The resilience of towns and cities refers to their ability to adapt and recover when confronted with pressures or challenges. This study employs ten variables as indicators to assess the resilience of urban areas by analyzing official data and constructing a multilevel mixed-effects structural equation model. The empirical findings demonstrate that enhancing resilience significantly influ-ences urban service functions, such as strengthening healthcare systems, stabilizing the real estate market, and addressing socio-economic challenges. Specifically, factors such as healthcare re-sources, housing demand, population structure, and social security exhibit varying levels of resil-ience, which profoundly impact the spatial distribution of these factors and socio-economic de-velopment. Disparities in healthcare resource allocation, demographic aging trends, and shifts in the housing market closely correlate with resilience levels in different regions. Additionally, the study emphasizes that improving resilience not only boosts the reliability and security of urban services but also ensures that communities receive necessary support and protection during times of adversity. Consequently, policymakers should recognize the pivotal role of urban resilience in resource allocation and social equity, devising corresponding strategies to enhance the resilience of these areas.

Nowadays, there is an increasing concern about environmental challenges ranging from emissions to overconsumption. Most of the environmental problems today are direct consequences of human consumption. Understanding the factors that affect consumer purchasing decisions is critical to developing demand for and commitment to sustainable consumption. In this regard, this study aims to explore the environmentally sustainable consumption behavior of Ethiopian consumers by using an extended model of the theory of planned behavior. Data were collected using a self-administered questionnaire having open and closed-ended questions. A total of 523 Ethiopian consumers were selected using convenience sampling technique. Structural equation modeling with AMOS V.26.0. was applied for data analysis. The findings show that Ethiopian consumers have very low awareness about the impact of their clothing consumption and disposal. Their consideration of sustainability attributes during purchasing decisions is also low. The structural equation model analysis showed that all variables had a positive and significant effect on the dependent variables at p<0.05, except the effect of personal norms on an environmentally responsible purchasing intention. These results provide additional evidence on the role of environmental labels in purchasing sustainable apparel products. The results of the study allow a better understanding of the factors determining sustainable consumption behavior and suggest practical solutions to their producers. As theory-building activities, with implications for the conceptualization of sustainable consumption behavior are sparse in the literature, this work has also been able to detect sustainable consumption behavior trends and practices by using the availability of a sustainable apparel product and consumers price perceptions of environmentally responsible apparel as a mediating effect of intention and behavior in developing countries, particularly Ethiopia.

The Cordoba Guitar Festival is one of the most important cultural events in Spain. This article analyses the musical preferences, satisfaction, attitudinal loyalty and behavioural loyalty of spectators who attended the 36th festival held in July 2016, as well as the festival’s economic impact on the city. To achieve this aim, a structural equation model (SEM) was used. The results show the goodness-of-fit of the model and indicate that the observed data fit the expected dataset.

Lap joints were friction stir welded in AA 7075-T6 at 1320 rpm and using two welding speeds: 70 mm/min and 120 mm/min. The temperature profiles of the weld zone were registered during the process; furthermore, the microhardness, tensile strength, and microstructure of the joints produced were examined. This study brings new insights into the thermomechanical behavior of the material during the process. The peak temperature obtained with the lower welding speed (70 mm/min) is 10% higher than that obtained with the higher speed (120 mm/min). Moreover, a 5% increase in microhardness and a 6% increase in tensile strength were were observed increasing the welding speed. Addition-ally, the microstructure examination demonstrated that, by decreasing the welding speed, the larger interaction between the tool and the material results in a deeper stir zone due to the increased heat diffusion downwards to the material. This heat flow affects the thermal profile and influences the resulting mechanical properties of the welded joints.

The adapted Posner spatial cue-target paradigm was used to explore the relationship between exogenous temporal attention caused by rhythm and endogenous and exogenous spatial attention. The study was divided into two experiments. In Experiment 1, 33 participants used arrow cues to orient endogenous spatial attention and rhythm to orient exogenous temporal attention. In Experiment 2, with 29 participants, exogenous spatial attention was directed by highlighting the cue box. Exogenous temporal attention was directed by rhythm. Experiment 1 indicated that RTs were faster for attended targets than the unattended. The main effect of temporal attention was significant, with RTs being faster for synchrony and late compared to early. RTs were faster for late compared to synchrony. The main effect of stimulus repetition was significant, with faster RTs for targets when the rhythmic cue consisted of five compared to four. The interaction between spatial attention and temporal attention was not significant. Experiment 2 demonstrated that exogenous spatial attention only exhibited IOR under early four stimulus repetitions. The main effect of temporal attention was significant, with RTs being faster for synchrony and late compared to early. The main effect of stimulus repetition was significant, with faster RTs for targets when the rhythmic cue consisted of five compared to four. The interaction between spatial attention and temporal attention was significant. The results indicated that rhythmic temporal attention supported foreperiod effects. Exogenous temporal attention and endogenous spatial attention independently affect behavior, while exogenous temporal attention and exogenous spatial attention mutually influenced behavior.

This study analyzes the eating behavior and factors associated with the presence of disordered eating attitudes in patients undergoing bariatric surgery. It is a cross-sectional, descriptive, and analytical study conducted at a hospital in the Amazon region of Brazil. The Disordered Eating Attitude Scale reduced version (DEAS-s) was used to assess the risk of eating disorders and the Three-Factor Eating Questionnaire (TFEQ-R21) to characterize eating behavior. A total of 205 patients participated, with a mean age of 37.5 ± 8.6 years, the majority being female (93.7%; p&lt;0.001), the mean BMI was 45.3±6.7 kg/m2. It was found that cognitive restraint had the highest mean (52.6±19.9; p&lt;0.001). As for the DEAS-s, the question with the highest mean was "spending one or more days without eating or consuming only liquids to lose weight" (2.80±1.99). Female participants had a higher score in the emotional eating (p=0.016). Disordered eating attitudes showed a correlation with emotional eating and uncontrolled eating. These results suggest that candidates for bariatric surgery may have susceptibility to eating disorders. The importance of a multidisciplinary team in monitoring during the preoperative period is highlighted.

Dhaka one of the fastest-growing megacities in the world is increasingly vulnerable to urban flooding due to rapid urbanization, inadequate drainage infrastructure, and climate change-induced extreme weather events. This study presents the development of an urban flood forecasting system for Dhaka City using the MIKE+ hydrodynamic modeling software. The system integrates detailed hydrological and hydraulic models to simulate urban flooding scenarios, accounting for complex drainage networks and catchment characteristics. Real-time data from river gauges, rainfall stations, and drainage systems are incorporated to enhance the accuracy and reliability of the forecasts. The model's predictive capability is validated against historical flood events, demonstrating its effectiveness in forecasting flood extents, depths, and durations in critical areas of the city. This system serves as a valuable tool for city planners, emergency response teams, and decision-makers, enabling proactive flood management and risk mitigation. The study underscores the importance of such advanced modeling tools in safeguarding urban populations and infrastructures from the increasing threat of urban floods in Dhaka and similar rapidly urbanizing cities.

Recently, the awareness of energy conservation, carbon emission reduction, and environmental protection in Taiwan has begun to gradually improve, and bicycles have become an important vehicle for residents. In 2009, Kaohsiung began promoting public bicycle sharing. The number of users in that year amounted to 140,000. By 2015, the accumulated number of users reached nine million. This study adopted the Theory of Planned Behavior (TPB) to explore the factors influencing the behavioral intentions of public bicycle users, including the three dimensions of attitude, subjective norm, and perceived behavioral control, and probed into the relationship between the factors influencing the behavioral intentions of public bicycle users in Kaohsiung City and the dimensions. This study used a questionnaire to collect data and SPSS & AMOS for statistical analysis. The empirical results demonstrated that the most prominent factors influencing the behavioral intentions of public bicycle users in Kaohsiung City included perceived behavioral control, attitude, and subjective norm, in order. Among the influencing factors in the three dimensions, personal interests, main groups, and self-competence had a positive and significant correlation. Administrators should provide more incentives related to the three influencing factors to encourage the public in Kaohsiung City to use public bicycles more frequently as their short-distance travel mode, so as to achieve the purposes of saving energy, reducing carbon emissions, and protecting the urban environment.

This paper investigates, experimentally and numerically, the buckling behavior of innovative sustainable Low-Cost Bamboo Composite (LCBC) structural columns under compressive loading. The LCBC columns are manufactured from bamboo culms in combination with bio-based resins to form composite structural columns. Different LCBC cross-sectional configurations are investigated in this study including the Russian doll (RD), Big Russian doll (BRD), Hawser (HAW), and Scrimber (SCR). Extra-large, large, medium, and small sizes of bamboo are employed to form the proposed configurations. Two bio-based resins including one bio-epoxy and one furan-based resin, in addition to a soft bio-based filler and a synthetic epoxy resin are applied. The bamboo species used as the cast-in-place giant bamboo for all configurations include Moso, Guadua, and Tali. In addition to experimental testing of the slender LCBC short columns, finite element analysis (FEA) software ABAQUS is applied to model the composite columns and predict their behavior. A buckling analysis using static Riks method is carried out to determine the LBCB’s response to axial compressive loading. A model is calibrated using test results with various imperfections, accounting for the variable behavior of each bamboo specimen, to accurately predict the behavior of LCBC columns with different resin contents. Slender LCBC columns showed maximum stress at buckling up to 60 MPa, highlighting the potential of bio-based resins for structural applications. The study found that the samples with bio-epoxy resin (BE2) exhibited enhanced material stiffness when compared to with synthetic epoxy (EPX) and furan-based resin (PF1), while PF1 specimens demonstrated increased ductility. The BE2 samples showed strain hardening in their stress-strain behavior, and the PF1 samples exhibited a long plateau phase before reaching the maximum load. Among the specimens with Moso bamboo and BE2 resin, those with SCR and HAW configurations achieved the highest compressive strengths.

By introducing environmental mediator, for avoiding randomness in selecting indicators and subjectivity in deciding interaction path coefficients to reveal interaction mechanism among forest industry, ecology and environmental capacity, structural Pressure–State–Impact–Response (PSIR) and quantitative Structural Equation Modeling (SEM) are utilized with data on thirty–one provinces of China. We can find that: (i) forest industry has a negative influence on ecology, whereas ecology has a positive influence on industry; (ii) the destructive influence that industry has on ecology is much greater than the positive effect ecology has on industry; and (iii) environmental capacity plays a partial mediating role between industry and ecology. According to these results we can conclude that: (i) forest industry and ecology are not in a symbiotic relationship and have not reached a level of ecological security; (ii) the interaction between industry and ecology is in a period of transition from antagonistic to beneficial; and (iii) industry dominates ecology. However, we prospect the following advice: (i) methods of forest industry should be changed; (ii) new modes of industrial integration and circular economy should be developed; and (iii) the ability of the environment to sustain itself should be enhanced. The level of forest ecological security to discuss the symbiotic mechanism of industry and ecology will propose to be measured in future.

The raw material purchasing (RMP) problem is to determine the purchasing quantities of raw materials in given periods or cycles. Raw material purchasing optimization is crucial for large-scale steel plants because it is closely related to the supply of raw materials and cost savings. The raw material purchasing of large-scale steel enterprises is characterized by many varieties, large quantities, and high costs. The RMP objective is to minimize the total purchasing cost consisting of the price of raw materials, purchasing set-up costs, and inventory costs and meet product demand. We present a mixed integer linear programming (MILP) model and a column generation (CG) solution for the resulting optimization problem. The column generation algorithm is the generalization of the branch & bound algorithm with solving the linear programming (LP) relaxation of MILP using column generation (CG), and its advantage is to handle large-sized MILPs. Experimental results show the effectiveness and efficiency of the solution.

