Value In Environment Research Articles

The effects of physician’s brand positioning on diagnostic dispensing continuity and cross-provincial healthcare flow: Evidence from an online traditional Chinese medicine community

Given the dilemma of inheriting and protecting Traditional Chinese Medicine (TCM), online personal branding can be an effective solution for TCM physicians to promote themselves and provide patients with better choices. However, there is a lack of understanding of the antecedents and consequences of TCM physicians’ brand value on online traditional Chinese medicine community (OTCMC). This paper empirically investigates the influences of physician brand positioning on brand value and added value, and examines the moderating effects of service quality and TCM regional disparity. Our results show that physicians on OTCMC could increase their brand value and added value by improving professional level, service price, and integration degree of four diagnostic methods. Moreover, service quality and TCM regional disparity positively moderate these effects. Our research contributes to the OTCMC literature and provides practical implications for TCM physicians to create brand value in online environment.

Histones Methyltransferase NSD3 Inhibits Lung Adenocarcinoma Glycolysis Through Interacting with PPP1CB to Decrease STAT3 Signaling Pathway.

Histones methyltransferase NSD3 targeting H3K36 is frequently disordered and mutant in various cancers, while the function of NSD3 during cancer initiation and progression remains unclear. In this study, it is proved that downregulated level of NSD3 is linked to clinical features and poor survival in lung adenocarcinoma. In vivo, NSD3 inhibited the proliferation, immigration, and invasion ability of lung adenocarcinoma. Meanwhile, NSD3 suppressed glycolysis by inhibiting HK2 translation, transcription, glucose uptake, and lactate production in lung adenocarcinoma. Mechanistically, as an intermediary, NSD3 binds to PPP1CB and p-STAT3 in protein levels, thus forming a trimer to dephosphorylate the level of p-STAT3 by PPP1CB, leading to the suppression of HK2 transcription. Interestingly, the phosphorylation function of PPP1CB is related to the concentration of carbon dioxide and pH value in the culture environment. Together, this study revealed the critical non-epigenetic role of NSD3 in the regulation of STAT3-dependent glycolysis, providing a piece of compelling evidence for targeting the NSD3/PPP1CB/p-STAT3 in lung adenocarcinoma.

The impact of the nurse practice environment, workload, and professional support on job outcomes and standards of care at primary health care clinics in South Africa: A structural equation model approach

BackgroundThere is substantial evidence on the associations between a positive nurse practice environment and improved nurse and patient outcomes, as well as the factors that mediate these associations, in high-income countries and in hospital settings. The knowledge gaps in African and primary health care settings motivated this empirical study. ObjectiveThe objective of this study was to examine the impact of the dimensions of the nurse practice environment, specifically human resource management, foundations for nursing care, and participation in clinic affairs, on job outcomes and standards of care. DesignA cross-sectional study was conducted between November 2021 and June 2022. Setting180 primary health care clinics in two South African provinces of Gauteng and North West. Participants665 nurses of all categories. MethodsA causal model was developed with pathways between the nurse practice environment dimensions and the outcomes of job satisfaction, intention to leave, and standards of care. A set of standardised instruments was used to measure the study variables. Using structural equation modelling, workload and professional support were tested as potential mediators between the nurse practice environment and the outcome variables. ResultsThe nurses scored the domain of foundations for nursing care 71.2 out of 100 on average, indicating high agreement, while the mean scores for nurses’ participation in clinic affairs and human resources management were lower at 68.0 and 61.7 respectively. Although nurses expressed moderate satisfaction with professional support (67.7), they were less satisfied with their workload (52.2). The mean score of overall job satisfaction was moderate (58.9), with 53.8 % of the nurses reporting that they intended leaving the clinic where they were working. Thirty-six percent intended leaving the nursing profession, indicating low intention to stay. The final mediation model was judged to fit the data adequately based on goodness-of-fit indices, confirming that workload and professional support had a mediating role between the nurse practice environment dimensions of interest and both nurses’ job outcomes and standards of care. ConclusionsWe have highlighted the value of supportive practice environments, effective workload management, and enhanced professional support in improving nurses’ job outcomes and satisfaction with standards of care. Improving nurses’ practice environments at primary health care level may have a wide-ranging impact on the performance of the health system. Therefore, primary health care facility managers should ensure that workload is distributed equitably, professional support for nurses is enhanced, and the overall work environment is improved.

TCellSI: A novel method for T cell state assessment and its applications in immune environment prediction.

