean diet was assessed using the validated 14-item MD-Adherence-Screener (MEDAS) from the PREDIMED study. A sub-study classifying the participants according to their MEDAS scores was performed. Results: The lipid profile was improved in the SMD group vs. that in the control group (delta-total cholesterol and delta-B-lipoprotein). The immune activation (CD4+HLADR+CD38+ and CD8+HLADR+CD38+ cells) and IFN-γ-producing T-cells significantly decreased at week 12 compared to the baseline in the SMD group but not in the control group. The gut microbiota in those from the high-adherence group presented significantly high diversity and richness at the end of the intervention. Succinivibrio and Bifidobacterium abundances were influenced by the adherence to the MD and significantly correlated with Treg cells. Conclusion: The Mediterranean diet improved metabolic parameters, immune activation, Treg function, and the gut microbiota composition in HIV-1-infected individuals. Further, Mediterranean diet increased the Bifidobacterium abundances after the intervention, and it was associated to a beneficial profile.

Description: Community detection plays an essential role in understanding network topology and mining underlying information. A bipartite network is a complex network with more important authenticity and applicability than a one-mode network in the real world. There are many communities in the network that present natural overlapping structures in the real world. However, most of the research focuses on detecting non-overlapping community structures in the bipartite network, and the resolution of the existing evaluation function for the community structure’s merits are limited. So, we propose a novel function for community detection and evaluation of the bipartite network, called community density D. And based on community density, a bipartite network community detection algorithm DSNE (Density Sub-community Node-pair Extraction) is proposed, which is effective for overlapping community detection from a micro point of view. The experiments based on artificially-generated networks and real-world networks show that the DSNE algorithm is superior to some existing excellent algorithms; in comparison, the community density (D) is better than the bipartite network’s modularity.

Description: Background: Pasteurized donor milk (PDM) is typically prescribed to preterm or low birthweight newborns when their mother’s own milk is unavailable. In surplus, PDM is prescribed to meet the nutritional needs of healthy newborns in the first few days of life. However, its overuse can undermine efforts to promote and support breastfeeding, waste resources, and reduce the availability of PDM for at-risk newborns. We conducted this study to examine factors associated with the prescription and prolonged use (〉48 h) of privately purchased PDM to healthy newborns. Methods: Prospective observational study of 2440 mothers of healthy, term, and normal birthweight newborns born at Da Nang Hospital for Women and Children between April and August 2019. In addition to the descriptive analysis, we performed multiple logistic regressions to examine factors associated with the prescription of PDM (n = 2440) and prolonged PDM use among those who used PDM (n = 566). Results: Twenty-three percent (566/2440) of healthy, term, and birthweight ≥2500 g newborns received PDM and were included in the study. The prevalence of PDM use was higher for cesarean births (OR: 2.05; 95% CI: 1.66, 2.55) and among male newborns (OR: 1.33; 95% CI: 1.09, 1.62), but lower for farmers or workers (vs. other jobs; OR: 0.71; 95% CI: 0.54, 0.93), family income

Description: Vitamin D has been hypothesized to play an important role in preventing the development and progression of periodontal disease, but the underlying immune modulatory mechanisms remain understudied. We examined the cross-sectional association between biomarkers of vitamin D status and C-reactive protein (CRP) among postmenopausal women aged 53–81 years. Linear regression was used to examine the association between plasma 25-hydroxyvitamin D (25[OH]D) concentrations, a biomarker of vitamin D status, and both salivary and serum CRP concentrations in 567 women from the Buffalo Osteoporosis and Periodontal Disease (OsteoPerio) Study (1997–2000). CRP concentrations were measured with multiplex arrays and transformed for normality using the natural log. Concentrations above and below the limit of detection were included in analysis as right- and left-censored observations. An inverse association was observed between 25(OH)D and salivary CRP in a model adjusted for age, smoking status, frequency of tooth brushing and flossing, and hormone therapy use (−7.56% difference in salivary CRP concentrations per 10 nmol/L increase in 25(OH)D, 95% CI: −12.78 to −2.03). Further adjustment for percent body fat attenuated this association (−2.48%, 95% CI: −7.88 to 3.24). No significant associations were found between 25(OH)D and serum CRP. Plasma vitamin D concentrations were not associated with salivary or serum CRP concentrations in this cohort of postmenopausal women.

Description: Owing to the toxicity of polycyclic aromatic (PCA) oils, much attention has been paid to the replacement of PCA oils by other nontoxic oils. This paper reports comparative study of the effects of new vegetable oils, i.e., Moringa oil (MO) and Niger oil (NO), on rheological, physical and dynamic properties of silica–filled natural rubber composite (NRC), in comparison with petroleum–based naphthenic oil (NTO). The results reveal that MO and NO exhibit higher thermal stability and better processability than NTO. Cure characteristics of the rubber compounds are not significantly affected by the oil type. It is also found that the NRCs containing MO or NO have better tensile strength and lower dynamic energy loss than the NRCs containing NTO. This may be because both MO and NO improve filler dispersion to a greater extent than NTO as supported by storage modulus and scanning electron microscopy results. Consequently, the present study suggests that MO and NO could be used as the alternative non–toxic oils for NRC without any loss of the properties evaluated.

Description: Planetary boundaries are an important sustainability concept, defining absolute limits for resource use and emissions that need to be respected to avoid major and potentially irreversible earth system change. To remain within the safe operating space for humanity, there is a need for urgent adoption of climate-neutral diets, which make no additional contribution to warming. In the first study of its kind, a new climate metric, the Global Warming Potential Star (GWP*), was used to assess greenhouse gas (GHG) emissions associated with 9341 Australian adult diets obtained from the Australian Health Survey. Dietary climate footprints averaged 3.4 kg CO2-equivelent per person per day, with total energy intake explaining around one quarter of the variation. Energy-dense and nutrient-poor discretionary foods contributed around one third. With lower climate footprint food choices, a diet consistent with current Australian dietary guidelines had a 42% lower climate footprint. Currently, it is not possible to define a climate-neutral dietary strategy in Australia because there are very few climate-neutral foods in the Australian food system. To bring Australian diets into line with the climate stabilization goals of the Paris Agreement, the most important need is for innovation across the agricultural and food processing industries to expand the range of climate-neutral foods available.

