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Bamboo has being used as alternative raw material for construction, reinforcing fibers, paper production, among other applications. Although its recognized potentials as raw material, there are doubts about its environmental performance compared to traditional wood-based products, including paper production, which hinders bamboo-based paper plants in large scales. This study aims to assess the environmental performance of producing office paper from bamboo. Emergy synthesis (with 'm') and global warming potential indicators are calculated and compared with the traditional eucalyptus paper-based production. Results highlights the importance in including the renewability fractions of each input resources into emergy calculations for production systems with high human-labor intensity such as the bamboo agricultural production. Office paper produced from bamboo has similar renewability (28%), moderate environmental load (3.23 vs. 2.49), and emergy unsustainability (0.34 vs. 0.60) compared to paper produced from eucalyptus, but bamboo showed lower performance for global efficiency (568 vs. 442 sej/ton paper), emergy yield (1.09 vs. 1.49), and emergy investment (10.79 vs. 2.05). Focusing on global warming potential, office paper produced from bamboo releases 98 kgCO 2 eq. /ton paper compared to 56–267 kgCO 2 eq. /ton paper for eucalyptus. Notwithstanding, bamboo-based office paper demands four times more land area of agricultural production than eucalyptus, but it has a positive social aspect by requiring higher amount of direct human labor. This work shows the advantages of using eucalyptus rather than bamboo in producing office paper from an emergy and land demand perspectives, while global warming can still be considered inconclusive. Future efforts should consider a quantitative and qualitative analysis of human labor availability in both systems, as well an economic analysis to support discussions towards more sustainable office paper production from different raw materials. • Environmental load of bamboo and eucalyptus for office paper production are compared. • Bamboo has lower emergy performance than eucalyptus. • Including the renewability fraction of labor and services better reflects emergy results. • Bamboo paper emits 98kgCO2eq/ton, eucalyptus paper emits 56–267kgCO2eq/ton. • Bamboo paper needs 4x land compared to eucalyptus and requires more human labor. [ABSTRACT FROM AUTHOR]

There is now a growing interest in early-life influences on adult diseases in China. A number of birth cohorts have been established. This systematic review provided a better understanding of the development of mother–baby cohorts in China. Systematic review. We conducted a systematic review for research or profile papers in English/Chinese that reported data from mother–baby cohorts in mainland China, with ≥1y follow-up after birth. We identified 315 papers, corresponding to 31 cohorts from 19 provinces/megacities. All cohorts started in 1999–2017 (21 after 2010) and were set up with broad objectives or specific scientific focus. The baseline sample size varied, from <500 to >300,000 mothers. A majority of cohorts were initiated during pregnancy and followed children to <10y, only six to adolescence and none into adulthood. These cohorts mostly collected samples from mothers and babies, in addition to using interviews/questionnaires to collect information about pregnancy, birth and child health. Most cohorts were recruited from a single province/city. The large western region was understudied. Mother–baby cohorts have developed rapidly in China, but usually with a short follow-up duration. Extending the follow-up of children and developing cross-cohort collaboration will increase the diversity, size and coverage of the sample, allow studying early influences on life-course health and identify targets for early intervention in the Chinese population. [ABSTRACT FROM AUTHOR]

The mechanical vapor compression system (MVC) coupled with the evaporative-cooling condenser is an effective method to improve its high temperature adaptability. However, this hybrid systems typically use an evaporative cooler as a single-stage pre-cooling unit of condenser and is mainly designed for hot–dry climates. In this paper, based on conventional evaporative-cooling condenser configuration, three two-stage evaporative-cooling condenser systems (MVC-TSEC(A), MVC-TSEC(B) and MVC-TSEC(C)) were proposed. The MVC-TSEC(A) consists of one condenser and an indirect/direct evaporative-cooler. The MVC-TSEC(B) and MVC-TSEC(C) have two condensers (in series), which are coupled with a two-stage evaporative cooling system. The refrigerant in the MVC-TSEC(C) forms a counter-flow configuration with the outdoor air, while it is concurrent flow in MVC-TSEC(B). Subsequently, the effects of the ambient parameters and outdoor air flowrate on the three two-stage hybrid systems were analyzed comparatively based on detailed numerical models. Finally, the application potential of these hybrid systems was evaluated comprehensively in hot–humid climates. The results showed that the seasonal COP and energy-saving rate for the MVC-TSEC(C) are reached by 4.2–4.7 and 12.7–21.1 %, respectively. Moreover, the static equipment payback period of the three two-stage hybrid systems are 3.8, 3.3 and 3.0 years, respectively. [ABSTRACT FROM AUTHOR]

Hydrogen stands out as a compelling alternative to fossil fuels for combustion engines. Predictive combustion models are instrumental in developing hydrogen-fuelled engines. A fundamental metric of these models is the laminar burning velocity (LBV), which can be precisely determined through laminar flame propagation simulations. In this context, the selection of an appropriate combustion mechanism is critical. This paper aims to propose the appropriate combustion mechanism for calculating LBV in predictive combustion models of hydrogen-fuelled engines. 15 state-of-the-art combustion mechanisms were applied to reproduce the LBV measurements in engine-like conditions, especially considering the application of lean combustion and water injection. The FFCM 1.0 mechanism was identified from them and further optimised to improve its prediction accuracy at elevated pressures for the lean mixture. The maximum deviation of LBV was reduced from 17.6 % to 8.7 % by this optimisation, in comparison to 10.5 % for its closest competitor mechanism, ELTE (Varga et al., 2015). • 15 combustion mechanisms were selected as the candidates for optimisation. • Test cases consider applications of lean combustion and water injection. • Many mechanisms predict laminar burning velocities at elevated pressure inadequately. • FFCM 1.0 mechanism was optimised to a new mechanism for modelling H2-fuelled engines. • Prediction errors of laminar burning velocity by the new mechanism are within 8.7 %. [ABSTRACT FROM AUTHOR]

• This works confirms the interest of differentiating car drivers and motorcyclists. • The results show an effect of both the type of vehicle and the health crisis on the rules respected. • This wok allows for theoretical reflection on the construction of the relationship to social and legal rule. The aim of this article is to examine the construction of the relationship with rules, their links in individuals throughout their lives and their possible interactions. More precisely, this paper looks at the impact of the health crisis, COVID 19, on compliance with road rules among three categories of road user: car drivers, motorcyclists with a cylinder capacity of no more or more than 125 cm3. A questionnaire was designed and distributed to 4382 car users, motorcyclists with a cylinder ca-pacity of more or no more than 125 cm3. representative of the French population. The results show an effect of both the type of vehicle and the health crisis on the frequency and number of safety rules respected. These results confirm the value of differentiating the road-user population by showing the differences between motorists and motorcyclists, which are not due solely to the mode of travel used. In terms of road safety policy, they show the importance of prevention campaigns targeting different modes of travel, and taking into account the specificities of their users in terms of perception of rules and the factors involved in their observance. [ABSTRACT FROM AUTHOR]

Human desire to explore Mars has persisted throughout history, and especially, it is required to achieve precise and safe landings on the Martian surface. The atmospheric entry phase plays a crucial role in ensuring mission success, and active research on entry guidance methods continues. This paper presents a comparative study between the two primary types of entry guidance methods: (1) path planning-tracking and (2) predictor–corrector methods by applying them to solve two distinct Mars atmospheric entry guidance problems: (a) robotic entry and (b) human entry missions. Optimization approaches are adopted for the path planning-tracking method. After generating an optimal reference trajectory based on a mission concept-defined cost function, the receding horizon control method is employed to minimize tracking errors. In the predictor–corrector method, two parameterized entry guidance approaches are explored and analyzed. A well-known numerical predictor–corrector method that utilizes a parameterized bank angle profile for entry trajectory generation is tested to demonstrate its robustness against random dispersions. On the other hand, another predictor–corrector type guidance method that assumes a polynomial shape to shape an altitude profile over range-to-go is adopted to show its range control capability. Numerical simulations reveal the pros and cons of each type of entry guidance method, and a suitable guidance method for each Mars entry mission is identified depending on the mission concept and requirements. The analysis results provide future work. • A comparative study between path planning-tracking and predictor-corrector guidance methods. • Mars atmospheric entry problem for robotic and human landing missions. • Optimization approaches for reference trajectory generation and path tracking. • Numerical predictor-corrector based on parameterized bank angle and altitude profiles. [ABSTRACT FROM AUTHOR]

