Nowadays, the wasting of resources is one of the fundamental challenges of the industrial sector. The rectangle packing problem can be very effective in this context. Practical applications of this issue in the timing and designing of the industries and businesses are very remarkable. The purpose of this issue is to arrange a set of rectangles with specific dimensions in a rectangular page with a specific width and unlimited height without overlapping. The fundamental challenge in this issue is that this is an NP-complete issue. Therefore, it is difficult to achieve the best arrangement, which has the maximum rate of resource utilization and also has a linear running time. Many algorithms have been presented to estimate a practical solution for this issue. In the past decades, the best fit method has been one of the most useful methods for this purpose. This study presents a combinatorial algorithm based on two algorithms, including the lowest front-line strategy and the best-fit algorithm. The running results indicate that the suggested algorithm performs well, despite its simplicity. The time complexity of the suggested algorithm is O(nm), in which n is the number of input rectangles and m is the number of the created front lines.

In this report the positive cases of Covid19 in India with effect from 7th September ,2020 to 25th October ,2020 are analysed for statistical relevance . The scattered data are used to find out a model equation correlating two variables number of recovered Covid –patient with an interval of regular seven days . The best fit regression analysis shows a significant correlation of Pearson coefficient (r) with standard error ( s ) with a probable lower mortality rate . Finally the limitations of this analysis is discussed herewith .

Background: The COVID-19 pandemic has promoted a shortage of filtering facepiece respirators (FFRs) and the emergence of new FFRs brands. We aimed to determine the fit provided by in-use FFRs in Peruvian healthcare workers (HCWs) during the COVID-19 pandemic. Methods: We enrolled 279 HCWs from 37 primary healthcare centers with highest burden of care for TB in Peru, of which 263 were assessed using quantitative fit tests (QNFT). Results were expressed as real-time fit factor (rt-FF) and overall fit factor (overall-FF), which was categorized as ≥100 (optimal result), 50-99, and <50. Results: We identified 3M 1860 FFRs (33.1%), Xiantao Zhong Yi ZYB-11 FFRs (24.7%) and Makrite 9500 FFRs (20.5%), mainly. Eighty-seven HCWs (33.1%) had an optimal overall-FF, 27 (10.3%) between 50-99, and 149 (56.7%) less than 50. Of the 87 HCWs with optimal over-all-FF, 73 (83.9%) were 3M 1860 FFR. Of the 27 participants with overall-FF between 50-99, 7 (25.9%) were Makrite 9500, while of the 149 with overall-FF less than 50, 58 (38.9%), and 47 (31.5%) were Xiantao Zhong Yi ZYB-11 and Makrite 9500, respectively. Conclusion: The Xiantao Zhong Yi and Makrite FFRs do not adapt adequately to the face of Peruvian HCWs, most having fit factors less than 50.

This study examines the effect of a corporate citizenship-oriented high performance work system (CC-oriented HPWS) and the interactive influence of CC-oriented HPWS and person-organization fit (PO fit) on creativity at the individual level. Our analysis of field data collected from 303 employees in two branch companies with a two-phase collection method provides empirical support for our theoretical model. The results indicate that high performance work system (HPWS) reflecting corporate citizenship (CC) correlates positively with individual creativity. In addition, the moderating effect of PO fit is significant in the relationship between CC-oriented HPWS and creativity at the individual level. On this basis, this paper discusses the theoretical and practical implications of these findings for future research.

This study explored what motivates university counselors. By analyzing various factors like personal values and work environment, they found counselors experience greater career satisfaction when their work aligns with their own values and societal impact, and when they receive recognition and opportunities for growth. Universities can utilize these findings to create a more supportive environment for counselors by highlighting their impact, offering development opportunities, and fostering a positive work culture. This can ultimately lead to a more motivated and effective counseling team, benefiting both the counselors and the students they serve.

Snap-fit is a commonly used jointing/connention mechanism, and its easy installation and difficult removal are the result of the coordinated interaction between friction, geometric shape, and elasticity. This paper presents a detailed study on the assembly/disassembly forces of thin-walled torus snap-fit through finite element simulation, experimental testing, and data fitting of approximate analytical solutions. The research reveals that the non-zero Gaussian curvature of the torus has a significant impact on the mechanical performance of the torus snap fit. The findings in this study are of great significance for future design of high-performance structural connections.

The snap fit is a common mechanical mechanism. We have studied the spherical snap fit carefully for its physical asymmetry which is easy to assemble but difficult to disassemble, and obtained the general law.Because of the complexity of spherical structure, it is difficult to get a theoretical formula to describe its physical asymmetry.In this paper, through the method of combining theory, simulation and experiment, and based on the general rule of cylindrical snap fit obtained in the early stage, pushing assembly and pulling disassembly of spherical snap fit are studied,we not only get the theoretical formula of spherical snap fit, but also further verify the correctness of previous research conclusions on cylindrical snap fit.This research provides strong theoretical support and basis for the optimization design and further research of snap fit.

Energy use is of crucial importance for the global challenge of climate change but also an essential part of daily life. Hence, research on energy needs to be robust and valid. Other scientific disciplines have experienced a reproducibility crisis, that is, existing findings could not be reproduced in new studies, and energy research might be impacted as well. In this paper, we suggest the ‘TReQ’ approach to improve the research practices in the energy field and arrive at greater Transparency, Reproducibility, and Quality. We acknowledge the specific challenges of energy research and suggest a highly adaptable suite of tools that can be applied to research approaches across this multi-disciplinary and fast-changing field. In particular, we introduce preregistration of studies, making data and code publicly available, using preprints, and employing reporting guidelines to heighten the standard of research practices within the energy field. We argue that through wider adoption of these tools, we will be able to have greater trust in the findings of research used to inform evidence-based policy and practice in the energy field.

