Integrating artificial intelligence (AI) in the construction industry could revolutionise workplace safety and efficiency. However, this integration also carries complex socio-legal implications that require further investigation. Presently, there is a research gap in the socio-legal dimensions of AI use to enhance health and safety regulations and protocols for the construction sector in the United Kingdom, particularly in understanding how the existing legal frameworks can adapt to AI integration effectively. Comprehensive research is indispensable to identify where the existing regulations may fall short or require more specificity in addressing the unique implications introduced by AI technologies. This article aims to address the pressing socio-legal challenges surrounding the integration of AI in the UK construction industry, specifically in enhancing health and safety protocols on construction sites, through a systematic review encompassing the PRISMA protocol. The review has identified that the existing legal and regulatory framework provides a strong foundation for risk management. Still, it needs to sufficiently account for the socio-legal dimensions introduced by AI deployment and how AI may evolve in the future. The Health and Safety Executive (HSE) will require standardised authorities to effectively oversee the use of AI in the UK construction industry. This will enable the HSE to collect data related to AI processes and carry out technical, empirical, and governance audits. The provision of sufficient resources and the empowerment of the HSE within the context of the construction industry are critical factors that must be taken into consideration to ensure effective oversight of AI implementation. Full article

(1) Background: Independently owned restaurants (IORs) are prevalent in under-resourced racial and ethnic minority communities in the US and present a unique setting for public health nutrition interventions. (2) Methods: We conducted 14 in-depth interviews with IOR owners in Baltimore about their perceptions of healthy food, and customers’ acceptance of healthier menus and cooking methods and concurrent observations of the availability of healthy options on their menus. Qualitative data were coded and analyzed using ATLAS.ti. Observations were analyzed with statistical analysis performed in R. (3) Results: Owners perceived non-fried options, lean proteins, and plant-based meals as healthy. While open to using healthier cooking fats, they had mixed feelings about reducing salt, adopting non-frying methods for cooking, and adding vegetables and whole grains to the menu, and were reluctant to reduce sugar in recipes and beverages. Only 17.5% of 1019 foods and 27.6% of 174 beverages in these IORs were healthy, with no significant differences in the healthfulness of restaurant offerings within low-healthy-food-access/low-income neighborhoods and those outside. (4) Conclusion: Healthy options are generally scarce in Baltimore’s IORs. Insights from owners inform future interventions to tailor healthy menu offerings that are well-received by customers and feasible for implementation. Full article

This paper analyzes the effect of crosslinking reactions on a thermoset polymer’s viscoelastic properties. In particular, a numerical model to predict the evolution of epoxy’s mechanical properties during the curing process is proposed and implemented in an Ansys APDL environment. A linear viscoelastic behavior is assumed, and the scaling of viscoelastic properties in terms of the temperature and degree of conversion is modeled using a modified version of the TNM (Tool–Narayanaswamy–Mohynian) model. The effects of the degree of conversion and structural relaxation on epoxy’s relaxation times are simultaneously examined for the first time. This formulation is based on the thermo-rheological and chemo-rheological simplicities hypothesis and can predict the evolution of epoxy’s relaxation phenomena. The thermal–kinetic reactions of curing are implemented in a homemade routine written in APDL language, and the structural module of Ansys is used to predict the polymer’s creep and stress relaxation curves at different temperatures and degrees of conversion. Full article

Background: Colorectal cancer (CRC) significantly contributes to cancer-related mortality, necessitating the exploration of prognostic factors beyond TNM staging. This study investigates the composition of the gut microbiome and microbial DNA fragments in stage II/III CRC. Methods: A cohort of 142 patients with stage II/III CRC and 91 healthy controls underwent comprehensive microbiome analysis. Fecal samples were collected for 16S rRNA sequencing, and blood samples were tested for the presence of microbial DNA fragments. De novo clustering analysis categorized individuals based on their microbial profiles. Alpha and beta diversity metrics were calculated, and taxonomic profiling was conducted. Results: Patients with CRC exhibited distinct microbial composition compared to controls. Beta diversity analysis confirmed CRC-specific microbial profiles. Taxonomic profiling revealed unique taxonomies in the patient cohort. De novo clustering separated individuals into distinct groups, with specific microbial DNA fragment detection associated with certain patient clusters. Conclusions: The gut microbiota can differentiate patients with CRC from healthy individuals. Detecting microbial DNA fragments in the bloodstream may be linked to CRC prognosis. These findings suggest that the gut microbiome could serve as a prognostic factor in stage II/III CRC. Identifying specific microbial markers associated with CRC prognosis has potential clinical implications, including personalized treatment strategies and reduced healthcare costs. Further research is needed to validate these findings and uncover underlying mechanisms. Full article