We do this research to investigate the relationship between renewable energy, public health expenditure, logistics performance indices, and economic and environmental sustainability in the ASEAN member states, through the analysis of a panel data from 2007 to 2017. The study used secondary data, which is downloaded from the World Bank Website and employs SEM (Structural Equation Modelling) model for testing hypothesis. The results show that the usage of renewable energy in logistical operations would enhance the environmental and economic performance in terms of mitigating carbon emissions and greenhouse gas emissions. While, public health expenditure and environmental performance is negatively correlated, which confirms that greater environmental sustainability with lower carbon emissions and greenhouse gases will improve human health and economic growth. Moreover, greater public health expenditure and poor environmental performance has negative effect on economic growth, inefficiency and low productivity of labor slowdown to the economic activities. For another side, the usage of renewable energy and the adoption of green practices in international logistics will develop the environmental sustainability, establish better image of a country and attract foreign direct investment inflows, and also minimize carbon emissions and public health expenditure, spurring sustainable economic growth with better export opportunities in pro-environmental countries.

The intelligent morphing wing structure has the characteristics of flexibility, large deformation and adaptive change, which are different from those of the conventional wing. The motion law of the variable-camber leading edge is analysed by the numerical simulation method based on kinematics theory to solve the problem of verifying the motion function and structural strength of the variable camber wing. The driving deformation and aerodynamic load simulation of the variable camber leading edge are realised by designing a follow-up load test apparatus. Based on the numerical simulation of the mechanical boundary, the motion trajectory of the upper and lower wing loading points was predicted, and a multi-point cooperative control system was developed. Multi-sensor iteration was used to ensure the loading accuracy of the test control. The test results show that the average error of the deflection angle is 4.59% in the variable camber leading edge motion test. In the variable camber leading edge strength test, the average error of applied load magnitude and direction is 0.54% and 0.24%, respectively.

Estimating parameters for multiple datasets can be time consuming, especially when the number of datasets is large. One solution is to sample from multiple datasets simultaneously using Bayesian methods such as adaptive multiple importance sampling (AMIS). Here we use the AMIS approach to fit a von Misses distribution to multiple datasets for wind trajectories derived from a Lagrangian Particle Dispersion Model driven from a 3D meteorological data. The primary objective is to characterise the uncertainties in wind trajectories in a form that can be used as inputs for predictive models of wind-dispersed insect pests and pathogens of agricultural crops for use in evaluating risk and in planning mitigation actions. Our results show that AMIS can significantly improve the efficiency of parameter inference for multiple datasets.

This research challenges the traditional perspective on consumer behavior, which focuses on external factors shaping the sequential stages of decision-making. Instead, it proposes a paradigm shift by treating the decision-making process itself as an independent variable, exploring its impact on various outcomes like purchasing behavior, brand loyalty, and post-purchase satisfaction. This novel approach offers deeper insights into the intricacies of consumer behavior, particularly in the digital age. By uncovering the reciprocal relationships between the decision-making process and other variables, the research provides a more nuanced understanding of how consumers navigate today's complex landscape. It further delves into how variations in the decision-making process across diverse consumer groups influence various outcomes, recognizing the unique characteristics and needs of different demographics. The research also acknowledges the interplay of psychological, social, and contextual factors that shape both the decision-making process and its downstream effects, offering a comprehensive understanding of the multifaceted influences on consumer behavior. Ultimately, by studying the decision-making process as an independent variable, this research aims to equip businesses and researchers with valuable insights, enabling them to better navigate the ever-evolving world of consumer behavior.

In 2018, Iran witnessed approximately 21,000 fatalities resulting from road accidents, ranking it as the fifth leading cause of death across all age groups. These incidents carry substantial economic and social burden for the nation, claiming more than 5% of its GDP. Human behavior emerges as a significant contributing factor to high-risk driving offenses. It has been proposed that by influencing general deterrence, a rigorous defense can be established against such violations. Various theories posit that by reinforcing or diminishing influential factors, general deterrence perception can be molded, presenting a potential avenue for an effective deterrent against traffic infractions. This study examines deterrence perceptions prevailing among the public in Iran regarding the enforcement of traffic laws. Employing Structural Equation Modeling (SEM), we delve into the intricate relationships between variables, allowing for a comprehensive exploration of the factors influencing general deterrence. The study draws on the data derived from a survey comprising 548 questionnaires for modeling purposes. An innovative concept, private sector enforcement, is introduced and incorporated into the questioning and modeling process. The findings reveal that socioeconomic status (p-value&lt;0.01), police enforcement (p-value&lt;0.05), private sector enforcement (p-value&lt;0.05), specific deterrence (p-value&lt;0.01), and the use of technology (p-value&lt;0.01) have direct and indirect impacts on the general deterrence perception of drivers.

Abstract Peripartum depression (PPD) is a major complication of pregnancy and many risk factors have been associated with its development, including dysfunctional coping strategies and insecure attachment styles, both during pregnancy and postpartum. The aim of our study was to investigate the role of coping strategies in mediating the relationship between women’s attachment style and PPD in pregnancy, and one week after childbirth, in a large cohort of women. We hypothesized that the relationship between anxious and avoidant attachment and PPD would be mediated by use of maladaptive coping strategies. The assessment instruments were Edinburgh Postnatal Depression Scale (EPDS), Brief Coping Orientation for Problem Experiences (COPE), Experiences in Close Relationship Scale (ECR). The results indicated that the effect of insecure attachment styles (anxious and avoidant attachment) on antepartum depressive symptomatology was partially mediated by dysfunctional coping styles. Anxious attachment has also an indirect significant effect on postpartum depression through emotional coping; however, avoidant attachment does not seem to be significantly related to postpartum depression. Our findings revealed that not only it is important to consider attachment in understanding PPD but also that coping plays an important role in these relationships. These findings would help a preventive coping-based intervention strategy to enhance the capacity of women with insecure attachment styles to use more adaptive coping during and after pregnancy.

The paper presents the problem of damage detection in steel girders. Static displacements at the selected point of the structure play the role of measured variables. Structural response signal decomposition is performed according to the Mallat pyramid algorithm, which is used to perform the discrete wavelet transform (DWT). This procedure allows us to quite well determine the location of structural damage. The geometry and the placement of any defective part of the structure may have a random character. It can be assumed that the random processes occurring in the broadly understood structure mechanics are Gaussian in nature. The first four probabilistic moments are estimated using three approaches independent: semi-analytical (SAM), perturbative (SPT), and Monte-Carlo simulations (MCS). The semi-analytical random approach seems to be the most optimal due to the necessary computation time. The incorporation of the mathematical stochastic apparatus into the classical (deterministic) analysis of the statics of the structure makes it possible to estimate the reliability measures of the analyzed girder.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

This study, based on the AISAS model, explores the impact of the interaction effect between visual and auditory signals on consumer purchase behavior. Using experimental methods, 120 participants were randomly assigned to four different visual and auditory signal combinations, and their purchase intentions and actual purchase behavior were measured. The results show that the interaction effect between visual and auditory signals has a significant impact on both purchase intentions and actual purchase behavior, and there is a significant positive relationship. Specifically, when visual and auditory signals are mutually consistent, consumers have the highest purchase intentions and actual purchase behavior; when both visual and auditory signals are absent, consumers have the lowest purchase intentions and actual purchase behavior; when either the visual or auditory signal is missing, consumers' purchase intentions and actual purchase behavior are in between the two extremes. This study provides a new perspective for understanding consumers' decision-making processes in multi-sensory environments and offers valuable insights for the development of marketing strategies.

Effects of oxygen content on microstructure and creep property of FGH96 superalloy were investigated. When oxygen content increased from 135ppm to 341ppm, prior particle boundary (PPB) rose from degree 2 to degree 3, and the size of γ′ phase on PPB enlarged from 1.07μm to 1.27μm, and MC carbide size grew from 77.4nm to 104.0nm. Meanwhile, the steady creep rate accelerated form 4.34×10-3 h-1 to 1.87×10-2 h-1, and the creep rupture life shortened from 176h to 94h, and the creep rupture mode transferred from intergranular and transgranular mixed fracture to along PPB fracture. During creep, the micro-twins formation and gliding will be restrained by ∑3 boundaries. FGH96 superalloy with higher oxygen content contains less ∑3 boundaries and its micro-twins cross slipped instead of single direction slip in lower oxygen content superalloy. Consequently, specimen with higher oxygen content creeped faster and raptured earlier.

In this paper, we consider a fourth-order suspension bridge equation with nonlinear damping term |u_t|^m-2u_t and source term |u|^p-2u. We give necessary and sufficient condition for global existence and energy decay results without considering the relation between m and p. Moreover, when p>m, we give sufficient condition for finite time blow-up of solutions. The lower bound of the blow-up time T_max is also established. It worth to mention that our obtained results extend the recent results of Wang (J. Math. Anal. Appl., 2014) to the nonlinear damping case.

Background: This study was designed to adapt the Delis-Kaplan Executive System (D-KEFS) version of the Color-Word Interference (CWIT) and Trail making Tests (TMT) in Greek adult population from 20 to 49 years old, since it is of research as well as clinical importance to detect executive functions’ impairment in young adults with neurological or/and psychiatric conditions. Aims: Norms for the Greek adult population have been calculated to be available for neuropsychologists and health professionals who work in relevant settings. Methods: The study sample consisted of 101 healthy adults (41% male and 60% female), aged 20 to 49 years (M=32.16, SD=11.57) with education from 12 to 19 years of schooling (M=14.51, SD= .89). Pearson correlation test as well as chi square test were conducted to examine potential associations between gender, age, education, and participants’ performance. Afterwards, we calculated normative data using raw scores and transformed them to percentile scores. Finally, Greek norms were compared to the original raw scores, which were transformed in scaled scores by Delis et al. (2001). Results: The findings showed that age was the only variable which affected CWIT, whereas level of education as well as age were predictive factors for most TMT conditions, except for the visual scanning test (Condition 1). Gender did not affect both tests. Finally, D-KEFS norms for CWIT and TMT are available for Greek adult population to help clinicians detect executive functions’ deficits and therefore adjust tailored therapeutic strategies. Additionally, it is of great importance to use these tests for research purposes. Conclusion: Given that executive functions are assumed as high- level skills, which are highly related to everyday functionality, adapted tests contribute not only to assess the progression of any existing neurological as well as psychiatric disorders, but they can also be used to evaluate patients’ ability to live independently, as well as their access to work.

Abstract Introduction: In the last thirty years, brain neuromodulation techniques have been used as an alternative to pharmacological treatment of neurological disorders. Parkinson's disease (PD) is a neurodegenerative disorder leading to bradykinesia, rest tremor, postural changes, and non-motor symptoms such as depression, anxiety, sleep disorders, pain, and cognitive decline that compromises executive functions (EFs), responsible for the orderly execution of behaviors and tasks of daily life and intentional and directed actions. To this date, a few studies with transcranial direct current stimulation (tDCS) have shown beneficial effects in PD patients concerning specific motor and non-motor symptoms, targeting the motor cortex and/or prefrontal regions. Objective: The main objective of this study was to evaluate the effects of left prefrontal tDCS across a broad spectrum of motor and non-motor symptoms of PD using established validated scales. Method: Single-blind randomized clinical trial with 18 volunteers with PD, aged between 45 and 80 years (66.1 ± 9.65), who met inclusion and exclusion criteria. Participants were submitted to assessments of motor and non-motor functions employing psychometric scales and tests to evaluate EFs and were randomly divided into two groups: control (sham stimulation) and experimental (active stimulation). All participants were involved in three separate tDCS sessions. The anode was positioned over the left dorsolateral prefrontal cortex and the cathode over the right supraorbital region, with a direct current intensity of 2mA, lasting 20 minutes. At the end of the three sessions, all participants were reassessed. Results: Significant effects of tDCS on non-motor functions were observed for cognition (verbal fluency of actions, clock copy test, appointment by visual confrontation, and verbal memory with immediate free recall) and subjective assessment of sleep quality (overall restlessness and discomfort in the arms and legs at night, leg and arm cramps at night and distressing dreams). There was also an improvement in the rate of errors and successes for congruent and incongruent stimuli of the Stroop Test. The beneficial effects on motor function were decreased rigidity, improved gait, and greater agility in the finger-tapping test. Conclusion: Three tDCS sessions showed positive results for participants with PD, producing significant improvements in various motor and non-motor functions, including sleep quality, cognition, and EFs. Additionally, the present results indicate that tDCS neuromodulation of the left dorsolateral prefrontal cortex region is feasible, safe, and provides significant objective benefits for PD patients.