T cell is an indispensable component of the immune system and its multifaceted functions are shaped by the distinct T cell types and their various states. Although multiple computational models exist for predicting the abundance of diverse T cell types, tools for assessing their states to characterize their degree of resting, activation, and suppression are lacking. To address this gap, a robust and nuanced scoring tool called T cell state identifier (TCellSI) leveraging Mann-Whitney U statistics is established. The TCellSI methodology enables the evaluation of eight distinct T cell states-Quiescence, Regulating, Proliferation, Helper, Cytotoxicity, Progenitor exhaustion, Terminal exhaustion, and Senescence-from transcriptome data, providing T cell state scores (TCSS) for samples through specific marker gene sets and a compiled reference spectrum. Validated against sizeable pseudo-bulk and actual bulk RNA-seq data across a range of T cell types, TCellSI not only accurately characterizes T cell states but also surpasses existing well-discovered signatures in reflecting the nature of T cells. Significantly, the tool demonstrates predictive value in the immune environment, correlating T cell states with patient prognosis and responses to immunotherapy. For better utilization, the TCellSI is readily accessible through user-friendly R package and web server (https://guolab.wchscu.cn/TCellSI/). By offering insights into personalized cancer therapies, TCellSI has the potential to improve treatment outcomes and efficacy.

The influence of utilitarian and hedonic value on customer satisfaction and repurchase intention in e-commerce

This research aims to examine factors affecting consumers’ shopping value in the online environment, which, in turn, lead to customer satisfaction and repurchase intention based on an integrated model of the cognition-affect-behavior model and personal shopping value. An online questionnaire was administered to 202 consumers of e-commerce purchases in Vietnam. Partial least square structural equation modelling (PLS-SEM) was utilized for data analysis. Results show that system quality and perceived price fairness positively affect hedonic shopping value, while information quality and service quality positively affect utilitarian shopping value. These shopping values collectively nurture customer satisfaction, resulting in repurchase intention. This study contributes to the literature on online consumer behavior by examining both the antecedents and outcomes of consumer shopping values in e-commerce. The findings can help e-commerce enterprises optimize marketing strategies to improve consumer shopping experiences and repurchase intention.

Development and validation of sex-linked molecular markers for rapid and accurate identification of male and female Hippophae tibetana plants

Hippophae tibetana, one of the highest-altitude woody plants endemic to the Qinghai-Tibet Plateau, primarily thrives on riverbanks formed by glacial meltwater. As a dioecious species, it demonstrates significant ecological and economic value in extreme alpine environments. However, the lack of sex identification techniques outside of the flowering period severely limits research on sex ratio, differentiation, and breeding. There is an urgent need to develop effective sex-linked molecular markers that are independent of developmental stages, but current research in this area remains limited. This study developed a set of accurate sex-linked molecular markers for the rapid identification of male and female individuals of H. tibetana. Through whole-genome resequencing of 32 sexually differentiated H. tibetana samples, this study offers strong evidence supporting chromosome 2 as the sex chromosome and successfully identified key loci related to sex determination on this chromosome. Utilizing these loci, we, for the first time, developed three reliable pairs of sex-specific molecular markers, which exhibited high accuracy during validation across various geographic populations, offering an effective tool for the sex identification of H. tibetana. Additionally, this study lays the groundwork for further research into the mechanisms of sex determination and the evolution of sex chromosomes in H. tibetana.

Home ranges, habitat selection, and energy expenditure of Strix varia (Barred Owls): Understanding the full diel cycle matters for enhancing urban landscapes

Abstract We integrated GPS and accelerometer data to examine habitat selection and energy expenditure patterns across the diel cycle in Strix varia (Barred Owls), addressing a critical gap in wildlife research that often overlooks activity during the “inactive” phase. Owls in Baton Rouge, Louisiana, selected forests with tall canopies and open understories, particularly in affluent neighborhoods, supporting the “luxury effect” in urban biodiversity. Nocturnal home ranges were larger (31.8 ha) compared to diurnal home ranges (8.9 ha), indicating broader habitat use at night. The total area of preferred nocturnal habitat was 33% of the Baton Rouge study area, whereas preferred diurnal habitat comprised only 5%. Energy expenditure was inversely related to preference in nocturnal home ranges but increased with preference in diurnal home ranges. Our models were validated using independent data from Clemson, South Carolina, supporting the robustness of our analysis and revealing generalities in owl habitat selection across these regions. This research contributes to a deeper understanding of urban ecology, highlighting habitat components preferred by owls and possibly other forest-dwelling species. It emphasizes the difference in nocturnal and diurnal home range sizes, the scarcity of daytime refuges for S. varia in urban landscapes, and the variation in energy expenditure in preferred habitats. Our findings advocate for urban designs that accommodate wildlife activity throughout the day and night, and highlight the positive correlation between preferred owl habitat and affluent neighborhoods, underscoring the need for equitable distribution of green spaces to foster biodiversity across socioeconomic gradients. These insights will help develop strategies to enhance the ecological value of urban environments and the conservation of S. varia and associated forest-dwelling species in rapidly urbanizing areas.

