Industry 4.0 (I4.0) epitomizes the nexus of technological evolution and manufacturing process enhancements, underpinned by four critical pillars: Cyber-Physical Systems (CPS), Digital Twins (DT), the Industrial Internet of Things (IIoT), and Cloud Computing (CC). Through the lens of the German Reference Architectural Model Industrie (RAMI) 4.0, these components are integral to fostering Smart Manufacturing (SM) practices. In conjunction, the Asset Administration Shell (AAS) facilitates seamless inter-company communication and enables adaptability to fluctuating market demands. This paper delves into the structural intricacies of AAS and SM within the RAMI 4.0 framework, unveiling three distinct implementation strategies. Furthermore, it meticulously scrutinizes challenges that hinder the full realization of I4.0 potential, such as interoperability, security concerns, and standardized communication protocols. By examining these models and identifying current barriers, the study illuminates pathways for future research, particularly in enhancing the integration of AAS and SM systems, ensuring robust security measures, and advocating for the development of universal standards. This exploration aims to contribute to the ongoing discourse on I4.0, proposing avenues for advancing manufacturing technologies and operational frameworks in alignment with the principles of RAMI 4.0.

This review will explore the four major pillars required for design and development of an saRNA vaccine: antigen design, vector design, non-viral delivery systems, and manufacturing (both saRNA and lipid nanoparticles (LNP)). In will report on the major innovations, preclinical and clinical data reported in the last five years and will discuss future prospects.

Rapid urbanization has profoundly impacted regional ecosystem services. However, few studies have comprehensively examined the spatiotemporal relationship between multi-dimensional urbanization processes and ecosystem services. This study investigated the spatiotemporal dynamics of urbanization and ecosystem services value (ESV) in the Yangtze River Delta (YRD) region, China, from 2010 to 2020. We measured urbanization levels from two dimensions: Urbanization I (demographic, economic, and land urbanization) and Urbanization II (social and cultural urbanization). The ESV was quantified using the equivalent factor method. The results showed that: (1) The level of Urbanization I increased steadily, while Urbanization II, despite a lower level, exhibited a faster growth rate, especially after 2017; (2) The total ESV declined, with regulating services decreasing the most. The spatial distribution of ESV showed significant heterogeneity; (3) Urbanization had a significant negative correlation with ESV, with Urbanization I exerting a greater negative impact than Urbanization II; (4) The eastern region was dominated by high urbanization-low ESV clusters, while the western region was characterized by low urbanization-high ESV clusters. The findings provide important implications for regional sustainable development and can serve as a reference for related studies in other rapidly urbanizing areas around the world.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

Precision metagenomic approaches using Oxford Nanopore Technology (ONT) sequencing has been shown to allow recovery of complete genomes of Escherichia coli O157:H7 from overnight enrichments of agricultural waters. This study tests the applicability of a similar approach for Cronobacter genome recovery from powdered infant formula (PIF) overnight enrichments, where Cronobacter typically dominates the overall microbiome (>90%). In this study, we aimed to test whether using ONT sequencing of overnight PIF enrichments could recover a completely closed Cronobacter genome for further genomic characterization. Ten PIF samples, each inoculated with different Cronobacter strains, covering Cronobacter sakazakii, C. muytjensii, C. dublinensis, C. turicensis, and C. universalis, were processed according to the Bacteriological Analytical Manual (BAM) protocol. qPCR was used for initial screening (detection and quantification) of the overnight enrichments and confirmed that the spiked PIF samples after the overnight enrichment have high levels of Cronobacter (107 to 109 CFU/mL). DNA from overnight PIF enrichments was extracted from the enrichment broth and sequenced using ONT. Results showed that ONT sequencing could accurately identify, characterize, and close the genomes of Cronobacter strains from overnight PIF enrichments in 3 days, much faster than the nearly two weeks required by the current BAM method. Complete genome recovery and species differentiation were achieved. This suggests that combining qPCR with ONT sequencing provides a rapid, cost-effective alternative for detecting and characterizing Cronobacter in PIF, enabling timely corrective actions during outbreaks.