Sustainable food consumption has attracted a widespread attention during last decades by scholars, policy makers and consumers. In line with this, farmers’ markets (FMs) have the potential to encourage sustainable agricultural production and consumption. By reducing the number of actors and distances along the food chain, these alternative food systems foster the reconnection between farmers and consumers and contribute to different social, economic and environmental sustainable goals. This paper provides insights on the role of consumers' sustainability concerns related to their motivation for shopping at FMs. By means of a choice experiment, we analyze the determinants of consumers’ WTP for buying apples at FMs. We are particularly interested in understanding how attitudes towards the three sustainability dimensions are related to consumer preferences in this context. We find that consumer attitudes towards direct contact with producers, contributing to farmers’ income, and environmental benefits can be directly related to product characteristics that are specific to FMs.

This literature review provides an in-depth exploration of the research conducted on the investigation and measurement of residual stress (RS) in Wire Arc Additive Manufacturing (WAAM) products, particularly focusing on how process parameters influence the phenomenon. RS plays a crucial role in determining the mechanical behavior and structural integrity of WAAM components. This review article gives an understanding of the relationship between process parameters and RS to optimize the WAAM processes and ensure the durability of the final products. It also summarizes key findings, measurement techniques, challenges, and future directions in this evolving field. The review also analyzes a measurement of RS in the products of WAAM as a function of process parameters depending on examining various research studies, techniques, and methodologies employed in their studies. Experimental measuring techniques and numerical analysis of RS to determine the impacts of RS in mechanical response in products of WAAM were discussed. By offering a comprehensive overview of current research trends and insights, this review serves as a valuable resource to guide future investigations, fostering the advancement of WAAM as a robust and efficient manufacturing technology.

The superfamily of Acid proteases has two catalytic aspartates for proteolysis of their peptide substrates. Here, we show a minimal structural scaffold, the Structural Catalytic Core (SCC), which packs all conserved substructure elements around the catalytic machinery, and which can be found in all enzymes of the Acid proteases superfamily. The SCC is a dimer of several structural blocks, such as the DD-link, the D-loop and the G-loop, around two catalytic aspartates in each protease subunit or within an individual chain. The dimer of two D-loop/DD-link substructures makes a DD-zone, and the dimer of two D-loop/G-loop substructures makes a psi-loop. These structural markers are useful for protein comparison, structure identification, protein family separation and protein engineering.

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and brain volumes and white matter integrity (FA and MD) with magnetic resonance imaging in the BrainSCALE cohort, consisting of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years of the twins. Genes influenced externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to –0.20); with sizeable genetic correlations (FA ra up to +0.42; MD ra up to –0.33). Cortical gray matter (CGM; rph up to –0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genotypically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence from the same genetic factor.

The current study compared the goodness of fit and estimation precision of Bayes and maximum likelihood (ML) structural equation modeling across sample sizes. Data consisted of Markov Chain Monte Carlo generated samples of 50, 75, 100, 125, 150, 200, 250, 500, 750, 1000, and 1500 observations. The Bayes and ML methods were used to estimate a structural equation model with 40 parameters, including 12 continuous observed indicators, four latent variables, and three structural paths. Analyses were conducted with the Mplus 8.0 statistical software and were replicated 500 times with each of the 22 conditions (11 sample sizes x 2 estimation methods). Indices of model fit were the Bayes information criterion, the Tucker-Lewis index, the comparative fit index, the root mean square error of approximation, the posterior predictive p-value (for Bayes models), and the ꭓ2 test (for ML models). Results showed that as the sample size increased, both estimation methods exhibited improved model fit and enhanced estimation precision, and both methods performed well with samples of 200 or larger; however, ML demonstrated a marginally superior fit with smaller samples. These findings were not consistent with previous research and suggest that ML remains a better choice with continuous data and small samples.

E-commerce platforms created to meet the needs of digital consumers, who are the leading actors of digital-oriented consumption, are increasing rapidly. Revolutionizing our daily lives by offering the digital equivalent of real-world experiences, e-commerce now offers a comfortable shopping experience that transcends the limitations of time and space. This phenomenon has been embraced by individuals spanning all age groups, from young children to the elderly. Structural equation modeling was used in this study, in which the factors affecting online shopping addiction were determined. In this direction, the causal and correlational relationships between the variables of fear of missing out (FoMO), cognitive load, personality types, some socio-demographic characteristics (gender and monthly shopping amount) and online shopping addiction in online shopping were revealed structurally. Since the purposive sampling was used, the study was carried out on 488 people. The goodness-of-fit indices included in the created model were found at an “acceptable” level (χ2/df= 2.248, p=0.000; RMSEA=0.051; GFI=0.878; AGFI=0.856; CFI=0.950; NFI=0.914). These results show that the final version of the model meets the necessary criteria for a good fit, its validity and accuracy. The study revealed the causal and correlational relationship between online shopping addiction and cognitive load, personality types, FoMO, gender, and monthly online shopping amount.

The effectiveness of a hybrid technique for identifying seismic damage in planar, multistory, steel X or V-braced frames is demonstrated here through an example of a six-story frame. This proposed technique, referred to as “M and P”, combines the instrumental Monitoring (M) with Pushover analysis (P). According to the methodology, the diagram of stepping eigenfrequencies of the frame in the inelastic region is initially plotted against seismic roof displacement. The fundamental natural frequency detected via the monitoring process is then utilized in this key diagram to reveal the inelastic roof displacement that corresponds to the damage state of the steel braced frame. This displacement is subsequently used as the target in the pushover analysis, facilitating the identification of seismic damage in the existing steel braced frame. Finally, the damage image is correlated with the damage stiffness matrix of the frame at the same inelastic roof displacement. The investigation results indicate that combining instrumental monitoring with pushover analysis enables accurate identification of seismic damage potential in existing steel braced frames.

The paper delves into the critical issue of damage detection within the guy cable of a truss steel mast, a pivotal component in structural integrity. It introduces a model wherein damage manifests as a localized cross-section reduction in a single element of the cable. Employing Discrete Wavelet Transform (DWT), a pioneering methodology, the study scrutinizes the behavior of the affected elements through static structural analyses. Signal decomposition via the Mallat pyramid algorithm facilitates comprehensive examination. Static displacements at the connection point between the cable and the truss mast serve as the measured variables. Through systematic investigation, the paper evaluates the impact of damage size and location, external loading force, and cable tension force on the efficacy of the proposed approach. Utilizing data derived from Finite Element Method (FEM) computations for wavelet analysis the authors substantiate the findings with numerical examples, thus offering valuable insights into damage detection strategies for structural health monitoring and engineering applications.

This study estimates the effects of double long memory and structural breaks on the persistence level of six major cryptocurrency markets. We apply the Bai and Perron’s structural break test, Inclán and Tiao’s iterated cumulative sum of squares (ICSS) algorithm, and the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model with different distributions. The results show that long memory and structural breaks characterize the conditional volatility of cryptocurrency markets and confirm our hypothesis that ignoring structural breaks leads to an underestimation of the persistence of volatility modelling. The ARFIMA-FIGARCH model with structural breaks and a skewed Student–t distribution fits the cryptocurrency market’s price dynamics well.

Promoting organic foods production and consumption contributes to accomplishing United Nations sustainable development goals. Social commerce provides a promising opportunity to develop the organic food industry. However, there is limited knowledge regarding customer behaviors in relation to purchasing organic foods via social commerce platforms. Therefore, this study expanded upon the unified theory of acceptance and use of technology (UTAUT-2) to develop a comprehensive model that explains how customers' social commerce trust and behavioral intentions to purchase organic foods using Instagram social commerce affect their purchasing behaviors. The research model was analyzed by employing partial least squares structural equation modeling (PLS-SEM) for the data collected from a quantitative survey of 410 customers who used Instagram to purchase organic foods in Iran. The results revealed that facilitated purchasing conditions, hedonic motivations, social influence, rating and reviews, and influencers’ endorsements increase customers' purchase intentions. Moreover, Instagram’s recommendations and referrals, influencers’ endorsements, as well as social influence boost customers' trust in the social commerce platform. Eventually, it was determined that influencers’ endorsements, social commerce trust, and purchase intention determine a customer’s organic foods purchasing behaviors. This research provides valuable insights for organic food marketers to optimize their social commerce strategies.

This study provides an in-depth review of the available literature on metal composite material machining, focusing on traditional machining operations such as turning, milling, shaping, drilling, and grinding. The motivation for the study is that this composite type has emerged as a vital material in applications requiring functionality, resilience, cost-effective operation, low consumption of energy and lightweight. Despite its superior characteristics, the manufacturing complexity and poor machinability of metal matrix composites have been the primary barriers to its adoption. Nevertheless, there is a reduction of exceptional efficiency, increase in surface roughness, tool wear and so on in metal matrix composites throughout machining. As a result, this review gives a comprehensive investigation of metal matrix composite machining and effect on process parameters and procedures. Furthermore, this study distinguishes metal matrix composites towards sustainable manufacturing and the metals employed by the researchers, as well as the gaps discovered for future recommendations in metal-based composites.

The epidemic of obesity has increased worldwide and is associated with comorbidities as diabetes as cardiovascular disease. Strategies that modulate body weight and improves glycemic metabolism has increased, and the bariatric surgeries as Sleeve Gastrectomy (SG) has been highlighted in obesity treatment. However, the mechanism by which SG reduces body weight and improves glycemic control are unknow. C57BL mice were submitted to a 10 weeks high fat-diet protocol and submitted to SG. Food intake, fed/fasted glycemia and hypothalamic anorexigenic and orexigenic gene expression were evaluated. SG reduces body weight, fasting glycemia, insulinemia and leptinemia in obese mice. Moreover, SG reduces food and total calorie intake with no alterations in the expression of anorexigenic and orexigenic gene expression. These data indicates that SG improves obesity associated alterations, at least in part, by reduction on food intake. This effect is not associated with the classic food intake pathway in hypothalamus, indicating the involvement of supplementary pathways in this process.

The unsafe behavior of frontline workers at construction sites is the most important cause of construction accidents. This study proposed a comprehensive model of frontline workers' unsafe behaviors based on a systems perspective and used structural equation modeling (SEM) to explore the influence mechanisms between Objective Conditions (e.g., work environment, work climate, task complexity), Safety Management (e.g., safety education and training, safety reward and punishment regulations, safety inspection, safety technology disclosure, safety warning signs), Group Influence (propagation of unsafe behaviors among workers), Personal Perception (subjective judgment of operators on their safety knowledge and skills), and Unsafe Behaviors. Data from 460 frontline workers were collected through questionnaires and the correlation hypotheses were tested using SPSS 26.0 and Amos 26.0 software. The following conclusions were obtained: (1) Objective Conditions directly positively influence Safety Management, Group Influence, and Personal Perception, but indirectly negatively influence Unsafe Behavior; (2) Safety Management not only directly positively affects Personal Perception but also directly negatively affects Unsafe Behavior. However, the direct effect of Safety Management on Group Influence is not significant; (3) Group Influence has a direct positive effect on Unsafe Behavior, but the direct effect on Personal Perception is not significant; (4) The direct effect of Personal Perception on Unsafe Behavior is insignificant. These findings can be used as preliminary data to guide decision-makers or managers in construction companies to develop reasonable management plans to curb unsafe behaviors of frontline workers.