Description: A few prospective studies have suggested that tea, alcohol, and fruit consumption may reduce the risk of kidney stones. However, little is known whether such associations and their combined effect persist in Chinese adults, for whom the popular tea and alcohol drinks are different from those investigated in the aforementioned studies. The present study included 502,621 participants from the China Kadoorie Biobank (CKB). Information about tea, alcohol, and fruit consumption was self-reported at baseline. The first documented cases of kidney stones during follow-up were collected through linkage with the national health insurance system. Cox regression was used to calculate the hazard ratio (HR) and 95% confidence interval (CI). During a median of 11.1 years of follow-up, we collected 12,407 cases of kidney stones. After multivariable adjustment, tea, alcohol, and fruit consumption were found to be negatively associated with kidney stone risk, but the linear trend was only found in tea and fruit consumption. Compared with non-tea consumers, the HR (95% CI) for participants who drank ≥7 cups of tea per day was 0.73 (0.65–0.83). Compared with non-alcohol consumers, the HR (95% CI) was 0.79 (0.72–0.87) for participants who drank pure alcohol of 30.0–59.9 g per day but had no further decrease with a higher intake of alcohol. Compared with less-than-weekly consumers, the HR (95% CI) for daily fruit consumers was 0.81 (0.75–0.87). Even for those who did not drink alcohol excessively, increasing tea and fruit consumption could also independently reduce the stone risk. Among Chinese adults, tea, alcohol, and fruit consumption was associated with a lower risk of kidney stones.

Description: There is growing evidence for a global transition to a more highly processed diet. While the dietary share of ultra-processed foods depends on a country’s economic status, food choice and consumption are also influenced by the socioeconomic situation of individuals. This study investigated whether ultra-processed food consumption differed across socioeconomic subgroups and over time (2010–2018) in Korea. Cross-sectional data from the Korea National Health and Nutrition Examination Survey 2010–2018 were analyzed. Food and beverages reported in a one-day 24 h recall were classified according to the NOVA food classification criteria. The dietary energy contribution of ultra-processed foods was high among men and urban residents, and increased with education and income level; additionally, it reached its peak in adolescents and thereafter decreased with increasing age. After adjusting the socioeconomic variables, such associations remained significant, except for income level. The overall contribution of ultra-processed foods increased from 23.1% (2010–2012) to 26.1% (2016–2018), and the same trend over time was observed in all age groups and socioeconomic strata. In the Korean population, ultra-processed food consumption differed by individual socioeconomic characteristics, but gradually increased over time, and this trend was consistently found in all socioeconomic subgroups. Future strategies to promote healthy food choices are needed for the Korean population.

Description: Organoclay nanoparticles (Cloisite® C10A, Cloisite® C15) and their combination with carbon black (N330) were studied as fillers in chloroprene/natural/butadiene rubber blends to prepare nanocomposites. The effect of filler type and load on the physical mechanical properties of nanocomposites was determined and correlated with its structure, compatibility and cure properties using Fourier Transformed Infrared (FT-IR), X-ray Diffraction (XRD), Thermogravimetric Analysis (TGA) and rheometric analysis. Physical mechanical properties were improved by organoclays at 5–7 phr. Nanocomposites with organoclays exhibited a remarkable increase up to 46% in abrasion resistance. The improvement in properties was attributed to good organoclay dispersion in the rubber matrix and to the compatibility between them and the chloroprene rubber. Carbon black at a 40 phr load was not the optimal concentration to interact with organoclays. The present study confirmed that organoclays can be a reinforcing filler for high performance applications in rubber nanocomposites.

Description: In this study unique blended biopolymer mycocel from naturally derived biomass was developed. Softwood Kraft (KF) or hemp (HF) cellulose fibers were mixed with fungal fibers (FF) in different ratios and the obtained materials were characterized regarding microstructure, air permeability, mechanical properties, and virus filtration efficiency. The fibers from screened Basidiomycota fungi Ganoderma applanatum (Ga), Fomes fomentarius (Ff), Agaricus bisporus (Ab), and Trametes versicolor (Tv) were applicable for blending with cellulose fibers. Fungi with trimitic hyphal system (Ga, Ff) in combinations with KF formed a microporous membrane with increased air permeability (〉8820 mL/min) and limited mechanical strength (tensile index 9–14 Nm/g). HF combination with trimitic fungal hyphae formed a dense fibrillary net with low air permeability (77–115 mL/min) and higher strength 31–36 Nm/g. The hyphal bundles of monomitic fibers of Tv mycelium and Ab stipes made a tight structure with KF with increased strength (26–43 Nm/g) and limited air permeability (14–1630 mL/min). The blends KF FF (Ga) and KF FF (Tv) revealed relatively high virus filtration capacity: the log10 virus titer reduction values (LRV) corresponded to 4.54 LRV and 2.12 LRV, respectively. Mycocel biopolymers are biodegradable and have potential to be used in water microfiltration, food packaging, and virus filtration membranes.

Description: Water with the necessary quality is indispensable to the functioning of most of the known life forms, being essential to human health, social and economic development, and ecosystems functioning [...]

Description: In this paper, we discuss the critical characteristics of user experience in sixth generation (6G) cellular networks. We first describe cellular networks’ evolution through 5G and then discuss the enabling technologies and projected services in 6G networks. We note that these networks are markedly centered around expanded intelligence, end-to-end resource and topology synchronization, and the intrinsic support to low-latency, high-bandwidth communication. These capabilities make context-rich, cyberphysical user experiences viable. It thereby becomes necessary to define and identify the role of quality of experience in 6G networks, especially when it comes to network management. We elaborate on these expected challenges and allude to viable opportunities in emerging technologies.

Description: Additive Manufacturing Techniques such as Fused Filament Fabrication (FFF) produce 3D parts with complex geometries directly from a computer model without the need of using molds and tools, by gradually depositing material(s), usually in layers. Due to the rapid growth of these techniques, researchers have been increasingly interested in the availability of strategies, models or data that may assist process optimization. In fact, 3D printed parts often exhibit limited mechanical performance, which is usually the result of poor bonding between adjacent filaments. In turn, the latter is influenced by the temperature field history during deposition. This study aims at evaluating the influence of the phase change from the melt to the solid state undergone by semi-crystalline polymers such as Polylactic Acid (PLA), on the heat transfer during the deposition stage. The energy equation considering solidification is solved analytically and then inserted into a MatLab® code to model cooling in FFF. The deposition and cooling of simple geometries is studied first, in order to assess the differences in cooling of amorphous and semi-crystalline polymers. Acrylonitrile Butadiene Styrene (ABS) was taken as representing an amorphous material. Then, the deposition and cooling of a realistic 3D part is investigated, and the influence of the build orientation is discussed.

Description: In the present work, we have reported a facile and large-scale synthesis of TiO2 nanoparticles (NPs) through urea-assisted thermal decomposition of titanium oxysulphate. We have successfully synthesized TiO2 NPs by using this effective route with different weight ratios of titanium oxysulphate: urea. The structures and properties of TiO2 NPs were confirmed by scanning electron microscope) (SEM), transmission electron microscopy (TEM), thermogravimetric analysis (TGA), fourier transform infrared spectroscopy (FT-IR), ultra violet–visible spectroscopy (UV-vis), and photoluminescence (Pl) techniques. XRD demonstrated that TiO2 NPs holds of anatase crystal phase with crystallizing size 14–19 nm even after heating at 600 °C. TGA, SEM, and TEM images reveal urea’s role, which controls the size, morphology, and aggregation of TiO2 NPs during the thermal decomposition. These TiO2 NPs were employed for photodegradation of Methyl Orange (MO) in the presence of ultraviolet (UV) radiation. An interesting find was that the TiO2 NPs exhibited better photocatalytic activity and excellent recycling stability over several photodegradation cycles. Furthermore, the present method has a great perspective to be used as an efficient method for large-scale synthesis of TiO2 NPs.