Drainage pipes are often positioned downstream of embankments to mitigate pore pressure, thereby reducing the risk of dam failure. Considering that the size of drainage pipes is much smaller than that of embankment dams, directly discretizing the drainage pipes will generate a huge number of elements. Therefore, this paper proposes a seepage element containing drainage pipes. In this element, the permeability of the drainage pipe is taken as the third type of permeable conductivity condition, and it is considered in the energy functional. The governing equations for the steady-state and the transient seepage element containing drainage pipe are derived using the variational principle, and the infiltration matrix, equivalent nodal seepage array, and water storage matrix of the seepage element containing drainage pipe are obtained. In conjunction with the user-defined element module UEL of ABAQUS 2016 software, the established seepage element containing drainage pipe is programmed. The accuracy and efficiency of the proposed seepage element containing drainage pipe are verified through seepage field simulations of three examples. Finally, the influence of the permeable conductivity of drainage pipes on the pressure reduction effect is investigated, providing a reference for the layout of drainage pipes in embankment defense systems. Full article

This study investigated the reliability of Zener diodes subjected to a gradually increasing DC switching surge amplitude with delay internals between surges to avoid thermal degradation from different manufacturers with similar specifications. The analysis involved applying occasional 3 ms direct current (DC) switching surges with a gradual increasing surge voltage, followed by a constant current test to verify device functionality for three different selected manufacturer 5.1 V Zener diodes. This experimental approach was used to identify the maximum surge current that each Zener diode could handle before failing to clamp the surge voltage at the specified Zener reference voltage. Statistical analysis revealed significant differences in the maximum average surge current between different manufacturers. The maximum average surge current findings just before failure were 1.98 A, 3.18 A, and 3.33 A, respectively, and associated 95% confidence interval ranges can be used as a reliable metric to compare Zener diode population reliability against occasional DC switching surges. The findings revealed variations in the DC switching surge current handling capabilities between Zener diodes from different manufacturers with similar electrical specifications. The statistically measured maximum average surge current just before device failure can be considered an effective metric to compare the reliability of Zener diodes against DC switching surge degradation. Full article

One of the most challenging problems when diagnosing autism spectrum disorder (ASD) is the need for long sets of data. Collecting data during such long periods is challenging, particularly when dealing with children. This challenge motivates the investigation of possible classifiers of ASD that do not need such long data sets. In this paper, we use eye-tracking data sets covering only 5 s and introduce one metric able to distinguish between ASD and typically developed (TD) gaze patterns based on such short time-series and compare it with two benchmarks, one using the traditional eye-tracking metrics and one state-of-the-art AI classifier. Although the data can only track possible disorders in visual attention and our approach is not a substitute to medical diagnosis, we find that our newly introduced metric can achieve an accuracy of $93\%$ in classifying eye gaze trajectories from children with ASD surpassing both benchmarks while needing fewer data. The classification accuracy of our method, using a 5 s data series, performs better than the standard metrics in eye-tracking and is at the level of the best AI benchmarks, even when these are trained with longer time series. We also discuss the advantages and limitations of our method in comparison with the state of the art: besides needing a low amount of data, this method is a simple, understandable, and straightforward criterion to apply, which often contrasts with “black box” AI methods. Full article