The Value and Evaluation of Educational Environments: The Case of Lithuanian General Education Schools

The Value and Evaluation of Educational Environments: The Case of Lithuanian General Education Schools

Construction of digital twin workshop integrated with edge computing and deep learning

Abstract This study addresses the challenges of real-time data synchronization and big data processing in the construction of digital twin workshops under the background of intelligent manufacturing. A solution that integrates edge computing with deep learning technology is proposed. Through a multi-layered, modular framework structure, this solution achieves real-time synchronous mapping and interaction between physical workshops and virtual workshops, effectively improving production efficiency, reducing maintenance costs, and ensuring product quality. The edge computing layer in the research is responsible for preprocessing heterogeneous data from multiple sources and making rapid response decisions. Simultaneously, deep learning algorithms are employed to conduct in-depth analysis, forecasting, and optimization of the production process. Case studies demonstrate that this solution can significantly improve equipment utilization and optimize workpiece scheduling, validating its application value in actual manufacturing environments.

Mismatch Resistance and the Problem of Evolutionary Novelty

AbstractIn evolutionary medicine and other related fields, the concept of evolutionary mismatch is used to explain phenomena whereby traits reduce in adaptive value and eventually become maladaptive as the environment changes. This article argues that there is a similar problem of persistent adaptivity—what has been called the problem of evolutionary novelty—and it introduces the concept of mismatch resistance in order to explain phenomena whereby traits retain their adaptive value in novel environments that are radically different from the organisms’ environment of evolutionary adaptedness (EEA). The possible role of variability selection in the evolution of mismatch-resistant traits is discussed, and it is suggested that mismatch resistance provides a useful tool for making progress on certain issues related to evolutionary theory, such as the modularity debate, cases of adaptivity outside of organisms’ ancestral environment, and the viability of naturalism as an overarching philosophical framework for understanding the natural world.

The Effect of Employee Recruitment and Selection, Management Support, and Work-Life Balance on Individual Performance and Employee Well-Being in the Manufacturing Industry in West Java

This quantitative study explores the relationship between hiring and selection processes, work-life balance, management support, individual performance, and employee well-being in West Java's manufacturing sector. Using a systematic questionnaire, 200 employees from different manufacturing companies provided data for the study. To investigate the correlations between the variables, the analysis used partial least squares (PLS) in conjunction with structural equation modeling (SEM). The findings show a strong positive correlation between management support, work-life balance, employee well-being, individual performance, and recruitment and selection procedures. Additionally, mediation analysis emphasizes how work-life balance and management support mediate the relationships between hiring and selection procedures and employee outcomes. These results highlight the value of supportive work environments and strategic HRM techniques in raising worker performance and well-being in West Java's manufacturing sector.

A Data Matrix Code Recognition Method Based on L-Shaped Dashed Edge Localization Using Central Prior.

The recognition of data matrix (DM) codes plays a crucial role in industrial production. Significant progress has been made with existing methods. However, for low-quality images with protrusions and interruptions on the L-shaped solid edge (finder pattern) and the dashed edge (timing pattern) of DM codes in industrial production environments, the recognition accuracy rate of existing methods sharply declines due to a lack of consideration for these interference issues. Therefore, ensuring recognition accuracy in the presence of these interference issues is a highly challenging task. To address such interference issues, unlike most existing methods focused on locating the L-shaped solid edge for DM code recognition, we in this paper propose a novel DM code recognition method based on locating the L-shaped dashed edge by incorporating the prior information of the center of the DM code. Specifically, we first use a deep learning-based object detection method to obtain the center of the DM code. Next, to enhance the accuracy of L-shaped dashed edge localization, we design a two-level screening strategy that combines the general constraints and central constraints. The central constraints fully exploit the prior information of the center of the DM code. Finally, we employ libdmtx to decode the content from the precise position image of the DM code. The image is generated by using the L-shaped dashed edge. Experimental results on various types of DM code datasets demonstrate that the proposed method outperforms the compared methods in terms of recognition accuracy rate and time consumption, thus holding significant practical value in an industrial production environment.