• Methodology for a complete geometrical analysis of the vaults of Notre-Dame de Paris after the fire. • 2D image-based method for comparison before and after the fire. • 3D point cloud-based method for comparison before and after the fire. • New method for accurate alignment of very large point clouds. The work presented in this article was carried out following the fire (April 15, 2019) that ravaged Notre-Dame de Paris. The goal was to establish in a short and limited time-span the structural diagnosis of the remaining vaults of the cathedral. The analysis relied on 2D and 3D data acquired before and after the fire, and available at that time. Two complementary methods have been developed to estimate potential displacements from multi-temporal surveys. The first method is mainly based on the processing of image collections obtained with photogrammetric routines right after the fire. The second method, based on the processing of raw 3D data acquired with Terrestrial Laser Scanning, was developed afterward to refine and complete the analysis. Both methods have benefited from essential functionalities offered by two open-source solutions proven to enable "real-based" modeling in Cultural Heritage contexts, namely Micmac and CloudCompare. This paper presents the complementary use of these two software packages whilst detailing some procedural computing approaches to document and support structural diagnosis in an emergency situation. The limits and capabilities of each method are exposed and analyzed, toward the objective to develop 2.5D and 3D based geometrical analysis, respectively from photogrammetric and lasergrammetric sources. The results are presented and discussed regarding their potential usage for a quantitative and accurate diagnosis of vaults. [ABSTRACT FROM AUTHOR]

The escalating demand and complexity of monitoring services handled by Network Operations Centers (NOCs) have led Mobile Network Operators (MNOs) to prioritize automated solutions for network fault detection and diagnosis. Consequently, various Machine Learning (ML)-based Root Cause Analysis (RCA) systems have been developed, however their lack of explainability poses a challenge due to the predominantly black-box nature of ML models. This paper addresses this issue by presenting a supervised clustering methodology capable of integrating both glass-box and black-box models, the latter complemented by post-hoc explainability techniques. While black-box models excel in predictive capabilities, necessitating post-hoc techniques for explainability, glass-box models prioritize transparent decision-making, fostering a clearer understanding of the model's behavior. This work delineates a methodology for performing RCA of faults in the User Downlink (DL) Average Throughput Key Performance Indicator (KPI), simultaneously comparing the performance of black-box models (Light Gradient-Boosting Machine (LightGBM) and Extreme Gradient Boosting (XGBoost)) with glass-box models (Logistic Regression (LR) and Explainable Boosting Machine (EBM)). Results revealed that the LightGBM black-box algorithm coupled with the SHapley Additive exPlanations (SHAP) method demonstrated superior performance in fault detection and diagnosis, without compromising the overall explainability. Consequently, it was possible to identify faults related to radio conditions, low network usage in specific user groups, low network capacity, and mobility issues. The paper concludes with practical mitigation strategies for each identified fault cluster. • Supervised clustering detects and diagnoses critical mobile network KPI failures. • LightGBM + SHAP outperformed other models in detecting User DL THP faults. • The methodology diagnosed User DL faults as radio, usage, capacity, and mobility. [ABSTRACT FROM AUTHOR]

As many services convert to digital based on human-machine communication technology, older adults face considerable challenges. With the goal to identify ways to design digital services that are easier for older adults to use, this paper uses the strategy of making self-ordering kiosks more similar to the original version (i.e., paper menu) focusing on three familiarity design approaches: representation, manipulation, and organization. A 2 (skeuomorphic vs. flat design) x 2 (hierarchical vs. linear navigation structure) between-subject design experiment was conducted with individuals aged over 65 years (N = 60). Participants perceived that the skeuomorphic design was easier to use compared to the flat design, and the linear navigation structure increased perceived self-efficacy, usefulness, and intention to use compared to the hierarchical navigation structure. Participants also completed the tasks more quickly in the skeuomorphic design (vs. flat design) and linear navigation structure (vs. hierarchical structure) conditions. Interaction effects suggest that the task completion time was further reduced when skeuomorphic design was used with a linear navigation structure. Furthermore, fewer people requested assistance when they used a linear navigation structure. Serial multiple mediation results showed that the influence of linear navigation structure on intention to use was mediated by perceived self-efficacy and usefulness. • Skeuomorphic design offers better user experience for seniors than the flat one. • Linear navigation structure offers better user experience for seniors than the hierarchical one. • Combining skeuomorphism and linear structure decreases the task completion time. • The effect of linear navigation structure on intention to use is mediated by self-efficacy and perceived usefulness. [ABSTRACT FROM AUTHOR]

At present, ubiquitous learning has been becoming an important learning style for college students. However, the current studies on ubiquitous learning mostly focus on aspects such as communication and data interaction methods, while ignoring students' academic emotions. In this paper, we propose an individual adaptive ubiquitous learning paradigm that focuses on college students' academic emotions. The paradigm collects and analyses students' academic emotions to grasp student's individual characteristics. Then, the adaptive planning and adjusting learning contents is beneficial for improving students' academic emotions and enhancing the ubiquitous learning effects, initiative and concentration. In this study, the 2-year-long comparative experiments and tracking analyses were conducted from four aspects: academic grades, average study hours in after-school spare time, academic emotions status and classroom participation. The experimental results show that the individual adaptive ubiquitous learning paradigm proposed in this paper has significant positive effects and impacts on college students' learning outcomes, initiative, engagement and academic emotions. • An individual adaptive ubiquitous learning paradigm considering the impact of academic emotions is proposed. • The paradigm focuses on academic emotions to adaptively adjust individual learning content. • Academic emotions analysis and adjustment algorithms are designed to improve learning outcomes. [ABSTRACT FROM AUTHOR]

Social gradients in health and aging have been reported in studies across many human populations, and - as the papers included in this special collection highlight – also occur across species. This paper serves as a general introduction to the special collection of Neuroscience and Biobehavioral Reviews entitled "Social dimensions of health and aging: population studies, preclinical research, and comparative research using animal models". Authors of the fourteen reviews are primarily members of a National Institute of Aging-supported High Priority Research Network on "Animal Models for the Social Dimensions of Health and Aging". The collection is introduced by a foreword, commentaries, and opinion pieces by leading experts in related fields. The fourteen reviews are divided into four sections: Section 1: Biodemography and life course studies; Section 2: Social behavior and healthy aging in nonhuman primates; Section 3: Social factors, stress, and hallmarks of aging; Section 4: Neuroscience and social behavior. [ABSTRACT FROM AUTHOR]

• Childcare policy responses towards Covid-19 differed in European welfare states. • Policy responses cause informalization of childcare to different degrees. • Informalization of childcare is mainly connected with social risks for women. • Cultural and institutional differences help to understand varying policy responses. The closure of extra-familial childcare facilities by European governments in 2020 was an important part of interventions against the spread of the COVID-19 pandemic. One consequence was that childcare was provided by parents at home, mainly by women. As a result, women mainly experienced financial and employment risks related to this "informalization" of childcare. The childcare policies of European welfare states differ in the extent to which they include measures to reduce the social risks related to informalization. Against this backdrop, this paper asks: How should one understand cross-national differences in childcare policies during the pandemic? We are also particularly interested in the effects of childcare policies on the social risks connected with the informalization of childcare and what these mean for the gendered division of paid work and care. Differences in childcare policies during the pandemic are commonly explained in terms of the path dependence of such policies. Using the theoretical approach of "care arrangement," this article introduces a broader theoretical framework that considers the role of cultural and institutional factors for understanding the cross-national differences in childcare policies during the pandemic. We introduce the findings of a comparative empirical study of childcare policies in three European welfare states—Denmark, Germany and England—that represent different types of care arrangements. This paper uses policy and media documents, quantitative data on childcare and women's employment, cultural ideas and secondary analysis of empirical studies. We find that governments did not per se respond to the pandemic based on institutional path dependence regarding childcare policies, while the integration of culture into the theoretical framework allows for a more comprehensive understanding. [ABSTRACT FROM AUTHOR]