The scalar meson f0(980) has been a long-standing puzzle in light hadron physics. The mass and width of the f0(980) in normal decay processes are estimated to be M=990±20 MeV/c2 and Γ=40−100 MeV, respectively. Theoretically, the internal structure of the f0(980) is proposed to be a conventional quark-antiquark meson, tetraquarks state, KK¯ molecule, or quark-antiquark gluon hybrid. So far, explanations about the nature of f0(980) have been controversial for a long time. Recently, anomalously narrow width f0(980) were observed by the BESIII experiment in five independent isospin-violating decay channels. Based on the experimental data, we performed a simultaneous fit to ππ invariant mass distributions, and the mass and width in isospin-violating decays are determined to be M=990.0±0.4 MeV/c2 and Γ=11.4±1.1 MeV, respectively. In addition, we use the parameterized Flatté formula to simultaneously fit the same ππ invariant mass distributions, the two coupling constants of gfππ and gfKK¯ are measured to be gfππ=0.46±0.03 and gfKK¯=1.24±0.32, respectively. According to the joint confidence regions of gfππ and gfKK¯, we conclude that the experimental data tend to support the KK¯ molecule model and the quark-antiquark (qq¯) model, but tend not to support the tetraquarks (q2q¯2) model and the quark-antiquark gluon (qq¯g) hybrid model.

Snap fit is a common mechanical mechanism. It uses the physical asymmetry that is easy to assemble but difficult to disassemble to provide a simple and fast link between objects. The ingenious combination of geometric shape, bending elasticity and friction of the snap fit is the mechanism behind the easy to assemble but difficult to disassemble disassemble. Yoshida and Wada (2020) has done a groundbreaking work in the analysis of the elastic snap fit. During our study of their paper, while we really enjoyed their research, unfortunately we detected several questioning formulations. After careful checking, we found that those formulations are not typographical, therefore it is necessary to make corrections. This paper reformulates the linear elasticity of a cylindrical snap fit, obtains an exact solution and proposes an accurate relation between the opening angle and bending tangent angle. Under the first order approximation, our formulations can reduced to the results of Yoshida and Wada and hence confirms the scientific correctness of Yoshida and Wada's work. Furthermore, this paper also derives a correct vertical displacement expression, and propose a new way of disassembly by bending for the first time and formulate a scaling law by data fitting. All formulations are validated by finite element simulation and experiment. The research here is helpful to the design of elastic snap fit or adjustable mechanical mechanism and metamaterial cell.

The major global pressures of rapid urbanization and urban growth are compounded by climate impacts resulting in increased vulnerability for urban dwellers, with these vulnerabilities exacerbated during COVID-19. Much of this is concentrated in urban and peri-urban areas where urban development spreads into hazard-prone areas. Often this development is dominated by poor quality homes in informal settlements or slums with poor tenure security. Lessons from a current resilience-building project shows that the fit-for-purpose (FFP) approach to land administration can provide a solution to increase the number of households with security of tenure and improve resilience outcomes as informal settlements grow. This paper discusses the influence of FFP land administration on vulnerabilities to multiple shocks related to climate change and COVID-19. This paper proposes ways the growth of human settlements can be better managed through responsible governance of land tenure rights, and effective land-use planning to improve resilience to different shocks and stresses and provide adequate access to safe land and shelter. Land administration systems can support improved resilience to the multiple stressors of climate and pandemics through improving tenure security and enhancing land use planning controls. Climate change adaptation and risk management need to be better mainstreamed into two major elements of land governance: (i) securing and safeguarding of land rights, and (ii) planning and control of land-use.

A new discrete distribution for count data called extended biparametric Waring (EBW) distribution is developed. Its name is related to the fact that, in a specific configuration of its parameters, it can be seen as a biparametric version of the univariate generalized Waring (UGW) distribution, a well-known model for the variance decomposition into three components: randomness, liability and proneness. Unlike the UGW distribution, the EBW can model both overdispersed and underdispersed data sets. In fact, the EBW distribution is a particular case of a UWG distribution when its first parameter is positive; otherwise, it is a particular case of a Complex Triparametric Pearson (CTP) distribution. Hence, this new model inherits most of their properties and, moreover, it helps to solve the identification problem in the variance components of the UGW model. We compare the EBW with the UGW by a simulation study, but also with other over and underdispersed distributions through the Kullback-Leibler divergence. Additionally, we have carried out a simulation study in order to analyse the properties of the maximum likelihood parameter estimates. Finally, some application examples are included which show that the proposed model provides similar or even better results than other models, but with fewer parameters.

In this paper, we study the asymptotic behavior of the sequential empirical process and the sequential empirical copula process, both constructed from residuals of multivariate stochastic volatility models. Applications for the detection of structural changes and specification tests of the distribution of innovations are discussed. It is also shown that if the stochastic volatility matrices are diagonal, which is the case if the univariate time series are estimated separately instead of being jointly estimated, then the empirical copula process behaves as if the innovations were observed; a remarkable property. As a by-product, one also obtains the asymptotic behavior of rank-based measures of dependence applied to residuals of these time series models.

The two-parameter distribution introduced by Kumaraswamy (1980) is a very flexible alternative to the Beta distribution with the same (0,1) support. Originally proposed in the field of hydrology, it has subsequently received a good deal of positive attention in both the theoretical and applied statistics literatures. Interestingly, the problem of testing formally for the appropriateness of the Kumaraswamy distribution appears to have received little or no attention to date. To fill this gap, in this paper we apply the “biased transformation” methodology proposed by Raschke (2009) to several standard goodness-of-fit tests based on the empirical distribution function. A simulation study reveals that these (modified) tests perform well in the context of the Kumaraswamy distribution, in terms of both low size distortion, and respectable power. In particular, the “biased transformation” Anderson-Darling test dominates the other tests that are considered.

Given a fuzzy normed space $ \left( X,N \right) $‎, ‎we will introduce the notion of fuzzy near best approximation within a relative distance $ \rho \geq 0 $‎. ‎Some basic properties are characterized and also many examples for illustration are presented‎.