Attapulgite-hydroxyethyl cellulose-poly (acrylic acid-co-2-acrylamide-2-methylpropanesulfonic acid) (ATP-HEC-P(AA-co-AMPS)) in-concrete curing material was synthesized by aqueous solution polymerization using attapulgite (ATP) as an inorganic filler and hydroxyethyl cellulose (HEC) as a backbone. The effects of relevant factors such as ATP dosage, HEC dosage, degree of neutralization, initiator quality, and cross-linking agent quality on the water absorption characteristics of ATP-HEC-P (AA-co-AMPS) were investigated through expansion tests. The micro-morphology of ATP-HEC-P (AA-co-AMPS) was also comprehensively characterized using Fourier transform infrared spectroscopy, scanning electron microscopy, a thermal analysis, and other applicable means. The results showed that the prepared ATP-HEC-P (AA-co-AMPS) had a strong water absorption and water retention capacity, with a water absorption multiplicity of 382 g/g in deionized water and 21.55% water retention capacity after being placed at room temperature for 7 d in a bare environment. Additionally, ATP-HEC-P (AA-co-AMPS) showed good performance for absorbing liquids within the pH range of 7–12. The material’s thermal stability and mechanical properties were also significantly improved after the addition of ATP. The preparation cost is low, the process is simple, and the material meets the requirements for concrete curing materials. Full article

The COVID-19 pandemic has made assessing vaccine efficacy more challenging. Besides neutralizing antibody assays, systems vaccinology studies use omics technology to reveal immune response mechanisms and identify gene signatures in human peripheral blood mononuclear cells (PBMCs). However, due to their low proportion in PBMCs, profiling the immune response signatures of dendritic cells (DCs) is difficult. Here, we develop a predictive model for evaluating early immune responses in dendritic cells. We establish a THP-1-derived dendritic cell (TDDC) model and stimulate their maturation in vitro with an optimal dose of attenuated yellow fever 17D (YF-17D). Transcriptomic analysis reveals that type I interferon (IFN-I)-induced immunity plays a key role in dendritic cells. IFN-I regulatory biomarkers (IRF7, SIGLEC1) and IFN-I-inducible biomarkers (IFI27, IFI44, IFIT1, IFIT3, ISG15, MX1, OAS2, OAS3) are identified and validated in vitro and in vivo. Furthermore, we apply this TDDC approach to various types of vaccines, providing novel insights into their early immune response signatures and their heterogeneity in vaccine recipients. Our findings suggest that a standardizable TDDC model is a promising predictive approach to assessing early immunity in DCs. Further research into vaccine efficacy assessment approaches on various types of immune cells could lead to a systemic regimen for vaccine development in the future. Full article

Lysophosphatidic acid (LPA) type 3 (LPA₃) receptor mutants were generated in which the sites detected phosphorylated were substituted by non-phosphorylatable amino acids. Substitutions were made in the intracellular loop 3 (IL3 mutant), the carboxyl terminus (Ctail), and both domains (IL3/Ctail). The wild-type (WT) receptor and the mutants were expressed in T-REx HEK293 cells, and the consequences of the substitutions were analyzed employing different functional parameters. Agonist- and LPA-mediated receptor phosphorylation was diminished in the IL3 and Ctail mutants and essentially abolished in the IL3/Ctail mutant, confirming that the main phosphorylation sites are present in both domains and their role in receptor phosphorylation eliminated by substitution and distributed in both domains. The WT and mutant receptors increased intracellular calcium and ERK 1/2 phosphorylation in response to LPA and PMA. The agonist, Ki16425, diminished baseline intracellular calcium, which suggests some receptor endogenous activity. Similarly, baseline ERK1/2 phosphorylation was diminished by Ki16425. An increase in baseline ERK phosphorylation was detected in the IL3/Ctail mutant. LPA and PMA-induced receptor interaction with β-arrestin 2 and LPA₃ internalization were severely diminished in cells expressing the mutants. Mutant-expressing cells also exhibit increased baseline proliferation and response to different stimuli, which were inhibited by the antagonist Ki16425, suggesting a role of LPA receptors in this process. Migration in response to different attractants was markedly increased in the Ctail mutant, which the Ki16425 antagonist also attenuated. Our data experimentally show that receptor phosphorylation in the distinct domains is relevant for LPA₃ receptor function Full article