ObjectivesThe present study is aimed at characterizing and identifying the important research trends of the application of structural equation modelling (SEM) in nursing research by bibliometric analysis, and further providing reference for nursing researchers to conduct SEM research.MethodsA descriptive bibliometric analysis of publications in the application of SEM in nursing research. Literatures were retrieved from the Web of Science (WoS) core collection database On April 30, 2022. CiteSpace 6.1.R1 and VOSviewer 16 software were used for visualization and bibliometric analysis.ResultsThe annual publication indicated an increasing trend in the future. The intellectual structures of the application of SEM in nursing researches included patient safety, cross-cultural comparison, compassion fatigue, benchmarking, patient discharge, China, psychometrics, and policy. The hotpots and development trends include job satisfaction, nursing home, and nursing student.ConclusionThe hotspots and development trends related to the application of SEM in nursing research mentioned in this study may be helpful for researchers to explore new directions in this field. The intellectual structures and development trends were found in the application of SEM in nursing researches in this study. The awareness of the clusters and bursts in this field can help nursing researchers avoid overlooking some important issues when conducting SEM, and provide nurse researchers with good practice guidelines for conducting SEM.

The purpose of this research is to determine if the tradeoffs that Kissick proposed among cost containment, quality, and access remain as rigidly interconnected as originally conceived in the contemporary health care context. Although many have relied on the Kissick model to advocate for health policy decisions, to our knowledge, the model has never been empirically tested. Some have called for policy makers to come to terms with the premise of the Kissick model tradeoffs, others have questioned the model given the proliferation of quality enhancing initiatives, automation, and information technology in the health care industry. One wonders whether these evolutionary changes alter or disrupt the originality of the Kissick paradigms themselves. Methods: Structural Equation Modeling (SEM) was used to evaluate the Kissick hypothetical relationships among the unobserved constructs of cost, quality, and access in hospitals for the year 2018. Hospital data were obtained from Definitive Healthcare a subscription site which contains Medicare data as well as non-Medicare data for networks, hospitals, and clinics (final n= 2,766). Results: Reporting significant net effects as defined by our chosen study variables, we find that as quality increases costs increase, as access increases quality increases, and as access increases, costs increase. Policy and Practice Implications: Our findings lend continued relevance to a balanced approach to health care policy reform efforts. Simultaneously bending the health care cost curve, increasing access to care, and advancing quality of care is as challenging now as it was when the Kissick model was originally conceived.

Flour yield determined the profitability of flour mill, but the intrinsic variability of the grain makes it very complex to analysis and estimate wheat grain flour yield. Simulation for flour yield attributes offer considerable advantages in flour mill, if reliable predictions of flour yield can be provided, because the wheat grain characteristics can be tested before milling. If this is possible, the characteristics thus observed could be quantified more reliably and objectively by Structural Equation Modelling (SEM). SEM was used to look for the most important wheat grain characteristics on flour yield, and then these wheat grain characteristics were used to simulate flour yield. Furthermore, the regressive equation was verified by the field experiment. The coefficient of variation of grain characteristics was low and distributed rather closely. The results of SEM showed that test weight had the most significantly effects on flour yield, followed by the hardness index. Test weight and hardness index could excellently estimate flour yield by multiplicative effect of test weight and hardness index, and which could determine 68% of the variation in flour yield. The simulation result can not only predict flour yield, but also look for the important grain characteristics for the flour yield.

The principal aim of this descriptive-survey investigation is to ascertain the factors influencing individuals' choice to purchase organic commodities in Tehran. The statistical populace for this examination comprised all patrons of food retail establishments in Tehran, with the sample size determined using the Cochran formula for an unknown community size, involving the distribution of 30 questionnaires to customers (n=439). Data collection was carried out through a random sampling technique. The survey instrument consisted of a questionnaire with two sections consisting of general queries (7 questions) and specific inquiries (23 items) categorized into four dimensions (product, price, place, and promotion) for the clientele. The questionnaire's validity was confirmed through face and content validation, while its reliability was assessed utilizing Cronbach’s alpha. Data analysis was conducted using SPSS25 software, encompassing both descriptive and inferential statistical analyses. The results revealed a positive and significant correlation between customers' inclination to consume organic goods and the characteristics of the product, price, and promotion. However, no association was found between the propensity to consume organic products and location characteristics. Concerning contextual variables, a solely positive and significant correlation was identified between the willingness to purchase organic items and consumer income levels. No significant relationships were detected between other contextual variables and organic product consumption. A notable contrast was observed between respondents' gender and their readiness to buy organic products, while no significant variances were noted regarding age, income, occupation, and education in relation to the propensity to purchase organic commodities.

Construction projects are usually operating in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Construction projects are complex and frequently involve substantial uncertainties including process complicatedness, intricate organization structure, dynamic environment, and financial strain. The study aims to categorize the influencing factors into three groups, namely construction project system, economic-market climate, and external environment. It attempts to adopt a novel analysis tool to examine the relationship between the project cost and multiple influencing factors by using Bayesian SEM. While the Bayesian SEM method has been receiving increasing attention in exploring the relationship between latent variables, construction studies still heavily rely on the covariance-based SEM approach. This study introduces several advantages of Bayesian SEM that make it more flexible and powerful than covariance-based SEM and provides the foundation of Bayesian SEM estimation and inference by illustrating this method in a project cost application.

Construction projects are usually operating in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Construction projects are complex and frequently involve substantial uncertainties including process complicatedness, intricate organization structure, dynamic environment, and financial strain. The study aims to categorize the influencing factors into three groups, namely construction project system, economic-market climate, and external environment. It attempts to adopt a novel analysis tool to examine the relationship between the project cost and multiple influencing factors by using Bayesian SEM. While the Bayesian SEM method has been receiving increasing attention in exploring the relationship between latent variables, construction studies still heavily rely on the covariance-based SEM approach. This study introduces several advantages of Bayesian SEM that make it more flexible and powerful than covariance-based SEM and provides the foundation of Bayesian SEM estimation and inference by illustrating this method in a project cost application.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

This paper proposes an enhanced Quantum Key Distribution (QKD) protocol by incorporating a Three-Dimensional Angular Momentum Representation (3D AMR) to address vulnerabilities inherent in traditional two-dimensional polarization states-based systems. The 3D AMR method expands the state space, potentially increasing security against sophisticated quantum attacks. We present a theoretical and computational framework that transitions from the conventional two-dimensional polarization to a three-dimensional angular momentum space, which inherently increases the complexity and security of the quantum states used in QKD.

Queretaro is currently one of the states with the highest growth rate in the automotive industry. In the last five years, the number of companies has increased, reaching more than 300 small and medium-sized companies in the sector. However, they show a high degree of ignorance and lack of strategic foresight, which translates into poor planning in the short, medium and long term and low competitiveness, leading many of them to failure. This paper presents the results of a study within a strategic foresight evaluation with the development of a Structural Equation Model that allows the analysis of foresight and strategic planning within the automotive SMEs in the state of Queretaro. The study analyzes the necessary indicators to be evaluated and establishes the relationship of dependence between the variables, which is necessary to create the constructs of the model. It is confirmed that the adjustment of the model used is adequate for the evaluation of SMEs. The contributions of the research were: A theoretical contribution related to strategic foresight within SMEs and the construction of the structural equation model to evaluate strategic foresight in automotive SMEs in the state of Queretaro.

This paper investigates the energy dissipation level of a nonlinear vehicle suspension system. The suspension system is modelled as a mass-spring-damper system, which is designed using the output frequency response function (OFRF) method. This method enables the derivation of an explicit relationship, between the system output spectrum (or Performance metric) and the system nonlinear parameters of interest. The OFRF polynomial, of the energy dissipation level, was derived in terms of the nonlinear parameters of interest. The results obtained show that the OFRF model, of the energy dissipation level, could be used to estimate the amount of heat dissipated, for a set of design parameters. This has potentials of providing some insights, in the design of vibration-based energy harvesters, as some of the wasted heat energy could be converted to electrical energy.

Full depth precast deck panel (FDDP) is one element of the prefabricated bridge element and systems (PBES) that allows for quick un-shored assembly of the bridge deck on-site as part of the accelerated bridge construction (ABC) technology. This paper investigates the structural response of full-depth precast deck panels (FDDPs) constructed with new construction materials and connection details. FDDP is cast with normal strength concrete (NSC) and reinforced with high modulus (HM) glass fiber reinforced polymer (GFRP) ribbed bars. The panel-to-girder V-shape connections use the shear pockets to accommodate the clustering of the shear connectors. A novel transverse connection between panels has been developed, featuring three distinct female-to-female joint configurations, each with 175-mm projected GFRP bars extending from the FDDP into the closure strip, complemented by a female vertical shear key and filled with cementitious materials. The ultra-high performance fiber reinforced concrete (UHPFRC) was selectively used to joint-fill the 200-mm transverse joint between adjacent precast panels and the shear pockets connecting the panels to the supporting girders to ensure full shear interaction. Two actual-size FDDP specimens for each type of the three developed joints were erected to perform fatigue tests under the footprint of the Canadian Highway Bridge Design Code (CHBDC) truck wheel loading. The FDDP had a 200-mm thickness, 2500-mm width, and 2400-mm length in traffic direction; the rest was over braced steel twin girders. Two types of fatigue tests were performed; incremental variable amplitude fatigue (VAF) loading and constant amplitude fatigue (CAF) loading, followed by monotonically loading the slab ultimate-to-collapse. It was observed that fatigue test results showed that the ultimate capacity of the slab under VAF loading or after 4 million cycles of CAF exceeds the factored design wheel load specified into the CHBDC. Also, punching shear failure mode was dominant in all the tested FDDP specimens.

Reliable and precise damage localization in mechanical structures is of high importance in the context of structural health monitoring (SHM). The acoustic emission (AE) method has already shown its excellent suitability for damage localization. However, low signal-to-noise ratios (SNRs) are often prevalent in SHM, thus an increase in localization accuracy and robustness is still in demand. The present study faces this task through the integration of various model knowledge for AE source localization. The basis of the presented algorithm is the consideration of the dispersive behavior of elastic waves in thin-walled structures. The continuous wavelet transform (CWT) is used to obtain time-frequency representations of the signals, where frequency-dependent values for time-of-arrival (TOA) are extracted. Furthermore, the algorithm incorporates the knowledge that all sensors receive signals with the same time and location of origin, as well as the slightly different sensitivity of the theoretically equal sensors. The final localization results are achieved by a two-parameter grid search optimization. The algorithm is experimentally tested on a large aluminum plate with four piezoelectric wafer active sensors (PWASs) arranged in an array of 100 mm × 100 mm. The mean localization error of pencil lead breaks at ten different positions within the sensor array is used as an accuracy measure. It is shown that as more of the described model knowledge is incorporated into the localization, the accuracy increases. With the final algorithm, the mean localization error is more than halved compared to AE localization based on classical TOA estimation. Although the experiment described is conducted under laboratory conditions, the remarkable increase in accuracy suggests that AE source localization may be successful even at low SNR as typical for operational conditions.