The digital era offers many opportunities to the wind energy industry and research community. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenges in successfully implementing digitalisation is the lack of data sharing and collaboration between organisations in the sector. In order to overcome this challenge, a new collaboration method called WeDoWind was developed in recent work. The main innovation of this method is the way it creates tangible incentives to motivate and empower different types of people from all over the world to actually share data and knowledge in practice. In this present paper, the challenges related to comparing and evaluating different SCADA data based wind turbine fault detection models are investigated by carrying out a new case study, the "WinJi Gearbox Fault Detection Challenge", based on the WeDoWind Method. Six new solutions were submitted to the challenge, and a comparison and evaluation of the results show that, in general, some of the approaches (Particle Swarm Optimisation algorithm for constructing health indicators, performance monitoring using Deep Neural Networks, Combined Ward Hierarchical Clustering and Novelty Detection with Local Outlier Factor and Time-to-failure prediction using Random Forest Regression) appear to have a high potential to reach the goals of the Challenge. However, there are a number of concrete things that would have to have been done by the Challenge providers and the Challenge moderators in order to ensure success. This includes enabling access to more details of the different failure types, access to multiple data sets from more wind turbines experiencing gearbox failure, provision of a model or rule relating fault detection times or a remaining useful lifetime to the estimated costs for repairs, replacements and inspections, provision of a clear strategy for training and test periods in advance, as well as provision of a pre-defined template or requirements for the results. These learning outcomes are used directly to define a set of best practice data sharing guidelines for wind turbine fault detection model evaluation. They can be used by the sector in order to improve model evaluation and data sharing in the future.

The development in information technology has played an influential role in transforming the restaurant industry services. Therefore, this research’s main agenda is to investigate factors that motivate employees to adopt and continue using information technology services by integrating two famous information system (IS) theories, namely, task technology fit (TTF) and technology continuance theory (TCT). The extant integrative perspective model details the cause-effect relationship between technology adoption and continuance intention. The positivist paradigm forms the basis of this research design, and the approach followed is quantitative research. Using the stratified random sampling technique, the empirical data was collected from 417 restaurant industry employees in the US (United States) on a five-point Likert scale. The PLS-SEM technique was utilized to analyze data while using Smart PLS 3 because of its suitability and wider application currently in the hospitality sector. Results suggest that the recently developed integrated technology continuance research model has considerable influence on predicting pre- and post-adoption behavior with continuance intention for technology usage within the restaurant industry. All hypotheses were found significant except one for the direct association of hedonic motivation and continuance intention of technology adoption. Moreover, the results revealed that factors like perceived security & information privacy and assisting conditions were the most important factors in determining the usage of information technology with continuance intention. Unlike previous research studies that focus majorly only on issues before adoption of informational technology usage, the current focus on investigating continuance intention toward information technology usage by focusing on factors that can also boost post-adoption behavior and pre-adoption usage information technology.

The contribution of readymade garment (RMG) industry is immense behind the rapid development of some countries with emerging economies. This industry is empowering these countries to provide employment opportunities for millions of people. However, the health as well as safety issues of the workers in this industry are often ignored, particularly in these developing countries. In recent times, because of the several undesirable and obnoxious conditions that exist in their working environments, they are vulnerable to various health related problems which are increasing at a staggering rate. The main purpose of this paper is to assess and prioritize the major health related problems faced by these garment workers in these countries where the economy is flourishing. In addition, the main hazards responsible for these health perils are also quantified. Data were collected from three different garment factories situated in different locations of Bangladesh. Thirty workers from each factory rated the frequency and severity of 14 health related issues. The health risks were then assessed and prioritized through risk priority number (RPN). Afterwards, three experts provided their opinion on the main hazards prevalent in the workplace of almost every garment factory in this country. These hazards were grouped into four main classes which are: 1) Physical 2) Ergonomic 3) Chemical and 4) Psychological hazards. The main classes were later divided into sub classes also. Best-worst method (BWM) was then applied to analyze these hazards by assessing their relative weights depending on the experts’ judgement. The results showed that the health issues faced by the workers in three different garment factories varied to some extent. The results obtained from the experts’ opinion indicated that physical hazards in the workplace are the most detrimental ones whereas the chemical hazards were the least harmful.

The Covid-19 pandemic strained global supply chains, and companies faced numerous produc-tion, logistics, or material management problems. It is claimed that the digitalization of supply chains can have the potential to make supply chains more resilient to interruptions and disrup-tions. This article focuses on describing the experiences of three large Austrian family-owned business during the supply chain disruptions caused by the pandemic and the Ukraine war. This assessment is done from the perspective of the supply chain leaders in the organization. We provide insights on what worked and what did not for these firms and what we can take away from their experiences.

Given the high levels of overall volume of alcohol use, detrimental drinking patterns, and high levels of alcohol-attributable mortality and burden of disease, Lithuania implemented a series of alcohol control policies within a relatively short period of time (2008 to 2019). Based on their expected impact on alcohol consumption and alcohol-attributable harm, as well as their target population, the respective policies were classified using a set of objective criteria and expert opin-ion. The classification criteria included: positive vs. negative outcomes, mainly immediate versus delayed outcomes, and general population versus specific group outcomes. The judgement of the alcohol policy experts converged on the objective criteria, and, as a result, two tiers of inter-vention were identified: Tier 1 – general population interventions with an anticipated immediate impact; Tier 2 – other interventions aimed at the general population. In addition, interventions for specific populations were identified. This adaptable methodological approach to alcohol control policy classification is intended to provide guidance and support the evaluation of alcohol policies elsewhere, lay the foundation for the critical assessment of the respective policies to im-prove health and increase life expectancy, and to reduce crime and violence.

In this paper, we introduced many new notions and new contraction named as S-weakly contraction after that we obtained the p-common best proximity point theorems for different types of contractions in the setting of complete metric spaces by using weak P_p-property and proved the uniqueness of these points. Also we presented some examples to prove the validity of our results.

