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ObjectiveLow individual socioeconomic status (SES) is known to be associated with a higher risk of type 2 diabetes mellitus (T2DM), but the extent to which the local context in which people live may influence T2DM rates remains unclear. This study examines whether living in a low property value neighbourhood is associated with higher rates of T2DM independently of individual SES.Research design and methodsUsing cross-sectional data from the Maastricht Study (2010-2013) and geographical data from Statistics Netherlands, multilevel logistic regression was used to assess the association between neighbourhood property value and T2DM. Individual SES was based on education, occupation and income. Of the 2,056 participants (aged 40-75 years), 494 (24%) were diagnosed with T2DM.ResultsIndividual SES was strongly associated with T2DM, but a significant proportion of the variance in T2DM was found at the neighbourhood level (VPC = 9.2%; 95% CI = 5.0%-16%). Participants living in the poorest neighbourhoods had a 2.38 times higher odds ratio of T2DM compared to those living in the richest areas (95% CI = 1.58-3.58), independently of individual SES.ConclusionsNeighbourhood property value showed a significant association with T2DM, suggesting the usefulness of area-based programmes aimed at improving neighbourhood characteristics in order to tackle inequalities in T2DM.

Human population density in the coastal zone and potential impacts of climate change underscore a growing conflict between coastal development and an encroaching shoreline. Rising sea-levels and increased storminess threaten to accelerate coastal erosion, while growing demand for coastal real estate encourages more spending to hold back the sea in spite of the shrinking federal budget for beach nourishment. As climatic drivers and federal policies for beach nourishment change, the evolution of coastline mitigation and property values is uncertain. We develop an empirically grounded, stochastic dynamic model coupling coastal property markets and shoreline evolution, including beach nourishment, and show that a large share of coastal property value reflects capitalized erosion control. The model is parameterized for coastal properties and physical forcing in North Carolina, U.S.A. and we conduct sensitivity analyses using property values spanning a wide range of sandy coastlines along the U.S. East Coast. The model shows that a sudden removal of federal nourishment subsidies, as has been proposed, could trigger a dramatic downward adjustment in coastal real estate, analogous to the bursting of a bubble. We find that the policy-induced inflation of property value grows with increased erosion from sea level rise or increased storminess, but the effect of background erosion is larger due to human behavioral feedbacks. Our results suggest that if nourishment is not a long-run strategy to manage eroding coastlines, a gradual removal is more likely to smooth the transition to more climate-resilient coastal communities.

Objective: Low individual socioeconomic status (SES) is known to be associated with a higher risk of type 2 diabetes mellitus (T2DM), but the extent to which the local context in which people live may influence T2DM rates remains unclear. This study examines whether living in a low property value neighbourhood is associated with higher rates of T2DM independently of individual SES. Research design and methods: Using cross-sectional data from the Maastricht Study (2010–2013) and geographical data from Statistics Netherlands, multilevel logistic regression was used to assess the association between neighbourhood property value and T2DM. Individual SES was based on education, occupation and income. Of the 2,056 participants (aged 40–75 years), 494 (24%) were diagnosed with T2DM. Results: Individual SES was strongly associated with T2DM, but a significant proportion of the variance in T2DM was found at the neighbourhood level (VPC = 9.2%; 95% CI = 5.0%–16%). Participants living in the poorest neighbourhoods had a 2.38 times higher odds ratio of T2DM compared to those living in the richest areas (95% CI = 1.58–3.58), independently of individual SES. Conclusions: Neighbourhood property value showed a significant association with T2DM, suggesting the usefulness of area-based programmes aimed at improving neighbourhood characteristics in order to tackle inequalities in T2DM. [ABSTRACT FROM AUTHOR]

Human population density in the coastal zone and potential impacts of climate change underscore a growing conflict between coastal development and an encroaching shoreline. Rising sea-levels and increased storminess threaten to accelerate coastal erosion, while growing demand for coastal real estate encourages more spending to hold back the sea in spite of the shrinking federal budget for beach nourishment. As climatic drivers and federal policies for beach nourishment change, the evolution of coastline mitigation and property values is uncertain. We develop an empirically grounded, stochastic dynamic model coupling coastal property markets and shoreline evolution, including beach nourishment, and show that a large share of coastal property value reflects capitalized erosion control. The model is parameterized for coastal properties and physical forcing in North Carolina, U.S.A. and we conduct sensitivity analyses using property values spanning a wide range of sandy coastlines along the U.S. East Coast. The model shows that a sudden removal of federal nourishment subsidies, as has been proposed, could trigger a dramatic downward adjustment in coastal real estate, analogous to the bursting of a bubble. We find that the policy-induced inflation of property value grows with increased erosion from sea level rise or increased storminess, but the effect of background erosion is larger due to human behavioral feedbacks. Our results suggest that if nourishment is not a long-run strategy to manage eroding coastlines, a gradual removal is more likely to smooth the transition to more climate-resilient coastal communities. [ABSTRACT FROM AUTHOR]

Across the Western United States, human development into the wildland urban interface (WUI) is contributing to increasing wildfire damage. Given that natural disasters often cause greater harm within socio-economically vulnerable groups, research is needed to explore the potential for disproportionate impacts associated with wildfire. Using Zillow Transaction and Assessment Database (ZTRAX), hereafter "Zillow", real estate data, we explored whether lower-priced structures were more likely to be damaged during the most destructive, recent wildfires in Southern California. Within fire perimeters occurring from 2000–2019, we matched property price data to burned and unburned structures. To be included in the final dataset, fire perimeters had to surround at least 25 burned and 25 unburned structures and have been sold at most seven years before the fire; five fires fit these criteria. We found evidence to support our hypothesis that lower-priced properties were more likely to be damaged, however, the likelihood of damage and the influence of property value significantly varied across individual fire perimeters. When considering fires individually, properties within two 2003 fires–the Cedar and Grand Prix-Old Fires–had statistically significantly decreasing burn damage with increasing property value. Occurring in 2007 and later, the other three fires (Witch-Poomacha, Thomas, and Woolsey) showed no significant relationship between price and damage. Consistent with other studies, topographic position, slope, elevation, and vegetation were also significantly associated with the likelihood of a structure being damaged during the wildfire. Driving time to the nearest fire station and previously identified fire hazard were also significant. Our results suggest that further studies on the extent and reason for disproportionate impacts of wildfire are needed. In the meantime, decision makers should consider allocating wildfire risk mitigation resources–such as fire-fighting and wildfire structural preparedness resources–to more socioeconomically vulnerable neighborhoods. [ABSTRACT FROM AUTHOR]

In this study we examined three correlates of personal wealth–financial capability, buying impulsiveness, and attitudes to money in a large UK adult sample (N = 90,184). We were interested in how these psychological variables related to personal wealth controlling for well-established demographic correlates: age, education, gender, and household income. We drew on three personal wealth variables based on savings and investments, property wealth and personal items. Using correlational and regression analysis we tested three specific hypotheses which each received support. Our variables accounted for around half the variance with respect to property value, and two thirds with respect to investments. The hierarchical regression onto the savings and investment factor showed two thirds of the variance was accounted for: the demographic variables accounted for 27% of the variance, money attitudes an additional 14%; financial capability an additional 24% and buying impulsivity no additional variance. Age, income, and planning ahead were the most powerful and consistent predictors of wealth variables, with associating money with security as an important predictor for savings and investments. Implications for helping improve financial literacy and capability are noted. Limitations are acknowledged. [ABSTRACT FROM AUTHOR]