Description: Prospective epidemiological studies concur in an association between habitual coffee consumption and a lower risk of type 2 diabetes. Several aspects of these studies support a cause–effect relationship. There is a dependency on daily coffee dose. Study outcomes are similar in different regions of the world, show no differences between sexes, between obese versus lean, young versus old, smokers versus nonsmokers, regardless of the number of confounders adjusted for. Randomized controlled intervention trials did not find a consistent impact of drinking coffee on acute metabolic control, except for effects of caffeine. Therefore, lowering of diabetes risk by coffee consumption does not involve an acute effect on the post-meal course of blood glucose, insulin or insulin resistance. Several studies in animals and humans find that the ingestion of coffee phytochemicals induces an adaptive cellular response characterized by upregulation and de novo synthesis of enzymes involved in cell defense and repair. A key regulator is the nuclear factor erythroid 2-related factor 2 (Nrf2) in association with the aryl hydrocarbon receptor, AMP-activated kinase and sirtuins. One major site of coffee actions appears to be the liver, causing improved fat oxidation and lower risk of steatosis. Another major effect of coffee intake is preservation of functional beta cell mass via enhanced mitochondrial function, lower endoplasmic reticulum stress and prevention or clearance of aggregates of misfolded proinsulin or amylin. Long-term preservation of proper liver and beta cell function may account for the association of habitual coffee drinking with a lower risk of type 2 diabetes, rather than acute improvement of metabolic control.

Description: Most nutrition studies looking at the association of food with cardiometabolic markers rely on food frequency questionnaires, which are prone to recall bias. Pentadecanoic acid, heptadecanoic acid and trans-palmitoleic acid are fatty acids that are not synthesized endogenously but are obtained from the diet, particularly dairy, making them reasonable biomarkers of dairy consumption. We investigated the association of dairy fatty acid biomarkers with glycated hemoglobin (HbA1c) and cardiovascular risk factors in type 2 diabetes (T2D). In a clinical trial, 111 participants with T2D (age 58.5 ± 8.9 years, HbA1c 8.09 ± 0.96%) were randomized into three groups: a control group that maintained baseline dairy intake, a low-fat (LF) group that incorporated ≥3 servings/day of LF dairy and a high-fat (HF) group that incorporated ≥3 servings/day of HF dairy. We compared the fatty acids (FA) composition between the three groups at 24 weeks. Pentadecanoic acid and trans-palmitoleic acid increased in the HF group by 14.1% ± 5.4% and 17.5% ± 5.1%, respectively, but not in the control and LF groups (p = 0.0474 and p= 0.0025 for group-by-time interaction, respectively). Those increases were positively associated with changes in total cholesterol, very-low-density lipoprotein cholesterol VLDL-C and triglycerides but were not associated with changes in HbA1c from baseline to 24 weeks. These results suggest that the intervention was successful and that participants were likely compliant, which supports the validity of the main trial.

Description: The bark of Norway spruce (Picea abies) contains up to 13% pectins that can be extracted by pressurized hot water, which constitute a valuable renewable resource in second-generation lignocellulosic biorefineries. This article proposes, for the first time, structural molecular models for the pectins present in spruce bark. Pectin fractions of tailored molar masses were obtained by fractionation of the pressurized hot water extract of the inner bark using preparative size-exclusion chromatography. The monosaccharide composition, average molar mass distribution, and the glycosidic linkage patterns were analyzed for each fraction. The pectin fraction with high molecular weight (Mw of 59,000 Da) contained a highly branched RG-I domain, which accounted for 80% of the fraction and was mainly substituted with arabinan and arabinogalactan (type I and II) side chains. On the other hand, the fractions with lower molar masses (Mw = 15,000 and 9000 Da) were enriched with linear homogalacturonan domains, and also branched arabinan populations. The integration of the analytical information from the macromolecular size distributions, domain composition, and branch lengths of each pectin fraction, results in a comprehensive understanding of the macromolecular architecture of the pectins extracted from the bark of Norway spruce. This paves the way for the valorization of spruce bark pectic polymers in targeted applications based on their distinct polymeric structures and properties.

Description: (1) A compound protectant was prepared using manganese chloride, phosphoric acid, boric acid and ammonium chloride, and then a veneer was immersed in the prepared protectant to prepare plywood in this paper. Great attention was paid to discussing influences of such protectant on fire resistance, decay resistance, anti-mold property and bonding performance of plywood. Results demonstrated that after protectant treatment, the plywood showed not only good fire resistance and smoke inhibition, but also strong char-formation ability, slow flame spreading, long time to ignition, small fire risk and high safety level. (2) The mass loss rates of plywood with protectant treatment after infection and erosion in wood-destroying Coriolus versicolor and Gloeophyllum trabeum were 19.73% and 17.27%, reaching the II-level corrosion grade. (3) There is not a significant difference with Aspergillus niger V.; however, it was possible to observe a strong difference with Trichoderma viride Pers. ex Fr., indicating that the protectant acted as a good anti-mold product for plywood. (4) The protectant influenced the bonding interface of wood and bonding conditions of the adhesive. The bonding strength of plywood was weakened, but it still met the requirements on bonding strength of GB/T 9846-2015. (5) The protectant changed the thermal decomposition and thermal degradation of plywood, inhibiting the generation of inflammable goods, blocking transmission of heats and lowering the thermal decomposition temperature of plywood. These promoted dehydrations and charring of wood and the generated carbon had a high thermal stability. (6) Compared with untreated plywood, the prepared protectant treatment significantly enhanced the fire resistance of plywood, reduced its biodegradability by wood-decaying fungi and showed good mold resistance.

Description: As emission legislation becomes more stringent, the modelling of turbulent lean premixed combustion is becoming an essential tool for designing efficient and environmentally friendly combustion systems. However, to predict emissions, reliable predictive models are required. Among the promising methods capable of predicting pollutant emissions with a long chemical time scale, such as nitrogen oxides (NOx), is conditional moment closure (CMC). However, the practical application of this method to turbulent premixed flames depends on the precision of the conditional scalar dissipation rate,ζ ⟨Nc|ζ⟩, model. In this study, an alternative closure for this term is implemented in the RANS-CMC method. The method is validated against the velocity, temperature, and gas composition measurements of lean premixed flames close to blow-off, within the limit of computational fluid dynamic (CFD) capability. Acceptable agreement is achieved between the predicted and measured values near the burner, with an average error of 15%. The model reproduces the flame characteristics; some discrepancies are found within the recirculation region due to significant turbulence intensity.