The high-temperature stability of RuAl-based electrodes for application in microelectronic devices is analyzed for long-term duration. The electrodes are prepared on Ca₃TaGa₃Si₂O₁₄ (CTGS) substrates using SiO₂ and Al-N-O cover and barrier layers as oxidation protection. The samples are annealed at 600, 700, or 800 °C in air for 192 h. Minor degradation is observed after thermal loading at 700 °C. The annealing at 800 °C for 192 h leads to a partial oxidation of the Al in the extended contact pad and to a complete oxidation of the Al within the structured interconnect electrodes. The different degradation of the interconnect electrodes and the contact pads is caused by their different lateral dimensions. In summary, long-term high-temperature stability is demonstrated up to at least 700 °C in air. Less oxidizing atmospheres should allow the application at higher temperatures and for a significantly longer duration. Full article

Seventy-one healthy subjects with sleep disturbances participated in a randomized, double-blind controlled trial in which dietary supplementation with an extract of Aloysia citrodora (lemon verbena) (n = 33) or placebo (n = 38) was administered for 90 days. There were between-group differences in favor of the experimental group in the visual analogue scale (VAS) for sleep quality (6.5 ± 1.6 vs. 5.5 ± 2.1, p = 0.021) as well as in the overall score (5.8 ± 2.4, p = 0.008) and scores for sleep latency (1.6 ± 1.0 vs. 1.9 ± 0.7, p = 0.027) and sleep efficiency (84.5 ± 12.8 vs. 79.8 ± 13.6, p = 0.023) in the Pittsburgh Sleep Quality Index (PSQI). Sleep-related variables (latency, efficiency, wakefulness after sleep onset, awakenings) assessed by actigraphy also showed better scores in the experimental group (p = 0.001). Plasma nocturnal melatonin levels also increased significantly in the experimental group (199.7 ± 135.3 vs. 174.7 ± 115.4 pg/mL, p = 0.048). Changes in anthropometric parameters and physical activity levels were not found. In summary, a dietary supplement of lemon verbena administered for 3 months was associated with a significant improvement in sleep quality as compared with placebo in a population of healthy subjects with sleep problems. Full article

High-density lipoproteins (HDLs) are key regulators of cellular cholesterol homeostasis but are functionally altered in many chronic diseases. The factors that cause HDL functional loss in chronic disease are not fully understood. It is also unknown what roles antioxidant carotenoids play in protecting HDL against functional loss. The aim of this study was to measure how various disease-associated chemical factors including exposure to (1) Cu²⁺ ions, (2) hypochlorous acid (HOCL), (3) hydrogen peroxide (H₂O₂), (4) sialidase, (5) glycosidase, (6) high glucose, (7) high fructose, and (8) acidic pH, and the carotenoid antioxidants (9) lutein and (10) zeaxanthin affect HDL functionality. We hypothesized that some of the modifications would have stronger impacts on HDL particle structure and function than others and that lutein and zeaxanthin would improve HDL function. HDL samples were isolated from generally healthy human plasma and incubated with the corresponding treatments listed above. Cholesterol efflux capacity (CEC), lecithin–cholesterol acyl transferase (LCAT) activity, and paraoxonase-1 (PON1) activity were measured in order to determine changes in HDL functionality. Median HDL particle diameter was increased by acidic pH treatment and reduced by HOCl, high glucose, high fructose, N-glycosidase, and lutein treatments. Acidic pH, oxidation, and fructosylation all reduced HDL CEC, whereas lutein, zeaxanthin, and sialidase treatment improved HDL CEC. LCAT activity was reduced by acidic pH, oxidation, high fructose treatments, and lutein. PON1 activity was reduced by sialidase, glycosidase, H₂O₂, and fructose and improved by zeaxanthin and lutein treatment. These results show that exposure to oxidizing agents, high fructose, and low pH directly impairs HDL functionality related to cholesterol efflux and particle maturation, whereas deglycosylation impairs HDL antioxidant capacity. On the other hand, the antioxidants lutein and zeaxanthin improve or preserve both HDL cholesterol efflux and antioxidant activity but have no effect on particle maturation. Full article