Due to the complexity of socio-economic-related issues, people thought of housing market as a chaotic nucleus situated at the intersection of neighboring sciences. It has been known that the dependence of house features on the residential property value can be estimated employing the well-established hedonic regression analysis method in teams of location characteristic, neighborhood characteristic and structure characteristic. However, to further assess the roles of urban infrastructures in housing markets, we proposed a new kind of volatility measure for house prices utilizing the Lie symmetry analysis of quantum theory based on Schrödinger equation, mainly focusing on the effects of transportation systems and public parks on residential property values. Based on the municipal open government data regularly collected for four cities, including Boston, Milwaukee, Taipei and Tokyo, and all spatial sampling sites were featured by United States Geological Survey (USGS) National Map, transportation and park were modelled as perturbations to the quantum states generated by the feature space in response to the environmental amenities with different spatial extents. In an attempt to ascertain the intrinsic impact of the location-dependent price information obtained, the similarity functions associated with the Schrödinger equation were considered to facilitate revealing the city amenities capitalizing into house prices. By examining the spatial spillover phenomena of house prices in the four cities investigated, it was found that the mass transit systems and the public green lands possessed the infinitesimal generators of Lie point symmetries Y2 and Y5, respectively. Compared statistically with the common performance criteria, including mean absolute error (MAE), mean squared error (MSE) and, root mean squared error (RMSE) obtained by hedonic pricing model, the Lie symmetry analysis of the Schrödinger equation approach developed herein was successfully carried out. The invariant-theoretical characterizations of economics-related phenomena are consonant with the observed residential property values of the cities internationally, ultimately leading to develop a new perspective in the global financial architecture. [ABSTRACT FROM AUTHOR]

Background: Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Methods: Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002–2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants. Results: HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences. Discussion: The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic areas may not be appropriate. Future screening interventions need to consider the spatially varying association between HCV risk and associated demographic and socio-economic determinants. [ABSTRACT FROM AUTHOR]

The increasingly frequent occurrence of major natural disasters can pose a serious threat to national stability and the safety of people's lives, and cause serious economic losses. How to quickly and accurately dispatch emergency materials to all disaster areas across regions in post-disaster has attracted wide attention from the government and academia. In response to the characteristic of high uncertainty in emergency rescue for major natural disasters, and considering differentiated disaster severity levels in different disaster areas, the entropy weight method is used to determine the urgency coefficient of emergency material demand for disaster areas. This study aims to minimize the emergency materials dispatching time and cost, also maximize the dispatching fairness for disaster areas. The triangular fuzzy number method is used to represent the uncertain variables mentioned above, so that a cross-regional emergency materials intelligent dispatching model in major natural disasters (CREMIDM-MND) is constructed. The extremely heavy rainstorm disaster in Henan Province of China in 2021 is selected as a typical case. Based on objective disaster data obtained from official websites, this study applies the constructed model to real disaster case and calculates the results by MATLAB. The ant colony algorithm is further used to optimize the transportation route based on the calculation results of the emergency material dispatching for disaster areas, and finally forms the intelligent emergency materials dispatching scheme that meets the multiple objectives. The research results indicate that compared to the actual situation, CREMIDM-MND can help decision-maker to develop a cross-regional emergency materials intelligent dispatching scheme in time, thereby effectively improving the government's emergency rescue performance in major natural disasters. Moreover, some managerial insights related to cross-regional emergency materials dispatching practice problem in major natural disasters are presented. [ABSTRACT FROM AUTHOR]

Promoting the social integration of rural migrants is key to improving the mechanism of rural-urban integration and development. This study utilizes the 2017 China Migrants Dynamic Survey and matched urban macro data to systematically explore the impact of homesteads on the social integration of rural migrants. Research has shown that social integration of rural migrants will be inhibited if they own homesteads. Simultaneously, the degree of inhibition varies according to the individual characteristics of rural migrants, the region to which they belong, and other factors. Specifically, when rural migrants aged 18 to 50 own homesteads, their degree of social integration into the cities they move into will be low. At the same time, for rural migrants in the central region, homestead ownership will not affect their degree of social integration. In addition, the mechanism analysis shows that increased housing expenditure inhibits rural migrants' willingness to integrate. Meanwhile, owning contracted land and owning a house in the city also affect the degree of social integration of rural migrants to a certain extent. The findings of this study can broaden research on the effects of land on the free movement of population factors. In the meantime, it provides theoretical references for improving the level of social integration of migrants, enhancing people's well-being, and improving the mechanism of urban-rural integration and development. [ABSTRACT FROM AUTHOR]

Along with the process of rapid economic development and integration, Vietnam is facing serious environmental problems, largely caused by manufacturing enterprises. Environmental management accounting (EMA) is a strong management tool to improve an organization's financial and environmental performance, hence supporting businesses for sustainability. This study focused on examining the factors that influence the firms' intention to adopt EMA in Vietnam. The study used the theory of planned behavior and the technology acceptance model to develop an empirical model and hypotheses. Research data was collected through a survey of 330 businesses in 4 provinces in the North region. We analyzed the data using descriptive statistics, Anova test, Cronbach' s Alpha analysis, Exploratory factor analysis, and regression. The results showed that there are 6 significant factors driving EMA applying intention including environmental attitude, perceived benefits of EMA, subjective norms, coercion and social pressure, perceived control and barrier, and policy mix condition, in which coercion and social pressure was the strongest influencing factor. From there, the study makes some implication for government and business sectors aimed at encouraging the implementation of EMA in Vietnam. [ABSTRACT FROM AUTHOR]

Second-hand luxury goods feature both characteristics of luxury products like perceived value including social, emotional, and quality value, and second-hand goods like price-performance ratio. Enlarging the second-hand luxury market is of significance to protect the environment and save rare and valuable natural resources, and thus investigating the determinants of purchase intention is meaningful. From the perspective of the psychology of consumers, the influence of factors related to consumers (recycling awareness, subjective norms, attitudes, perceived behavioral control) and products (perceived value, price-performance ratio) on the intention to buy second-hand luxury goods is explored in this study through an online survey with Chinese consumers as a sample. The results are analyzed using the structural equation model (SEM) and show that consumers' attitudes, perceived behavioral control, and recycling awareness will promote the intention of purchasing second-hand luxury goods, and the perceived value and price-performance ratio of second-hand luxury goods also have a positive impact on the purchase intention. However, there is no significant relationship between subjective norms and purchase intention. In addition, this study also explores the interrelationship between constructs and draws corresponding conclusions, providing references for the subsequent development of the second-hand luxury market. [ABSTRACT FROM AUTHOR]

The digital economy (DE) has become a major breakthrough in promoting industrial upgrading and an important engine for high-quality economic growth. However, most studies have neglected the important driving effect of regional economic and social (RES) development on DE. In this paper, we discuss the mechanism of RES development promoting the development of DE, and establish a demand-driven regional DE development model to express the general idea. With the help of spatial analysis toolbox in ArcGIS software, the spatial development characteristics of DE in the Yangtze River Delta City Cluster (YRDCC) is explored. We find the imbalance of spatial development is very significant in YRDCC, no matter at the provincial level or city level. Quantitative analysis reveals that less than 1% likelihood that the imbalanced or clustered pattern of DE development in YRDCC could be the result of random chance. Geographically weighted regression (GWR) analysis with publicly available dataset of YRDCC indicates RES development significantly promotes the development of DE. [ABSTRACT FROM AUTHOR]