Energy distance is used to eigenvalue distributions in this new Wishart distribution study, providing a new perspective on high-dimensional data. Multivariate statistics relies on Wishart distribution to explain covariance matrices. This analysis shows how degrees of freedom and covariance matrix configurations affect eigenvalue dispersion. We use energy distance based on eigenvalue distributions to assess Wishart distribution differences without the "curse of dimensionality" via extensive simulation simulations. This approach improves measurement accuracy and processing efficiency in distribution comparisons and enables new analytical pathways in scientific fields that need data covariance comprehension. Our results show that degrees of freedom and matrix structure considerably affect energy distances, expanding the theoretical framework and practical applications of statistical models.

The design and operation of quantum networks are both decisive in the current push towards a global quantum internet. Although space-enabled quantum connectivity has already been identified as a beneficial candidate for long-range quantum channels for over two decades, the architecture of a hybrid space-ground network is still a work in progress. Here, we propose an analysis of such a network based on a best-path approach, where either fiber- or satellite-based elementary links can be concatenated to form a repeater chain. The network consisting of quantum information processing nodes, equipped with both ground and space connections, is mapped into a graph structure, where edge weights represent the achievable secret key rates, chosen as the figure of merit for the network analysis. A weight minimization algorithm allows identifying the best path dynamically, i.e., as the weather conditions, stray light radiance, and satellite orbital position changes. From the results we conclude that satellite links will play a significant role on the future large-scale quantum internet, and both a constellation of satellites and significant advances in filtering technology are required to fulfill continuous coverage.

Background: As long-lived organisms, urban trees often encounter development and redevelopment activities in close proximity during their lifespans. These activities can damage tree roots, often through methods like root severing during trenching or excavation. Methods: In 2017, we simulated trenching damage on mature Quercus virginiana Mill. trees at three different distances from the base (3x, 6x, and 12x the stem diameter). After five years, we revisited these trees to assess root regrowth based on the cut root's cross-sectional area (CSA) and distance from the base. Results: We observed regrowth in all but 38 (6.7%) of the 557 cut roots revisited. The lack of regrowth in some roots was not associated with our original treatments, the CSA of the roots at the time of trenching, or distance between the cut root end and the trunk (minimum P-value = 0.841). On average, the observed CSA of the regrowth was 22.2% of the original root's CSA. Only our original trenching treatments significantly predicted the level of regrowth observed five years after pruning (P-value = 0.024). Discoloration due to root pruning was minimal. Conclusion: In summary, our findings indicate that root systems require many years to recover from trenching damage. Increasing the distance between trenching activities and trees may have a minor effect on root regrowth but primarily helps reduce initial stress on the tree.

The interference-fit size has a significant effect on CFRP/Al-alloy laminates riveted lap joints, the requirements for the interference-fit size are different because of the strengthening of heterogeneous materials. However, in the process of the riveted CFRP/Al-alloy, the heterogeneous laminates lead to poor structural strength because of the different requirements of interference-fit size. Therefore, the different assembly types of riveting mold are designed to acquire a novel interference-fit size, and the tensile test is adopted to evaluate the tensile property. In addition, the fracture failure of CFRP/Al-alloy laminates riveted lap joint is observed by the ultra-depth of field microscope. Finally, the best assembly type is the trapezoid riveting mold combined with an arc riveting die, and the sidewall intersection angle of the trapezoid riveting mold is 66° which could achieve a suitable interference-fit size and a better mechanical performance.

This paper studies the goodness of fit test for the bivariate Hermite distribution. Specifically, we propose and study a Cramér-von Mises-type test based on the empirical probability generation function. The bootstrap can be used to consistently estimate the null distribution of the test statistics. A simulation study investigates the goodness of the bootstrap approach for finite sample sizes.

Background: Best Possible Medication History (BPMH) collected by clinical pharmacists is crucial for effective medication review but, in Italy, it is often left to the nursing staff. This study aims to compare the quality and accuracy of a clinical pharmacist-documented BPMH with the current standard practice of ward staff-collected BPMH at an Italian perioperative surgical setting. Methods: A 20-week prospective observational non-profit study was conducted in a major University hospital. The study comprised a feasibility, an observational, and an interventional phase. During the feasibility phase, 10 items for obtaining a correct BPMH were identified. The control group consisted of retrospectively analyzed BPMHs collected by the ward staff during the observational phase, while interventions included BPMHs collected by the clinical pharmacist during the third phase. Omissions between the two groups were compared. Results: 14 (2%) omissions were found in the intervention group, compared with 400 (57.4%) found in the controls (p<0.05); data collection was more complete when collected by pharmacists compared to the current modalities (98.0% versus 42.6%; p<0.05). Conclusions: The involvement of a pharmacist significantly reduced the number of omissions in perioperative surgical-collected BPMHs. This intervention holds the potential to decrease the risk of medication errors associated with inaccurate or incomplete BPMHs prior to surgical hospitalization.

Best management practices (BMPs) are a way to control pollution in river basins. Prioritization of BMPs helps improve efficiency and effectiveness of pollution reduction, especially in critical source areas (CSAs) that produce the highest pollution loads. Recently, the Dez River, Khuzestan, Iran, has become highly eutrophic from overuse of fertilizers and pesticides. Dry and irrigated farming produce 77.34% and 6.3% of the total nitrogen (TN) load, and 83.56% and 4.3% of the total phosphorus (TP) load in this basin, respectively. Residential, pasture, and forest land uses account for 16.36% of the TN and 12.14% of the TP load cumulatively. In this study, the Soil and Water Assessment Tool (SWAT) was implemented to model the Dez River basin, and evaluate the applicability of several BMPs including point source elimination, filter strips, livestock grazing, and river channel management, in reducing the entry of pollution loads to the river. Sensitivity analysis and calibration/validation of the model was performed using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). CSAs were identified using individual (sediment, TN, TP) and combined indices, based on the amount of pollution produced. Among the BMPs implemented, filter strips were most effective in reducing TN loads (59%), and, increasing the D₅₀ of particles for river channel management was most effective in reducing TP loads (49%).