Continuous non-invasive blood pressure (CNBP) monitoring is of the utmost importance in detecting and managing hypertension, a leading cause of death in the United States. Extensive research has delved into pioneering methods for predicting systolic and diastolic blood pressure values by leveraging pulse arrival time (PAT), the time difference between the proximal and distal signal peaks. The most widely employed pairing involves electrocardiography (ECG) and photoplethysmography (PPG). Possessing similar characteristics in terms of measuring blood flow changes, a recently investigated optical signal known as speckleplethysmography (SPG) showed its stability and high signal-to-noise ratio compared with PPG. Thus, SPG is a potential surrogate to pair with ECG for CNBP estimation. The present study aims to unlock the untapped potential of SPG as a signal for non-invasive blood pressure monitoring based on PAT. To ascertain SPG’s capabilities, eight subjects were enrolled in multiple recording sessions. A third-party device was employed for ECG and PPG measurements, while a commercial device served as the reference for arterial blood pressure (ABP). SPG measurements were obtained using a prototype smartphone-based system. Following the completion of three scenarios—sitting, walking, and running—the subjects’ signals and ABP were recorded to investigate the predictive capacity of systolic blood pressure. The collected data were processed and prepared for machine learning models, including support vector regression and decision tree regression. The models’ effectiveness was evaluated using root-mean-square error and mean absolute percentage error. In most instances, predictions utilizing ${PAT}_{SPG}$ exhibited comparable or superior performance to ${PAT}_{PPG}$ (i.e., SPG Rest ± 12.4 mmHg vs. PPG Rest ± 13.7 mmHg for RSME, and SPG 8% vs. PPG 9% for MAPE). Furthermore, incorporating an additional feature, namely the previous SBP value, resulted in reduced prediction errors for both signals in multiple model configurations (i.e., SPG Rest ± 12.4 mmHg to ±3.7 mmHg for RSME, and SPG Rest 8% to 3% for MAPE). These preliminary tests of SPG underscore the remarkable potential of this novel signal in PAT-based blood pressure predictions. Subsequent studies involving a larger cohort of test subjects and advancements in the SPG acquisition system hold promise for further improving the effectiveness of this newly explored signal in blood pressure monitoring. Full article

Detecting objects, particularly naval mines, on the seafloor is a complex task. In naval mine countermeasures (MCM) operations, sidescan or synthetic aperture sonars have been used to search large areas. However, a single sensor cannot meet the requirements of high-precision autonomous navigation. Based on the ORB-SLAM3-VI framework, we propose ORB-SLAM3-VIP, which integrates a depth sensor, an IMU sensor and an optical sensor. This method integrates the measurements of depth sensors and an IMU sensor into the visual SLAM algorithm through tight coupling, and establishes a multi-sensor fusion SLAM model. Depth constraints are introduced into the process of initialization, scale fine-tuning, tracking and mapping to constrain the position of the sensor in the z-axis and improve the accuracy of pose estimation and map scale estimate. The test on seven sets of underwater multi-sensor sequence data in the AQUALOC dataset shows that, compared with ORB-SLAM3-VI, the ORB-SLAM3-VIP system proposed in this paper reduces the scale error in all sequences by up to 41.2%, and reduces the trajectory error by up to 41.2%. The square root has also been reduced by up to 41.6%. Full article

Engineering managers leverage the expertise of engineers in their teams to inform decisions. Engineers may convey their expertise in the form of opinions and/or judgements. Given a decision, it is common to elicit and aggregate the expertise from various engineers to capture a broader set of experiences and knowledge. Establishing an internally and externally consistent aggregation framework is therefore paramount to yield a meaningful aggregation, that is, to make sure that the expertise of each engineer is accounted for reasonably. However, we contend that most de facto aggregation techniques lack such consistency and lead to the inadequate use and aggregation of engineering expertise. In this paper, we investigate the consistency or lack thereof of various expertise aggregation techniques. We derive implications of such inconsistencies and provide recommendations about how they may be overcome. We illustrate our discussion using safety decisions in engineering as a notional case. Full article