This study addresses the satisfaction of housing-related needs in single-person households across European countries. The primary objective is to assess the housing satisfaction of single-person households in European countries, specifically within the Visegrad Group. The study seeks to identify trends in housing conditions, create a ranking of countries based on these conditions, and categorize countries with similar levels of unmet housing needs. The study employs statistical measures and methods to achieve its objectives. Time series are constructed for European countries, and linear trends are analyzed to identify statistically significant changes in selected housing aspects from 2005 to 2022. Various research tasks, including ranking countries and grouping them based on housing conditions, are accomplished using established methods like linear ranking and Ward's cluster analysis. Key findings include significant variations in financial burdens related to housing costs, thermal comfort, environmental pollution, and safety issues across European countries. The study reveals both improvements and challenges in housing conditions from 2005 to 2022 in one-person households. For instance, financial stress due to housing costs decreased in some countries, while thermal comfort issues improved in several nations. The results also highlight the heterogeneity within the Visegrad Group. The study concludes that there is a need for targeted actions to address housing-related issues in single-person households. The findings underscore the importance of investments in building energy efficiency, initiatives for affordable housing construction, and environmental policies. The research emphasizes the impact of housing conditions on health, well-being, and overall community life, urging policymakers to consider these factors for holistic improvement in the housing sector. [ABSTRACT FROM AUTHOR]

Background: First metatarsophalangeal joint arthrodesis is a typical medical treatment performed in cases of arthritis or joint deformity. The gold standard for this procedure is arthrodesis stabilisation with the dorsally positioned plate. However, according to the authors' previous studies, medially positioned plate provides greater bending stiffness. It is worth to compare the mechanical conditions for bone formation in the fracture callus for both placements of the locking plate. Methods: Two finite element models of the first metatarsophalangeal joint with the dorsally and medially positioned plate were defined in the Abaqus software to simulate differentiation of the fracture callus. A simplified load application, i.e. one single step per each day and the diffusion of the mesenchymal stem cells into the fracture region were assumed in an iterative hardening process. The changes of the mesenchymal stem cells into different phenotypes during the callus stiffening were governed by the octahedral shear strain and interstitial fluid velocity according to Prendergast mechanoregulation theory. Basing on the obtained results the progress of the cartilage and bone tissues formation and their distribution within the callus were compared between two models. Findings: The obtained results suggest that after 6 weeks of simulation the healing progress is in general comparable for both plates. However, earlier closing of external callus was observed for the medially positioned plate which had greater vertical bending stiffness. This process enables faster internal callus hardening and promotes symmetrical bridging. [ABSTRACT FROM AUTHOR]

This research study aims to understand the application of Artificial Neural Networks (ANNs) to forecast the Self-Compacting Recycled Coarse Aggregate Concrete (SCRCAC) compressive strength. From different literature, 602 available data sets from SCRCAC mix designs are collected, and the data are rearranged, reconstructed, trained and tested for the ANN model development. The models were established using seven input variables: the mass of cementitious content, water, natural coarse aggregate content, natural fine aggregate content, recycled coarse aggregate content, chemical admixture and mineral admixture used in the SCRCAC mix designs. Two normalization techniques are used for data normalization to visualize the data distribution. For each normalization technique, three transfer functions are used for modelling. In total, six different types of models were run in MATLAB and used to estimate the 28th day SCRCAC compressive strength. Normalization technique 2 performs better than 1 and TANSING is the best transfer function. The best k-fold cross-validation fold is k = 7. The coefficient of determination for predicted and actual compressive strength is 0.78 for training and 0.86 for testing. The impact of the number of neurons and layers on the model was performed. Inputs from standards are used to forecast the 28th day compressive strength. Apart from ANN, Machine Learning (ML) techniques like random forest, extra trees, extreme boosting and light gradient boosting techniques are adopted to predict the 28th day compressive strength of SCRCAC. Compared to ML, ANN prediction shows better results in terms of sensitive analysis. The study also extended to determine 28th day compressive strength from experimental work and compared it with 28th day compressive strength from ANN best model. Standard and ANN mix designs have similar fresh and hardened properties. The average compressive strength from ANN model and experimental results are 39.067 and 38.36 MPa, respectively with correlation coefficient is 1. It appears that ANN can validly predict the compressive strength of concrete. [ABSTRACT FROM AUTHOR]

Hematopoietic stem cell transplantation is a common life-saving treatment for hematologic malignancies, though can lead to long-term functional impairment, fatigue, muscle atrophy, with decreased quality of life. Although traditional exercise has helped reduce these effects, it is inconsistently recommended and infrequently maintained, and most patients remain sedentary during and after treatment. There is need for alternative rehabilitation strategies, like neuromuscular electrical stimulation, that may be more amenable to the capabilities of hematopoietic stem cell transplant recipients. Patients receiving autologous HCT are being enroled in a randomized controlled trial with 1:1 (neuromuscular electrical stimulation:sham) design stratified by diagnosis and sex. Physical function, body composition, quality of life, and fatigue are assessed prior to hematopoietic stem cell transplant (prior to initiating preparatory treatment) and 24±5 days post hematopoietic stem cell transplant (Follow-up 1); physical function and quality of life are also assessed 6-months post hematopoietic stem cell transplant (Follow-up 2). The primary outcome is between-group difference in the 6-minute walk test change scores (Follow-up 1—Pre-transplant; final enrolment goal N = 23/group). We hypothesize that 1) neuromuscular electrical stimulation will attenuate hematopoietic stem cell transplant-induced adverse effects on physical function, muscle mass, quality of life, and fatigue compared to sham at Follow-up 1, and 2) Pre-transplant physical function will significantly predict fatigue and quality of life at Follow-up 2. We will also describe feasibility and acceptability of neuromuscular electrical stimulation during hematopoietic stem cell transplant. This proposal will improve rehabilitative patient care and quality of life by determining efficacy and feasibility of a currently underutilized therapeutic strategy aimed at maintaining daily function and reducing the impact of a potent and widely used cancer treatment. This trial is registered with clinicaltrials.gov (NCT04364256). [ABSTRACT FROM AUTHOR]

Globally, old urban neighborhood transformation has become a new urban sustainability focus for its significant contribution to the United Nation's Sustainable Development Goal 11. A regeneration-oriented approach is particularly important for Chinese cities with a dwindling land supply, obsoleting infrastructure, and inadequate standard of living. Using a mixed-methods approach informed by BREEAM Communities, we examined two Chinese initiatives—old urban neighborhood renewal (OUNR) and sponge city development (SCD)—through a comprehensive study of pilot project sustainability, policy emphases and gaps, and broader governance implications. We found that SCD's top-down technocratic management was highly efficient in enhancing neighborhood hydrological functions and physical environment. However, successes were undermined by the lack of climate considerations and civic participation. Besides actionable recommendations for applied scholarship and policymaking in China, we provide insight into how the OUNR/SCD initiatives may broadly inform worldwide urban regeneration practices through project and policy experimentations that build adaptive capacity. [ABSTRACT FROM AUTHOR]