To expand the application area of the reference group and enrich exercise theoretical research, based on Stimulus-Organism-Response (S–O-R) framework, this study examines the factors that motivate for adherence to exercise from the external. Taking reference group and strategy and cultural fit as the main stimulus, and personal investment and life satisfaction as mediating variables, this study try to explore the influence of external stimulus on residents’ exercise behavior. In order to enrich the sample size, two surveys of 734 Chinese residents in two cities (Xiamen vs. Fuzhou) were conducted using factor analyses, regression analysis, and T-test analysis. The results indicated that the reference group and strategic and cultural fit as external stimulus have impact on residents’personal investment, life satisfaction and exercise adherence, personal investment and life satisfaction as the organism has impact on residents’ exercise adherence. Personal investment and life satisfaction play a chain mediating role between the reference group and exercise adherence, strategy and cultural fit, and exercise adherence. Moreover, the T-test determined the differences between Xiamen and Fuzhou residents’ exercise adherence and life satisfaction. Residents’ surroundings affect their exercise behavior and life satisfaction. These findings have implications for policymaking aimed at promoting national exercise, which could gradually improve residents’ physical fitness, particularly in light of the current coronavirus emergency.

To mitigate the adverse impacts of urban stormwater on streams, watershed managers are increasingly using low impact development and green infrastructure (LID-GI) stormwater control measures such as rain gardens—vegetated depressional areas that collect and infiltrate runoff from rooftops and driveways. Their catchment-scale performance, however, can vary widely, and few studies have investigated the cumulative performance of residential rain gardens for event runoff control in intermediate-sized (i.e., 1-10 km2) suburban catchments. We modeled three years of continuous rainfall-runoff from a 3.1 km2 catchment in Columbia, MD, USA, using the Storm Water Management Model (SWMM). Various extents of rain garden implementation at residential houses were simulated (i.e., 25%, 50%, 75%, and 100% coverage) to determine the effects on peak flow, runoff volume, and lag time. On average, treating 100% of residential rooftops in the catchment reduced peak flows by 14.3%, reduced runoff volumes by 11.4%, and increased lag times by 3.2% for the 223 rainfall events during the simulation period. Peak flow reductions were greater for smaller storm events (p&lt;0.01). Our results show that residential rain gardens can significantly improve the runoff response of suburban catchments, and that they represent an effective and relatively low-cost option for urban watershed management and restoration.

In these times, consumers mistakenly believe that the terms “expiration date” and “best before” found on packages only convey information about food safety. Consequently, a misunderstanding of these terms contributes to food waste. In this sense, the understanding and behavior of the con-sumer with respect to the two terms were evaluated; in addition, the consumer's perception of the health risks of consuming expired food was analyzed. The research was carried out with the population of the sector of Lurigancho-Chosica, Lima – Peru; sample size was 555 participants. An online survey was sent to consumers over 18 years of age, from different sociodemographic and socioeconomic conditions. In general terms, it was found that 45% (p <0.01) consider that both terms mean the same thing, this result is a problem for food safety. The 67% (p <0.05) and 45% (p <0.05) correctly defined the first and second terms, respectively; however, the behavior is not coherent with the understanding of the terms. In addition, irrational and dangerous behavior toward expired food was evidenced, i.e., they consume expired food - "expiration date", and discard expired food - "best before". Finally, the health risks they perceived from consuming expired foods of both terms were: upset stomach, vomiting, gas, intoxi-cation, and malnutrition; these perceptions are erroneous and unfounded. Sociodemographic and socioeconomic conditions influence the under-standing, behavior, and perception of health risks. Therefore, in general lines, the level of understanding of the terms was low (p<0.01), the be-havior was inappropriate toward expired food (p<0.01), and the percep-tion of the health risk of consuming expired food was incorrect (p<0.01).

Machine learning is an established and frequently used technique in industry and academia but a standard process model to improve success and efficiency of machine learning applications is still missing. Project organizations and machine learning practitioners have a need for guidance throughout the life cycle of a machine learning application to meet business expectations. We therefore propose a process model for the development of machine learning applications, that covers six phases from defining the scope to maintaining the deployed machine learning application. The first phase combines business and data understanding as data availability oftentimes affects the feasibility of the project. The sixth phase covers state-of-the-art approaches for monitoring and maintenance of a machine learning applications, as the risk of model degradation in a changing environment is eminent. With each task of the process, we propose quality assurance methodology that is suitable to address challenges in machine learning development that we identify in form of risks. The methodology is drawn from practical experience and scientific literature and has proven to be general and stable. The process model expands on CRISP-DM, a data mining process model that enjoys strong industry support but lacks to address machine learning specific tasks. Our work proposes an industry and application neutral process model tailored for machine learning applications with focus on technical tasks for quality assurance.

The workplace is an ideal setting for health promotion. The regular medical examination of workers enables us to screen for numerous diseases, spread good practices and correct lifestyles, and obtain a favourable risk/benefit ratio. The continuous monitoring of the level of workers' wellbeing using a holistic approach that goes beyond the simple prevention of occupational risks enables us to promptly identify problems in work organization and the company climate. Problems of this kind can be adequately managed by using a participatory approach. In this study participatory ergonomics groups were used to improve occupational life in a small company. After intervention we observed a reduction in levels of perceived occupational stress measured with the effort / reward imbalance model, and an improvement in psychological wellbeing assessed by means of the Goldberg anxiety / depression scale. Although the limited size of the sample calls for a cautious evaluation of this study, the GEP© strategy proved to be a useful tool due to its cost-effectiveness.

Shafts with a stepped shoulder are particularly well known in the field of drive technology. In combination with a form-fit shaft–hub connection, the shaft shoulder fixes the hub on the shaft as well as the absorption of the axial forces. With profiled shafts, there is a notch overlay in the shaft shoulder, involving the shaft shoulder and profile. If the hub is also connected with the profiled shaft, the hub edge acts as an additional notch in the shaft shoulder area. The multiple resulting notches have not previously been part of research activities in the field of innovative trochoidal profile connections. Compared to conventional positive-locking connections, such as the keyway connection or the involute splined shaft profile, the favourable features of trochoidal profiles have only been based on connections with smooth shafts without a shoulder in previous studies. Accordingly, this article addresses the numerical and experimental investigations of trochoidal profile connections with offset shafts for pure torsional loading. Focusing on a hybrid trochoid with four eccentricities and six drivers, a well-founded numerical and experimental investigation was carried out with numerous fatigue tests. In addition, the influence of a shaft shoulder was also demonstrated on simple epi- and hypotrochoidal profiles.