Exploring job satisfaction’s impact on turnover tendency among employees in Kosova’s microfinance institutions

Purpose The purpose of this paper is to delve into the intricate link between job satisfaction and employees’ turnover intentions. To accomplish this, a detailed structural model was constructed, incorporating five essential constructs: job satisfaction, turnover intention, satisfaction with financial factors, satisfaction with non-financial factors and external factors. Design/methodology/approach The research used a questionnaire with 28 items based on established tools, focusing on five different constructs. The model’s validation involved applying structural equation modelling to 147 non-managerial employees in microfinance institutions. Findings The findings reveal a significant negative correlation between job satisfaction and turnover intention. Satisfaction with financial factors significantly outweighs satisfaction with non-financial factors in shaping job satisfaction. In addition, the impact of external factors on turnover intention was observed to be minimal and inconsequential. Research limitations/implications This review highlights the importance of investigating the moderating factors in the job satisfaction–turnover relationship, distinguishing between types of satisfaction and conducting longitudinal studies across diverse contexts. It notably presents a diverse range of recent findings in this field, emphasising the breadth of the results that have emerged in this area of research. Practical implications Understanding job satisfaction and turnover intention is crucial for microfinance institutions. By prioritising efforts to enhance job satisfaction through improved financial offerings and non-financial factors like a supportive work environment and opportunities for growth, organisations can effectively mitigate turnover rates and foster success. Social implications The study underscores the societal value of supportive work environments beyond just benefits and career opportunities. By understanding the external influences on employee satisfaction, organisations can contribute to building more decent workplaces and promote social well-being, while advocating for social considerations in organisational practices. Originality/value This paper uses a novel integrated model comprising five distinct constructs not previously used together. It stands among the pioneering works that not only elucidate the correlation between job satisfaction and turnover intention but also delineate the constituents of job satisfaction itself.

Analysis of the Development of Drones and their Application in the Logistics Field

This study discusses the evolution of drone technology and its application in the logistics field, analyzes its impact on the logistics industry, and predicts future development trends. Through case study and technology comparison, this article thoroughly researches the technological development, classification, characteristics of drones, and their application in the logistics field. The application of drones in the logistics field has gradually become widespread, and it shows significant advantages in the aspects of aerial transportation of cargo, inventory management of warehouses, and planning of distribution routes. The results show that drone not only improves logistics efficiency and reduce cost but also have a unique value in special environments and emergencies.

FeNi alloys with controllable composition for tunable magnetic properties and broadband absorption

For the further enhancement to the microwave absorbing capabilities of magnetic dendritic materials, this work has successfully prepared dendritic FexNi1-x (x = 0.5, 0.33, 0.25, 0.2) alloys through a facile electrodeposition method. FexNi1-x alloy composition can be easily tuned by changing iron ion concentration in the electrolyte. We investigate the effects of alloy composition on the crystal structure and morphology whereby we intrinsically analyzes the magnetic characteristics and microwave absorbing performance of FexNi1-x alloys. Particularly, Fe0.25Ni0.75 alloy demonstrates the strongest microwave absorption intensity, achieving the minimum reflection loss (RLmin) of −59.02 dB at 4.96 GHz. Comprehensively, Fe0.33Ni0.67 alloy (RLmin = −49.42 dB, d = 1.68 mm) attains optimal microwave absorption performance when combining the perspectives of absorber thickness, RLmin and effective bandwidth (RL<-20 dB). RL values of Fe0.33Ni0.67 alloy at the thickness of 1.4–2.5 mm, exceed −20 dB over a wide frequency range, covering almost the whole X and Ku band (8–18 GHz). Such exceptional microwave absorption performance is attributed to the unique dendritic structure which conduces to the multiple scattering of electromagnetic microwave, hence improving impedance matching and promoting energy dissipation. In addition, the practicability of FexNi1-x alloys is further confirmed by simulating the RCS value in the far field environment.