Intellectual property is crucial for the development of firms. At the micro level, firm comprehensive intellectual property ability involves abilities about intellectual property creation, utilization, protection, and management. In order to develop the comprehensive intellectual property ability of firms, the China National Intellectual Property Administration began to implement the national intellectual property demonstration advantage firm (NIPDAF) policy in 2013. Based on this exogenous policy shock, using data from listed companies from 2011 to 2020 as the research sample, the time-varying DID method is used to test the impact of the NIPDAF policy intended to cultivate comprehensive intellectual property ability on firm productivity. The results show that after policy implementation, the total factor productivity of NIPDAFs increased by about 3.3% compared to the control group. This finding is robust after a series of tests. Furthermore, the NIPDAF policy promotes firm productivity through stimulating technology innovation, improving investment efficiency, and enhancing competitive advantage. In addition, the NIPDAF policy has a more significant incentive effect on the total factor productivity of non-state-owned enterprises, firms in the eastern region, and firms in patent intensive industries. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop and validate regression models to predict the chemical composition and ruminal degradation parameters of corn silage by near-infrared spectroscopy (NIR). Ninety-four samples were used to develop and validate the models to predict corn silage composition. A subset of 23 samples was used to develop and validate models to predict ruminal degradation parameters of corn silage. Wet chemistry methods were used to determine the composition values and ruminal degradation parameters of the corn silage samples. The dried and ground samples had their NIR spectra scanned using a poliSPECNIR 900–1700 model NIR sprectrophotometer (ITPhotonics S.r.l, Breganze, IT.). The models were developed using regression by partial least squares (PLS), and the ordered predictor selection (OPS) method was used. In general, the regression models obtained to predict the corn silage composition (P>0.05), except the model for organic matter (OM), adequately estimated the studied properties. It was not possible to develop prediction models for the potentially degradable fraction in the rumen of OM and crude protein and the degradation rate of OM. The regression models that could be obtained to predict the ruminal degradation parameters showed correlation coefficient of calibration between 0.530 and 0.985. The regression models developed to predict CS composition accurately estimated the CS composition, except the model for OM. The NIR has potential to be used by nutritionists as a rapid prediction tool for ruminal degradation parameters in the field. [ABSTRACT FROM AUTHOR]

An increasing number of measurement electrodes have been designed to satisfy the demand for high-resolution detection using galvanic logging technology in complex formations. The forward modeling response analysis of logging tools has important guiding significance in the design of galvanic logging tools. Based on a three-dimensional finite element numerical simulation method, we established a forward model of galvanic multi-electrodes in a complex formation. We also designed a symmetrical resistance network model of the formation with equivalent resistance between two electrodes. A symmetrical resistance network was derived using the balanced bridge method. The asymmetrical admittance matrix was extended to a symmetrical extended admittance matrix to realize a convenient calculation of the equivalent symmetrical resistance network in complex formations. Verification of the microcolumn-focused logging tool, with nine electrodes in a simulated standard well, and an evaluation of the degree of invasion in an actual oil well indicate that this calibration method can improve the measurement accuracy of galvanic logging instruments. [ABSTRACT FROM AUTHOR]

Anoxia in the mammalian brain leads to hyper-excitability and cell death; however, this cascade of events does not occur in the anoxia-tolerant brain of the western painted turtle, Chrysemys picta belli. The painted turtle has become an important anoxia-tolerant model to study brain, heart, and liver function in the absence of oxygen, but being anoxia-tolerant likely means that decapitation alone is not a suitable method of euthanasia. Many anesthetics have long-term effects on ion channels and are not appropriate for same day experimentation. Using whole-cell electrophysiological techniques, we examine the effects of the anesthetic, Alfaxalone, on pyramidal cell action potential amplitude, threshold, rise and decay time, width, frequency, whole cell conductance, and evoked GABAA receptors currents to determine if any of these characteristics are altered with the use of Alfaxalone for animal sedation. We find that Alfaxalone has no long-term impact on action potential parameters or whole-cell conductance. When acutely applied to naïve tissue, Alfaxalone did lengthen GABAA receptor current decay rates by 1.5-fold. Following whole-animal sedation with Alfaxalone, evoked whole cell GABAA receptor current decay rates displayed an increasing trend with 1 and 2 hours after brain sheet preparation, but showed no significant change after a 3-hour washout period. Therefore, we conclude that Alfaxalone is a suitable anesthetic for same day use in electrophysiological studies in western painted turtle brain tissue. [ABSTRACT FROM AUTHOR]

The text describes improvements made to the random forest model to enhance its distinctiveness in addressing tax risks within the real estate industry, thereby tackling issues related to tax losses. Firstly, the paper introduces the potential application of the random forest model in identifying tax risks. Subsequently, the experimental analysis focuses on the selection of indicators for tax risk. Finally, the paper develops and utilizes actual taxpayer data to test a risk identification model, confirming its effectiveness. The experimental results indicate that the model's output report includes basic taxpayer information, a summary of tax compliance risks, value-added tax refund situations, directions of suspicious items, and detailed information on common indicators. This paper comprehensively presents detailed taxpayer data, providing an intuitive understanding of tax-related risks. Additionally, the paper reveals the level of enterprise risk registration assessment, risk probability, risk value, and risk assessment ranking. Further analysis shows that enterprise risk points primarily exist in operating income, selling expenses, financial expenses, and total profit. Additionally, the results indicate significant differences between the model's judgment values and declared values, especially in the high-risk probability of total operating income and profit. This implies a significant underreporting issue concerning corporate income tax for real estate enterprises. Therefore, this paper contributes to enhancing the identification of tax risks for real estate enterprises. Using the optimized random forest model makes it possible to accurately assess enterprises' tax compliance risks and identify specific risk points. [ABSTRACT FROM AUTHOR]

Urban trees are at risk of stress due to heat island effects and the increased proportion of impervious areas surrounding them. Among pests of trees, insect borers such as bark beetles (Coleoptera: Curculionidae) and flatheaded borers (Coleoptera: Buprestidae) are some of the most devastating, frequently colonizing stressed trees. The objective of this study was to explore the effects of biotic and abiotic risk factors on borer attacks on trees in urban areas. In the summer of 2021 and 2022, this study was conducted in 50 urban sites in Atlanta and Augusta, Georgia (USA). Specific factors explored include overall tree health, differentially warmer maximum and minimum temperatures of sites compared to surrounding areas, tree species, and the percentage of impervious surface surrounding trees. Generalized linear models and zero-inflated models explored how these factors were related to damage from these borers. The number of borer attacks on trees increased with higher percentage impervious area. As the two most commonly encountered trees, Acer rubrum was found to be significantly more susceptible to attack from borers than Ulmus parvifolia. Unhealthy trees were more likely to experience more frequent and more severe borer attack. Trees with increased impervious cover around them as well as those with differentially warmer daily maximum and minimum temperatures relative to surrounding were more likely to be attacked. [ABSTRACT FROM AUTHOR]

Ensuring and improving the green value acquisition of manufacturing enterprises is one of the critical issues to be solved for manufacturing enterprises to achieve green value and high-quality development. Based on the theory of enterprise value acquisition and dynamic capability theory, we explain the "black box" of the relationship between green value creation and enterprise performance of manufacturing enterprises. The logical thread of "green value creation—profit model—enterprise performance" is constructed, and a green value acquisition mechanism model is proposed. Based on 263 questionnaires from Chinese manufacturing enterprises, the model is empirically tested using multiple regression analysis. The results show that green value creation has a positive impact on corporate performance, while the profit model plays a mediating role between green value creation and corporate performance. Green dynamic capability plays a positive moderating role between green value creation and corporate performance, while green active ability plays a positive moderating role between value creation and profit model. [ABSTRACT FROM AUTHOR]