In the context of Inverse Analysis in Civil Engineering, parameter identification and model calibration, of a structural system, relying on dynamic measurements, are subjects of a growing research interest. In the present contribution, the topic is tackled with reference both to simplified structural numerical examples and to a specific case study, namely a historical road three-span reinforced concrete arched bridge, with vibrational data previously acquired by standard wired accelerometers on the deck, under operational traffic conditions. In particular, the present work aims at focussing on the identification issues, concerning the definition of a maximum allowable threshold number of sought material parameters (e.g., Young’s moduli and mass densities of different structural components), with respect to the amount of available measurement data, and the investigation of the inverse analysis discrepancy function to be optimised, in order to set the intrinsic issue of multiple “realizations”, in case of a plain use of modal properties, and in view of forming a well–posed optimisation problem. Structural modelling, sensitivity analysis and numerical optimisation approaches are herein combined toward a robust and efficient identification strategy, to be effectively employed in structural assessment and diagnosis, also with respect to originally available or enriched sets of experimental data. The proposed methodology, and collected results, shall outline an efficient identification procedure, in view of automated inverse analysis, practically oriented to the dynamic assessment and structural diagnosis in the Civil Engineering context, as applied e.g. to strategic bridge infrastructures.

Fintech's emergence is one of the most significant developments in finance, and its application has been of much interest and popularity in recent decades. This study aims to explore the adoption of fintech in emerging economies by employing a structural equation model. The study's sample population consists of bank clients of Ethiopian commercial banks who have used financial technology platforms for at least one year. The total number of sample sizes is 440. The data collection instrument used for this study is a questionnaire (seven-point likert scales ranging from strongly disagree to strongly agree). Structural equation model (SEM) analysis was implemented using Amos software to examine the relationship between variables. The findings of the study support the hypotheses that various factors, including performance expectancy, effort expectancy, social influence, facilitating condition, traliaility, and user innovativeness, significantly influence the adoption and usage of fintech services. The study recommends that FinTech companies implement pilot programs to allow potential users to trial FinTech services on a limited basis before full commitment. Fintech industries should engage with local communities through events, seminars, and workshops to introduce fintech services. Having community leaders and respected individuals advocate for the technology can enhance acceptance.

The main objective of this study is to apply structural equation modeling with partial least squares and based on covariance to assess the satisfaction of residential electricity consumers. The methodology used compares the results of both structural equation models to indicate the model that best fits the problem of measuring the satisfaction of residential consumers of electricity concessionaires and licensees. The sample used in the survey contained questionnaire responses from 86.175 individuals considering the period from 2014 to 2018. The constructs evaluated were satisfaction, quality, value, loyalty, and trust. Confidence interval analysis shows that all weights are significant, demonstrating the importance of all the indicators that represent the constructs. The trust, quality, and value constructs can explain 74.4% of the variability of the satisfaction construct, so the explanatory capacity of this relationship is considered substantial. Finally, the evaluation of the performance of the service provided by the electric energy concessionaires/licensees, measured by customer satisfaction, allows for the continuous improvement of services and meeting, even if minimally, the expectations of its consumers.

Many causal factors to marine traffic accidents (MTA) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to the accident mechanisms, the complex structural chains on causes to MTA systems were analyzed combining the Human Failure Analysis and Classification System (HFACS) with theoretical Structural Equation Modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of MTA, and the constituent elements of the causes of accident was conducted. Second, a hypothetical model of Human factors classification was proposed applying the practice of the structural model. Third, with the data resource from ship accident cases, this hypothetical model was discussed and simulated, and as a result the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behaviors. Application examples show that relationships in HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

In recent years, there has been an increasing interest in adopting novel sensing technologies for the continuous monitoring of structural systems. In this respect, Micro-Electro-Mechanical System (MEMS) sensors are widely used in several applications, including Structural Health Monitoring (SHM). Thanks to their significantly lower cost, ease of installation on the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through the network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analysis show that MEMS can correctly detect modal frequencies, useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

Lightweight component design is effectively achievable through the sandwich structures, many past research studies in the aerospace and racing sectors (since 1920s) has proven it. To extend their application into automotive and other transport industries, the manufacturing cycle times must be reduced. This can be achieved by thermoplastic sandwich materials of continuous fibre-reinforced thermoplastic (CFRTP) cover layers and thermoplastic honeycomb cores. To widespread the application of flat thermoplastic-based sandwich panels into complex parts, a novel forming technology was developed by the Fraunhofer Institute of Microstructure of Materials and Systems (IMWS). For an increase in reproducibility of the sandwich component production and a decrease in manufacturing defects, numerical modelling methods and experimental validation are needed. The finite element (FE) modelling of this thermoforming process is a thermo-mechanical assignment with all three: material, geometry, and boundary non-linearities. In the scope of this work, the material behavior of different sandwich components (cover layers, honeycomb core, interface) under thermo-mechanical loads is characterized in detail, and a complex numerical model is developed to describe the thermoforming process of thermoplastic-based sandwich laminate. The critical forming condition like wrinkling that occurs due to friction in a sandwich or poor intra-ply shear in cross-ply studied, validated, and optimized. A thermoplastic sandwich made of polypropylene (PP) honeycomb core and polypropylene glass fibre (PP/GF) cross-ply as cover layers was used for this study, and numerical modelling was executed in LS-DYNA software.

Prompt removal of misfolded membrane proteins and misassembled membrane protein complexes is essential for membrane homeostasis. However, the elimination of these toxic proteins from the hydrophobic membrane environment has high energetic barriers. Transmembrane FtsH is the only known ATP-dependent protease responsible for this task, unlike other well-studied soluble ATP-dependent proteases. The mechanisms by which FtsH recognizes, unfolds, translocates, and proteolyzes its substrates remain unclear. Here, we report the crystal structures of the Thermotoga maritima FtsH periplasmic domain (PD) in an associative trimeric state at a 1.5-1.95 Å resolution. We also describe the pH-dependent oligomerization states of the isolated PD using dynamic light scattering. These observations help us understand how FtsH recognizes membrane-anchored misfolded proteins.

Sodium-phosphate-based glass-ceramics (GCs) are promising materials for a wide range of applications, including solid-state sodium-ion batteries, microelectronic packaging substrates, and humidity sensors. This study investigates the impact of 24-hour heat-treatments at varying temperatures on Na-Ge-P glass, with a focus on (micro)structural, electrical, and dielectric properties of prepared GCs. Various techniques such as powder X-ray diffraction (PXRD), infrared spectroscopy-attenuated total reflection (IR-ATR), and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) are employed. With the elevation of heat-treatment temperature, crystallinity progressively rises; at 450 °C, the microstructure retains amorphous traits featuring nanometric grains, whereas at 550 °C, heat-treatment results in fully crystallized structures characterized by square-shaped micron-scale grains of NaPO3. The insight into the evaluation of electrical and dielectric properties is provided by Solid-State Impedance Spectroscopy (SS-IS), revealing a strong correlation with the conditions of controlled crystallization and observed (micro)structure. The glass-ceramic heat-treated at 450 °C achieves the highest DC conductivity of 2.30×10–8 Ω–1 cm–1 at 393 K. As the heat-treatment temperature rises, the crystallization of the NaPO3 phase depletes the glass matrix of mobile Na+ ions, resulting in a reduction in DC conductivity. Dielectric parameters also decrease with rising heat-treatment temperature, with the glass-ceramic heat-treated at 550 °C displaying the lowest permittivity of 19.37 and the dielectric loss of 0.008. This research uncovers the intricate relationship between heat-treatment conditions and material properties, emphasizing that controlled crystallization allows for precise modifications to microstructure and phase composition within remaining glassy phase, ultimately facilitating fine-tuning of material properties.

In recent years, with the increase in maritime trade, the necessity of increasing the capacities of the ports has emerged. However, while it is planned to increase the capacities of the ports, it is important that the port continues to operate at the same time. In this respect, the old port structures should not be damaged during the capacity increase. In this study, the strengthening of a port in Guinea is discussed as a case study. In the study, the existing quay wall was evaluated, and geotechnical and structural alternatives of the new structure to be built for capacity increase were evaluated. A combined system was designed as a pile foundation and a reinforced foundation with plastic piles so as not to damage the existing quay wall. The pile capacities obtained as a result of the analyses were verified by loading tests.

This paper is showing the results of a study focused on the occurrence of failures in heterogeneous structural materials, especially on the issue of modelling the formation and propagation of cracks. Attention is paid to the application of the finite element method to various types of materials in order to find critical parameters determining the behaviour of materials during the damage process. Application of damage mechanisms and approaches to modelling the origin of crack propagation by modifications in FEM systems are presented. Furthermore, some practical applications are tested. The main effort is devoted to composites and searching for procedures when using cohesion models for their more accurate modelling, especially near the stress concentrators, or before the crack tip. The use of the cohesive approach of elements that represent the physical nature of energy release in front of the crack front has proven to be promising not only in the direct use of cohesive elements, but also in combination with modified methods of standard finite elements. The authors of this article use their long-term experience in the given issue, which they consistently confront with developments in this area in recent years.

This paper aims to propose improvements for plastic waste management in Salvador – the Brazilian third most populated metropolis – via Partial Least Squares Structural Equation Modeling (PLS-SEM). All indicators, constructs, and hypotheses regarding collection, sorting, recycling, and disposal in the proposed PLS model were derived from the literature review, and the dependence of the performance construct on efficiency, effectiveness, municipality's socioeconomic aspects and municipality infrastructure is evaluated. Academic and practitioner publics were surveyed, and after analysis in both SmartPLS and RStudio software, suggestions for improvement regarding plastics recycling rate, market maturity, and infrastructural aspects for optimized reverse logistics were made. Since almost double the minimum number of respondents answered the survey questionnaire and the PLS-SEM statistics showed that the modeling presents consistency, the discussion is relevant. The model can and will evolve, but examples of suggested improvement are the installation of Deposit-Return Systems (DRS) in parks, streets, and avenues for increasing selective collection and the direct purchasing of waste from residents by municipal administration, compensating them with vouchers for food. The model can be a basis for other cities worldwide sharing analogous characteristics. By considering it, organizations can contribute to both reduced Greenhouse Gas (GHG) emissions and reduced terrestrial pollution.

This study investigates the critical success factors (CSFs) of Lean Six Sigma (LSS) implementation and their impact on organizational growth in Nigerian enterprises. The objectives were to identify crucial CSFs for successful LSS deployment and assess their significance in achieving organizational growth. A mixed-method approach was used, including literature analysis, expert judgments, and a survey of 130 participants from various industries. The survey questionnaire employed a 5-point Likert scale to collect data on LSS CSFs and implementation success metrics. Structural equation modeling (SEM) with SmartPLS 4.0 analyzed the data, revealing that LSS CSFs significantly contribute (up to 39.2 percent) to the success of LSS implementations. The study identified 12 critical LSS CSFs, categorized into workers, business, and management, each influencing LSS implementation. Recommendations include creating a supportive environment, providing comprehensive training, and prioritizing continuous improvement efforts for successful LSS deployment. Future research possibilities include longitudinal studies, sector-specific analyses, and qualitative investigations to deepen understanding and enhance LSS implementation outcomes. In conclusion, successful LSS implementation empowers Nigerian organizations with improved productivity, waste reduction, and sustainable production systems, leading to overall growth and success.

In order to sustain the marine environment relationship between the environmental factors and marine biota must be investigated. This study aims to study such a correlation in the adjacent waters of Nan Wan Bay, Kenting, Taiwan, and to explore the covariance of environmental factors on marine life (whether they enhance or diminish it). To achieve these objectives, factor analysis was used to identify potential latent variables that could affect the water quality of the adjacent waters, including phytoplankton (quantity), zooplankton (quantity), and fish (quantity and species). These potential variables were named based on the results of past studies and related literature. Finally, a structural equation model (SEM) was constructed to establish a marine ecological model among the potential variables. The factor analysis results revealed that nutrients, upwelling, and primary productivity are the primary factors affecting the environmental changes in the adjacent waters of Nan Wan Bay. The comprehensive SEM showed that nutrients and primary productivity significantly impact plankton. Path analysis indicated that primary productivity has the highest direct effect on the phytoplankton cluster. However, the upwelling has a low significance in its effect on phytoplankton, zooplankton, and fish clusters. Compared to the results of past related studies, the SEM proposed in this study can reflect a considerable degree of change in the waters.