Research into professionalization in health and safety has recently gained in interest. Graduate training is one of the factors that determines or conditions the role of the safety professional, thus intervene in the professionalization process. This article is the result of a workshop and the discussions of nine academic directors of safety education programs about quality evaluation. This article introduces the issue with a historic overview of safety education, presents a synthesis of nine selected education programs, discusses quality evaluation of health and safety education programs, propose a quality evaluation frame and finally, proposes a process for designing a quality safety education program with an associated model of the learning objectives. The outcomes are interesting for everyone who is interested in health and safety education and quality evaluation and will give insights into how safety professionals are educated.

Plasmodium falciparum dihydroorotate dehydrogenase (PfDODH) is one of the enzymes currently explored in the treatment of malaria. Although there is currently no clinically approved drug targeting PfDODH, many of the compounds in clinical trials have [1, 2, 4,] triazolo [1, 5-a] pyrimidin-7-amine backbone structure. This study sought to design new compounds from the fragments of known experimental inhibitors of PfDODH. Nine experimental compounds retrieved from Drug Bank online were downloaded and broken into fragments using Schrodinger power shell; the fragments were recombined to generate new ligand structures using BREED algorithm. The new compounds were docked with PfDODH crystal structure, after which the compounds were filtered with extensive drug-likeness and toxicity parameters. A 2D-QSAR model was built using the multiple linear regression method and externally validated. The compounds electronic behaviours were studied using DFT calculations. Structural investigation of the six designed compounds, which had lower binding energies than the standard inhibitors, showed that five of them had [1, 2, 4,] triazolo [1, 5-a] pyrimidin-7-amine moieties and interacted with essential residues at the PfDODH binding site. In addition to their drug-like and pharmacokinetic properties, they also showed minimal toxicities. The externally validated 2D-QSAR model with R² and Q² values of 0.6852 and 0.6691, confirmed the inhibitory prowess of these compounds against PfDODH. The DFT calculations showed regions of the molecules prone to electrophilic and nucleophilic attack. The current study thus provides insight into the development of a new set of potent PfDODH inhibitors.

The KcsA is a prokaryotic potassium-oriented channel, which is sourced from the Streptomyces lividans soil bacteria. From extensive studies that have been carried over the KcsA potassium channel, it has been proved that various factors enable the gating and shuttling of the potassium ions into and out of the cells. Some of the factors include the different concentration of protons in the inside and outside membrane. The other factor is the existence of the selectivity filter equipped in the exit of channel pore, which enables the movement of the K⁺ ions. Not only are potassium ions present in the channel but also sodium ions. Potassium and sodium ions are the ions that are essential in the conductivity of a cell because of their charge. An intuitive idea about why K⁺ ions are at least 10,000 times more permeant than Na⁺ ions is presented in various entities. The hypothesis is that the selectivity ratio is probably related to the successive entry of Na⁺ ions, based on the premise that the ratio seems to be relevant to unpredictable quantities caused by Brownian corrosion of ions.

Fall prediction using machine learning has become one of the most fruitful and socially relevant applications of computer vision in gerontological research. Since its inception in the early 2000s, this subfield has proliferated into a robust body of research underpinned by various machine learning algorithms (including neural networks, support vector machines, and decision trees) as well as statistical modeling approaches (Markov chains, Gaussian mixture models, and hidden Markov models). Furthermore, some advancements have been translated into commercial and clinical practice, with companies in various stages of development capitalizing on the aging population to develop new commercially available products. Yet despite the marvel of modern machine learning-enabled fall prediction, little research has been conducted to shed light on the security and privacy concerns that such systems pose for older adults. The present study employs an interdisciplinary lens in examining privacy issues associated with machine learning fall prediction and exploring the implications of these models in elderly care and the Internet of Medical Things (IoMT). Ultimately, a justice-informed set of best practices rooted in social geroscience is suggested to help fall prediction researchers and companies continue to advance the field while preserving elderly privacy and autonomy.

The doctoral defense is an important step in the doctoral journey and an essential requirement for obtaining the doctoral degree. Past research on the doctoral defense has focused solely on national practices. In this work, I investigate the potential link between the doctoral defense format based on its major and minor elements and the perception of the defense by the student. For this purpose, I first reviewed the different defense formats used internationally to extract the different elements of the doctoral defense, as well as the literature on students’ perceptions of the doctoral defense. Then, I carried out an international survey which received 297 responses, of which 204 completed surveys which I used for the analysis in this article. I first analyzed the outcomes of the survey using qualitative and quantitative methods, and then cross-correlated the outcomes of defense format to the outcomes of student perception. From this analysis, I observe that the defense elements that positively impact the students’ perception are: publication of the thesis before the defense, receiving committee feedback before the defense, knowing the recommendation of one or more committee members in advance, having the supervisor present in the audience or as part of the committee, using a dress code, and including a laudatio. The final conclusion of this work is threefold. The first conclusion is that the details of the defense format impact most the students’ perception. The second conclusion is that doctoral students on average value the defense as a positive experience. The third conclusion is that the defense format cannot influence two important aspects of how a student perceives the defense: the student’s inner life and lived experience during the defense, and the behavior of the committee members.