People's preferences regarding their neighborhood environment can vary depending on their socioeconomic status and the cities where they live. This study aims to discern the relationship between neighborhood environment factors and single-family detached house sales by sale price and by central and noncentral cities. We analyzed sale prices in the Tokyo Metropolitan Area from 2015 to 2020. The neighborhood environment was assessed using flood/sediment risk and neighborhood walkability measured by net residential density, intersection density, and facility density (walking opportunity). Flood and sediment risk is a major concern that restricts the available land and is included as a negative aspect of the neighborhood environment, taking the topographic features into consideration. A comparison of the results showed that the preference for neighborhood walkability varies by socioeconomic status as well as by target cities. For most facility types, the number of walking opportunities within walking distance from houses was found to be positively related to the sale price of single-family detached houses in all quantiles. The relationship of house price with population and intersection density was found to vary depending on the price level, with a negative relationship with the sale price of relatively more expensive houses being exhibited. People who considered buying houses with relatively higher sale prices were found to devalue houses located in flood/sediment-hazardous areas more. However, it was also found that the negative relationship was slightly mitigated in the highest quantile of sale prices for houses in areas with a moderate flood risk (maximum flooding depth: 3–5 m). Plains near rivers with amenities offer high walkability but pose a flood risk, resulting in a trade-off between flood risk and neighborhood walkability. The findings suggest the use of indices representing diverse preferences in accordance with the target socioeconomic status when policymakers assess the neighborhood environment. [ABSTRACT FROM AUTHOR]

In this paper, we develop a DSGE model including heterogeneous households, introduce the financial friction of credit constraint mechanism, and study the impact of house price shocks on the consumption of heterogeneous household. Based on this, the CHFS data in 2011, 2013, 2015, 2017, and 2019 were used to test the marginal propensity to consume for housing wealth appreciation under different credit constraints. Results show that: Firstly, the financial accelerator mechanism plays an important role in the transmission of housing price shocks to household consumption. The looser the degree of credit constraints, the more obvious the rise in housing prices will be to the consumption expenditure of borrowing household. Secondly, the impact of housing wealth appreciation on household consumption under different credit constraints is heterogeneous. Among them, housing wealth appreciation has a significant positive impact on household consumption expenditure with multiple houses, credit cards, non-loan restrictions, while the marginal effect on the consumption expenditure of households with only one house, loan limited, and no credit cards decreases. Thirdly, for every 1% increase in the housing wealth appreciation, household consumption will increase significantly by 0.10–0.14%. [ABSTRACT FROM AUTHOR]

Both climate risk and race are factors that may affect municipal bond yields, yet each has received relatively limited empirical research attention. We analyzed > 712,000 municipal bonds representing nearly 2 trillion USD in par outstanding, focusing on credit spread or the difference between a debt issuer's interest cost to borrow and a benchmark "risk-free" municipal rate. The relationship between credit spread and physical climate risk is significant and slightly positive, yet the coefficient indicates no meaningful spread penalty for increased physical climate risk. We also find that racial composition (the percent of a community that is Black) explains a statistically significant and meaningful portion of municipal credit spreads, even after controlling for a variety of variables in domains such as geographic location of issuer, bond structure (e.g., bond maturity), credit rating, and non-race economic variables (e.g., per capita income). Assuming 4 trillion USD in annual outstanding par across the entire municipal market, and weighting each issuer by its percent Black, an estimated 19 basis point (bp) penalty for Black Americans sums to approximately 900 million USD annually in aggregate. Our combined findings indicate a systemic mispricing of risk in the municipal bond market, where race impacts the cost of capital, and climate does not. [ABSTRACT FROM AUTHOR]

This paper presents the design and construction of vacuum preloading incorporated with electroosmosis (VPE) engineering application for the treatment of soft soil on complex terrain for sluice foundation excavation in order to reduce the amount of cement used in construction. Monitoring was conducted during the VPE treatment and laboratory geotechnical tests were carried out once the treatment came to an end. Results show that the electrification mode has a significant influence on electric energy consumption. Stepped-up voltage helped in saving electric energy while electrode conversion consumed a lot of electric energy. The dispersion of soil parameters became larger after VPE treatment. The stability of physical parameters is better than the mechanical parameters, and the latter is better than the deformation parameters. Soil water content has a linear relationship with density and compression coefficient. The given linear fitting equations can help in simplifying the calculation and acquisition of these indexes. Although the mean values of the soil index parameters slightly improved, their coefficient of variation (COV) significantly increased. These locations with improved index parameters scattering in the construction site ensured that the subsequent construction tasks such as pit slope and excavation were successfully realized in this area. [ABSTRACT FROM AUTHOR]

As standards of material living continue to improve and urbanization advances, an increasing number of remote ethnic minority areas are becoming tourist destinations. Understanding tourists' perceptions on a large scale is thus crucial for the development of the regional tourism industry. However, traditional research methods suffer from high costs, small sample sizes, and low efficiency, making it difficult to measure the spatial perception of remote areas on a large scale. This study constructs a research framework for spatial perception measurement of remote ethnic minority areas by collecting reviews data from Ctrip using spatiotemporal data calculation and the Geodetector model. We considered Dali Prefecture as an empirical case and analyzed tourists' perceptions of the area's attractions, the spatial distribution of the attractions, and the process of change in the explanatory power of their influencing factors over an eight-year period (2014–2021). The results indicated that the most visited attractions were concentrated in Dali City. The perception of humanistic resources (attractions) with historical value was the highest, followed by natural resources. The high perception of attractions was influenced by the level of tourism development, traffic accessibility and attractiveness, and had an increasing influence on tourists' perceptions over time. Additionally, changes in the mode of transportation from road to high-speed rail played an important role in the selection of tourist attractions. Conversely, the tourists paid relatively less attention to humanistic resources (e.g., national cultural heritage protection units and traditional villages). Our study provides a basis for the measurement of spatial perception in remote minority areas and can be used as a reference for tourism development planning in Dali Prefecture, thus promoting the sustainable development of tourism in the area. [ABSTRACT FROM AUTHOR]

Understanding the spatial distribution of urban forest ecosystem services is essential for urban planners and managers to effectively manage cities and is an essential part of sustainable urban development. Mapping the spatial distribution of urban forest ecosystem services and improving the accuracy of its assessment scale will undoubtedly provide a more accurate reference basis for later management. In this study, we used the i-Tree Eco model and kriging interpolation to quantify and map urban forest ecosystem services and their spatial distribution in Zhengzhou, a city along the lower reaches of the Yellow River in China; analyzed the mapping errors and applicable conditions; and further explored the spatial differences using geographic probes. The i-Tree Eco model estimation results showed that the total carbon storage in the urban forest of Zhengzhou city was 75.7 tons, the annual carbon sequestration was 14.66 tons, the trees and shrubs in the urban area of Zhengzhou city could effectively avoid a total of 307.86 m3 of surface runoff per year, and trees and shrubs removed 411.8 kg/year of air pollution (O3, CO, NO2, PM2.5, PM10, and SO2). The spatial distribution of all urban forest ecosystem services showed significant heterogeneity, but the spatial evaluation precision of different factors varied. GDP and population data showed a negative correlation with ecosystem services, and ecosystem services were abundant in watershed and woodland areas. This study differs from traditional assessments based on regional data due to its improved spatial evaluation accuracy, and the results, discussion, and analysis not only help Zhengzhou's own urban development, but also provide a basis for the future construction and management of other cities, the Central Plains urban agglomeration, and the surrounding larger regions. This will contribute to the enhancement of ecosystem services and thus improve the ecological conditions of the region. This will also have a positive effect on the health of urban residents. [ABSTRACT FROM AUTHOR]