This study addresses the implementation of the International Financial Reporting Standard 9 (IFRS 9) in the European Union as of January 1, 2018, replacing the International Accounting Standard 39 (IAS 39) to introduce a new model for recognizing Loan Loss Provisions (LLP) based on Expected Credit Loss (ECL). This model responds to criticisms of the former Incurred Credit Loss (ICL) system for its inability to reflect credit losses in a timely manner, potentially exacerbating the effects of financial crises (Bushman & Williams, 2015; Gebhardt & Novotny-Farkas, 2011). The study focuses on the effects of adopting the ECL model on the level of Loan Loss Allowances (LLA) in loans, own equity, and the Common Equity Tier 1 (CET1) ratio across 13 Portuguese commercial banks. A mean comparison test is used to evaluate scenarios before and after the application of the ECL model, highlighting the importance of regulator actions and the adequacy of loss recognition policies, including the effects of Regulation (EU) 2017/2395 of December 12. The results obtained demonstrate significant negative impacts on the net values of loans, own equity, and the CET1 ratio upon adopting the IFRS 9 ECL model, due to the widespread increase in LLAs.

(1) Background: in the context of sustainable development goals (SDGs), this work explores the repair direction of future cultivated land protection policies based on the Smith policy implementation model from the historical evolution to ensure that the cultivated land protection policy does not deviate during the implementation process. (2) Methods: this paper uses literature research and inductive deduction methods to sort out the evolution process of Chinese cultivated land protection policy, summarize the successful experience of transferring the focus of cultivated land protection in chronological order, and conclude the repair direction of Chinese cultivated land protection. (3) Results: although the Chinese cultivated land protection policy in the historical evolution has through three significant phases, there are still certain issues in the development trend of Chinese cultivated land protection policy based on regional division of labor for grain transportation and sales. (4) Conclusion: directly utilizing feedback from farmers as stakeholders will contribute to the maturity and improvement of cultivated land protection policies in the specific implementation of cultivated land protection policies.

This study examines the relationship between entrepreneurship and sustainable devel-opment in Saudi Arabia from 2006 to 2022, focusing on the economic, social, and en-vironmental dimensions. Using the Autoregressive Distributed Lag (ARDL) model, the research investigates both short-run and long-run dynamics to understand how entre-preneurial activities influence sustainable development within the framework of Saudi Arabia's Vision 2030 initiative. The findings indicate that entrepreneurship significantly contributes to economic growth through job creation and innovation, thereby aiding in the diversification of the economy away from oil dependency. Socially, entrepreneurial ini-tiatives have a positive impact on gender equality and social inclusion by empowering women and integrating youth into the labour market. Environmentally, entrepreneurship helps reduce carbon emissions and promotes sustainable business practices. Despite these positive outcomes, challenges such as regulatory barriers, limited access to finance, and the need for a supportive entrepreneurial ecosystem remain. Recommendations include enhancing entrepreneurial education, providing financial incentives, and streamlining regulatory processes to better support start-ups and SMEs. The study highlights the ne-cessity of addressing these challenges to fully realize the potential of entrepreneurship for sustainable development in Saudi Arabia. By providing empirical evidence on the sig-nificant role of entrepreneurship in driving sustainable development, this research offers actionable insights for policymakers aiming to foster a more resilient and diversified economy in line with Vision 2030. .

Accurate measurement of water vapor is essential for researches and applications of meteorology, climatology and hydrology. Based on the BeiDou PPP-B2b service, real-time precipitable water vapor (PWV) is retrieved with the precise point positioning (PPP) software. The experiment was conducted in Beijing in January, 2023. Three solutions are designed with PPP using the BeiDou system only, the GPS system only and the BeiDou-GPS combined solution. Real-time PWVs for the 3 solutions are validated with the ERA5 reanalysis data. Between PWVs from single BeiDou and ERA, there are a bias of 0.7 mm and a RMSE of 1.8 mm. While for the GPS case, the bias is 0.73 mm and RMSE is 1.97 mm. The biases are less than 1 mm and RMSEs are less than 2mm. Both the BeiDou and the GPS processing performs very well. But little improvement is found for the BeiDou-GPS combined solution, comparing with the BeiDou system only and the GPS system only solution. This may be due to the poor handling of two different kinds of errors for the GPS and the BeiDou systems in our PPP software. A better PWV estimation with the two systems is to estimate PWV with single system at first step, and then to obtain the optimization by Bayesian model averaging.