General Linear Modelling (GLM) has been widely employed to estimate the hemodynamic changes evoked by cognitive processing, which are more likely to be nonlinear than linear. First, this study re-analyzed the fNIRS data (N = 38, Mage = 5.0 years, SD = 0.69 years, 17 girls) collected in the Mixed-Order Design Dimensional Change Card Sort (DCCS) task. The results indicated that the quadratic equation was better than GLM to model HbO changes in this task. Second, analysis of a new set of data indicated that the Habit-DisHabit design of DCCS was more effective in identifying the neural correlates of cognitive shifting than the Mixed-Order Design. Third, this study found that the Non-users were more attentive and engaged than the Heavy-users, with a slower but more steady increase of brain activation in BA8 and BA9.

The fear of missing out (FoMO) is characterized in the literature as a fear that others are having rewarding experiences while one is missing out, and a constant need to keep connected with one’s social network. Driven by Social Determination Theory (SDT) FoMO has been linked with Problematic Social Networking Sites use (PSNSU), negative affectivity (NA), self-esteem (SE) and sleep disturbances. The present study reports findings from 512 individuals (79.1% women, mean age 30.5 years, SD= 8.61). Structural equation modelling (SEM) suggests that the duration of SNSs use and the numbers of SNSs platforms actively used partially mediated the relationship between FoMO and PSNSU. In turns, PSNSU partially mediated the relationship between FoMO and NA. Furthermore, the present study has extended the literature by incorporating the Vulnerability Model in the FoMO concept, identifying that SE partially mediated the relationship between FoMO and NA, while NA fully mediated the relationship between FoMO and sleeping disturbances. Accordingly, the present has extended previous research findings in showing exercise as a potential protective factor to prevent against FoMO. Practical and theoretical implications are discussed.

The process of viral integration into the host genome is an essential step of the HIV-1 life cycle. The viral Integrase (IN) enzyme catalyses integration. IN is an ideal therapeutic enzyme targeted by several drugs; raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG) and bictegravir (BIC) having been approved by the USA Food and Drug Administration (FDA). Due to high HIV-1 diversity, it is not well understood how specific naturally occurring polymorphisms (NOPs) in IN may affect the structure/function and binding affinity of Integrase Strand Transfer Inhibitors (INSTIs). In this study, we applied computational methods of molecular modelling and docking to analyse the effect of NOPs on the full-length IN structure and INSTI binding. We identified 16 NOPs within the Cameroonian derived CRF02_AG IN sequences and further identified 17 NOPs within HIV-1C South African sequences. The NOPs in the IN structures did not show any effect on INSTI binding. INSTIs displayed similar binding affinities to each IN structure. All INSTIs are clinically effective against diverse HIV-1 strains from INSTI treatment naïve populations. This study supports the use of second-generation INSTI DTG as part of first-line combination antiretroviral therapy (cART) regimens, due to DTG possessing a stronger genetic barrier to the emergence of drug resistance.

The current work investigates the auxetic tensile deformation behavior of the inversehoneycomb structure with 5 × 5 cells made of biodegradable poly(butylene adipate-coterephthalate) (PBAT). Fused deposition modeling, an additive manufacturing method, produced such specimens. Residual stress (RS) and warpage, more or less, always exist in such specimens due to layer-by-layer fabrication, i.e., repeated heating and cooling. The RS influences the auxetic deformation behavior, but its measurement is challenging due to the very fine structure. Instead, the finite-element(FE)-based process simulation realized by an ABAQUS plug-in numerically predicts the RS and warpage. The predicted warpage shows a negligible slight deviation compared to the design topology. This process simulation also delivers the temperature evolution of a small volume material, revealing the local cyclic heating and cooling. The achieved RS serves as the initial condition for the FE model used to investigate the auxetic tensile behavior. With the outcomes from FE calculation without considering RS at hand, the effect of the RS on the deformation behavior is discussed for the global force-displacement curve, the structural Poisson’s ratio evolution, the deformed structural status, the stress distribution, and evolution, where the first three and the warpage are also compared with experimental results. Furthermore, the FE simulation can easily provide the global stress-strain flow curve with the total stress calculated from the elemental ones.

When wildlife and motor vehicles collide, the result for the animals is often death (roadkill). A commercial roadkill Virtual Fence (VF) mitigation device (iPTE Traffic Solutions) was used in a field trial to test its effectiveness along a 4.9-km segment of road on Bruny Island, Tasmania. A total of 585 days of monitoring of roadkill by species was conducted, with six sections alternatively switched on or off, according to a variation of a Crossover and Multiple Before-After-Control-Impact (MBACI) experimental designs that divided monitoring into “off-on” then “on-off” blocks of periods with each “on” period followed by a 16 d “wash-out” period. For the six sections over the four periods that exclude wash-outs, the 24 aggregated values of daily counts of roadkill of Tasmanian pademelons (Thylogale billardierii), that gave a total count of 222, were modelled. Other species were killed in insufficient numbers for analysis to be informative. The statistical analysis exploited the MBACI design to estimate the VF effect using a log-odds ratio parameter (LORP) while accounting for local spatio-temporal effects. Both versions of the analysis, either averaging over the three spatial replicates (paired sections) or two temporal replicates (blocks) gave no statistically significant effect of the VF judged as a LORP estimate not sufficiently below zero. Corresponding percentage reduction estimates of 9% and 16% were derived from the LORP estimates and given parameter uncertainty estimates the power to detect as significant a LORP corresponding to a 50% reduction in rate were 0.5 and 0.6, respectively. This study confirms results from a similar field trial carried out in 2018 also in southern Tasmania and adds to the evidence that this VF is likely to give if anything only a minor reduction in roadkill for a commonly killed species for which researchers have the best chance of detecting any practically useful reduction.

Despite air pollution being a leading cause of health issues in developing nations, public awareness and understanding of local air quality remains notably low. The present study assesses the perception, attitude, and environmental knowledge of local air pollution among adult urban residents (n=870) in a city with leading air pollution rates among cities of emerging economies: Astana, Kazakhstan. Structural equation modeling (SEM) was employed to investigate the causal relationship between perceived air quality, environmental literacy, and willingness to pay (WTP) for environmental protection. Findings indicate over 40% of residents neither consider the city being highly polluted nor recognize the association between air quality and adverse health outcomes, correlated with a generally low level of environmental literacy. The age, education, and health status of the participants significantly affected (p&lt;.001) their level of environmental knowledge and awareness. The SEM analysis indicates that knowledge is the major determinant in improving public awareness and perception of local air pollution (path value=0.626). Moreover, a close association between WTP and environmental attitude was also evident (path value=0.533). The findings of the present study may provide valuable insights for healthcare professionals, environmental researchers, and governmental institutions for implementing more effective public interventions to protect local air quality.

The main issue in this work is to study limit functions necessary for the reliability assessment of the structural steel with the use of the relative entropy apparatus. This would be done using a few different mathematical theories relevant to this relative entropy, namely those proposed by Bhattacharyya, Kullback-Leibler, Jeffreys, and Hellinger. Probabilistic analysis in the presence of uncertainty in material characteristics would be delivered using three different numerical strategies – Monte-Carlo simulation, stochastic perturbation method as well as the semi-analytical approach. All these methods are based on the Weighted Least Squares Method approximations of the structural response functions versus the given uncertainty source and they would allow efficient determination of the first two probabilistic moments of the structural responses including stresses, displacements, and strains. The entire computational implementation would be delivered using the Finite Element Method system ABAQUS and computer algebra program MAPLE, where relative entropies, as well as polynomial response functions, would be determined. This study would demonstrate that the relative entropies may be efficiently used in reliability assessment close to the widely engaged First Order Reliability Method (FORM).

Smart flexible materials with piezoresistive property are increasingly used in sensors field. When embedded in structures, they would allow an in-situ structural health monitoring and damage assessment of impact loading such as crash, bird strikes and ballistic impacts. However, this could not be achieved without a deep characterization of the relation between piezoresistivity and mechanical behavior. The aim of this paper is to study the potential use of the piezoresistivity effect of a conductive foam made of a flexible polyurethane matrix filled with active carbon for integrated Structural Health Monitoring (SHM) and damage assessment applications. To do so, PolyUrethane Foam filled with Active Carbon, namely PUF-AC, are manufactured and tested under quasi-static compression tests and under Dynamic Mechanical Analyser (DMA) with in-situ measurement of its resistivity during tests. A relation is proposed for describing the evolution of the resistivity versus strain and stress. In addition, a demonstrative experiment of a PUF-AC sample subjected to low velocity impact assesses the interest of this type of materials for damage assessments.

The objective of this paper was to verify the applicability of statistical learning (SL) compared to human reasoning with respect to the Universal Thermal Climate Index (UTCI), a complex tool for the assessment of outdoor thermal stress. UTCI is an equivalent temperature index based on the 48-dimensional output of an advanced model of human thermoregulation formed by 12 variables at four consecutive 30-minute intervals, which were calculated for 105642 thermal conditions from extreme cold to extreme heat. Comparing the performance of SL algorithms to the results accomplished by an international endeavor involving more than 40 experts from 23 countries, we found that random forests and k-nearest neighbors closely predicted UTCI values, but that clustering applied after dimension reduction algorithms (principal component analysis and t-distributed stochastic neighbor embedding) were inadequate for risk assessment in relation to the UTCI stress categories. This indicates a potential supportive role for SL, as it will not (yet) fully replace the bio-meteorological expert knowledge.

This study presents the development of a number of finite element (FE) models of the pelvis using different continuum and structural modelling approaches. Four FE models were developed using different modelling approaches: continuum isotropic, continuum orthotropic, hybrid isotropic and hybrid orthotropic. The models were subjected to an iterative adaptation process based on the Mechanostat principle. Each model was adapted to a number of common daily living activities (walking, stair ascent, stair descent, sit-to-stand and stand-to-sit) by applying onto it joint and muscle loads derived using a musculoskeletal modelling framework. The resulting models, along with a structural model previously developed by the authors, were compared visually in terms of bone architecture, and their response to a single load case was compared to a continuum FE model derived from CT imaging data. The main findings of this study were that the continuum orthotropic model was the closest to the CT derived model in terms of load response albeit having less total bone volume, suggesting that the role of material directionality in influencing the maximum orthotropic Young's modulus should be included in continuum bone adaptation models. In addition, the hybrid models, where trabecular and cortical bone were distinguished, had similar outcomes, suggesting that the approach to modelling trabecular bone is less influential when the cortex is modelled separately.

In this paper, we consider the Cauchy problem of a time fractional nonlinear diffusion equation. According to the Kaplan’s first eigenvalue method, we first prove the blow-up of the solutions in finite time for some sufficient conditions. We next give sufficient conditions for the existence of global solutions by using the result of Zhang and Sun. In conclusions, we find the second critical exponent for the existence of global and non-global solutions via the decay rates of the initial data at spatial infinity.

This paper presents the results of investigations on the kinetic of Brilliant Blue FCF (BB) discoloration reactions in aqueous solutions with different ozone concentrations and pH conditions. Kinetic studies involve knowledge of the structure and properties of the dye and ozone, as well as the experimental conditions. In general, scientists admit that the predominant oxidation pathway is direct (by free oxygen atoms) or indirect (by free hydroxyl radicals), it will depend on influencing factors such as: the physicochemical properties of the dye, the pH of the aqueous solution, ozone concentration, reaction time and the contact mode with/without stirring. In the experimental research, two pathways were chosen following CBB = f(t): 1. constant dye concentration and different ozone concentration on the concentration range (100 - 250 mg/L) at three pH media (acidic, neutral and basic) with and without stirring; 2. Constant concentration of ozone and different dye in the range of concentrations (2.5 - 10 mg/L) under the conditions of point 1. With obtained experimental data the curves CBB = f(t) were drawn and were processed by the integral method of classical kinetic based on first and second order equations. Unfortunately, this simple procedure this not yield any minim full results and any pH level. The rate constants been negative and/or the reaction order been dependent on initial conditions. Due to its structure, the BB dye has several chromophore groups, thus multiple attack centers, resulting in more oxidation by-products, which is why the 1H - NMR spectrum of BB discoloration with ozone was recorded.