A numerical framework for interstitial fluid pressure imaging (IFPI) in biphasic materials is investigated based on three-dimensional nonlinear finite element poroelastic inversion. The objective is to reconstruct the time-harmonic pore-pressure field from tissue excitation in addition to the elastic parameters commonly associated with magnetic resonance elastography (MRE). The unknown pressure boundary conditions (PBCs) are estimated using the available full-volume displacement data from MRE. A subzone-based nonlinear inversion (NLI) technique is then used to update mechanical and hydrodynamical properties, given the appropriate subzone PBCs, by solving a pressure forward problem (PFP). The algorithm was evaluated on a single-inclusion phantom in which the elastic property and hydraulic conductivity images were recovered. Pressure field and material property estimates had spatial distributions reflecting their true counterparts in the phantom geometry with RMS errors around 20% for cases with 5% noise, but degraded significantly in both spatial distribution and property values for noise levels > 10%. When both shear moduli and hydraulic conductivity were estimated along with the pressure field, property value error rates were as high as 58%, 85% and 32% for the three quantities, respectively, and their spatial distributions were more distorted. Opportunities for improving the algorithm are discussed. [ABSTRACT FROM AUTHOR]

Neighborhood conditions influence people's health; sustaining healthy neighborhoods is a New York City (NYC) Health Department priority. Gentrification is characterized by rapid development in historically disinvested neighborhoods. The gentrification burden, including increased living expenses, and disrupted social networks, disproportionally impacts certain residents. To ultimately target health promotion interventions, we examined serious psychological distress time trends in gentrifying NYC neighborhoods to describe the association of gentrification and mental health overall and stratified by race and ethnicity. We categorized NYC neighborhoods as hypergentrifying, gentrifying, and not-gentrifying using a modified New York University Furman Center index. Neighborhoods with ≥100% rent growth were hypergentrifying; neighborhoods with greater than median and <100% rent growth were gentrifying; and neighborhoods with less than median rent growth were not-gentrifying. To temporally align neighborhood categorization closely with neighborhood-level measurement of serious psychological distress, data during 2000–2017 were used to classify neighborhood type. We calculated serious psychological distress prevalence among adult populations using data from 10 NYC Community Health Surveys during 2002–2015. Using joinpoint and survey-weighted logistic regression, we analyzed serious psychological distress prevalence time trends during 2002–2015 by gentrification level, stratified by race/ethnicity. Among 42 neighborhoods, 7 were hypergentrifying, 7 were gentrifying, and 28 were not gentrifying. In hypergentrifying neighborhoods, serious psychological distress prevalence decreased among White populations (8.1% to 2.3%, β = -0.77, P = 0.02) and was stable among Black (4.6% to 6.9%, β = -0.01, P = 0.95) and Latino populations (11.9% to 10.4%, β = -0.16, P = 0.31). As neighborhoods gentrified, different populations were affected differently. Serious psychological distress decreased among White populations in hypergentrifying neighborhoods, no similar reductions were observed among Black and Latino populations. This analysis highlights potential unequal mental health impacts that can be associated with gentrification-related neighborhood changes. Our findings will be used to target health promotion activities to strengthen community resilience and to ultimately guide urban development policies. [ABSTRACT FROM AUTHOR]

Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods. However, current medical NLP systems fall considerably short when faced with the task of logically interpreting clinical text. In this paper, we describe a framework inspired by mechanisms of human cognition in an attempt to jump the NLP performance curve. The design centers on a hierarchical semantic compositional model (HSCM), which provides an internal substrate for guiding the interpretation process. The paper describes insights from four key cognitive aspects: semantic memory, semantic composition, semantic activation, and hierarchical predictive coding. We discuss the design of a generative semantic model and an associated semantic parser used to transform a free-text sentence into a logical representation of its meaning. The paper discusses supportive and antagonistic arguments for the key features of the architecture as a long-term foundational framework. [ABSTRACT FROM AUTHOR]

Decarbonization policies are being stymied by political conflict. Local communities might oppose decarbonization infrastructure such as solar farms, mines, or transmission lines if they view these projects as imposing high costs on them in relation to their benefits. To decarbonize, the automobile industry seeks to shift from the internal combustion engine to electric vehicles, which require lithium-based rechargeable batteries. In the United States, to meet the increasing lithium demand through domestic sources, there is a proposal for a lithium mine in Thacker Pass, Nevada, which faces strong opposition from native nations and environmental groups. Using a representative sample of Nevada residents (n = 1,368), we explore if proximity to the Thacker Pass mine and to any Nevada mine influence public support for the proposed lithium mine. In addition, we test three frames that emphasize different benefits of the proposed mine: climate policy, national security, and local economic development. We find that respondents living closer to the Thacker Pass mine tend to be more supportive of the proposed lithium mine but exposure to existing Nevada mines does not affect public support. Among the treatment frames, only the national security frame increases public support. This suggests that to navigate local public opposition, the national security—domestic sourcing of key inputs required for decarbonization, aspect of decarbonization projects should be highlighted. [ABSTRACT FROM AUTHOR]

Residents of socioeconomically disadvantaged neighbourhoods have higher rates of overweight and obesity and chronic disease than their counterparts from advantaged neighbourhoods. This study assessed whether associations between neighbourhood disadvantage and measured body mass index (BMI) and waist circumference, are accounted for by obesogenic environments (i.e., residential distance to the Central Business District [CBD], supermarket availability, access to walkable destinations). The study used 2017–18 National Health Survey data for working-aged adults (aged ≥18 years, n = 9,367) residing in 3,454 neighbourhoods across Australia's state and territory capital cities. In five of eight cities (i.e., Sydney, Melbourne, Brisbane, Adelaide, and Perth) residents of disadvantaged neighbourhoods had significantly higher BMI and a larger waist circumference than residents of more advantaged areas. There was no association between neighbourhood disadvantage and body size in Hobart, Darwin, and Canberra. Associations between neighbourhood disadvantage and body size were partially explained by neighbourhood differences in distance to the CBD but not supermarket availability or walkable amenities. The results of this study point to the role of urban design and city planning as mechanisms for addressing social and economic inequities in Australia's capital cities, and as solutions to this country's overweight and obesity epidemic and associated rising rates of chronic disease. [ABSTRACT FROM AUTHOR]