This study delves into the Schrödinger equation's new invariants, shedding light on their crucial implications for theoretical physics and beyond. Specifically, it explores the behavior of scattering amplitudes and bound states concerning the choice of coordinate systems. The research unveils that while the energy of bound states remains invariant under coordinate transformations, the phase of scattering amplitudes undergoes variations, underscoring its pivotal role in theories reliant on phase normalization. Moreover, these findings have played a pivotal role in constructing estimates for three-dimensional Navier-Stokes equations, enhancing our ability to model complex fluid dynamics with greater precision and reliability. Additionally, in seismic exploration, tomography, and ultrasound imaging, these properties allow researchers to optimize phase selection, facilitating the most effective interpretation of measurement results. This strategic phase manipulation ensures clearer insights into subsurface structures, tissue composition, and fluid dynamics, with the flexibility to seamlessly transition back to the original coordinate system post-interpretation. This interdisciplinary synergy underscores the profound impact of fundamental theoretical research on advancing practical applications across diverse scientific domains.

Brazil has ideal conditions for the large-scale use of cabotage cargo transportation: a vast coastline with almost 7,400 km, approximately 70% of the population resident in a coastal range of up to 200 km from the coast and a strong concentration of activities economic along the coast. However, there is an absolute domain of road modal for the transportation of goods, and cabotage is underused. The purpose of the study was to raise the main barriers that negatively impact the performance of Brazilian cabotage. To this end, it was used to bibliographic and documentary research, based on studies already published in journals, doctoral theses, master's dissertations, congress annals, technical reports and research on government-related government agencies sites, navigation companies and entities related to cabotage. The main barriers that contribute to the low use of cabotage in Brazil were identified and analyzed, as well as possible alternatives of solution for sustainable development of this mode of transport. Such a study will certainly serve as subsidies for the definition of public policies aimed at better use of Brazilian cabotage, as well as to encourage navigation companies to invest more in the transport of goods by cabotage, in order to contribute to the reduction of trucks on highways Brazilian and for environmental preservation.

This article delves into the enduring relevance of Liberal International Relations (IR) Theory amidst persistent criticisms regarding power dynamics and its applicability in emerging states. Despite its detractors, Liberal IR Theory offers a nuanced understanding of state behavior, blending social contexts with power dynamics. It recognizes the intricacies of economic interdependence and advocates for a balanced approach in advancing democracy and human rights. While nationalism poses challenges to international institutions, their adaptability endures. Leaders, albeit constrained, retain the capacity to foster peace through visionary leadership and global cooperation. By acknowledging its limitations and fostering open dialogue, Liberal IR Theory continues to evolve, poised to contribute to a just and peaceful global order.

Conditional Independence (CI) testing is fundamental in statistical analysis. For example, CI testing helps validate causal graphs or longitudinal data analysis with repeated measures in causal inference. CI testing is difficult, especially when testing involves categorical variables conditioned on a mixture of continuous and categorical variables. Current parametric and non-parametric testing methods designed for continuous variables and can quickly fall short in the categorical case. This paper presents a computational approach for CI testing for categorical data types, which we call computational conditional independence (CCI) testing. The test procedure is based on permutation and combines machine learning prediction algorithms and Monte Carlo Cross-Validation. We evaluated the approach through simulation studies and assessed the performance against alternative methods; the generalized covariance measure (GCM) test, the kernel conditional independence (KCI) test, and testing with multinomial regression. We find that the computational approach to testing has utility over the alternative methods, and we can achieve better control over type-I-error rates. We hope this work can expand the toolkit for CI testing for practitioners and researchers.