Description: Background: The ‘Primary Care SHOPping Intervention for Cardiovascular Disease Prevention’ (PCSHOP) trial tested the effectiveness and feasibility of a behavioural intervention to reduce saturated fat in food purchases. The intervention offered feedback from data collected through a supermarket loyalty card to supplement brief advice from a nurse. This qualitative study aimed to describe participants’ experiences of receiving this intervention. Methods: We conducted semi-structured, one-to-one, telephone interviews with participants from the PCSHOP trial. Interviews were audio-recorded and transcribed verbatim. We employed the one sheet of paper technique and a thematic analysis to develop high-level themes in NVivo software. Results: Twenty-four participants were interviewed (mean age: 63 years (SD 12)). They reported that the brief advice did not provide any new information but they welcomed the sense of accountability the nurse provided. The personalised shopping feedback and healthier swap suggestions provided novel information that challenged previously held beliefs about the saturated fat content of food purchases and encouraged some positive dietary changes. However, the taste preferences of the participant or other household members were a barrier to changing food shopping behaviours. Conclusion: Harnessing loyalty card data is a novel and acceptable method to offering personalised dietary feedback. Yet, issues on the suitability of the healthier swap suggestions limited the extent of dietary change. Trial registration: ISRCTN14279335. Registered 1 September 2017.

Description: Deep Neural Networks are state-of-the-art in a large number of challenges in machine learning. However, to reach the best performance they require a huge pool of parameters. Indeed, typical deep convolutional architectures present an increasing number of feature maps as we go deeper in the network, whereas spatial resolution of inputs is decreased through downsampling operations. This means that most of the parameters lay in the final layers, while a large portion of the computations are performed by a small fraction of the total parameters in the first layers. In an effort to use every parameter of a network at its maximum, we propose a new convolutional neural network architecture, called ThriftyNet. In ThriftyNet, only one convolutional layer is defined and used recursively, leading to a maximal parameter factorization. In complement, normalization, non-linearities, downsamplings and shortcut ensure sufficient expressivity of the model. ThriftyNet achieves competitive performance on a tiny parameters budget, exceeding 91% accuracy on CIFAR-10 with less than 40 k parameters in total, 74.3% on CIFAR-100 with less than 600 k parameters, and 67.1% On ImageNet ILSVRC 2012 with no more than 4.15 M parameters. However, the proposed method typically requires more computations than existing counterparts.

Description: This paper presents an effective stochastic algorithm that embeds a large neighborhood decomposition technique into a variable neighborhood search for solving the permutation flow-shop scheduling problem. The algorithm first constructs a permutation as a seed using a recursive application of the extended two-machine problem. In this method, the jobs are recursively decomposed into two separate groups, and, for each group, an optimal permutation is calculated based on the extended two-machine problem. Then the overall permutation, which is obtained by integrating the sub-solutions, is improved through the application of a variable neighborhood search technique. The same as the first technique, this one is also based on the decomposition paradigm and can find an optimal arrangement for a subset of jobs. In the employed large neighborhood search, the concept of the critical path has been used to help the decomposition process avoid unfruitful computation and arrange only promising contiguous parts of the permutation. In this fashion, the algorithm leaves those parts of the permutation which already have high-quality arrangements and concentrates on modifying other parts. The results of computational experiments on the benchmark instances indicate the procedure works effectively, demonstrating that solutions, in a very short distance of the best-known solutions, are calculated within seconds on a typical personal computer. In terms of the required running time to reach a high-quality solution, the procedure outperforms some well-known metaheuristic algorithms in the literature.

Description: The e-commerce industry in Indonesia is growing in line with the increasing number of internet users in Indonesia. Unfortunately, many internet users in Indonesia are still unsure about shopping online because of the lack of buyer trust with sellers and service providers. This study aims to identify the factors that influence online shop consumers to conduct transactions online. This research used a questionnaire survey distributed to customers who had ever used an online shop application. The sample used in this research was 468 respondents. The data collected was then analyzed using Partial Least Square. The results of this research indicated that trust, perceived value, and buying interest positively influence consumers’ decisions to purchase using an online shop application.

Description: This study investigates the formation of microstructured macromaterials from thermo- and pH-sensitive microgels based on interpenetrating networks of poly-N-isopropylacrylamide (PNIPAM) and polyacrylic acid (PAA). Macromaterials are produced as a result of the deposition of microgel particles and subsequent crosslinking of polyacrylic acid subnetworks to each other due to the formation of the anhydride bonds during annealing. Since both PNIPAM and PAA are environment-sensitive polymers, one can expect that their conformational state during material development will affect its resulting properties. Thus, the influence of conditions of preparation for annealing (pH of the solution, the temperature of preliminary drying) on the swelling behavior, pH- and thermosensitivity, and macromaterial inner structure was investigated. In parallel, the study of the effect of the relative conformations of the IPN microgel subnetworks on the formation of macromaterials was carried out by the computer simulations method. It was shown that the properties of the prepared macromaterials strongly depend both on the temperature and pH of the PNIPAM-PAA IPN microgel dispersions. This opens up new opportunities to obtain materials with pre-chosen characteristics and environmental sensitivity.

Description: Dielectric elastomer (DE) is a type of electric field type electroactive polymer material that can produce greater deformation under the action of an electric field and has a faster recovery speed. It has the advantages of high energy density, large strain, low quality, and commercialization, and has become the most widely concerned and researched electroactive polymer material. In this study, copper calcium titanate (CCTO) particles with a large dielectric constant were selected as the filling phase, and a silicone rubber (PDMS) with better biocompatibility and lower elastic modulus was used as the matrix to prepare CCTO/PDMS, which is a new type of dielectric elastomer material. The structure of the dielectric elastomer is analyzed, and its mechanical properties, dielectric properties, and driving deformation are tested. Then, KH550, KH560, and KH570 modified CCTO is used in order to improve the dispersibility of CCTO in PDMS, and modified particles with the best dispersion effect are selected to prepare dielectric elastomer materials. In addition, mechanical properties, dielectric properties, and driving deformation are tested and compared with the dielectric elastomer material before modification. The results show that as the content of CCTO increases, the dielectric constant and elastic modulus of the dielectric elastomer also increase, and the dielectric loss remains basically unchanged at a frequency of 100 Hz. When the filling amount reaches 20 wt%, the dielectric constant of the CCTO/PDMS dielectric elastomer reaches 5.8 (100 Hz), an increase of 120%, while the dielectric loss at this time is only 0.0038 and the elastic modulus is only 0.54 MPa. When the filling amount is 5 wt%, the dielectric elastomer has the largest driving deformation amount, reaching 33.8%. Three silane coupling agents have been successfully grafted onto the surface of CCTO particles, and the KH560 modified CCTO has the best dispersibility in the PDMS matrix. Based on this, a modified CCTO/PDMS dielectric elastomer was prepared. The results show that the improvement of dispersibility improves the dielectric constant. Compared with the unmodified PDMS, when the filling content is 20 wt%, the dielectric constant reaches 6.5 (100 Hz). Compared with PDMS, it has increased by 150%. However, the improvement of dispersion has a greater increase in the elastic modulus, resulting in a decrease in its strain parameters compared with CCTO/PDMS dielectric elastomers, and the electromechanical conversion efficiency has not been significantly improved. When the filling amount of modified CCTO particles is 5 wt%, the dielectric elastomer has the largest driving deformation, reaching 27.4%.