Experimental study on inhibition of coal spontaneous combustion by carbon dioxide and nitrogen

ABSTRACT Injecting CO2 and N2 to reduce the concentration of O2 in the air is a commonly used measure to prevent coal spontaneous combustion (CSC). To study the difference in inhibitory effects of CO2 and N2 on coal oxidation, experiments in this study were conducted using a setup of self-developed gas-bath coal oxidation for low temperatures. The oxidation process of the coal-oxygen system was then analyzed using reaction kinetics. Two different coal samples were tested in experiments under two inert gas environments, i.e. CO2 and N2 with various O2 concentrations, respectively. The changes in O2 and CO concentrations were measured during the oxidation process. By studying the standard oxygen consumption rate (SOCR) and the apparent activation energy of the coal-oxygen reaction system, inhibitory effects of CO2 and N2 on CSC were analyzed and compared. The results showed that the SOCR of the same coal sample remained consistent and independent of the O2 concentration within the same inert gas environment although under different O2 levels. In both CO2-O2 and N2-O2 environments, the SOCR of the coal sample exhibits exponential growth with temperature. The SOCR was found to have a functional connection with temperature, it can be represented as y = a ⋅ e bT , and the R 2 (determination coefficients) of the fitting formulas are all greater than 0.94. In the correlation, the inert gas environment has minimal impact on coefficient “b,” while in the CO2-O2 environment, reducing the value of coefficient “a” can effectively lower the coal sample’s SOCR. The GBMK sample and YMWK sample have an “a” value that is 20% of the value in the N2-O2 environment when oxidizing in the CO2-O2 environment. The SOCR in the CO2-O2 environment showed a decrement of between 26.0% and 52.1% when compared to that in the N2-O2 environment, whereas the activation energy showed an increment between 1.4% and 18.6%. The findings in this work provide an in-depth understanding of the prevention of CSC in the gob for risk mitigation.

Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis.

In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established techniques, FreeSurfer-Aseg and FSL-FIRST, using three-dimensional T1-weighted MRI scans (n = 1447) procured from public databases. Our evaluation focused on the accuracy and reproducibility of these tools in estimating hippocampal volume. The findings suggest that both SynthSeg and TigerBx are on a par with Aseg and FIRST in terms of segmentation accuracy and reproducibility, but offer a significant advantage in processing speed, generating results in less than 1 min compared with several minutes to hours for the latter tools. In terms of Alzheimer's disease classification based on the hippocampal atrophy rate, SynthSeg and TigerBx exhibited superior performance. In conclusion, we evaluated the capabilities of two deep learning-based segmentation techniques. The results underscore their potential value in clinical and research environments, particularly when investigating neurological conditions associated with hippocampal structures.

Analyzing the added value of common data environments for organizational and project performance of BIM-based projects

Analyzing the added value of common data environments for organizational and project performance of BIM-based projects

Greater Expectations: An Appreciative Inquiry into How UK Home-Educating Families Support Their Children’s Learning

Elective home education is a significant aspect of the UK educational system, yet dedicated research on this topic is limited. This study, employing Appreciative Inquiry, explored the best practices perceived by 90 UK home-educating parents. It uncovered diverse strategies, emphasising the importance of resources such as technology, curricula, and collaborative efforts within home education co-operatives. Parents stressed the value of flexible learning environments and strong family commitment, envisioning a future with an enhanced home learning atmosphere and government and school support. They recommended concrete guidance for prospective home-educating parents, focusing on comprehensive child development. Ultimately, families aspired to shape a future for home education that prioritises enriched learning environments, broader societal recognition, and practical support for those embarking on the home education journey. The study’s findings have implications for children’s development, facilitating collaboration between homes and schools, as well as partnerships between families and educators.

Predicting nonradiative decay barrier of BODIPY dye in polar environment by applying ONIOM multiscale method

Fluorescent molecular sensors are widely used in biological research. They allow straightforward viscosity, temperature or polarity measurements at the microscopic level, including live cells. Maps of desired physical properties can be obtained by applying fluorescence lifetime imaging microscopy (FLIM) to cells. One of the most important properties of a cell is viscosity, as it affects other parameters, such as the rate of biochemical reactions and particle diffusion. Boron-dipyrromethene (BODIPY) compounds are widely used for viscosity measurements, but current variants have the undesirable sensitivity to polarity, and more suitable alternatives are being sought using theoretical computations. The polarizable continuum model (PCM) used in previous studies did not adequately take into account the influence of the polar environment when calculating the BODIPY activation energy associated with polarity sensitivity. After applying the multilayer ONIOM method in polar and non-polar environments, the calculated maximum wavelengths of the fluorescence spectra of the 8PhBODIPY compound were closer to the experimental results compared to PCM. The activation energy was also calculated, its value in polar and non-polar environments qualitatively corresponded to the experimental results, and the quantitative agreement was reached using the empirical correction.