The core motivation for this study emanates from Voronin S.'s seminal work on the universality of the zeta function. This universality positions the zeta function as a pivotal element in the conceptual framework of global artificial intelligence, suggesting its potential as a foundational component. A critical barrier to harnessing this promising universality has been the absence of efficient algorithms capable of actualizing this concept.

This paper presents an analysis of the number of zeros in the binary representation of natural numbers. The primary method of analysis involves the use of the concept of the fractional part of a number, which naturally emerges in the determination of binary representation. This idea is grounded in the fundamental property of the Riemann zeta function, constructed using the fractional part of a number. Understanding that the ratio between the fractional and integer parts of a number, analogous to the Riemann zeta function, reflects the profound laws of numbers becomes the key insight of this work. The findings suggest a new perspective on the interrelation between elementary properties of numbers and more complex mathematical concepts, potentially opening new directions in number theory and analysis.

The economic, social and environmental benefits generated by the use of urban public transportation infrastructure constitute a complex dynamic urban public transportation infrastructure utilization benefit system. This paper evaluates the coupling coordination among these three benefits taking four Chinese autonomous municipalities as an example. These four cities have large-scale urban public transportation infrastructures but their utilization has many serious problems. The basic function of urban public transportation infrastructure has not been fully played in these cities. Whether the different benefits of urban public transportation infrastructure have been developed in harmony or not is unclear. We analyzed the coordinated development among three benefits by constructing coupling coordination degree model and used Gini coefficient to study the difference of coordinated development among three benefits of four cities. The result shows that the levels of coordinated development among three benefits of urban public transportation infrastructure were lower in these four cities and have positive correlation with it of urban public transportation infrastructure utilization benefit. Raising the level of urban public transportation infrastructure utilization benefit is the most crucial solution of promoting the coordinated development among three benefits.

This research investigates the intricate dynamics between intellectual Capital (VAIC) and the stability of banks in the evolving context of Saudi Arabia's banking sector. Against the backdrop of rapid economic reforms under Vision 2030 and the challenges imposed by the COVID-19 pan-demic, the research provides a nuanced analysis of how intellectual capital and intellectual capital's components—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—affect the financial stability of Saudi banks. The research analyses a decade-long panel dataset from 2012 to 2022, utilizing both fixed effects and cross-section random effects models to discern the impact of intellectual capital on bank stability. The findings reveal a positive overall influence of intellectual capital on bank stability; however, individual compo-nents present a complex relationship, with CEE showing a positive association and HCE and SCE demonstrating unexpected negative correlations with bank stability. The research identifies lev-erage (LEV) as a significant factor negatively impacting stability. Operational efficiency (OPEF) and size (SIZE) also negatively affect stability. Surprisingly, macroeconomic indicators and bank size exhibit non-significant effects on bank stability. Similarly, the direct impact of the COVID-19 pandemic was found to be non-significant, suggesting a resilient banking environment or the presence of effective mitigating strategies. As Saudi Arabia continues its ambitious economic transformation, this research underscores the critical role of effectively managed intellectual capital in ensuring the banking sector's stability. It provides a foundation for ongoing research in this vital area.