Generative Artificial Intelligence (AI) is heralding a new era in AI for performing a spectrum of complex tasks that are indistinguishable from humans. Alongside language and text, Generative AI models have been built for all other modalities of digital data, image, video, audio, and code. The full extent of Generative AI and its opportunities, challenges, contributions, and risks are still being explored by academic researchers, industry practitioners, and government policymakers. While this deep understanding of Generative AI continues to evolve, the lack of fluency, literacy, and effective interaction with Generative and conventional AI technologies are common challenges across all domains. Tertiary education institutions are uniquely positioned to address this void. In this article, we present the human-centred design of a universal AI literacy module, followed by its four primary constructs that provide core competence in AI to coursework and research students and academic and professional staff in a tertiary education setting. In comparison to related work in AI literacy, our design is inclusive due to the collaborative approach between multiple stakeholder groups and is comprehensive given the descriptive formulation of the primary constructs of this module with exemplars of how they activate core operational competence across the four groups. Full article

Going on holiday is often associated with taking the car or plane. Even for short distances, and where alternative, sustainable transportation modes would be available, we frequently choose the more unsustainable options. Affordability, comfortability, and time savings led to an increase in transportation, which in turn, negatively contributed to greenhouse gas emissions. The reduction in those emissions can be achieved by choosing public transportation. However, since transportation choices are often made unconsciously and habitually, it is crucial to transform those unsustainable habits into more sustainable ones. Contextual changes can serve as a catalyst. This research investigates whether pre-COVID-19 and pre-inflation unsustainable travel habits can be broken through the perceived impact of COVID-19, financial hardship, and green consumption values, increasing the intention for sustainable transportation modes using a survey design. We found that the context change, as such, does not predict future intentions to travel sustainably, but existing green consumption values do. Building on the self-activation theory, the results show that habits and the perceived impact of COVID-19 and financial hardship activate a person’s green consumption values. Consumers’ green values mediate the relationship between unsustainable habits and the intentions to use sustainable transportation modes, combining the habit discontinuity and self-activation hypotheses. Full article

Accurately assessing carbon emissions from recycling scrap steel is essential for reducing emissions in the steel industry, especially in China, the world’s largest crude steel producer. In this study, a carbon emission reduction index was introduced to evaluate the effectiveness of recycling scrap steel in reducing emissions. The index considers the three processes used in scrap steel recycling: blast furnace ironmaking, converter steelmaking, and electric arc furnace steelmaking. This study developed an evaluation model using fuzzy analytic hierarchy process and iterative cluster analysis to determine the reduction of carbon emission. From a life cycle perspective, this study identified primary factors contributing to emissions, including fuel, raw materials, electric energy, and auxiliary materials. Then, the carbon emission reduction index for scrap recycling was developed by examining the production of one ton of steel and each additional ton of scrap steel, which can provide valuable insights into the environmental impact of scrap recycling. Finally, the study forecasts the future Carbon Emission Reduction Index for steel scrap recycling. The study indicates an increase in the carbon emission reduction index for scrap recycling prior to 2017, followed by a decrease about 11.8% from 2017 to 2018 and increases from 2018 to 2021. Finally, it dropped by 8.7% per cent in 2022. Similarly, the carbon emission reduction index for electric furnace steelmaking increased prior to 2019, then subsequently decreased. It is changing by ten per cent a year. Additionally, the scrap recycling index experienced a significant decrease of 90% in 2015, followed by a gradual increase until 2017 and then a consistent decrease every year thereafter. The index suddenly rose in 2021 and then decreased change for policy reasons. The forecast results suggest a gradual increase in the carbon emission reduction index per ton of steel scrap in the future. In conclusion, the practicable modeling methodology has the ability to assist government organizations and private enterprises in devising efficient green and low-carbon development tactics. Full article