Significance: Globally, cardiovascular disease (CVD) and cancer are leading causes of morbidity and mortality. While having different etiologies, CVD and cancer are linked by multiple shared risk factors, the presence of which exacerbate adverse outcomes for individuals with either disease. For both pathologies, factors such as poverty, lack of physical activity (PA), poor dietary intake, and climate change increase risk of adverse outcomes. Prior research has shown that greenspaces and other nature-based interventions (NBIs) contribute to improved health outcomes and climate change resilience. Objective: To summarize evidence on the impact of greenspaces or NBIs on cardiovascular health and/or cancer-related outcomes and identify knowledge gaps to inform future research. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 and Peer Review of Electronic Search Strategies (PRESS) guidelines, we searched five databases: Web of Science, Scopus, Medline, PsycINFO and GreenFile. Two blinded reviewers used Rayyan AI and a predefined criteria for article inclusion and exclusion. The risk of bias was assessed using a modified version of the Newcastle–Ottawa Scale (NOS). This review is registered with PROSPERO, ID # CRD42021231619. Results & discussion: Of 2565 articles retrieved, 31 articles met the inclusion criteria, and overall had a low risk of bias. 26 articles studied cardiovascular related outcomes and 5 studied cancer-related outcomes. Interventions were coded into 4 categories: forest bathing, green exercise, gardening, and nature viewing. Outcomes included blood pressure (BP), cancer-related quality of life (QoL) and (more infrequently) biomarkers of CVD risk. Descriptions of findings are presented as well as visual presentations of trends across the findings using RAW graphs. Overall studies included have a low risk of bias; and alluvial chart trends indicated that NBIs may have beneficial effects on CVD and cancer-related outcomes. Conclusions & implications: (1)Clinical implication: Healthcare providers should consider the promotion of nature-based programs to improve health outcomes. (2)Policy implication: There is a need for investment in equitable greenspaces to improve health outcomes and build climate resilient neighborhoods. (3)Research or academic implication: Research partnerships with community-based organizations for a comprehensive study of benefits associated with NBIs should be encouraged to reduce health disparities and ensure intergenerational health equity. There is a need for investigation of the mechanisms by which NBIs impact CVD and exploration of the role of CVD biological markers of inflammation among cancer survivors. [ABSTRACT FROM AUTHOR]

Background: The emerging information and communications technology (ICT) and society 5.0 have integrated digital innovation and imaginative creativity to solve social problems and create social value in an aging society. Especially in China, the penetration rate of internet use has become more prominent. Nevertheless, the role of internet use in the relationship between occupational status and depression remains unknown. The purpose of this study was to estimate how internet use moderates the relationship between occupational status and depression in a sample of older adults in China. Methods: A cross-sectional design was used to assess the relationship between occupational status, internet use and depression. This study employed data from the Chinese General Social Survey (CGSS) conducted in 2017. The full sample size of this study is 2,403. OLS regression was adopted to explore the correlation between occupational status and depression and the moderating role of internet use. Meanwhile, a heterogeneity analysis based on residence registration was implemented to explore the difference between rural and urban sample groups. Results: The findings suggested that higher occupational status was related to lower depression level. By playing an inhibitory moderating role between the association of occupational status and depression, internet use and occupational status formed a substituting effect. Meanwhile, the above moderating effect was only significant in urban group and insignificant in rural group. Besides, being male and having higher social class were significantly and negatively correlated with depression. Conclusion: This study began with the theory of social stratification and social mobility, added the theory of social capital, constructed an analytical framework of regulatory effect, put forward two basic assumptions, selected measurement indicators taking into account Chinese cultural factors, and conducted empirical tests using authoritative statistical software and national representative data, providing a new theoretical contribution to our understanding of the impact of occupational status and depression in developing countries. [ABSTRACT FROM AUTHOR]

Self-sovereign identity authentication protocol is an active research topic in the field of identity authentication and management. However, the current SSI authentication protocols pay little attention to privacy protection and the fine-grained access control. Therefore, a secure and decentralized SSI authentication protocol with privacy protection and fine-grained access control is proposed. Firstly, the formal model of SSI including the SDPP-SSI identity model and management model is presented. And then, based on the federated blockchain, the distributed identifier is used as a global identifier for users in the decentralized domain. Finally, the verifiable statement is encapsulated using a policy control signature supporting privacy protection to develop the user's access control for identity registration in the centralized domain. Compared with the related work (Lin 2018, Zhu 2018, Stokkink 2018, Hammudoglu 2017, Othman 2017, Abraham 2018, Guan 2019, Lin 2019) from controllability, security, flexibility, privacy protection, authentication and fine-grained access control, the proposed SSI authentication protocol not only meets controllability, authentication, and flexibility, but also supports privacy protection and fine-grained access control. [ABSTRACT FROM AUTHOR]

Management of nonindigenous species includes prevention, early detection and rapid response and control. Early detection and rapid response depend on prioritizing and monitoring sites at risk for arrival or secondary spread of nonindigenous species. Such monitoring efforts require sufficient biosecurity budgets to be effective and meet management or policy directives for reduced risk of introduction. Such consideration of risk reduction is rarely considered, however. Here, we review the concepts of acceptable level of risk (ALOR) and associated costs with respect to nonindigenous species and present a framework for aligning risk reduction priorities with available biosecurity resources. We conclude that available biosecurity resources may be insufficient to attain stated and desired risk reduction. This outcome highlights the need to consider policy and management directives when beginning a biosecurity program to determine the feasibility of risk reduction goals, given available resources. [ABSTRACT FROM AUTHOR]

Increase in the variety of development in urban context has made it more complicated and complex for the users of public spaces. Absence of sufficient information to read the surrounding causes psychological anxiousness leading to perceived danger or discomfort for the urbanites. Consequently, perceived safety and comfort of the users is distinctively low in urban contexts, creating neglected and underused spaces. Complexity is one of the information processing variables as per Kaplan and Kaplan's informational model which helps users to comprehend the surrounding environment. The streetscape plays a vital role in the daily movement patterns within the urban cities and is the transition boundary between the public and private realms. Visual complexity of these streets is a result of different configurations of elements within the urban areas. This research is conducted to ascertain the relationship between visual complexity levels of the streets with the perceived safety and comfort of the users. Shannon Diversity Index (SDI) and Fractal dimension analysis were conducted with 48 SVIs (Street View Images) selected within 1km radius of Colpetty junction, Colombo Sri Lanka covering all the possible compositions found within the context. The visual index data extraction had identified ten major components within the selected 48 SVIs. 78 subjective ranking responses for perceived safety, comfort (preference) and perceived complexity were collected from snowball sampling. Findings of the study revealed that perceived safety levels and preference scores for the SVIs are related to the Shannon Diversity Index calculation in an inverted 'U' shape where the highest and lowest SDI values are related with low preference scores and low safety levels. The SVIs with medium SDI values are perceived as the safest and most preferred by the users of urban streets of Colombo Sri Lanka. The SDI and fractal dimension values were significantly correlated with the perceived complexity scores of the users. The results of this study can be accommodated in the planning and designing of urban streetscapes of tropical climates for sustainable and friendly urban expansions. [ABSTRACT FROM AUTHOR]

A recurrent neural network (RNN) is a machine learning model that learns the relationship between elements of an input series, in addition to inferring a relationship between the data input to the model and target output. Memory augmentation allows the RNN to learn the interrelationships between elements of the input over a protracted length of the input series. Inspired by the success of stack augmented RNN (StackRNN) to generate strings for various applications, we present two memory augmented RNN-based architectures: the Neural Turing Machine (NTM) and the Differentiable Neural Computer (DNC) for the de-novo generation of small molecules. We trained a character-level convolutional neural network (CNN) to predict the properties of a generated string and compute a reward or loss in a deep reinforcement learning setup to bias the Generator to produce molecules with the desired property. Further, we compare the performance of these architectures to gain insight to their relative merits in terms of the validity and novelty of the generated molecules and the degree of property bias towards the computational generation of de-novo drugs. We also compare the performance of these architectures with simpler recurrent neural networks (Vanilla RNN, LSTM, and GRU) without an external memory component to explore the impact of augmented memory in the task of de-novo generation of small molecules. [ABSTRACT FROM AUTHOR]