Description: Modern personal protective armor has been generally based on the Kevlar fabrics, with the main goal to offer defense against bullets. In addition to the high cost and poor processability, Kevlar has the disadvantage of limited stab-proofing capability. On the other hand, a large number of crimes involving deadly injures represent knife attacks. Our goal in this work was to investigate composites based on traditional commercially available fabrics of linen and silk, using different adhesives-polymers for forming laminates. The silk composites also contained different amounts of in-woven polyester. Three different water-based adhesives of polyurethane, urea formaldehyde and polyvinyl alcohol were considered. It was found, that besides the strength of the fabrics themselves, the adhesives polymers played a crucial role in the obtained performance of the laminates. The laminates were characterized in their mechanical properties, as well as with scanning electron microscopy and FTIR spectroscopy.

Description: A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures. In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often prohibited. Luckily, privacy-preserving technologies have been developed to overcome this hurdle by distributing the computation of the training and ensuring the data privacy to their owners. The distribution of the computation to multiple participating entities introduces new privacy complications and risks. In this paper, we present a privacy-preserving decentralised workflow that facilitates trusted federated learning among participants. Our proof-of-concept defines a trust framework instantiated using decentralised identity technologies being developed under Hyperledger projects Aries/Indy/Ursa. Only entities in possession of Verifiable Credentials issued from the appropriate authorities are able to establish secure, authenticated communication channels authorised to participate in a federated learning workflow related to mental health data.

Description: Renewable energy systems have been extensively developed and they are attractive to become widespread in the future because they can deliver energy at a competitive price and generally do not cause environmental pollution. However, stand-alone energy systems may not be practical for satisfying the electric load demands, especially in places having unsteady wind speeds with high unpredictability. Hybrid energy systems seem to be a more economically feasible alternative to satisfy the energy demands of several isolated clients worldwide. The combination of these systems makes it possible to guarantee the power stability, efficiency, and reliability. The aim of this paper is to present a comprehensive analysis and to propose a technical solution to integrate a self-excited induction generator in a low power multisource system. Therefore, to avoid the voltage collapsing and the machine demagnetization, the various parameters have to be identified. This procedure allows for the limitation of a safe operating area where the best stability of the machine can be obtained. Hence, the load variation interval is determined. An improvement of the induction generator stability will be analyzed. Simulation results will be validated through experimental tests.

Description: Based on additive manufacturing of wood flour and polyhydroxyalkanoates composites using micro-screw extrusion, device and process parameters were evaluated to achieve a reliable printing. The results show that the anisotropy of samples printed by micro-screw extrusion is less obvious than that of filament extrusion fused deposition modeling. The type of micro-screw, printing speed, layer thickness, and nozzle diameter have significant effects on the performance of printed samples. The linear relationship between the influencing parameters and the screw speed is established, therefore, the performance of printed products can be controlled by the extrusion flow rate related to screw speed.

Description: Antitumor effects of shikonins on chronic lymphocytic leukemia (CLL) and B-cell prolymphocytic leukemia (B-PLL) are mostly unexplored. The antitumor activity of shikonins, isolated from Onosma visianii Clem (Boraginaceae), in BCL1, mouse CLL cells and JVM-13, human B-PLL cells was explored in this study. The cytotoxicity of shikonin derivatives was measured by an MTT test. Cell death, proliferation, cell cycle, and expression of molecules that control these processes were analyzed by flow cytometry. Expression of STAT3-regulated genes was analyzed by real-time q-RT-PCR (Quantitative Real-Time Polymerase Chain Reaction). The antitumor effects of shikonin derivatives in vivo were analyzed, using flow cytometry, by detection of leukemia cells in the peripheral blood and spleens of mice intravenously injected with BCL1 cells. The two most potent derivatives, isobutyrylshikonin (IBS) and α-methylbutyrylshikonin (MBS), induced cell cycle disturbances and apoptosis, inhibited proliferation, and decreased expression of phospho-STAT3 and downstream-regulated molecules in BCL1 and JVM-13 cells. IBS and MBS decreased the percentage of leukemia cells in vivo. The link between the decrease in phosphorylated STAT3 by MBS and IBS and BCL1 cell death was confirmed by detection of enhanced cell death after addition of AG490, an inhibitor of Jak2 kinase. It seems that IBS and MBS, by decreasing STAT3 phosphorylation, trigger apoptosis, inhibit cell proliferation, and attenuate leukemia cell stemness.

Description: Chronic inflammation is a risk factor for colorectal cancer, and inflammatory cytokines secreted from inflammatory cells and active oxygen facilitate tumorigenesis. Intestinal bacteria are thought to regulate tumorigenesis. The longer the breastfeeding period, the lower is the risk of inflammatory bowel disease. Here, we investigated preventive effects of the probiotic Lactobacillus rhamnosus M9 (Probio-M9) on colitis-associated tumorigenesis. An inflammatory colorectal tumor model was established using a 6-week-old male C57BL/6NCrSlc mouse, which was intraperitoneally administered with azoxymethane (AOM: 12 mg/kg body weight). On weeks 2 and 4, 2% dextran sulfate sodium (DSS) was administered to mice for 7 days through drinking water. On weeks 8 and 10, Probio-M9 (2 × 109/day) was orally administered for 7 days. Animals were sacrificed at 20 weeks after AOM administration and immunohistochemical staining and Western blotting was performed. The α-diversity of microflora (Shannon index), principal coordinate analysis, and distribution of intestinal bacterium genera and metabolic pathways were compared. The AOM/DSS group showed weight loss, diarrhea, intestinal shortening, increased number of colon tumors, proliferating tumorigenesis, increased inflammation score, fibrosis, increased CD68+, or CD163+ macrophage cells in the subserosal layer of non-tumor areas. Inflammation and tumorigenesis ameliorated after Probio-M9 treatment. Fecal microbial functions were altered by AOM/DSS treatment. Probio-M9 significantly upregulated the fecal microbial diversity and reversed fecal microbial functions. Thus, Probio-M9 could suppress tumor formation in the large intestine by regulating the intestinal environment and ameliorating inflammation, suggesting its therapeutic potential for treatment of inflammation and colitis-associated tumorigenesis.