During shading conditions, performance of physical relocation techniques for PV formations is more effective than total cross-tied (TCT) type of PV formation. The main purpose of physical relocation technique is to rearrange the physical position of PV modules in TCT formation without changing the electrical connections. Due to relocation of PV modules, the lengths of required wires are increased. So, the appropriate selection of PV formation is also important. In this paper, three different variants of physical relocation techniques are considered for 6×6 size TCT formation. These three variants are named as SuDoKu (SDK), ShapeDoKu (SPDK) and Futoshiki (FS). Moreover, these variants are analyzed on realistic assumptions of shading situations and these shading situations are categorized into eight different cases. Also, the comparative analysis of PV formations is reported in terms of P-V profiles, effects of shadings on individual rows and generation of energy and incomes. Further, from the obtained results of this paper, it is concluded that these variants of physical relocation techniques enhance the output power, energy and income generation in comparison of TCT type of PV formation. The SPDK variant of physical relocation technique is performing better than the other variants. [ABSTRACT FROM AUTHOR]

This paper offers an exhaustive comparison of quantitative PCR (qPCR) and digital PCR (dPCR) technologies, focusing on their critical roles in molecular diagnostics, ranging from pathogen detection, and cancer screening to environment monitoring. The manuscript outlines the foundational theories behind both technologies and scrutinizes their capabilities, advances, and limits. It deeply investigates the primary factors based on the sample's nature, sample preparation strategies, and employing key parameters like reliability, accuracy, and specificity, thus critically evaluating the merits and demerits of each technology. It also proposes the avenues of research and development that impact both technologies. The paper concludes that the choice between qPCR and dPCR depends on factors such as the nature of the sample, the purpose of the study, and practical considerations like cost and operational ease. Our overarching goal is to furnish a guide that aids researchers in selecting the optimal PCR-based technique for their assay development. • Present an exhaustive comparison of quantitative PCR (qPCR) and digital PCR (dPCR) for biosensing applications. • Discusse the foundational theories, recent advances, and limitations of both qPCR and dPCR technologies. • Evaluate qPCR and dPCR based on reliability, accuracy, limit of detection, and specificity. • Provide a guide for researchers to select the optimal PCR technique based on study purpose, and practical considerations. • Forecast the development trajectories of qPCR and dPCR, including integration with AI and POC applications. [ABSTRACT FROM AUTHOR]

• Many mental health disorders first emerge during early childhood or adolescence. • Wait times for children's mental health services have been an international and widespread problem. • Long wait times prolong the emotional distress of children and/or adolescents and their caregivers which can exacerbate mental health difficulties. • The majority of research in this area has been conducted in the United Kingdom and Canada and focus on one waitlist strategy. • Common strategies include alternative service delivery models, increasing system capacity, and improving intake and assessment processes. Background: Although many mental health disorders first emerge during early childhood or adolescence, there is a significant gap between demand and availability of mental health resources, leading to long waitlists for services. Objective: The objective of this scoping review was to identify and characterize the research literature related to the range of waitlist management strategies that have been implemented in outpatient child and adolescent mental health care. Methods: Electronic databases reviewed included: Medline (Ovid), Embase (Ovid), PubMed, PsychINFO, SCOPUS, CINAHL, and ISI Web of Science. Grey literature databases included: OpenGrey, Conference Papers Index, and Proquest Digital Dissertations. Articles were screened by two reviewers in two steps: first by title and abstract, then full text level. Data were extracted using an a-priori developed data extraction framework, which was piloted and modified iteratively. Results: A total of 119 papers related to waitlist interventions in child and adolescent mental health were reviewed. Of these 119 papers, 11% were reviews, summary, or theoretical papers; 8% used a randomized control trial design and 2.5% were trial protocols. Most studies used less rigorous designs, such as uncontrolled before-and- after designs. The large majority focused on just one waitlist strategy each. The most commonly used approaches included: prioritization/triage and initial assessment; brief consultation and advice or brief therapy approaches; group-based models; interim services; increasing capacity; and strategies to decrease non-attendance. Most studies were conducted in the United Kingdom or Canada. Discussion: While mental health systems are complex, most studies examining waitlist initiatives explored the implementation of single initiatives. It is unlikely that a single waitlist strategy can be effective in managing wait times for children's mental health. Rather, consistent and systemic approaches to address wait times that consider the impact of the reduction approach on the patient, the program, and the community are needed. [ABSTRACT FROM AUTHOR]

The paper measures environmental efficiency and productivity change to then carry out a decomposition analysis of an environmental efficiency index and a productivity change index. The paper includes a novel comparative assessment to determine the drivers of environmental efficiency and the sources of productivity change of the manufacturing sector in Europe, Asia and the whole world. We explore the capability to convert in an environmentally efficient way, selected inputs into desirable and undesirable outputs. Our estimation results of environmental efficiency confirm that Europe is ahead the world's average. Our analysis shows, however, a slowdown of Europe compared with the productivity growth of Asia. The latter shows a better performance in management capabilities, optimal resource allocation, and economies of scale. The analysis carried out in a second stage using the dynamic effects of the generalized method of moments also shows that the annual growth rate of manufacturing value added and manufacturing exports positively influence the level of environmental efficiency in both Asia and Europe. Therefore, the internationalization and extroversion of manufacturing can be crucial for sustainable development in Europe and Asia. • Benchmarking the strategy for sustainable development in Asia and Europe. • Decomposition of environmental efficiency indices and productivity change. • Effect of manufacturing value added and exports on environmental efficiency. • Benchmarking the manufacturing sector in Asia and Europe. • Showing Asia's best practices and European pillar of industrial restructuring. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the zone-by-zone changes in Lochkovian conodont biodiversity in the Pyrenees region and compare the results with previous studies. Additionally, the paper seeks to identify evolutionary phases within the Lochkovian. We analyse the stratigraphic range data from eight classical Pyrenean Lochkovian sections. A total of 48 taxa at the species level, primarily confined to the Lochkovian, are included in the analysis. We employ both qualitative and quantitative approaches, including Clark's method for the conodont evolution index and Foote's parameters for measuring taxonomic diversity and rates. The zonal scheme employed in this study follows the global three-fold subdivision of the Lochkovian stage, with additional subdivisions based on local records. The zone-by-zone analysis of stratigraphically well-controlled successions contributes to our understanding of the conodont diversity dynamics in this region. The results are consistent with previous studies, but also highlight the unique aspects of the Pyrenean conodont record. Their highest diversity occurs in the middle Lochkovian within the kutscheri - pandora beta Zone, succeeded by an extinction event towards the end of this interval. Following a brief proliferation of species at the onset of the upper Lochkovian, another extinction event concludes this Stage. Results from all different rate measurements applied to Pyrenean Lochkovian conodonts are in disagreement with the prevailing perspective suggesting an escalation in the proportion of singletons and a concomitant decline in per-taxon rates with an increase in interval length. Comparative analysis of conodont records across various regions (Carnic Alps, Prague Synform, Central Nevada, and the Pyrenees) during the Lochkovian reveals significant differences in biodiversity, taxonomic composition, and zonal distribution. • This study delves into the dynamics of conodont diversity within the Pyrenees region. • The peak of conodont diversity is observed towards the end of middle Lochkovian. • An extinction event affecting conodont is identified at the end of Lochkovian. • Lochkovian conodont rates challenge previous interval length assumptions. • Total diversity and estimated mean diversity produce measurements discrepancy. [ABSTRACT FROM AUTHOR]

This paper investigates a novel CNN-based architecture for image resizing forensics in the presence of Double-JPEG compression. Two sub-problems are addressed as part of this paper: first, the detection of resizing in DJPEG images, and second, determining the factor used to resize the image before the second JPEG compression. The image resizing technique used in this paper is image scaling. The proposed network is based on utilizing specially chosen high pass filters that constitute the pre-processing layer, followed by four convolutional layers, two fully connected layers, and a final softmax layer. The high-pass filters preserve the resizing clues in the form of residuals applied at the pre-processing layer, followed by utilizing the residuals as inputs to a CNN to detect the presence of resizing and also for estimating the resizing factor. The proposed network is fully end-to-end and does not rely on any hand-crafting. Experimental validation is carried out utilizing images from the RAISE dataset. Comparative analysis with four state-of-the-art methods demonstrates the proposed CNN-based architecture's superiority for resizing detection and resize factor determination sub-problems. [ABSTRACT FROM AUTHOR]