Fit-for-purpose land administration (FFPLA) seeks to simplify cadastral mapping via lowering the costs and time associated with conventional surveying methods. The approach can be applied to both initial establishment and on-going maintenance of system. In Ethiopia, cadastral maintenance remains an on-going challenge, especially in rapidly urbanizing peri-urban areas, where farmers' land rights and tenure security are often jeopardized. Automatic Feature Extraction (AFE) is an emerging FFPLA approach, proposed as an alternative for mapping and updating cadastral boundaries. This study explores the role of the AFE approach for updating cadastral boundaries in the vibrant peri-urban areas of Addis Ababa. Open-source software solutions are utilized to assess the (semi-) automatic extraction of cadastral boundaries from orthophotos (segmentation), designation of 'boundary' and 'non-boundary' outlines (classification), and delimitation of cadastral boundaries (interactive delineation). Both qualitative and quantitative assessments of the achieved results (validation) are undertaken. A high-resolution orthophoto of the study area and a reference cadastral boundary shape file are used, respectively, for extracting the parcel boundaries and validating the interactive delineation results. Qualitative (visual) assessment verified the completed extraction of newly constructed cadastral boundaries in the study area, although non-boundary outlines such as footpaths and artefacts are also retrieved. For the buffer overlay analysis, the interactively delineated boundary lines and the reference cadastre were buffered within the spatial accuracy limits for urban and rural cadasters. As a result, the quantitative assessment delivered 52% correctness and 32% completeness for a buffer width of 0.4m and 0.6m, respectively, for the interactively delineated and reference boundaries. The study further demonstrated the potentially significant role AFE could assist in delivering fast, affordable, and reliable cadastral mapping. Further investigation, based on user input and expertise evaluation, could help to improve the approach and apply it to a real-world setting.

The entropy of the partition generated by an n-tone music scale is proposed to quantify its regularity. The normalized entropy relative to a regular partition, and its complementary, here referred to as the bias, allow to analyze various conditions of similarity between an arbitrary scale and a regular scale. Interesting particular cases are scales having limited bias because their tones are distributed along interval fractions of a regular partition. The most typical case in music concerns partitions associated with well-formed scales generated by a single tone h. These scales are maximal even sets that combine two elementary intervals. Then, the normalized entropy depends on the number of tones as well as the relative size of both elementary intervals. When well-formed scales are refined, several nested families stand out with increasing regularity. It is proven that a scale of minimal bias, i.e. with less bias than those with fewer tones, is always a best rational approximation of log2h.

Existing implants used with Total Knee Arthroplasty (TKA), Total Hip Arthroplasty (THA), and other joint reconstruction treatments, have displayed premature failures and frequent needs for revision surgery in recent years, particularly with young active patients who represent more than 55% of all joint reconstruction patients. Bone cement and stress shielding have been identified as the major reasons for premature joint failures. A breakdown of the cement may happen, and revision surgery may be needed because of the aseptic loosening. The significant mismatch of stiffness properties of patient trabecular bones and metallic implant materials in joint reconstruction surgery results in the stress shielding phenomenon. This could lead to significant bone resorption and increased risk of bone fracture and the aseptic loosening of implants. The present project introduces an approach for development of customized cellular structures to match the mechanical properties and architecture of human trabecular bone. It consists of four modules:1- characterization of geometry, microarchitecture, and stiffness properties of patient’s bones; 2- developing customized lattice structures tailored to mimic properties established in module 1; 3 - integration of developed lattice structure into full scale implant design and manufacturing; 4- implementation of the developed technology for use in implants that would overcome most of the issues related to aseptic loosening phenomenon. The present work aims at fulfilling the objectives of module 2 by exploring new designs of customized lattice structures and texture tailored to mimic closely patients’ bone anisotropic properties and that can incorporate an engineered biological press-fit fixation technique. The effects of various lattice design variables on mechanical performance of the structure are examined through systematic experimental plan using statistical design of experiments technique and analysis of variance method. All tested lattice designs were explored under realistic geometrical, biological, and manufacturing constraints. Of the four design factors examined in this study, strut thickness was found to have the highest percent contribution (41%) regarding the structure stiffness, followed by unit cell type, and cell size. Srut shape was found to have the lowest effect with only 11% contribution. The introduced solution offers lattice structure designs that can be adjusted to match bone stiffness distribution and promote bone ingrowth and hence eliminating the phenomenon of stress shielding while incorporating biological press-fit fixation technique.

This paper presents an analytical method for determining the bending stresses and deformations in prismatic noncircular profile shafts with trochoidal cross sections. The so-called higher trochoids can be used as form-fit shaft–hub connections. Hybrid (mixed) higher trochoids (M-profiles) were proposed in [1] and adapted to a practical industrial application in [2]. M-profiles combine the advantages of standardised polygon (DIN 32711 [3]) and spline (DIN 5486 [4]) contours used as shaft–hub connections for the transmission of torsional loads. In this study, the geometric and mechanical properties of the higher hybrid trochoids were investigated using complex functions to simplify the calculations. The pure bending stress and shaft deflection were determined for M-profiles using the bending theory formulated by Muskhelishvili [5]. The loading cases consisted of static and rotating bends. Analytical, numerical, and experimental results agreed well.

The prefabricated ECC/RC combined shear wall structure is an innovative prefabricated composite structure with better seismic performance by using ECC materials with better ductility in the main force and energy consumption regions of the prefabricated reinforced concrete (RC) shear wall structure. The key factors controlling the seismic energy dissipation capacity of this kind of structure are the use regions of ECC in composite coupling beams, use regions of ECC in shear walls, strength of ECC, stirrup ratio of coupling beams, strength of longitudinal reinforcement and so on. The parameters affecting seismic energy consumption are quantified by the finite element analysis method. By comparing and analyzing the load-displacement curves, hysteresis curves, energy dissipation capacity and stiffness degradation of the prefabricated ECC/RC combined shear wall structure specimen under these parameters, it is proposed that the best use regions of ECC is the cast-in-situ zone of the coupling beams with the scope of no more than400 mm at the shear walls’ bottom. The strength grade, the strength grade of longitudinal reinforcement, and the stirrup ratio of coupling beams are suggested design as E40, HRB400 and 0.5%, respectively.