Purpose: To evaluate the relationship between corneal nerve structure and function in a veteran population. Methods: 83 veterans (mean age: 55 ± 5 years) seen at the Miami Veterans Affairs (VA) eye clinic were included in the study. Each individual filled out questionnaires to evaluate ocular symptoms (5-Item Dry Eye Questionnaire, DEQ5, Ocular Surface Disease Index, OSDI) and ocular pain (Numerical Rating Scale, NRS, Neuropathic Pain Symptom Inventory modified for the Eye, NPSI-Eye). Individuals also underwent an ocular surface examination that captured functional nerve tests including corneal sensation, corneal staining, and Schirmer test for tear production. Corneal sub-basal nerve analysis was conducted using in vivo confocal microscopy (IVCM) images with corneal nerve density, length, area, width, and fractal dimension captured. IVCM and functional corneal metrics from the right eye were examined using correlational and linear regression analysis. Results: Most corneal structural metrics were not related to functional metrics, except for weak correlations between various IVCM metrics and tear production. In addition, corneal nerve fiber area was positively related to corneal sensation (r = 0.3, p = 0.01). On linear regression analyses, only corneal fractal dimension remained significantly related to tear production (β = -0.26, p = 0.02) and only corneal nerve fiber area remained significantly related to corneal sensation (β = 0.3, p = 0.01). Conclusions: Most corneal nerve structural metrics did not relate to functional metrics in our veteran population, apart from a few weak correlations between structural metrics and tear production. This highlights caution in using corneal nerve anatomy to predict corneal function.

Remote work as a new working pattern is considered of high importance in determining the competitiveness of the institutions that adopt this form of work. This trend toward remote working has benefited workers greatly in terms of flexibility and work-life balance and has had unanticipatedly positive effects on sustainability. The issue has grown in importance considering recent development of digitalization and high concern of countries to achieve the sustainable goals. This study attempts to examine the effect of three explanatory variables: remote work, institutional efficiency, and work management on the competitiveness of finance institutions in Saudi Arabia. To collect the primary data, a survey was conducted on a stratified random sample that comprised 1270 respondents. The sample covers the three finance sector segments: banks, insurance, and finance companies. Correlation analyses, one-sample t-tests, and multi-regression analyses are applied to analyze the data. The results of the study showed that there is a positive significant relationship between the three explanatory variables of the study and institutional competitiveness. Besides, the regression model revealed that the two explanatory variables; remote work and institution efficiency are statistically significant at 95% confidence intervals, while work management is not statistically significant. The study recommends promoting remote work to increase the finance institution's competitiveness by restructuring the work policies, designing work strategies, and introducing a new management system compatible with remote work.

This manuscript presents a novel approach to estimating the potential within Schrödinger equations, with a particular focus on applications to the Navier-Stokes problem in fluid dynamics. By establishing new theoretical estimates, we delve into the intricate dynamics of fluid flow, aiming to unveil previously obscured aspects of the Navier-Stokes equations. Through a rigorous mathematical framework, we explore how these new potential estimates can provide a fresh perspective on fluid mechanics, contributing to the ongoing quest to solve some of its most persistent challenges.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

We show how the Poincar\'e--Riemann--Hilbert boundary-value problem enables us to construct effective estimates of the potential in the Schr\"odinger equation. The apparatus of the three-dimensional inverse problem of quantum scattering theory is developed for this. It is shown that the unitary scattering operator can be studied as a solution of the Poincar\'e--Riemann--Hilbert boundary-value problem. This allows us to go on to study the potential in the Schr\"odinger equation

This study introduces a novel computational approach for testing conditional independence (BB CI test) within causal Directed Acyclic Graphs (DAGs), leveraging Bayesian non-parametric bootstrap and machine learning techniques. Our method offers an alternative for validating the assumptions underpinning causal DAGs. Through simulation studies and an industrial case analysis, we demonstrate the test procedure in accurately assessing conditional independence, comparing it with the Generalized Covariance Measure (GCM) test. Our findings suggest that the BB CI test is advantageous in scenarios where existing methods may falter due to violations of model assumptions. This research contributes to the causal inference literature by providing a computational tool for researchers and practitioners to validate causal models.

Environmental, social, and governance (ESG) investment has become a common trend in capital markets, and many institutional investors have publicly declared their long-term ESG investment target (ESGIT). This study focuses on investors who conduct strategic asset allocation (SAA) using composite indices but establish their ESGIT outside the SAA process. A mismatch could arise between investors’ planned and actual portfolios because they must pursue their ESGIT by asset selection, which inevitably makes the constituents of their portfolios different from those of composite indices. To scrutinize the potential existence of a misalignment between their SAA and ESGIT, this study analyzes actual stock and bond indices over the past decade using traditional mean-variance optimization. The results reveal significant differences between the expected and realized performances, and the misalignment is more significant when the analysis period is divided into two sub-periods: stable and volatile. Specifically, the results indicate that the efficient frontier constructed using ESG indices significantly differs from that constructed using composite indices, and that the difference between these two efficient frontiers becomes more significant during volatile periods. Furthermore, the results show that investors cannot meet their targets if their ESGIT is established outside the SAA process.