Description: The antihypertensive effect of wine lees (WL) has been previously evidenced. In this study, the antihypertensive properties of different doses of WL were evaluated in spontaneously hypertensive rats (SHR). In addition, the blood pressure (BP)-lowering effect of dried (dealcoholized) WL powder (WLPW) and the mechanisms involved in its functionality were investigated. Furthermore, a possible hypotensive effect of WLPW was discarded in Wistar–Kyoto (WKY) rats. The administration of WL at different doses caused a dose-dependent decrease in BP of SHR up to 5.0 mL/kg bw, exhibiting the maximum decrease at 6 h post-administration. WLPW caused a greater drop in BP than WL, showing an antihypertensive effect higher and more prolonged than the drug Captopril. Moreover, the BP-lowering effect of WLPW was specific to the hypertensive state since an undesirable hypotensive effect in normotensive WKY rats was ruled out. Finally, WLPW improved oxidative stress and increased the activity of the antioxidant endogen system of SHR. These results suggest that WLPW could be used as functional ingredient for foods or nutraceuticals to ameliorate hypertension. Nevertheless, further clinical studies are needed to evaluate its long-term antihypertensive efficiency.

Description: Agro-industrial wastes can be valorized as biorefinery raw materials through innovative, environmentally friendly bioprocessing for added value products. In this study, a process for citrus waste valorization within the biorefinery concept is proposed, including the development of an effective biocatalyst, based on immobilized cells, for aromatic beer production, and an alternative yeast extract (AYE) production in the same unit. Specifically, orange pulp from discarded oranges was applied as an immobilization carrier of the alcohol-resistant and cryotolerant yeast strain S. cerevisiae AXAZ-1. The yeast culture was produced by minor nutrient supplementation using diluted molasses as substrate. An effective Citrus Waste Brewing Biocatalyst (CWBB) was produced and applied for beer fermentation. The aroma-related compounds in beer produced with free yeast cells or the CWBB were evaluated by solid-phase micro-extraction (SPME) gas chromatography–mass spectrometry (GC–MS). The analysis showed that the beers produced by the CWBB had a more complex volatile profile compared with beer fermented by the free cells. More specifically, the CWBB enhanced the formation of esters and terpenes by 5- and 27-fold, respectively. In the frame of the proposed multiprocessing biorefinery concept, the spent CWBB, after it has completed its cycle of brewing batches, was used as substrate for AYE production through autolysis. The produced AYE significantly affected the yeast growth when compared to commercial yeast extract (CYE). More specifically, it promoted the biomass productivity and biomass yield factor by 60–150% and 110–170%, respectively. Thus, AYE could be successfully used for industrial cell growth as an efficient and cheaper substitute of CYE. Within a circular economy framework, the present study highlights the potential use of citrus waste to produce aromatic beer combined with AYE production as an alternative way to valorize these wastes.

Description: Knowledge graph embedding (KGE) models have become popular means for making discoveries in knowledge graphs (e.g., RDF graphs) in an efficient and scalable manner. The key to success of these models is their ability to learn low-rank vector representations for knowledge graph entities and relations. Despite the rapid development of KGE models, state-of-the-art approaches have mostly focused on new ways to represent embeddings interaction functions (i.e., scoring functions). In this paper, we argue that the choice of other training components such as the loss function, hyperparameters and negative sampling strategies can also have substantial impact on the model efficiency. This area has been rather neglected by previous works so far and our contribution is towards closing this gap by a thorough analysis of possible choices of training loss functions, hyperparameters and negative sampling techniques. We finally investigate the effects of specific choices on the scalability and accuracy of knowledge graph embedding models.

Description: The article deals with the topic of attention paid to online privacy policy statements by university students. Privacy policy statements were originally intended to mitigate the users’ privacy con-cerns and support trust, but users disregard them. The article uses the theory of planned behav-iour combined with privacy calculus to find and verify determinants of reading privacy policy statements. We used the survey method and evaluated the results with partial least square struc-tural equation modelling. We concluded that the attitude towards reading privacy policy state-ments is influenced by privacy risks and privacy benefits. The intention to read privacy policy statements is influenced by social norms, understanding the privacy policy and mainly by the willingness to spend time and effort reading the statements. The effect of attitude was also signif-icant, but its size was smaller. Finally, wider conclusions are drawn, as the confusion around pri-vacy policy statements is a symptom of a wider social change in the information society.

Description: The purpose of this work was to investigate the effect of cellulose nanocrystals (CNC) from bamboo fiber on the properties of poly (lactic acid) (PLA)/poly (butylene succinate) (PBS) composites fabricated by melt mixing at 175 °C and then hot pressing at 180 °C. PBS and CNC (0.5, 0.75, 1, 1.5 wt.%) were added to improvise the properties of PLA. The morphological, physiochemical and crystallinity properties of nanocomposites were analysed by field emission scanning electron microscope (FESEM), Fourier-transform infrared spectroscopy (FTIR) and X-ray diffractometry (XRD), respectively. The thermal and tensile properties were analysed by thermogravimetic analysis (TGA), Differential scanning calorimetry (DSC) and Universal testing machine (UTM). PLA-PBS blend shows homogeneous morphology while the composite shows rod-like CNC particles, which are embedded in the polymer matrix. The uniform distribution of CNC particles in the nanocomposites improves their thermal stability, tensile strength and tensile modulus up to 1 wt.%; however, their elongation at break decreases. Thus, CNC addition in PLA-PBS matrix improves structural and thermal properties of the composite. The composite, thus developed, using CNC (a natural fiber) and PLA-PBS (biodegradable polymers) could be of immense importance as they could allow complete degradation in soil, making it a potential alternative material to existing packaging materials in the market that could be environment friendly.

Description: γ-phase aluminum oxide (γ-Al2O3) films are grown on MgO (100) wafers by metal organic chemical vapor deposition (MOCVD). Post-annealing process is conducted to study the influence of annealing temperature on the properties of the films. Structural analyses indicate that all the deposited and annealed films present a preferred growth orientation of γ-Al2O3 (220) along the MgO (200) direction. And the film annealed at 1100 °C exhibits the best film quality compared with those of the films grown and annealed at other temperatures. Scanning electron microscopy measurements also imply the best surface morphology for the γ-Al2O3 film annealed at 1100 °C, which is in good accordance with the structural analyses. Optical transmittance spectra show good transparency for all the deposited and annealed films in the visible wavelength region with an average transmittance value of 83.5%. The optical bandgaps are estimated to be in the range of 5.56–5.79 eV for the deposited and annealed films. Semiconductor films with high optical transmittance in the visible region as well as wide bandgaps are appropriate for the manufacture of transparent optoelectronic devices and ultraviolet optoelectronic devices.