The classification rate is the most significant factor affecting the selection of an appropriate classification approach for achieving the desired quality of decisions. Several researchers have evaluated the influence of different features on the performance of classification approaches, but cost/loss functions, despite their theoretical impact on the classification rate, have been less considered in the comparative literature review. In this paper, a comparative study has been presented on the influence of different cost/loss functions on the classification rate of different classifiers. For this purpose, five of the most well-known and widely used categories of cost/loss functions and three of the most popular main categories of classification approaches are considered. Also, 23 benchmark datasets from six different domains are selected. In this paper, all modeling of the statistical and intelligent classifiers are run in the Eviews and MATLAB package software, respectively. In addition, all mathematical modeling of models run in the GAMS package software. Empirical results indicate that cost/loss functions can significantly affect the classification rate. Numerical results show that the discrete cost/loss function, by average 3.91% and 8.31% improvement rather than semi-continuous and continuous cost/loss functions, respectively, is the most effective one. This clearly illustrates that the consistency of the cost/loss function with the goal function of the classification approach has a positive direct relationship with the classification rate. Furthermore, nonlinear versions of semi-continuous and continuous cost/loss functions are on average slightly more efficient than linear ones. Numerical results indicate that nonlinear forms can averagely yield an 88.99% classification rate that is overall 0.98% higher than linear ones, which achieved an 88.13% classification rate. Although the type of cost/loss function can affect the classification rate of different classifiers, the improvement amount varies based on the type of classifier used. In general, the improvement amount in statistical classifiers, i.e., 15.07% is significantly higher than others, and intelligent by 7.86% and deep learning by 5.20% are in the second and third places, respectively. This overall demonstrates that the complexity of the used classifiers has a negative relationship with the improvement of the classification rate in changing cost/loss function. Finally, numerical results indicate that the difference between improvement amounts achieved by varying cost/loss functions, in general, is not significant and is independent of the type of classifier, as well as the type and domain/area of data. [ABSTRACT FROM AUTHOR]

Grid-interactive building control poses a critical challenge in the context of grid modernization and decarbonization. Recently, various artificial intelligence-based optimal control approaches have been proposed, providing innovative solutions to optimal building control problems. However, researchers and practitioners are now confronted with a dilemma when selecting appropriate control strategies, ranging from model-based (knowledge-incorporating) to learning-based (data-driven) approaches, and hybrid methods combining them. Although each algorithm in existing literature claims superiority over specific baselines, their performance has never been systematically compared and analyzed, owing to the absence of a unified platform for comprehensive evaluation. To fill this knowledge gap, we identify and implement all state-of-the-art approaches within a modular training and evaluation framework, assessing their efficacy in a grid-interactive building control problem. In this paper, we also introduce a streamlined hybrid method that complements existing hybrid approaches. Our comparative study reveals and quantifies the advantages of hybrid methods: on average, they achieve near-optimal control while requiring less than 14% of the online computation of traditional model-based methods. To achieve this performance, they need as few as 2% of the training samples of purely learning-based methods. Finally, we provide insights into the merits, limitations, and implementation of each method to help researchers better understand the state of the art and future directions. The software framework implemented in this study is open-sourced to facilitate future research. [ABSTRACT FROM AUTHOR]

• Evolution of contact force models for viscoelastic contact problems is reviewed. • Contact force models with and without coefficient of restitution are included. • Performance in predicting contact behavior with significant energy loss is analyzed. • Calculations of various contact force models are compared with experiment results. Applying a proper contact force model is of great importance for the modelling and analysis of contact behaviors. This paper presents a comprehensive review of various normal contact force models, including both elastic and viscoelastic models, where the difference between them lies in whether the energy dissipation is considered in the contact process, and the latter is usually composed of both elastic and viscoelastic components. The existing viscoelastic contact force models can be categorized into five major groups based on the powers of the displacement. Some of these models are analyzed using a parametric study that includes factors such as the coefficient of restitution, relative approaching velocity, shear viscosity and the ratio of the bulk viscosity to the shear viscosity. Additionally, the results obtained from these contact force models are compared with experimental data with different values of coefficient of restitution to analyze their applicability in practical engineering. The objective of this review lies in offering a reliable reference for the selection of an appropriate contact force model to solve contact problems. [ABSTRACT FROM AUTHOR]

• An improved Multi-Verse Optimizer named COMVO is proposed. • The modified normalized inflation rate is adjusted to increase the exploration ability of the universe individuals. • The personal best-known universe is introduced to provide the desired search direction. • The comprehensive opposition learning is selected to enhance the exploration accuracy. • COMVO combines a new constraint-handling technique to solve the hydro-thermal-wind hybrid systems. In this paper, a Comprehensive Opposition Multi-Verse Optimizer (COMVO) is proposed to find the optimal solution to the scheduling problem of hybrid hydro-thermal-wind systems. In COMVO, three improvement mechanisms are introduced to enhance the search performance of the original MVO. The proposed method is analyzed and statistically tested against existing state-of-the-art methods in 23 classic benchmark problems and CEC2009 test suite, which demonstrate the superiority of the proposed method. Meanwhile, a constraint-handling technique is developed to solve the complex coupling constraints in the HTW problem and is finally evaluated on a 4 hydro-3 thermal-2 wind system. The results of the comparative analyses show that the proposed method is able to achieve lower costs and fewer emissions than the existing popular methods. In addition, the proposed method reduces emissions by 54%, 81%, 3%, 44%, 17% and 5% in the mean value metrics compared to DA, FFA, GWO, HS, MFO and MVO at 2% wind penetration rate, which fully demonstrates the practicability of the proposed methodology and constraint-handling technique. [ABSTRACT FROM AUTHOR]

Various predictive models for the seismically-induced displacement (D) of flexible slopes during shallow crustal earthquakes are available in the literature, but the model-to-model difference of predictions remains unclear. This paper conducts a comprehensive comparative study of ten representative D models based on scenario- and probabilistic-based displacement analyses. Explicit expressions are provided to implement the probabilistic displacement hazard approach, in which copula theory is utilized for deriving the joint occurrence probability of ground-motion parameters. A total of 6048 displacement hazard analyses are performed considering different earthquake and slope scenarios. It is found that the model-to-model difference generally becomes larger with increasing the natural period (T s) of a sliding mass, whereas the within-type difference among different coupled models is notably smaller than that of the decoupled models. The coupled-type models generally result in smaller total variability of D as compared to the decoupled-type models. Meanwhile, the coupled models tend to, on average, yield larger (or smaller) hazard-consistent D than the decoupled models for T s larger (or smaller) than an intersection period T s,inter , though the difference between the two model types diminishes as T s approaches zero. The effects of ground-motion model selection and ground-motion parameter correlation are also discussed. This study could hopefully provide insights into the displacement model selection for the seismic slope performance assessment and regional landslide hazard mapping. • Comparative studies of ten slope displacement models are conducted. • Copula-assisted probabilistic displacement hazard procedures are presented. • Models yielding lower- and upper-bound displacement hazards are identified. • Relative difference between decoupled and coupled predictions is closely related to T s. • Within-type difference among coupled models is smaller compared to decoupled models. [ABSTRACT FROM AUTHOR]

The valorization of secondary sands is crucial for fostering a circular economy within the construction sector. One significant obstacle in this endeavor stems from the high water absorption (WA) rates commonly reported for secondary sands. This high WA leads to increased water and cement demand in cementitious mixes and elevates costs. The only widely standardized method to measure the WA of fine aggregates is the cone method, which has proven ill-suited for fine aggregates with angular particles or a high content of fines. This study undertakes a comparative evaluation of the cone method and seven alternative methods: immersion, centrifugation, paper sheet, colorimetric, volumetric flask, continuous drying, and electrical conductivity. Tests were performed on natural river sand and three types of secondary sand. Findings reveal that the continuous drying and electrical conductivity methods demonstrates the greatest potential in terms of reliability and applicability. Also the volumetric flask and centrifugation methods show some potential, provided that critical refinements are made to the corresponding test protocols. • Flaws of water absorption methods for secondary sands are exposed. • Caution should be taken in the interpretation of water absorption data from the literature. • There is an urgent need for improved water absorption assessment of secondary sands. • Electrical conductivity and continuous drying methods are recommended. [ABSTRACT FROM AUTHOR]