Magnetic resonance imaging (MRI) can facilitate accurate organ delineation and optimal dose distributions in high-dose-rate (HDR) MRI-Assisted Radiosurgery (MARS). Its use for this purpose has been limited by the lack of positive-contrast MRI markers that can clearly delineate the lumen of the HDR applicator and precisely show the path of the HDR source on T1- and T2-weighted MRI sequences. We investigated a novel MRI positive-contrast HDR brachytherapy or interventional radiotherapy line marker, C4:S, consisting of C4 (visible on T1-weighted images) complexed with saline. Longitudinal relaxation time (T1) and transverse relaxation time (T2) for C4:S were measured on a 1.5 T MRI scanner. High-density polyethylene (HDPE) tubing filled with C4:S as an HDR brachytherapy line marker was tested for visibility on T1- and T2-weighted MRI sequences in a tissue-equivalent female ultrasound training pelvis phantom. Relaxivity measurements indicated that C4:S solution had good T1-weighted contrast (relative to oil [fat] signal intensity) and good T2-weighted contrast (relative to water signal intensity) at both room temperature (relaxivity ratio > 1; r2/r1 = 1.43) and body temperature (relaxivity ratio > 1; r2/r1 = 1.38). These measurements were verified by the positive visualization of the C4:S (C4/saline 50:50) HDPE tube HDR brachytherapy line marker on both T1- and T2-weighted MRI sequences. Orientation did not affect the relaxivity of the C4:S contrast solution. C4:S encapsulated in HDPE tubing can be visualized as a positive line marker on both T1- and T2-weighted MRI sequences. MRI-guided HDR planning may be possible with these novel line markers for HDR MARS for several types of cancer. Full article

This article presents the findings of a study on the directionality effect observed in strong motion records. We set out to establish ratios between several seismic intensity measures that depend on sensor orientation (e.g., GM_ar, Larger) and others that are orientation-independent (e.g., RotDpp, GMRotDpp, and GMRotIpp), with the intention of proposing multiplicative correction factors. The analysis included an evaluation of the impact of site conditions, ground motion intensity, earthquake magnitude, and hypocentral distance on these ratios. Following a concise overview of the directionality effects and the associated intensity measures, the Costa Rican Strong Motion Database, comprising a total of 4199 horizontal accelerograms (two components), was employed to determine the correction factors. The analysis was carried out for 5% damped response spectra within the 0.01–5 s period range. The study focuses on orientation-independent intensity measures that are derived by combining the maximum values from the recorded motions. In the comprehensive analysis of the complete database, a trend was observed between these intensity measures and the magnitude of the earthquake along with the hypocentral distance. Specifically, records from earthquakes with greater magnitudes exhibited a lower maximum spectral response to the geometric mean of the response spectra of the as-recorded (ar) components ratio (RotD100/GM_ar), similar to records from earthquakes with larger hypocentral distances. Based on these findings, a proposal was put forth to estimate RotD100 values using GM_ar values. This ratio can prove useful in transforming data from previous seismic hazard studies, including those applied in many seismic codes, and in defining the maximum anticipated seismic intensity for design purposes in a more straightforward manner. Full article

Ischnura senegalensis, which widely spreads in paddy fields, has the potential to be used as a natural predator of insect pests. However, the application of insecticides in the field could pose a threat to the survival of I. senegalensis. Among these pesticides, indoxacarb, an oxadiazine insecticide, is renowned for its broad-spectrum efficacy against numerous insect pests. In this study, we examined the toxicity of indoxacarb towards the larvae of I. senegalensis. Behavioral experiments and transcriptome analyses were conducted under indoxacarb treatments. Results revealed that indoxacarb induced abnormal body gestures and significant locomotory impairments, which could ultimately reduce the survival rate of the larvae in their natural habitat. Moreover, transcriptome analyses indicated that genes related to muscle function were significantly affected. Interestingly, at lower concentrations of indoxacarb (0.004 mg/L), the larvae seem to detoxify the indoxacarb with the aid of the cytochrome P450 gene. However, under higher concentrations (0.4 mg/L), the sensory abilities of the larvae were significantly diminished, and they were unable to degrade the toxicity of indoxacarb. Our study underscores the importance of carefully evaluating the impact of insecticides on non-target predatory insects before their widespread application. Full article