As prominent oil producers, the Gulf Cooperation Council (GCC) countries have played a significant role in the global energy market. However, as the world's attention increasingly shifts towards environmental sustainability, understanding the implications of the GCC's economic activities on CO2 emissions becomes indispensable. This research paper investigates the relationship between specific economic indicators and their impact on CO2 emissions in the GCC from 2001 to 2021. The study employs quantile regression, a powerful statistical method that estimates the conditional quantiles of a response variable given a set of predictor variables. The findings reveal several important insights: Financial institution efficiency is significant and negative at a 1% level at the lower (10th) -83537.3 and the higher quantile (90th) -549002.3. The relationship between GDP per capita and CO2 emissions varies across quantiles, highlighting the complexity of the growth-environment nexus. Total patents exhibit a positive and significant relationship with emissions, underscoring the importance of directing innovation towards environmentally sustainable solutions. Renewable energy consumption displays a nuanced relationship with CO2 emissions, with a stronger negative impact observed at higher consumption levels. This underscores the potential of renewable energy to mitigate emissions when integrated at scale. The study's outcomes hold crucial policy implications for the GCC countries as they seek to align economic growth with environmental sustainability. The findings emphasize the importance of fostering financial institution efficiency, promoting green innovation, and expanding renewable energy sources to reduce emissions

The impacts of inflation on international finance are generally reflected in the decline of buying power, risks of investment and deposit loss from currency devaluation. For the purpose of optimized allocation and management of asset values, i.e., annual income or research grants, a framework of a three-level model for static financial management is presented to maximize banking interests, bonuses, and the remaining balance after spending necessary expenditures. Meanwhile, in retrospect to higher-level financial inflation, strategies of dynamic investment, i.e., posing regular tests of flipping coins, exploiting variations of the currency exchange rate, as well as applying the theory of broad money, are presented to increase the appreciation rate of net assets in and post the era of COVID-19. Quantitative evaluations in case studies verify the feasibility of improving the financial situation, indicating broader applications for budgeting and investing when US inflation rate is below 3.0%. Besides, combining approaches of static and dynamic strategies, the expected annual growth rate of individual zero-risk asset investment is predicted as within the range of 8.30~9.62% according to budgeted appreciation on net assets in 12 months, which is capable of overcoming negative impacts from higher level annual inflation, i.e., those as highest as 8.01% in the Year 2022.

Graphene was synthesized through a two-step pyrolysis method using waste candlenut (Aleurites moluccanus) shells as the precursor. Cerium (Ce)/graphene composites were prepared via an impregnation technique. The resulting graphene and Ce/graphene were characterized using various analytical methods, including Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo Gravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, Cyclic Voltammetry (CV), and Linear Sweep Voltammetry (LSV). The bio-carbon produced predominantly exhibited a graphene structure with flat carbon morphology and an interlayer distance of 0.33 nm. This structural information is supported by XRD data, which shows a broad and weak peak at 2θ = 26° corresponding to the C (002) plane, indicative of graphene presence. FTIR, XPS, and Raman spectroscopy further confirmed the presence of graphene through the detection of Csp2 aromatic bonds and the characteristic D, G, and 2D peaks. Notably, the performance of cerium can be enhanced by the incorporation of graphene, attributed to the large surface area and chemical interactions between Ce and graphene. Consequently, candlenut-derived graphene shows potential as a supportive material for modifying the properties of cerium, thereby opening avenues for various advanced applications, such as sustainable and high-performance energy storage systems.