Description: This study examined, the effect of chemically extracted raspberry pomace on the thermal stability, mechanical properties, flammability, chemical structure and processing of poly(vinyl chloride). It was observed that the pomace in this study was used to extract naphtha, thereby permitting the removal of bio-oil as a factor preventing the obtaining of homogeneous composites. Furthermore, adding 20% raspberry pomace filler after extraction extended the thermal stability time for the composites by about 30%. It was observed that composite density, impact strength, and tensile strength values decreased significantly with increasing concentrations of filler in the PVC matrix. At the same time, their modulus of elasticity and Shore hardness increased. All tested composites were characterized by a good burning resistance with a flammability rating of V0 according to the UL94 test. Adding 20 to 40% of a natural filler to the PVC matrix made it possible to obtain composites for the production of flame resistant elements that emitted less hydrogen chloride under fire conditions while ensuring good rigidity.

Description: Vitamins D have various biological activities, as well as intestinal calcium absorption. There has been recent concern about insufficient vitamin D intake. In addition to vitamins D2 and D3, there are lesser-known vitamins D4–D7. We synthesized vitamins D5–D7, which are not commercially available, and then evaluated and compared the mixed micelles-solubilized vitamins D uptake by Caco-2 cells. Except for vitamin D5, the uptake amounts of vitamins D4–D7 by differentiated Caco-2 cells were similar to those of vitamins D2 and D3. The facilitative diffusion rate in the ezetimibe inhibited pathway was approximately 20% for each vitamin D type, suggesting that they would pass through the pathway at a similar rate. Lysophosphatidylcholine enhanced each vitamin D uptake by approximately 2.5-fold. Lysophosphatidylcholine showed an enhancing effect on vitamin D uptake by reducing the intercellular barrier formation of Caco-2 cells by reducing cellular cholesterol, suggesting that increasing the uptakes of vitamins D and/or co-ingesting them with lysophosphatidylcholine, would improve vitamin D insufficiency. The various biological activities in the activated form of vitamins D4–D7 were estimated by Prediction of Activity Spectra for Substances (PASS) online simulation. These may have some biological activities, supporting the potential as nutritional components.

Description: Human gut microbiota (HGM) play a significant role in health and disease. Dietary components, including fiber, fat, proteins and micronutrients, can modulate HGM. Much research has been performed on conventional prebiotics such as fructooligosaccharides (FOS) and galactooligosaccharides (GOS), however, novel prebiotics or micronutrients still require further validation. We assessed the effect of FOS, xylooligosaccharides (XOS) and a mixture of an antioxidant vitamin blend (AOB) on gut microbiota composition and activity, and intestinal barrier in vitro. We used batch fermentations and tested the short-term effect of different products on microbial activity in six donors. Next, fecal inocula from two donors were used to inoculate the simulator of the human microbial ecosystem (SHIME) and after long-term exposure of FOS, XOS and AOB, microbial activity (short- and branched-chain fatty acids and lactate) and HGM composition were evaluated. Finally, in vitro assessment of intestinal barrier was performed in a Transwell setup of differentiated Caco-2 and HT29-MTX-E12 cells exposed to fermentation supernatants. Despite some donor-dependent differences, all three tested products showed beneficial modulatory effects on microbial activity represented by an increase in lactate and SCFA levels (acetate, butyrate and to a lesser extent also propionate), while decreasing proteolytic markers. Bifidogenic effect of XOS was consistent, while AOB supplementation appears to exert a specific impact on reducing F. nucleatum and increasing butyrate-producing B. wexlerae. Functional and compositional microbial changes were translated to an in vitro host response by increases of the intestinal barrier integrity by all the products and a decrease of the redox potential by AOB supplementation.

Description: Associating behavior of star-like amphiphilic polymers consisting of two or three poly(ethylene oxide) (PEO) chains and one stearyl chain (C18) was investigated. Although the aggregation number (Nagg) of linear analogue of amphiphilic polymers monotonically decreased with increasing number-average molecular weight of PEO (Mn,PEO), the Nagg of micelles of star-like amphiphilic polymers with Mn,PEO = 550 g/mol was smaller than that with Mn,PEO = 750 g/mol, whereas that with Mn,PEO ≥ 750 g/mol showed general Mn,PEO dependence. Small-angle X-ray scattering analyses revealed that the occupied area of one PEO chain on the interface between hydrophobic core and corona layer in the micelles of star-like polymers was much narrower than that in the linear amphiphilic polymers. This result indica ted the PEO chains of star-like polymers partially took unfavorable conformation near the core–corona interface in polymer micelles. The effect of local conformation of PEO chains near the interface on the associating behavior became significant as Mn,PEO decreased. Therefore, in polymer micelles of star-like amphiphilic polymers containing PEO with Mn,PEO = 550 g/mol, the enlargement of occupied area of PEO on the core–corona interface should be caused to avoid the formation of unfavorable conformations of partial PEO chains, resulting in a decrease in Naggs.

Description: Laser additive manufacturing is a promising technique for the preparation of complex-shaped SiC composites. High-quality powders are critical for high-precision laser printing. In this work, core-shell Cf @phenolic resin (PR) composites for selective laser sintering of carbon fiber reinforced silicon carbide (Cf/SiC) composites were fabricated by surface modification using 3-aminopropyltriethoxy silane coupling agent (KH550) in combination with planetary ball milling. PR coated uniformly on the fiber surface to form a core-shell structure. The effects of PR on the morphology, elemental composition, interfacial interactions, and laser absorption of the core-shell composite powder were investigated in detail. Results indicated that the composite powder exhibited good laser absorption within the infrared band.

Description: Thermally sprayed 316L stainless steel coatings are commonly used on metallic structures due to their corrosion and wear resistance when compared to carbon steel. Cold Gas Spray (CGS) is a convenient thermal spray process to deposit 316L coatings, producing thick and very dense coatings, with almost no deleterious changes on the feedstock properties to the coating condition. The powder characteristics have influence on the microstructure of the coating, such as porosity and oxide contents, which alter its corrosion and wear behavior. CGS is an efficient technique to reduce the problems associated with material melting commonly found in other conventional thermal spray methods. In this work, different 316L powders, produced by different manufacturers, were deposited by CGS, applying the same equipment and parameters, with the objective to evaluate the relation between the powders’ characteristics and coating properties. Their microstructure, adherence, hardness, as well as the performance on corrosion and wear testing were evaluated. The water atomized powders presented in general better results than gas atomized powders.

Description: One of the reasons for the implementation of information security threats in organizations is the insider activity of its employees. There is a big challenge to detect stego-insiders-employees who create stego-channels to secretly receive malicious information and transfer confidential information across the organization’s perimeter. Especially presently, with great popularity of wireless sensor networks (WSNs) and Internet of Things (IoT) devices, there is a big variety of information that could be gathered and processed by stego-insiders. Consequently, the problem arises of identifying such intruders and their transmission channels. The paper proposes an approach to solving this problem. The paper provides a review of the related works in terms of insider models and methods of their identification, including techniques for handling insider attacks in WSN, as well methods of embedding and detection of stego-embeddings. This allows singling out the basic features of stego-insiders, which could be determined by their behavior in the network. In the interests of storing these attributes of user behavior, as well as storing such attributes from large-scale WSN, a hybrid NoSQL database is created based on graph and document-oriented approaches. The algorithms for determining each of the features using the NoSQL database are specified. The general scheme of stego-insider detection is also provided. To confirm the efficiency of the approach, an experiment was carried out on a real network. During the experiment, a database of user behavior was collected. Then, user behavior features were retrieved from the database using special SQL queries. The analysis of the results of SQL queries is carried out, and their applicability for determining the attribute is justified. Weak points of the approach and ways to improve them are indicated.