Cash crops are agricultural crops intended to be sold for profit as opposed to subsistence crops, meant to support the producer, or to support livestock. Since cash crops are intended for future sale, they translate into large financial value when considered on a wide geographical scale, so their production directly involves financial risk. At a national level, extreme weather events including destructive rain or hail, as well as drought, can have a significant impact on the overall economic balance. It is thus important to map such crops in order to set up insurance and mitigation strategies. Using locally generated data -such as municipality-level records of crop seeding- for mapping purposes implies facing a series of issues like data availability, quality, homogeneity etc. We thus opted for a different approach relying on global datasets. Global datasets ensure homogeneity and availability of data, although sometimes at the expense of precision and accuracy. A typical global approach makes use of spaceborne remote sensing, for which different land cover classification strategies are available in literature at different levels of cost and accuracy. We selected the optimal strategy in the perspective of a global processing chain. Thanks to a specifically developed strategy for fusing unsupervised classification results with environmental constraints and other geospatial inputs including ground-based data, we managed to obtain good classification results despite the constraints placed. The overall production process was composed using ``good-enough" algorithms at each step, ensuring that the precision, accuracy, and data-hunger of each algorithm was commensurate to the precision, accuracy, and amount of data available. This paper describes the tailored strategy developed on the occasion as a cooperation among different groups with diverse backgrounds, a strategy which is believed to be profitably reusable in other, similar contexts. The paper presents the problem, the constraints and the adopted solutions; it then summarizes the main findings including that efforts and costs can be saved on the side of Earth Observation data processing when additional ground-based data are available to support the mapping task.

The present study evaluates ratcheting response of notched and press-fitted Al 7075-T6 specimens under stress-controlled asymmetric cycles. The degree of interference fit (DIF) directly influenced progressive plastic strain magnitude and rate at notch root region. Local ratcheting at the hole-pin interference region was analyzed by means of two kinematic hardening rules of Ahmadzadeh-Varvani (A-V) and Chaboche coupled with the Neuber rule. Ratcheting strains at notch root of aluminum samples with DIF=0 (non-press-fitting samples) were measured to be highest in magnitude. For the press-fitted samples, however ratcheting strains dropped noticeably as DIF increased from 1% to 2%. Press-fitted samples plastically deformed the perimeter edge of notches and improved materials locally at the notch edge, resulting in a better resistance against ratcheting progress. Local ratcheting at different distances of 0.5, 1.3 and 3.0 mm from the notch root were evaluated for both pinned and unpinned samples through the hardening rules and compared with those of measured values. The predicted ratcheting curves by means of the A-V and Chaboche hardening rules closely agreed with experimental data and respectively positioned above and below the measured data.

This paper focuses on the so-called proportional intensity-based software reliability models (PI-SRMs), which are extensions of the common non homogeneous Poisson process (NHPP)-based SRMs, and describe the probabilistic behavior of software fault-detection process by incorporating the time-dependent software metrics data observed in the development process. Especially we generalize the seminal PI-SRM in Rinsaka, Shibata and Dohi (2006) by introducing eleven well-known fault-detection time distributions, and investigate their goodness-of-fit and predictive performances. In numerical illustrations with four data sets collected in real software development projects, we utilize the maximum likelihood estimation to estimate model parameters with three time-dependent covariates; test execution time, failure identification work and computer time-failure identification, and examine the performances of our PI SRMs in comparison with the existing NHPP-based SRMs without covariates. It is shown that our PI-STMs could give better goodness-of-fit and predictive performances in many cases.

Identifying macroeconomic events that are responsible for dramatic changes of economy is of particular relevance to understand the overall economic dynamics. We introduce an open-source available efficient Python implementation of a Bayesian multi-trend change point analysis which solves significant memory and computing time limitations to extract crisis information from a correlation metric. Therefore, we focus on the recently investigated S&P500 mean market correlation in a period of roughly 20 years that includes the dot-com bubble, the global financial crisis and the Euro crisis. The analysis is performed two-fold: first, in retrospect on the whole dataset and second, in an on-line adaptive manner in pre-crisis segments. The on-line sensitivity horizon is roughly determined to be 80 up to 100 trading days after a crisis onset. A detailed comparison to global economic events supports the interpretation of the mean market correlation as an informative macroeconomic measure by a rather good agreement of change point distributions and major crisis events. Furthermore, the results hint to the importance of the U.S. housing bubble as trigger of the global financial crisis, provide new evidence for the general reasoning of locally (meta)stable economic states and could work as a comparative impact rating of specific economic events.

As the increase threat of flood risk and environmental safety due to the urbanization, Sponge city research has been attracting extensive attention both in practical and theoretical research field. To date, there are only scattered studies about Sponge city. Moreover, vary names of Sponge city prevalent in different countries, which leads to disconnection of literature in the same field of Sponge city. In this paper, a thorough systematic literature mining of Sponge city is presented. A literature analysis system is created, which includes literature export from Web of Sciences and systematic analysis via NoteExpress and CiteSpace. Some literature statistical results are derived. Challenges and opportunities for future research are anticipated. Our goals are to promote this promising thought, summarize past research, and identify issues for future research to create impacts on the practice of Sponge city.

It is known that the class of p-normed spaces (0 < p ≤ 1) is an important generalization of usual normed spaces with rich topological and geometrical structure, but the most of tools and general principles in nature with nonlinearity have not been developed yet, thus the main goal of this paper is to develop tools for nonlinear analysis under the framework of p-vector spaces. In particular, we first develop the general fixed point theorems which provide solutions to answer Schauder conjecture since 1930’s in the affirmative for p-vector spaces when p = 1 (which is just general topological vector spaces); then the one best approximation result for upper semi-continuous mappings is given, which is used as a powerful tool to establish fixed points for non-self set-valued mappings with either inward or outward set conditions; and finally we establish comprehensive existence results of solutions for Birkhoff-Kellogg Problems, and the general principle of nonlinear alternative by including Leray-Schauder alternative and related results. The results given in this paper not only include the corresponding results in the existing literature as special cases, but also expected to be useful tools for the study of nonlinear problems arising from theory to practice.