The current load is one of the most significant factors in the reliability of electrical contact under fretting conditions. In this paper, the fretting wear experiments are conducted for CuZn40 and AgCu10 alloys with varied current loads. The variations of electrical contact resistance (ECR), ECR endurance, temperature, and wear volume with the increasing current load of two alloy materials under fretting conditions are investigated, and the differences between their electrical contact behaviors are compared. The microstructures of the surface wear morphology are examined to reveal the mechanisms of fretting wear and electrical contact failure. In addition, the fretting wear volume evolution of both alloys under different fretting cycles is studied. The results show the current load impacts the wear morphology. The wear particles become smaller and the oxide layer becomes stable with the increase of current load. The effect of current load on ECR and temperature is more significant for CuZn40 alloy. The ECR endurance for both materials first increases and then decreases. This is attributed to two competitive mechanisms controlling the evolution of ECR endurance under varied current loads. [ABSTRACT FROM AUTHOR]

The cancer-specific health-related quality of life (HRQoL) questionnaire of the European Organisation for Research and Treatment of Cancer (EORTC), the EORTC QLQ-C30, is a frequently applied questionnaire to assess cancer patients' self-reported health used as part of research and clinical practice. Normative data obtained from the general population can facilitate the interpretation of these data. Despite its frequent application, no detailed EORTC QLQ-C30 normative data have yet been published for the United Kingdom (UK). This study presents detailed EORTC QLQ-C30 normative data for the United Kingdom overall and by sex and age. The data are drawn from a larger published, international, cross-sectional online survey. For the recruitment, the sample was stratified by sex (males, females) and age in five age groups with a sample size of n = 100 per subgroup. A total of N = 1026 UK respondents completed the survey (n = 517 females, n = 509 males). There were no clear subgroup patterns by sex or age; however, older patients tended to show higher (i.e., better) scores in emotional and social functioning; they also reported some of the lowest (i.e., best) scores for symptoms, such as insomnia, appetite loss, diarrhoea, nausea/vomiting or financial difficulties. This paper provides EORTC QLQ-C30 general population normative data for the UK, further stratified by sex and age. These data will greatly support the interpretation of EORTC QLQ-C30 scale scores obtained from UK cancer patients, and also enable comparison with other detailed national normative datasets collected in the same project, across several other European countries and the US. • EORTC QLQ-C30 is a cancer quality of life (QoL) tool for functioning and symptoms. • Normative QoL data collected from 1026 respondents in UK general population. • No clear patterns, generally oldest had better functioning and fewer symptoms. • Look-up tables for EORTC QLQ-C30 scales for the UK general population. • Interpretation aid for data from individual and groups of UK cancer patients. [ABSTRACT FROM AUTHOR]

Amidst growing concerns over global warming and the urgent need for viable solutions, electric vehicles (EVs) have emerged as a promising remedy. However, the full transition to EVs faces certain challenges, necessitating more efficient electric storage systems. In this context, structural batteries have garnered significant interest as a multifunctional solution. This paper presents a comprehensive review of the latest advancements in structural batteries, exploring their distinctive characteristics and their potential to enhance EVs' performance. Particularly, a comparative analysis will be conducted based on the chosen chemistry for the electrochemical component and the reinforcement materials used. Additionally, crucial aspects such as recycling and life cycle analysis will be briefly discussed. Through this examination, it is intended to shed light on the potential of structural batteries in driving a sustainable and efficient EV ecosystem. [Display omitted] • There has been an increase in research into structural batteries. • Decoupled structural batteries outperform their coupled counterparts. • The coupling mechanism affects more the specific energy than the underlying chemistry. • Structural batteries show promise in improving electric vehicles' range and autonomy. • Structural batteries can be more environmentally friendly than conventional batteries. [ABSTRACT FROM AUTHOR]

Metastatic femoral tumors may lead to pathological fractures during daily activities. A CT-based finite element analysis of a patient's femurs was shown to assist orthopedic surgeons in making informed decisions about the risk of fracture and the need for a prophylactic fixation. Improving the accuracy of such analyses ruqires an automatic and accurate segmentation of the tumors and their automatic inclusion in the finite element model. We present herein a deep learning algorithm (nnU-Net) to automatically segment lytic tumors within the femur. A dataset consisting of fifty CT scans of patients with manually annotated femoral tumors was created. Forty of them, chosen randomly, were used for training the nnU-Net, while the remaining ten CT scans were used for testing. The deep learning model's performance was compared to two experienced radiologists. The proposed algorithm outperformed the current state-of-the-art solutions, achieving dice similarity scores of 0.67 and 0.68 on the test data when compared to two experienced radiologists, while the dice similarity score for inter-individual variability between the radiologists was 0.73. The automatic algorithm may segment lytic femoral tumors in CT scans as accurately as experienced radiologists with similar dice similarity scores. The influence of the realistic tumors inclusion in an autonomous finite element algorithm is presented in (Rachmil et al., "The Influence of Femoral Lytic Tumors Segmentation on Autonomous Finite Element Analyses", Clinical Biomechanics, 112, paper 106192, (2024)). • A deep learning algorithm for automatic segmentation of lytic femoral tumors is developed. • The deep learning dice similarity score of ∼0.67 is obtained, higher than any former study. • Inter-individual dice similarity score variability between two radiologists was 0.73. • The automatic segmentation of lytic tumors is as good as a radiologist. [ABSTRACT FROM AUTHOR]

Trade-induced carbon transfer generates significant impacts on global carbon emissions, leading to carbon inequality (CI). This paper introduces a novel indirect metric, the trade-induced domestic carbon share (TDCS), designed to quantify economies' carbon benefits from international trade. Based on data from 17 manufacturing sectors in 66 major economies, this study compares the impact of developed and developing economies' participation in global value chains (GVCs) on TDCS, offering insights into trade-related carbon inequality. Our analysis reveals that GVCs participation by developed economies generally decrease their TDCS, in contrast to an increase in developing economies, thereby exacerbating carbon inequality. Notably, backward participation in GVCs reduces TDCS across all economies, whereas forward participation in GVCs results in increased TDCS in developing economies but a decrease in developed ones. Additionally, our study indicates that developed economies enhance their position in both forward and backward GVCs but experience a decline in the ratio of domestic value added (DVAR). In contrast, developing economies strengthen their forward GVCs position and DVAR but weaken their backward GVCs position. These findings offer new perspectives on carbon inequality in international trade and provide valuable guidance for policymakers in devising industrial trade and carbon reduction strategies. [ABSTRACT FROM AUTHOR]

Workplace cyberbullying is a significant problem in higher education institutions. This paper examines faculty self-reports based on victimization, coping, gender, and the Big 5 Personality traits. A cross-sectional survey was distributed via Qualtrics to obtain the perceptions of 179 faculty members. Prevalence results indicated that faculty victims experienced cyberbullying from colleagues/peers, administrators, staff, students, and external members. Results also demonstrate that university faculty are unaware of resources to address cyberbullying. The study found evidence of gender differences in cyberbullying victimization in higher education. Agreeableness and neuroticism were also related to experiencing workplace cyberbullying. The article concludes with a discussion of the study's implications and potential areas of future research. • Most faculty experienced cyberbullying from colleagues/peers, administrators, and students. • Cyberbullied faculty are not likely to report the incident, which make it difficult to be addressed in the future. • Females are more likely to experience cyberbullying across relationship types in comparison to male faculty members. • The personality traits of agreeableness and neuroticism related to workplace cyberbullying. [ABSTRACT FROM AUTHOR]