The aim of this study was to examine the oxidation of human serum albumin (HSA) caused by oxidative stress after an exhaustive exercise such as ultra-marathon race. Thus, blood samples from 12 adult runners who underwent a 103 km mountain ultra-marathon race were collected pre- and 24, 48 and 72 h post race. HSA was partially purified using affinity chromatography and then was subjected to Western blot analysis for disulfide dimers determination, indicating oxidation. The results were correlated with those from a previous study in which the same samples were analyzed using different oxidative stress markers and a good correlation with protein carbonyls (PC) at all time points was observed. Moreover there was a significant correlation with static oxidation-reduction potential (sORP) at 24 h, and a negative correlation with capacity oxidation-reduction potential (cORP) at 24 and 48 h. In addition, an individual analysis of albumin dimers exhibited great inter-individual differences. This inter-individual variability in the oxidation of HSA may suggest different interventions (e.g. through diet) in order to confront the effects on athletes’ organism after a strenuous exercise. In conclusion, this study supported the importance of the assessment of albumin dimers as a predictive marker for exercise-induced oxidative stress.

This study investigates the influence of digital marketing on consumer purchasing decisions, focusing on how various strategies impact consumer behavior. By analyzing data collected from in-depth interviews and thematic analysis, the research highlights several key factors driving consumer engagement and purchases. Personalized content emerged as a significant factor, with tailored recommendations and customized email campaigns creating a sense of individual attention and enhancing consumer involvement. Social media platforms played a pivotal role, with advertisements, influencer endorsements, and user-generated content significantly affecting purchasing decisions. The impact of visual content, including high-quality images and videos, was also notable, as these elements helped consumers better understand products and increased their confidence in making purchases. Email marketing proved effective, particularly when offering exclusive discounts and creating a sense of urgency. Mobile marketing demonstrated its growing influence, with consumers valuing the convenience of mobile-friendly websites and app notifications. The integration of artificial intelligence further improved the shopping experience by providing instant assistance and personalized recommendations. Ethical considerations, such as data privacy and honest advertising, were essential for maintaining consumer trust and loyalty. User-generated content provided authentic insights that influenced purchasing decisions, while omnichannel strategies offered a seamless and flexible shopping experience. Gamification elements, including reward programs and interactive challenges, enhanced consumer engagement and motivation. The study concludes that a multifaceted approach to digital marketing, incorporating these strategies, is crucial for effectively engaging consumers and driving sales. The findings offer valuable insights for marketers aiming to optimize their digital marketing strategies in the evolving digital landscape.

Project complexity is usually considered as one of main causes of cost overruns, resulting in poor performance and thus project failure. However, empirical studies focused on evaluating its effects on project cost remain lacking. Given this circumstance, this study attempts to develop the relationships between project cost and the multidimensional project complexity elements. We establish complexity as a multidimensional factor including the task, organization, market, legal, and environment complexities. This study uses an empirical evidence-based structural model to account for the relationships between project cost and project complexity. By doing so, a quantitative assessment of multi-dimensional project complexity has been developed. The findings suggest that task and organization complexities have direct effects on project cost, while market, legal and external environment complexities have indirect effects on project cost. The practical contribution is that the findings can improve the understanding of which dimension of complexity significantly influence project cost, and the need to focus efforts on strategically addressing that complexities.

Background: Delis-Kaplan Executive Function System (D-KEFS) is a neuropsychological tool used in clinical practice to measure executive function in clinical and non-clinical populations, in individuals aged 8-89 years, and consists of nine subtests that can be administered either as a single system or separately. Aims: In the present study, were established norms for the Verbal Fluency Test as well as the Design Fluency Test of the D-KEFS in a Greek population aged 20 to 49 years, since there is no previous study conducted in Greece for these age clusters. Methods: The study sample consisted of 100 healthy adults (44.4% male and 55.6% female), aged 20 to 49 years (M=32.81 SD=11.04) with education from 12 to 18 years (M=14.73, SD= .91). First, Spearman and Pearson tests explored the associations of gender, age and education with D-KEFS subtests’ performance. Afterwards, we calculated normative data using raw scores and transformed to percentile scores. Results: The present study is the first attempt to calculate norms for the two fluency subtests of the D-KEFS in Greek adult population stratified by age and educational level. Conclusion: Future research will promote the use of D-KEFS, in order to introduce a widely used tool which measures all basic executive functions subtypes for Greek adult population. Given that the majority of neuropsychological tools are adapted for older adult population, the current study aims at filling the gap in neuropsychological assessment of young adults as well as those who have co existing neurological or psychiatric disorders.

This paper investigates the effect of innovative cross-sectional configurations on Low-Cost Bamboo Composite (LCBC) structural members. The study employs both experimental and numerical methods with different resin matrices and bamboo species. In this study, LCBC short columns are designed with different innovative cross-sectional configurations in an attempt to overcome the costly production processes of engineered bamboo. This approach uses bundles of bamboo, both in culm and strip forms. A compatible, environmentally responsible, and economically justifiable resin matrix is used to fabricate an LCBC member. The production of LCBC members does not necessitate highly advanced technology. This capability enables the production of LCBC members in custom-designed cross-sectional shapes and lengths. This study introduces the Russian doll (RD), Big Russian doll (BRD), Hawser (HAW), and Scrimber (SCR) cross-sectional configurations. Extra-large, large, medium, and small sizes of bamboo are employed. Synthetic Epoxy (EXP), a Bio-based Experimental soft filler (BE1), Bio-Epoxy (BE2), Furan-based (PF1) matrices are applied. Furthermore, Moso, Guadua, Madake, and Tali bamboo species are incorporated. The results of this study reveal that the most efficient cross-sectional configuration for compressive strength is the HAW configuration, closely followed by SCR configuration. LCBC members with bio-resins have shown excellent promise in competing in strength with those made with their synthetic counterparts. The theoretical and numerical modeling of the LCBC members showed excellent correlation with the experimental results which provides the capacity to design LCBC for engineering projects. The LCBC design can be further developed with more bamboo and less resin content.

The objective of the research was to examine the determinants that determine farmer participation and shallot farming development in search of effective farm management practices. The study used Structural Equation Modeling data analysis. The primary data was collected from direct-structural interviews with 150 randomly chosen shallot farmers in Bantaeng Regency, Indonesia. It was found that the physical attributes of the land, the economic framework of the community, and the political system of the agricultural community were fundamental factors that exerted a positive and significant influence on farmer participation. Therefore, improvements in the physical aspects of land, the economic framework, and the political structure of agricultural communities could promote farmer participation. Furthermore, the farmers’ participation and the political structure of agricultural communities have a positive and significant impact on the development of shallot farming. Thus, by increasing the influence of government officials and community leaders, shallot farming can be promoted. The farmers can then enhance their participation in the shallot farming plan's formulation and implementation, providing the continued development of shallot farming. The findings of this study contribute significantly to the body of knowledge by validating previous research and proposing different ways to improve effective farm management practices in shallot farming.

The application of distributed fiber optic strain and temperature measurement can be utilized to address a multitude of measurement tasks across a diverse range of fields, particularly in the context of structural health monitoring in the domains of building construction, civil engineering, and special foundation engineering. However, a comprehensive understanding of the influences on the measurement method and the sensors is essential to prevent misinterpretations or measurement deviations. In this context, this study investigated the effects of moisture exposure, including various salt solutions and a high pH value, on a distributed strain measurement using Rayleigh backscattering. Three fiber optic sensors with different coating materials and one uncoated fiber were exposed to five different solutions for 24 hours. The study revealed significant discrepancies in deformation between the three coating types depending on the surrounding solution. Furthermore, in contrast to the prevailing literature, which predominantly describes swelling effects, a negative deformation was observed in a magnesium chloride solution. The findings of this study indicate that corresponding effects can impact the precision of measurement, potentially leading to misinterpretations. Conversely, these effects could be used to conduct large-scale monitoring of chemical components using distributed fiber optic sensing.

Dual generalized commutative quaternions have broad application prospects in many fields. Additionally, the matrix equation AXB = C has important applications in mathematics and engineering, especially in control systems, economics, computer science, and other disciplines. However, research on the matrix equation AXB = C over the dual generalized commutative quaternions remains relatively insufficient. In this paper, we derive the necessary and sufficient conditions for the solvability of the dual generalized commutative quaternion matrix equation AXB = C. Furthermore, we provide the general solution expression for this matrix equation, when it is solvable. Finally, a numerical algorithm and an example are provided to confirm the reliability of the main conclusions.

The expansion of renewable energies is progressing strongly. The influence on the power supply networks by the volatility of the infeed must be met with new concepts. In this paper we investigate the possibilities of integrating microgrids as a cooperating unit in the power supply network to support further expansion of RES power plants. In this paper a differentiation of microgrids from similar network structures is established, a classification of proposed groups is made. Then, after the description of simulation of components in a microgrid, with practical advice, an example model is shown, which aids the dimensioning of the components within a microgrid to achieve a specified goal.

The recent consecutive economic and social crises impose sustainable “form farm to fork” food chain management to feed the global population. In this study we investigate young consumers (Gen Z) price perceptions in purchasing foods in Greece to find out the determinants ensuring sustainable, future food consumption. We used 8 overall price perceptions determinants, 5 with negative roles namely value &amp; price consciousness, coupon &amp; sales proneness, price mavenism and 3 with positive roles namely price-quality, price-value, and prestige-sensitivity for the formation of the study’s questionnaire. A total of 514 students (Gen Z by 85%) answered the questionnaire, promoted through the Google platform during September and October 2023. Data was analyzed with statistical tools, combining cross and chi-square tests. Between the negative determinants the “value consciousness” price perceptions (71.02%) were the most important parameters in purchasing food, followed by “price consciousness” (55.02%) parameters. “Coupon proneness” by 48.4% and “sales proneness” by 49% parameters were equally lower to the participants’ references, while “price mavenism” parameters were minimally preferred by only 26.4% by the participants. Participants exhibited major preference for “value to price” interconnection (66.7%) such as for good value for money, value exceeding its price, overvalued low priced foods, while their preference for “quality to price” interconnection was significantly lower (48.8%) such as for getting what you pay, more money for better quality, priced quality foods. The “prestige- sensitivity” price perception was out of their preference for food purchase (only 7.1%). Our findings indicate that young consumers (Gen Z) pay more attention to the value negative and positive parameters concerning price perceptions for food purchase rather than quality, coupons &amp; sales, low price, and mavenism or even prestige of the foods. This means that value issues such as the perceived environmental impact (green value), the climate crisis, the social signaling potential and others are high in their concerns for their future including their price perceptions for food purchase.

In a multivariable system there are usually a number of relaxation times. When some of the relaxation times are shorter than others, the corresponding variables will decay to their equilibrium value faster than the others. After the fast variables have decayed, the system can be described with a smaller number of variables. From the theory of nonequilibrium thermodynamics, as formulated by Onsager, we know that the coefficients in the linear flux-force relations satisfy the so-called Onsager symmetry relations. The question we will address in this paper is how to eliminate the fast variables such that the coefficients in the reduced description for the slow variables still satisfy the Onsager relations. As the proof Onsager gave of the symmetry relations does not depend on the choice of the variables, it is equally valid for the subset of slow variables. Elimination procedures that lead to symmetry breaking are possible, but do not consider systems that satisfy the laws of nonequilibrium thermodynamics.