Description: Tissue engineering (TE) and regenerative medicine integrate information and technology from various fields to restore/replace tissues and damaged organs for medical treatments. To achieve this, scaffolds act as delivery vectors or as cellular systems for drugs and cells; thereby, cellular material is able to colonize host cells sufficiently to meet up the requirements of regeneration and repair. This process is multi-stage and requires the development of various components to create the desired neo-tissue or organ. In several current TE strategies, biomaterials are essential components. While several polymers are established for their use as biomaterials, careful consideration of the cellular environment and interactions needed is required in selecting a polymer for a given application. Depending on this, scaffold materials can be of natural or synthetic origin, degradable or nondegradable. In this review, an overview of various natural and synthetic polymers and their possible composite scaffolds with their physicochemical properties including biocompatibility, biodegradability, morphology, mechanical strength, pore size, and porosity are discussed. The scaffolds fabrication techniques and a few commercially available biopolymers are also tabulated.

Description: We used a sol–gel spin coating technique to synthesize nanocomposite thin films based on zinc oxide (ZnO) loaded with silver nanoparticles (NPs). We tested these ZnO/Ag NP photocatalysts, with a thickness of about 100 nm, for the photodegradation of the indigo carmine dye solution. The study focused on the effects of Ag NPs on the ZnO matrix as well as the impact of their concentration on the photocatalytic performance of the nanocomposite. The study also highlighted the high stability of the photocatalytic performance of these nanocomposites. This work is a contribution in the search for non-toxic thin film photocatalysts that is usable under solar radiation for the treatment of contaminated wastewater. Innovation in the field of heterogeneous photocatalysis requires the use of solar resource with efficient results in terms of photocatalytic performance.

Description: Antioxidant intake has been suggested to be associated with a reduced osteoporosis risk, but the effect of dietary total antioxidant capacity (TAC) on bone health and the risk of osteoporosis remains unclear. We aimed to assess the hypothesis that dietary TAC is positively associated with bone mass and negatively related to the risk of osteoporosis in Korean women. This cross-sectional study was performed using data from the Korea National Health and Nutrition Examination Survey. Dietary TAC was estimated using task automation and an algorithm with 24-h recall data. In total, 8230 pre- and postmenopausal women were divided into four groups according to quartiles of dietary TAC. Dietary TAC was negatively associated with the risk of osteoporosis (odds ratio, 0.73; 95% confidence interval, 0.54–0.99; p-value = 0.045) in postmenopausal women, but not in premenopausal women. Dietary TAC was positively associated with bone mineral content (BMC) and bone mineral density of the femoral neck and lumbar spine in postmenopausal women and BMC of the total femur and lumbar spine in premenopausal women. Our study suggests that dietary TAC is inversely associated with the risk of osteoporosis in postmenopausal women and positively associated with bone mass in both pre- and postmenopausal women.

Description: Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.

Description: The gut microbiome (GMB) plays an important role in developmental processes and has been implicated in the etiology of psychiatric disorders. However, the relationship between GMB and schizophrenia remains unclear. In this article, we review the existing evidence surrounding the gut microbiome in schizophrenia and the potential for antipsychotics to cause adverse metabolic events by altering the gut microbiome. We also evaluate the current evidence for the clinical use of probiotic and prebiotic treatment in schizophrenia. The current data on microbiome alteration in schizophrenia remain conflicting. Longitudinal and larger studies will help elucidate the confounding effect on the microbiome. Current studies help lay the groundwork for further investigations into the role of the GMB in the development, presentation, progression and potential treatment of schizophrenia.

Description: Existing product anti-counterfeiting and traceability solutions across today’s internationally spanning supply chain networks are indeed developed and implemented with centralized system architecture relying on centralized authorities or intermediaries. Vulnerabilities of centralized product anti-counterfeiting solutions could possibly lead to system failure or susceptibility of malicious modifications performed on product records or various potential attacks to the system components by dishonest participant nodes traversing along the supply chain. Blockchain technology has progressed from simply being a use case of immutable ledger for cryptocurrency transactions, to a programmable interactive environment of developing decentralized and reliable applications addressing different use cases globally. Key areas of decentralization, fundamental system requirements, and feasible mechanisms of developing decentralized product anti-counterfeiting and traceability ecosystems utilizing blockchain technology are identified in this research, via a series of security analyses performed against solutions currently implemented in supply chain industry with centralized architecture. The decentralized solution will be a secure and immutable scientific data provenance tracking and management platform where provenance records, providing compelling properties on data integrity of luxurious goods, are recorded and verified automatically across the supply chain.

Description: The third affiliation of the paper should have been completed in our original article [...]

Description: Background: Zinc is an essential trace element for the normal growth and development of human beings. The main objective was to evaluate the nutritional status of zinc and its association with nutritional indicators in a series of children with chronic diseases. Methods: The prevalence of patients with dietary zinc deficiency or deficit zinc intake (

Description: Bioremediation is a key process for reclaiming polluted soil and water by the use of biological agents. A commonly used approach aims to neutralise or remove harmful pollutants from contaminated areas using live microorganisms. Generally, immobilised microorganisms rather than planktonic cells have been used in bioremediation methods. Activated carbon, inorganic minerals (clays, metal oxides, zeolites), and agricultural waste products are acceptable substrates for the immobilisation of bacteria, although there are limitations with biomass loading and the issue with leaching of bacteria during the process. Various synthetic and natural polymers with different functional groups have been used successfully for the efficient immobilisation of microorganisms and cells. Promise has been shown using macroporous materials including cryogels with entrapped bacteria or cells in applications for water treatment and biotechnology. A cryogel is a macroporous polymeric gel formed at sub-zero temperatures through a process known as cryogelation. Macroporous hydrogels have been used to make scaffolds or supports for immobilising bacterial, viral, and other cells. The production of composite materials with immobilised cells possessing suitable mechanical and chemical stability, porosity, elasticity, and biocompatibility suggests that these materials are potential candidates for a range of applications within applied microbiology, biotechnology, and research. This review evaluates applications of macroporous cryogels as tools for the bioremediation of contaminants in wastewater.

Description: Polysiloxanes are reviewed for their properties depending on the functionalization of a silicon–oxygen backbone chain. Next, the properties were referred to the requirements that polymers used in plastic/polymer-bonded explosive (PBX)-type explosives must meet. Finally, the current state and prospects for the implementation of polysiloxanes in plastic/polymer-bonded explosive (PBX) formulations are presented.