The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 is a frequently used cancer-specific health-related quality of life (HRQoL) questionnaire. To aid interpretation of data obtained via EORTC QLQ-C30, general population norm data have been published for many countries. However, despite its frequent use in the United States, no normative data by sex and age exist to date. Therefore, this study aimed to generate sex- and age-specific EORTC QLQ-C30 normative data for the United States. Recruitment and data collection were carried out via online panels as part of a larger cross-sectional study. For the recruitment, the sample was stratified by sex and age (18–39, 40–49, 50–59, 60–69, ≥ 70 years) to achieve a balanced distribution, with n = 100 per subgroup. Descriptive statistics are presented by age and age/sex. A total of N = 1009 respondents completed the survey (n = 508 females, n = 501 males). More than two thirds of participants (72.5%) reported at least one health condition, e.g., arthritis (26%). Across EORTC QLQ-C30 scales, women and men 60 years and older reported generally better/higher functioning and better/lower symptom scores compared to the younger age groups. To date, no specific EORTC QLQ-C30 general population normative data have been published for the United States. This paper provides these important normative data, which will greatly support the interpretation of EORTC QLQ-C30 scale scores obtained from US cancer patients, and also enable comparison with European norms. • EORTC QLQ-C30 is a cancer-specific health related quality of life (HRQoL) measure. • HRQoL normative data from US general population was collected (1009 respondents). • EORTC QLQ-C30 look-up tables for the US general population by sex/age are presented. • Participants ≥ 60 years reported overall better functioning than younger age groups. • Results will enhance interpretation and validity from EORTC QLQ-C30 data in the US. [ABSTRACT FROM AUTHOR]

Central auditory processing disorders (CAPD) can significantly affect the daily functioning of a child, and the first step in determining whether rehabilitation procedures are required is a proper diagnosis. Different guidelines for making diagnoses have been published in the literature, and in various centers normative values for psychoacoustic tests of CAPD have been used internally. The material presented in this paper is based on more than 1000 children and is the largest collection so far published. The aim of this study is to present normative values for tests assessing CAPD in children aged 6 to 12 years, divided by age at last birthday. We tested 1037 children aged 6 to 12 years who were attending primary schools and kindergartens. The criteria for inclusion were a normal audiogram, intellectually normal, no developmental problems, and no difficulties in auditory processing. To evaluate auditory processing all children were given three tests on the Senses Examination Platform: the Frequency Pattern Test (FPT), Duration Pattern Test (DPT), and Dichotic Digit Test (DDT). The results from 1,037 children allowed us to determine normative values for FPT, DPT, and DDT in seven different age groups (6 through to 12 years). We developed a newapproach, based on quantile-based norms, to determine normative values in each group. Three categories – average, below-average, and above-average – allow for a broader but more realistic interpretation than those used previously. We compare our results with published standards. Our study is the largest normative database published to date for CAPD testing, setting a standard for each child by age in years. We used the Senses Examination Platform, a universal tool, to unify standards for the classification of CAPD. Our study can serve as a basis for the development of a Polish model for the diagnosis of CAPD. [ABSTRACT FROM AUTHOR]

• The finite element method is used to analyze complex grounding structures. • Measurements in operational grounding systems are used as reference. • Results from simulation, measurement, and calculation agree well. • The finite element method excels in low-frequency grounding structure analysis. • Analytical methods are insufficient for complex grounding systems. The safety of human beings and the integrity of electrical systems essentially depend on grounding systems. The main quality indicator of a grounding system is its resistance, measured after its implementation. During the design phase, it is essential to estimate this resistance, especially in complex structures. In this context, the Finite Element Method (FEM) is a highly effective numerical approach to estimating the resistance of the grounding system. This paper presents simulations using FEM for various types of complex grounding structures to determine their resistances. A variety of structures are subjected to simulations, and for reference purposes, the obtained results are compared with the resistance values obtained from operational grounding systems. Such analyses encompass structures employed in distribution, transmission, and substation systems. [ABSTRACT FROM AUTHOR]

• The manuscript highlights detailed mathematical threshold voltage modeling-based comparative performance analysis of a Junctionless and Junction-Based High-K Gate Stack Dual-Material Cylindrical Gate-All-Around Macaroni MOSFET. • Comparative analysis of the response of the proposed device and its Junction-based equivalent towards channel length downscaling has been examined through in-depth investigation of Threshold voltage, threshold voltage roll-off and DIBL by varying different device parameters. • The advantage of using a high-K gate stack architecture in the proposed device is evident through its improved Subthreshold Swing response. • All the mathematical results have been corroborated using simulation outputs from Silvaco Atlas. This paper presents explicit threshold voltage modeling based comparative threshold voltage exploration of Junctionless (JL) and Junction-based (JB) High-K gate stack (HKGS) Dual-Material (DM) Cylindrical Gate-all-around (CGAA) Macaroni (Mac.) MOSFET. Based on Young's popular Parabolic Potential Approximation (PPA), device features like inner potential has been formulated. Based on the expression of inner potential, threshold voltage has been extracted. Other major short channel effects like Drain-induced barrier lowering (DIBL) and subthreshold swing (SS) have also been analyzed. Device parameters such as inner, outer radii, channel lengths, type of high-k gate oxide, source/drain doping for JB device, etc. have also been varied to examine their effects on device parameters. Finally mathematical outputs have been corroborated with simulation outputs from Atlas. [ABSTRACT FROM AUTHOR]

• High throughput layer-by-layer laser milling. • Low surface roughness laser milling. • Laser milling of aluminum molds for LED diffusers. • Comparative study of ablation efficiency using ns, ps, and hybrid ns-ps pulses. • The highest values of laser milling efficiencies recorded in the literature. This paper reports a comparative study of ablation efficiency and quality using conventional nanosecond (ns), conventional picosecond (ps), and novel hybrid ns-ps irradiation modes. The aluminum alloy was machined using a laser with the traditional ns and ps pulses at various repetition rates. Also, the hybrid ns-ps irradiation regime was applied for the first time in laser milling. Laser fluence was optimized to ensure the efficient utilization of laser pulse energy for the maximal rate of material removal. For hybrid ns-ps, conventional ns, and conventional ps pulse processing regimes, direct comparisons of surface roughness of laser-milled cavities as well comparisons of ablation efficiencies with literature values were conducted. Experimental results coincided well with the theory of efficient ablation. The layer-by-layer efficient laser milling technique was applied for the fabrication of aluminum molds designed for LED diffusers. [ABSTRACT FROM AUTHOR]

Biometric security has emerged as a major concern in the field of Biometric Systems. The existing centralized Biometric Cryptosystems approach still suffers from privacy issues and network-based attacks. In particular, the Biometric Cryptosystems are susceptible to Attack via Record Multiplicity, brute force and collusion attacks. To address these issues, this paper proposes a multimodal biometric user authentication scheme using a decentralized fuzzy vault based on Blockchain technology. In this scheme, the facial biometric images and dorsal hand images together form the multimodal biometric. The proposed security framework is implemented in two phases. In the first phase, multimodal biometric user authentication using an improved fuzzy vault scheme is implemented. In the second phase, a privacy preservation technique using a decentralized fuzzy vault biometric system based on the Blockchain network is implemented. The performance of the proposed framework is verified on the biometric datasets consisting of both genuine and imposter users, and a comparative analysis with the existing state-of-the-art approaches is also presented. The Detection Error Trade-off (DET) curve and the Receiver Operating Characteristic (ROC) curve, obtained for verifying the efficacy of the proposed framework, are also presented. The proposed framework yielded an accuracy of 99.8% and an Equal Error Rate of 0.08. Furthermore, to validate the biometric template protection, the security analysis of the proposed scheme based on irreversibility, unlinkability, and revocability criteria is described. The proposed framework achieves significant improvement in terms of a low False Acceptance Rate (0.08), and a high True Acceptance Rate (0.96). [ABSTRACT FROM AUTHOR]

This paper focuses on the short-circuit withstand capability of the superjunction (SJ) Field-Stop (FS) IGBTs, considering both electrical and energy destruction modes. The short-circuit withstand capability is measured through the short-circuit time (T SC). The electrical destruction, which is usually earlier than the energy destruction in conventional FS IGBTs, is studied by using parallel 32-cells, with the help of numerical electrothermal simulations. The results show that the current filaments, which cause electrical destruction in conventional FS IGBTs, are not observed in the SJ-FS IGBTs even when the collector current density reaches 5000 A/cm2. The reason is that the SJ structure reduces the peak electric field and then suppresses impact ionization at the n-buffer region. As a result, the short-circuit withstand time of the SJ-FS IGBTs is larger than that of the conventional FS IGBTs. The maximum difference is up to 2.39 μs. • Comparative study on the short-circuit withstand capability between the superjunction and conventional FSIGBTs. • Current filaments, which cause electrical destruction in the conventional FS IGBTs, are not observed in the SJ-FS IGBTs. • Superjunction structure reduces the peak electric field and suppresses impact ionization. [ABSTRACT FROM AUTHOR]