In this paper, we study nonlocal problems for a fractional diffusion equation and a degenerate hyperbolic equation with singular coefficients in the lower terms. The uniqueness of the solution to the problem is proved by the method of energy integrals. The existence of a solution is equivalently reduced to the question of the solvability of Volterra integral equations of the second kind and a fractional differential equation. For a particular solution of the proposed problem, its visualization is carried out for various values of the order of the fractional derivative. It is shown that the order of the derivative affects the intensity of the diffusion process (subdiffusion), as well as the shape of the wave front.

Some of the recent large-scale national projects in South Korea are delayed or suspended due to belated responses to risk occurring on site. Currently, the Far East District (FED) project is being implemented to relocate the US Army bases from Yongsan to Pyeongtaek. Because of lack of experience and understanding about the characteristics of such a project, the deadline of taking over to the US Army Korea has been missed. This study identifies problems of each participant in the Yongsan Relocation Plan (YRP) of the US Army Korea with respect to construction project management and establishes a risk management strategy reflecting characteristics of FED project. To derive significant risk factors influencing YRP, various field data like weekly and monthly reports and other reports on construction condition are analyzed, and experts’ advices are collected and a survey is conducted. Mediators and latent variables are ultimately obtained. Furthermore, a structural equation model is used to both analyze and evaluate complex causal relations among many variables of YRP. The impact of risk factors on the schedule, quality and cost of the project is analyzed. In particular, the case of Site A is examined to see how the project is affected by those risk factors.

The role of human resource management practices and organizational loyalty dealing with employee retention has been widely explored and examined in the existing literature. The majority of human resource management researchers have focused on the role of policies and practices in different sectors related to employee retention. However, less attention has been given to identifying the practices and procedures common across all industries and sectors. The present study attempts to determine and examine the most important constructs like HR practices and organizational loyalty of employee retention management and proposes a comprehensive structural equation model to measure the impact of these constructs on employee retention. After an extensive review of the literature, organizational loyalty, and human resources management practices like recruitment and selection, compensation and benefit, training and development, supervision and evaluation have been identified as four essential practices dealing with employee retention and are common across all industries. These practices constitute the component factors of an employee retention management predicting employee’s turnover intentions. The survey method was adopted, and the original data obtained through the self-administered questionnaire. The valid one hundred and eighty-nine (189) respondents analyzed by using Lisrel 8.7, Structural equation model (SEM) analysis results shows that human resource management practices and organizational loyalty have strong positive impact on employee retention. This study tends to assist human resource managers and decision makers in selecting the appropriate motivating factors to retain and satisfy their employees

Excitotoxicity related to the dysfunction of the N-methyl-d-aspartate receptor (NMDAR) has been indicated to play an integral role in the pathophysiology of multiple disease states, including neurodegenerative disorders such as Parkinson’s disease. There is a notable gap in the market for novel NMDAR antagonists, however current methods to analyze potential antagonists rely on indirect measurements of calcium flux and hazardous radioligand binding assays. Recently, a fluorescent NMDAR ligand, N-adamantan-1-yl-dimethylamino-1-naphthalenesulfonic acid, known as AM-DAN was developed by our group. Additional studies on this ligand is necessary to evaluate its potential as a biological tool in NMDAR research. Therefore, this study was aimed at conducting structural analyses, fluorescence experiments, high-accuracy NMDAR molecular modelling and NMDAR phencyclidine (PCP) site competition binding studies using AM-DAN. Results revealed that AM-DAN has appropriate structural properties, significant fluorescent ability in various solvents and is able to bind selectively and compete for the PCP-binding site of the NMDAR. Therefore, AM-DAN holds promise as a novel fluorescent ligand to measure the affinity of prospective drugs binding at the NMDAR PCP-site and may circumvent the use of radioligands.

Fat and oils plays one of the major roles in Sri Lankan modern unhealthy diet. The study was guided to collect, analyze, and interpret data about the awareness of general community on edible fat and oil products available in the market and their knowledge about healthy ways of usage. A total of 250 purchasing women were surveyed with a welldeveloped questionnaire. Results revealed that, Coconut oil (71%) is the leading supermarket oil product purchased and consumption of animal fats and oil are very limited (<3%) in Kandy. Educational level affects significantly (P<0.05) on purchasing behavior. Regardless of educational level and working status, price (73%) will be the most significant factor look at during purchasing edible oils. Total of 57% of purchasing women use the same oil for both deep frying and stir frying. Besides, 43% of women keep two different types. From all respondents, 83% use oil more than one time after first cooking. Working women prefer internet and facebook (38%) as the major food related information searching resource, while newspapers (35%) are among non-working women. All in all, lowering the price of healthy fat and community awareness programs will encourage healthy fat and oil purchasing behavior in Sri Lanka.

Inverse Sumudu transform multiple shifting properties are used to design methodology for solving ordinary differential equations. Then algorithm applied to solve Whittaker and Zettl equations to get their new exact solutions and profiles which shown through Maple complex graphicals. Table of inverse Sumudu transforms for elementary functions given for supporting the differential equations solving using inverse Sumudu transform.

The strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a Lean Learning Factory was developed in the Pitesti University Center, which allows students to learn, experiment, and research, in an environment similar to that of enterprises, the new Lean Manufacturing methods and techniques, and Industry 4.0. The research presented in this study had as its objective identifying the minimum number of repetitions necessary to train operators who serve two differently organized workstations, one classic, the other including digital techniques, but on which the same assembly operation is performed. Several indicators were considered in the analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a Lean manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

Energy consumption modelling is of critical importance for improving energy efficiency in the drive towards sustainable manufacturing. Modern manufacturing processes and machine tools are very complex as they involve interplay of several advanced technologies. Therefore, energy modelling of modern machine tools is a complex multi-disciplinary task. This paper proposes a systematic and practical framework to choose the appropriate modelling approach for a given industrial problem. The framework was validated by applying it to diverse industrial scenarios.

This paper introduces innovative sensitivity indices based on Cliff's Delta for global sensitivity analysis of structural reliability. These indices build on Sobol's method, using binary outcomes (success or failure), but avoid the need to calculate failure probability Pf and the associated distributional assumptions of resistance R and load F. Cliff's Delta, originally for ordinal data, evaluates the dominance of resistance over load without specific assumptions. The mathematical formulations for computing Cliff's Delta between R and F quantify structural reliability by assessing the random realizations of R > F using a double-nested-loop approach. The derived sensitivity indices, based on the squared value of Cliff's Delta​, exhibit properties analogous to those in Sobol's sensitivity analysis, including first-order, second-order, and higher-order indices. This provides a comprehensive framework for evaluating the contributions of input variables and their interactions on structural reliability. This method is particularly significant for FEM applications, where repeated simulations of R or F are computationally intensive. The double-nested-loop algorithm of Cliff's Delta maximizes the extraction of information about structural reliability from these simulations. However, the high computational demand of Cliff's Delta is a disadvantage. Future research should optimize computational demands, especially for small Pf​, where the inner loop may often be unnecessary.

Food waste is a common issue arising from grinding of food by experimental animals, leading to excessive food scraps falling into cages. In the wild, animals grind food by gnawing vegetation and seeds, potentially damaging the ecological environment. However, limited ecology studies have focused on food grinding behavior since the last century, with even fewer on rodent food grinding, particularly recently. Although food grinding function is partially understood, biological purposes remain under-investigated and driving factors unclear. This review aims to explain potential causes of animal food grinding, identify influencing factors, and discuss contexts and limitations. Specifically, we emphasize recent progress on gut microbiota significance for food grinding. Moreover, we show abnormal food grinding is determined by degree of excess normal behavior, emphasizing food grinding is not meaningless. Findings from this review promote comprehensive research on the myriad factors, multifaceted roles, and intricate evolution underlying food grinding behavior, benefiting laboratory animal husbandry and ecological environment protection, and identifying potential physiological benefits yet undiscovered.

This paper investigates the ion-acoustic wave structures in fluid ions for the Benjamin-Bona-Mahony-Peregrine-Burgers (BBMPB) equation. The various types of wave structures, are extracted including the three-wave hypothesis, breather wave, lump periodic, mixed-type wave, periodic cross-kink, cross-kink rational wave, M-shaped rational wave, M-shaped rational wave solution with one kink wave and M-shaped rational wave with two kink wave solutions. The Hirota bilinear transformation is a powerful tool that allows us to accurately solutions and predict the behavior of these wave structures. Through our analysis, we gain a better understanding of the complex dynamics of ion-acoustic waves and their potential applications in various fields. Moreover, our findings contribute to the ongoing research in plasma physics that utilize ion-acoustic wave phenomena. To show the physical behavior of the solutions, some 3D plots have been performed and their respective contour level, choosing different values of the parameters.

The vast array of omics data in microbiology presents significant opportunities for studying bacterial pathogenesis and creating computational tools for predicting pathogenic potential. However, the field lacks a comprehensive, curated resource that catalogs bacterial strains and their ability to cause human infections. Current methods for identifying pathogenicity determinants often introduce biases and miss critical aspects of bacterial pathogenesis.In response to this gap, we introduce BacSPaD (Bacterial Strains’ Pathogenicity Database), a thoroughly curated database focusing on pathogenicity annotations for a wide range of high-quality, complete bacterial genomes. Our rule-based annotation workflow combines metadata from trusted sources with automated keyword matching, extensive manual curation, and detailed literature review. Our analysis classified 5,502 genomes as pathogenic to humans (HP) and 490 as non-pathogenic to humans (NHP), encompassing 532 species, 193 genera, and 96 families. Statistical analysis demonstrated a significant but moderate correlation between virulence factors and HP classification, highlighting the complexity of bacterial pathogenicity and the need for ongoing research. This resource is poised to enhance our understanding of bacterial pathogenicity mechanisms and aid in the development of predictive models. To improve accessibility and provide key visualization statistics, we developed a user-friendly web interface, accessible at https://bacspad.altrabio.com.

Research into lightweight structural concrete using volcanic tuff is of great importance to the construction industry. These materials have excellent thermal insulation properties, which helps improve the energy efficiency of buildings. A three-factor experimental design was used to build the statistical model. The test methods used were methods for determining the crushability of volcanic tuff, determining the average density, compressive strength and thermal conductivity of lightweight structural concrete. The influence of basalt fiber on the properties of lightweight structural concrete has been determined. The optimal compositions of lightweight structural concrete using tuff have been selected. The compressive strength of lightweight structural concrete reached 32.0 MPa. The average density range is 1754.6-2114.0 kg/m³. Good thermal conductivity values ​​were obtained in the range of 0.653-0.818 W/m·K. The article obtained the optimal compositions of lightweight structural concrete using volcanic tuff as a filler.

The fractional advection-dispersion equation FADE plays an important role, especially in explaining the process of solute-transport in natural porous media with different degrees of heterogeneity. However, studies of the flow and transport of contaminants in the underground environment are based on the knowledge of many functional parameters of the subsoil. The delay factor caused by nonlinear absorption is one of these parameters inheriting significant ambiguities in its estimation in heterogeneous media. In the study, a fractional advection-dispersion FADE model was developed by the implicit Euler method, based on a Grunwald and Caputo-Liousville approximation to explicitly evaluate and simulate the transport mechanism of contaminants in media with unsaturated porous materials subjected to a nonlinear sorption model. Better solute mass retention was observed for fractional advection-dispersion FADE model. Moreover, the absorption parameter of the retardation coefficient has a better impact on the motion of the solute in a saturated porous medium. In other words, it has a significant effect on the dispersion of pollutants in aquifers. This study highlights the need to characterize the aquifer to predict solute transport in porous media.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.