In an effort to gauge the global pandemic's impact on social thoughts and behavior, it is important to answer the following questions: (1) What kinds of topics are individuals and groups vocalizing in relation to the pandemic? (2) Are there any noticeable topic trends and if so how do these topics change over time and in response to major events? In this paper, through the advanced Sequential Latent Dirichlet Allocation model, we identified twelve of the most popular topics present in a Twitter dataset collected over the period spanning April 3rd to April 13th, 2020 in the United States and discussed their growth and changes over time. These topics were both robust, in that they covered specific domains, not simply events, and dynamic, in that they were able to change over time in response to rising trends in our dataset. They spanned politics, healthcare, community, and the economy, and experienced macro-level growth over time, while also exhibiting micro-level changes in topic composition. Our approach differentiated itself in both scale and scope to study the emerging topics concerning COVID-19 at a scale that few works have been able to achieve. We contributed to the cross-sectional field of urban studies and big data. Whereas we are optimistic towards the future, we also understand that this is an unprecedented time that will have lasting impacts on individuals and society at large, impacting not only the economy or geo-politics, but human behavior and psychology. Therefore, in more ways than one, this research is just beginning to scratch the surface of what will be a concerted research effort into studying the history and repercussions of COVID-19. [ABSTRACT FROM AUTHOR]

Early data from the COVID-19 pandemic suggests that the disease has had a disproportionate impact on communities of color with higher infection and mortality rates within those communities. This study used demographic data from the 2018 US census estimates, mortality data from the Cook County Medical Examiner's office, and testing results from the Illinois Department of Public Health to perform bivariate and multivariate regression analyses to explore the role race plays in COVID-19 outcomes at the individual and community levels. We used the ZCTA Social Deprivation Index (SDI), a measure of ZCTA area level deprivation based on seven demographic characteristics to quantify the socio-economic variation in health outcomes and levels of disadvantage across ZCTAs. Principal findings showed that: 1) while Black individuals make up 22% of Cook County's population, they account for 28% of the county's COVID-19 related deaths; 2) the average age of death from COVID-19 is seven years younger for Non-White compared with White decedents; 3) residents of Minority ZCTA areas were 1.02 times as likely to test positive for COVID-19, (Incidence Rate Ratio (IRR) 1.02, [95% CI 0.95, 1.10]); 1.77 times as likely to die (IRR 1.77, [95% CI 1.17, 2.66]); and were 1.15 times as likely to be tested (IRR 1.15, [95% CI 0.99, 1.33]). There are notable differences in COVID-19 related outcomes between racial and ethnic groups at individual and community levels. This study illustrates the health disparities and underlying systemic inequalities experienced by communities of color. [ABSTRACT FROM AUTHOR]

Chinese commercial pedestrian streets have developed rapidly in recent years. However, people's preferences were not sufficiently considered and reflected in the outdoor space and landscape design. With the outdoor landscapes along commercial pedestrian streets in the region south of the Five Ridges as the research objects, this study revealed the public's different preference evaluations of the landscapes under the reciprocal effects of street characteristics. The main results were as follows: (a) When arcade spaces were available, people prefer streets with taller trees and a lower planting density (50 plants/km or less). Conversely, they preferred streets with relatively low trees (3–6 m), a higher planting density (100–200 plants/km) and two or more vertical layers of plants. People did not like the way that plants are lined in the middle of a street. (b) When there were only one or two types of signage hanging, people preferred streets with a moderate planting density (50–100 plants/km); and there were three or more types of signage hanging, people preferred the plants with low linear density (50 plants/km or less) and that were arranged along one or two sides of the street. (c) When benches were available, people preferred streets with plants on one or both sides, fewer plant colours (one or two kind of colours) and better plant growth status. Specifically, the richer the vertical structure and the bigger number of colours were, the higher the preference score. This study provided design schemes to enhance the visual quality of landscapes by improving landscape characteristics in similar outdoor spaces. [ABSTRACT FROM AUTHOR]

In this study we examined three correlates of personal wealth-financial capability, buying impulsiveness, and attitudes to money in a large UK adult sample (N = 90,184). We were interested in how these psychological variables related to personal wealth controlling for well-established demographic correlates: age, education, gender, and household income. We drew on three personal wealth variables based on savings and investments, property wealth and personal items. Using correlational and regression analysis we tested three specific hypotheses which each received support. Our variables accounted for around half the variance with respect to property value, and two thirds with respect to investments. The hierarchical regression onto the savings and investment factor showed two thirds of the variance was accounted for: the demographic variables accounted for 27% of the variance, money attitudes an additional 14%; financial capability an additional 24% and buying impulsivity no additional variance. Age, income, and planning ahead were the most powerful and consistent predictors of wealth variables, with associating money with security as an important predictor for savings and investments. Implications for helping improve financial literacy and capability are noted. Limitations are acknowledged.

Chromium toxicity is a major problem in agricultural soils that negatively affects a plant's metabolic activities. It reduces biochemical and antioxidant defence system's activities. In search of the solution to this problem a two-year pot experiment (completely randomized design with three replications), in three genetically different varieties of sorghum (SSG 59–3, HJ 513 and HJ 541) under Cr toxicity (2 and 4 ppm) was conducted to determine the effect of glycine betaine (50 and 100mM) and Arbuscular mycorrhizal fungi (AMF) on the antioxidant system (enzymes viz. superoxide dismutase, ascorbate peroxidase, catalase, glutathione reductase, peroxidase and metabolites viz. glutathione, ascorbate, proline, β-carotene) along with Cr accumulation and indices of oxidative stress parameters (polyphenol oxidase, hydrogen peroxide and malondialdehyde) at two growth stages (vegetative and grain filling). According to results; Cr stress (2 & 4 ppm) increased its accumulation and indices of oxidative stresses significantly (p≤0.05) in all varieties of sorghum at both growth stages. However, soil application of glycine betaine (GB) and AMF decreased Cr accumulation and indices of oxidative stress by increasing antioxidant enzymes and metabolites activities at both growth stages in all varieties. The combination of 100mM GB with AMF was observed most significant (p≤0.05) in decreasing oxidative stress and improved the antioxidant system's activities. The SSG 59–3 cultivar showed the lowest Cr accumulation (1.60 and 8.61 ppm), indices of oxidative stress and highest antioxidant system's activity among these three cultivars at both growth stages. Thus, SSG 59–3 was found most tolerant cultivars followed by HJ 513 and then HJ 541. These findings suggest that both GB and AMF, either individually or combined can play a positive role to reduce oxidative stress and increased antioxidant attributes under Cr toxicity in sorghum. [ABSTRACT FROM AUTHOR]

Background: This study develops an ontology of Psychological First Aid (PFA) by extracting relevant knowledge from a review of PFA literature. Materials and methods: This study was conducted using the PFA ontology development 101 method. This review processes previously-developed PFA studies by consulting Google Scholar, CINHL, PUBMED, and MEDLINE. Protege 5.0 program was used to integrate with ontology development. The developed PFA ontology consisted of eight super classes: Action agenda, Assessment, Concrete method, Disaster type, Disaster disposition, Purpose, Qualification and Skill, Reaction. In total, 166 terms were collected. Results: The eight super classes were divided into 72 classes and 64 subclasses. The composition yielded in a total of 166 axioms (85 logical axioms; 81 declaration axioms). Conclusions: This study provides basic data to guide development and composition of PFA arbitration programs. [ABSTRACT FROM AUTHOR]