Word order, a linguistic concept essential for conveying accurate meaning, is seemingly not that necessary in language models based on the existing works. Contrary to this prevailing notion, our paper delves into the impacts of word order by employing carefully selected tasks that demand distinct abilities. Using three large language model families (ChatGPT, Claude, LLaMA), three controllable word order perturbation strategies, one novel perturbation qualification metric, four well-chosen tasks, and three languages, we conduct experiments to shed light on this topic. Empirical findings demonstrate that Foundation models take word order into consideration during generation. Moreover, tasks emphasizing reasoning abilities exhibit a greater reliance on word order compared to those primarily based on world knowledge. • Word order is reexamined by 4 tasks, 3 strategies, 3 languages and 5 models. • The tested datasets includes TruthfulQA, MGSM, XWinoGrande and WiQueen. • The word order perturbation strategies include Random , Rotate and Adjacent. • Both English, Chinese, and French dataset are tested on ChatGPT, Claude and LLaMA. [ABSTRACT FROM AUTHOR]

• Trauma-informed practice is being trialled in response to extra-familial risks and harms. • An institutional ethnography found sources of knowledge impact this innovation. • Professionals may say young people are 'known-to-services' but be distant from them. • Being proximal to young people and advocating for their needs helps to know them. • To be trauma-informed, professionals must relationally know those they support. Efforts to shift from criminal justice to welfare-based responses to exploitation and other forms of extra-familial risks and harms, have centred relational approaches. In particular, the role that relationships between professionals and young people can play in providing a sense of safety as well as a route to wider support services when young people come to harm beyond their families is under consideration. In parallel, trauma-informed practice is increasingly promoted as a tool for creating service conditions in which relational practice can thrive. In this paper we present data from an institutional ethnography of two social care organisations in the UK which are endeavouring to adopt trauma-informed responses to extra-familial risks and harms. We use observation, focus group, and case file data collected in two time periods, to illustrate a relationship we identified between the nature and source of knowledge that guided professional responses, the ability of professionals to form relationships with young people affected by extra-familial risks and harms, and the capacity for their organisations to be trauma-informed. In doing so we trouble an established discourse in many social care organisations, that young people subject to intervention are 'known-to-services' and call for more responses in which young people are 'known-by-professionals' who are supporting them. Far from being a matter of semantics, we discuss how these two ways of knowing about young people, and the situations they face, potentially facilitate or undermine key pillars of trauma-informed practice, and the relational approaches that make such practice possible. [ABSTRACT FROM AUTHOR]

Health insurance is one of the main financing mechanisms currently being used in low and middle-income countries to improve access to quality services. Tanzania has been running its National Health Insurance Fund (NHIF) since 2001 and has recently undergone significant reforms. However, there is limited attention to the causal mechanisms through which NHIF improves service coverage and quality of care. This paper aims to use a system dynamics (qualitative) approach to understand NHIF causal pathways and feedback loops for improving service coverage and quality of care at the primary healthcare level in Tanzania. We used qualitative interviews with 32 stakeholders from national, regional, district, and health facility levels conducted between May to July 2021. Based on the main findings and themes generated from the interviews, causal mechanisms, and feedback loops were created. The majority of feedback loops in the CLDs were reinforcing cycles for improving service coverage among beneficiaries and the quality of care by providers, with different external factors affecting these two actions. Our main feedback loop shows that the NHIF plays a crucial role in providing additional financial resources to facilities to purchase essential medical commodities to deliver care. However, this cycle is often interrupted by reimbursement delays. Additionally, beneficiaries' perception that lower-level facilities have poorer quality of care has reinforced care seeking at higher-levels. This has decreased lower level facilities' ability to benefit from the insurance and improve their capacity to deliver quality care. Another key finding was that the NHIF funding has resulted in better services for insured populations compared to the uninsured. To increase quality of care, the NHIF may benefit from improving its reimbursement administrative processes, increasing the capacity of lower levels of care to benefit from the insurance and appropriately incentivizing providers for continuity of care. • The NHIF influences service coverage and quality in complex ways. • NHIF reimbursement is crucial for facilities and its delay affects inputs for quality. • Lower levels of care benefit less from NHIF. • Need to improve reimbursement process to enhance quality of care. [ABSTRACT FROM AUTHOR]

While the domain of Automated Compliance Checking (ACC) has gained track, the construction industry has been flooded with different approaches. This paper studies these different approaches for use in compliance checking of construction data. The approaches are compared by defining constraints for the same set of five requirements, each of a different category, stemming from the Flemish building regulation on accessibility. Eight approaches have been selected for comparison: two IFC-based approaches (Solibri Model Checker and the upcoming buildingSMART standard IDS), two general data standards and their accompanying schema definition languages (JSON Schema and XSD), and four Linked Data approaches (OWL, SWRL, SPARQL, and SHACL). Besides the pure functional analysis, the relative uptake and support in tooling are also considered. While XML/XSD and JSON/JSON Schema and the Linked Data approaches are in essence domain-independent, only the latter has an extra layer for agreeing on high-level data modeling (and thus data validation) patterns in the construction domain with the EN17632-1:2022 standard. SHACL is considered the most adept method from the Linked Data approaches since it is fully standardized for both inputs and outputs and was developed for validation use cases. • The Flemish regulation on accessibility exemplifies five constraint categories. • Eight compliance checking approaches are compared by executing the five constraints. • The (dis)advantages of each approach are explained. • Sharing all constraints, datasets, outputs, and code, ensures full reproducibility. [ABSTRACT FROM AUTHOR]

• A novel signal decomposition method termed ERFD is proposed for gear fault diagnosis. • Based on sparse random feature model, the random feature energy spectrum of input signal is constructed. • A MHIR index guided adaptive continuous envelope segmentation strategy is designed. • The proposed segmentation strategy can achieve the accurate division of interested frequency bands. • Simulation and experimental cases verify the feasibility and effectiveness of the proposed method. Sparse random mode decomposition (SRMD) is an emerging signal decomposition method for analyzing time series data. However, SRMD is unable to adaptively select suitable clustering parameters, and its decomposition effect is easily affected by noise. To overcome the above deficiencies, a novel signal decomposition method named empirical random feature decomposition (ERFD) is proposed in this paper. Firstly, ERFD utilizes sparse random feature model to construct the random feature energy spectrum of input signal, and the extraction of signal components can be achieved via spectrum segmentation mechanism. Subsequently, an adaptive continuous envelope segmentation strategy guided by the mean harmonic intensity ratio (MHIR) index is designed for the adaptive frequency band division of random feature energy spectrum, which effectively attenuates the interference of noise extreme points and ensures the accurate separation of interested components. Finally, the random features corresponding to different frequency bands are reconstructed to obtain a series of mutually independent intrinsic random components (IRCs). Furthermore, the proposed ERFD method is applied to gear fault diagnosis, and its feasibility and effectiveness are fully verified through simulation and two experimental cases. The comparative analysis results indicate that ERFD has a better suppression effect on noise and can effectively extract weak fault features of gear. [ABSTRACT FROM AUTHOR]

This paper introduces a control method utilizing an active nonlinear negative stiffness device (ANNSD) to mitigate excessive displacement of isolation layers in base-isolated structures (BIS). The proposed approach, based on linear quadratic regulation (LQR), effectively controls the displacement of the isolation layers and enhances the seismic performance of the structure. To address the nonlinear characteristics inherent in the forward model of the negative stiffness device, a novel active nonlinear negative stiffness device model is introduced, allowing for the adjustment of the spring expansion ratio. The inverse model of the nonlinear negative stiffness device is predicted and fitted using an LSTM neural network, enabling real-time determination of the input spring expansion ratio based on the desired control force and system response. The feasibility and effectiveness of the proposed method are validated through numerical simulations on a two-degree-of-freedom BIS equipped with the ANNSD. A comparative analysis is conducted between the base-isolated structure with active nonlinear negative stiffness device (BIS-ANNSD) system and the uncontrolled system. The results demonstrate the favorable application advantages of using LSTM for the prediction and fitting of the inverse model of the nonlinear device. The ANNSD effectively mitigates excessive displacement of the isolation layer, while the integration of the LQR controller ensures effective suppression of acceleration responses in the superstructure. • An inverse model of a nonlinear negative stiffness device is developed using LSTM for prediction and fitting. • An active nonlinear negative stiffness device is proposed, based on altering the spring expansion ratio. • The effectiveness of an active nonlinear negative stiffness control method based on LQR is verified. • The superior seismic isolation performance of an ANNSD applies to a BIS is showed through numerical simulations. [ABSTRACT FROM AUTHOR]

Most case and comparative studies discuss urban characteristics that can hardly be influenced by urban transport policies. However, these studies do not quantify the impact of the so-called contextual factors on car ownership and car use. This paper focuses on these contextual factors and their associations with car ownership and car use. Regression models show that contextual factors - such as city size, the share of households with children and the jobs-housing balance - explain a substantial part of the variance in car ownership and car trips in 44 German cities. Residual analyses reveal that neglecting contextual factors leads to biases in comparative studies and consequently in the evaluation of urban transport policies. Thus, there is a risk that cities with favourable contextual factors may be mistakenly viewed as successful examples of transport policy, whereas successful policies in cities with less favourable contextual factors may be overlooked. • Contextual factors explain a large part of variance in car ownership and car trips. • Residual analyses show: Neglecting contextual factors leads to bias in benchmarking. • Transport policies should be evaluated while accounting for contextual factors. [ABSTRACT FROM AUTHOR]

• Design guidelines for a unique double-gated TFET-based biosensor (DG-TFET-BS) • Identifying main factor(s) affecting DG-TFET-BS performance with < 100 % fill-factor. • Projected DG-TFET-BS outperforming its MOS counterpart (MES) in sensing performance. • Capturing the change in biomolecule properties (k-value, diameter) with temperature. • More stability of MES against temperature and position variability than DG-TFET-BS. In this paper, marking the first instance, we introduce design guidelines for a unique double-gate TFET-based biosensor, considering the practical aspect of a non-100% fill-factor in the nanogap cavity, facilitating the successful conjugation and detection of diverse biomolecules with varying diameters and k-values. Throughout our study, we have sought to identify the most influential parameter(s) among k-value, fill-factor, and gate-oxide thickness, impacting the biosensor's sensing performance. Intriguingly, we have discovered that the complex interplay of electrostatics in the device is governed by a collective effect of these parameters, affecting sensing performance. Nevertheless, optimizing the nanogap cavity thickness is a trade-off between performance and fabrication complexity. Subsequently, we have conducted a comparison between the proposed biosensor and its MOS counterpart, evaluating their sensitivity, and stability against temperature fluctuation and position variability. While the projected TFET-based biosensor excels in sensitivity, it lags in the latter two aspects, making the choice between the two types of biosensors application-specific. [ABSTRACT FROM AUTHOR]

• This study reviewed four process models including DNDC, APSIM, DayCent, and STICS. • DNDC and DayCent perform better in simulating CH 4 emissions from rice. • APSIM is effective for simulating N 2 O emissions from maize and wheat. • Model mechanisms (44.57%) are the most influential factors affecting the accuracy of simulation. Agricultural ecosystems have long been recognized as significant greenhouse gas (GHG) sources. To accurately quantify GHG emissions, researchers have developed various process models. However, there are no summary studies of comparative model simulations of GHG emissions from different crop systems. This study compared four widely used process models: APSIM, DNDC, DayCent, and STICS, analyzing their mechanisms, input variables, and simulation results from different crops in simulating GHG emissions. In this study, a total of 94 relevant peer-review literature papers were considered. The research found that these models have strengths in simulating GHG emissions from different crops, but also have certain limitations. DNDC and DayCent performed better in simulating methane (CH 4) emissions from rice, while APSIM was more effective in simulating nitrous oxide (N 2 O) emissions from maize and wheat. The main factors affecting the simulation results include model mechanisms, management practices, climate, and data availability. To improve model accuracy, it is recommended that future research expands model applicability, evaluates models using standardized measured data, and enhances adaptability by optimizing algorithms and incorporating simulations of key processes. [ABSTRACT FROM AUTHOR]

• Using magnet fins as a reasonable storage material in a conical solar distiller enhance heat transfer, increase water productivity, and offer cost-effectiveness. • Accumulative productivity has an improving rate for CSD-MF-2, CSD-MF-1.5, CSD-MF-1, and CSD-MF-0.5 about 44.54, 32.73, 25.45 and 16.36 respectively. • System efficiency improving rate for CSD-MF-2, CSD-MF-1.5, CSD-MF-1, and CSD-MF-0.5 about 43.07, 31.79, 29.8 and 24.49%, respectively over the traditional one (TCSD). • CSD-MF-2 has the best performance with daily productivity of 7.95 L/m2/day and average system efficiency of 42.2 %. This paper presents a comparative experimental analysis aimed at improving the production of drinking water from conical solar distillers using magnet fins as a low-cost and efficient storage material. Cylindrical magnet fins with a diameter of 1.6 cm were strategically placed at various heights (2 cm, 1.5 cm, 1 cm, and 0.5 cm) with a spacing of 5 cm on the absorber plate to increase the absorption area and heat transfer to the basin water. Three modules were tested under identical conditions over a two-day period with a fixed water depth of 2 cm (corresponding to the maximum magnet fin height). On the first day, the Traditional Conical Solar Distiller (TCSD), the Conical Solar Distiller with Magnet Fins at a height of 2 cm (CSD-MF-2), and the Conical Solar Distiller with Magnet Fins at a height of 1.5 cm (CSD-MF-1.5) were evaluated. On the second day, the TCSD, the Conical Solar Distiller with Magnet Fins at a height of 1 cm (CSD-MF-1), and the Conical Solar Distiller with Magnet Fins at a height of 0.5 cm (CSD-MF-0.5) were tested. The results showed that the daily water yield from the TCSD at a water depth of 2 cm was 5.50 L, whereas the conical solar distillers with magnet fins at heights of 2 cm, 1.5 cm, 1 cm, and 0.5 cm produced 7.95 L, 7.30 L, 6.90 L, and 6.40 L, respectively. Consequently, the utilization of magnet fins led to a significant improvement in distiller productivity, with the best configuration being the CSD-MF-2 with a height of 2 cm, resulting in a 44.54 % increase in yield with an average overall efficiency about 42.2 %. [ABSTRACT FROM AUTHOR]

This study conducts a thorough investigation into the performance of steel O-ring bracing under progressive collapse conditions through a comparative nonlinear analysis. The structural responses of various bracing systems, including traditional steel frames, steel frames with concentric X-bracing, and the O-ring bracing system, are investigated and compared. Prototype buildings with two and three floors and four bays in the plan are selected and designed based on AISC code. Advanced finite element simulations and pushdown analysis with displacement control, validated rigorously against relevant experimental testing, are employed to replicate collapse scenarios. The study accurately identifies failure modes, establishes relationships between the vertical displacement of the collapsed column and the applied load, and examines the horizontal displacement of adjacent columns for each system. Considering initial stiffness and maximum force capacity at different stages, our findings reveal that the frame system with O-ring bracing offers a balanced combination of initial stiffness and progressive collapse resistance, showcasing superior ductility compared to the other two systems. Notably, for three-story buildings, the O-ring system exhibited eight times the initial stiffness of the unbraced frame and half that of the frame with X-bracing. Additionally, the maximum resistance provided by the O-ring bracing was 2.8 times that of the unbraced frame and 0.5 times that of the frame with X-bracing. These results contribute valuable insights for enhancing the design and retrofitting strategies of steel structures, particularly those employing O-ring bracing, with implications for improved structural integrity and safety in the face of unforeseen events. • This paper investigates a new O-ring bracing system to improve the overall strength and safety of buildings. • The study focuses on evaluating the effectiveness of new O-ring bracing systems and how they compare to moment frame and X-bracing systems. • Research addresses O-ring bracing systems' stability and ability to withstand progressive collapse scenarios. [ABSTRACT FROM AUTHOR]