The development of a Digital Track Model (DTM) within Kazakhstan's railway system presents an innovative approach to enhancing efficiency and safety across the network. This paper investigates the economic viability of DTM implementation, offering a comprehensive mathematical model that highlights potential reductions in maintenance costs and improvements in system accuracy and durability. The findings advocate for DTM's potential to significantly elevate railway operations, suggesting a pivotal step towards modernizing Kazakhstan's transit infrastructure.

The Eastern Kunlun Fault Zone (EKFZ) is located in a seismic blank area. This study investigates the hydrogeochemical characteristics of varied-temperature springs in the EKFZ to understand the relationship between fractures, fluids and earthquakes. It aids in establishing their induction mechanisms and assists in monitoring the earthquake precursors of the EKFZ. In this study, the main elements, trace elements, hydrogen and oxygen isotopes and strontium isotopes of 23 varied-temperature springs in the EKFZ were analyzed. The results reveal the source of groundwater recharge, hydrochemical types, mineral saturation, and for a select few springs indicative of geothermal activity, collected geothermal reservoir temperatures. The study also explores the relationship between earthquakes and springs, identifying sensitive chemical indicators. Based on continuous monitoring at Maqu Station, we found that before the occurrence of the Maerkang Ms 6.0 earthquake, the concentration of Cl− rose by 2.9 times, and 46 days before the Gande earthquake (Ms = 4.7), the concentrations of Na+ and SO42− significantly increased. Finally, a conceptual model of the hydrogeochemistry of springs is presented to describe the groundwater circulation in the study area. This research is of great significance for the analysis of fluid geochemistry in this area and for assessing the seismic hazards of the EKFZ.

In forests, the microbial populations living in the soil can directly affect the carbon decomposed by the surface plants, and promote carbon storage and stability. In this study, 3 plots of 25.82 m×25.82 m were set up in 5 stand types, respectively. Soil samples were collected from 0~20 cm, 20~40 cm and 40~60 cm layers. Soil microbial composition, organic carbon component, pH, water content, bulk density, nitrogen, phosphorus, potassium and other physicochemical indexes and correlations were determined, and the correlations between soil carbon components and soil microbial functional modules in different mixed modes were analyzed. The results showed that: (1) The SOC of the same soil layer varied significantly, which also showed significant differences on the composition of soil bacteria and fungal microbial communities. Moreover, the bacterial community was more sensitive to the vegetation change environment, and the fungal community structure was more resistant to the influence of soil environment changes. (2) Fun_mod 1,6 and Bac_mod 7 were the microbial functional modules that played a decisive role in the process of soil carbon pool change, and the diversity and composition of bacterial community had more positive effects on soil organic carbon than that of fungal community. (3) Linear fitting and RDA results showed that POC in soil had the strongest correlation with SOC content, indicating that soil microorganisms affected the storage and stability of soil carbon mainly by regulating the conversion of surface plants (carbon sources) into POC. The soil environment of different mixed modes has different effects on soil carbon accumulation. Soil microorganisms affect soil carbon storage and stability mainly by regulating the conversion of surface plants (carbon sources) into POC forms.

Achieving the dual development of rural revitalization and urbanization is an important strategic goal of China’s current modernization. Rural population and settlements are the main components of the countryside in traditional agricultural areas, and play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and settlements at the township level, as well as the degree and type of coupled development. A framework for urban–rural development relationships based on different types of coupled development is proposed, and a model of urban–rural forces is constructed to derive the spatial pattern of urban–rural development at the township level that may be formed in the future. Our study shows that the rural population and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of the township-level coupling measurements present four types of development in terms of the spatial pattern of urban–rural development: A-type is most likely to produce new cities or satellite towns in the Jixi–Harbin–Qiqihar area in the future; B-type is the fastest dying area in the future, located in the Harbin and Qitaihe clusters, with a tendency to merge into Harbin; C-type is the area to be focused on in the future to attract population and strictly control the growth of the rural settlement area to avoid it turning into B-type; D-type may develop regional township centers in the future in the combined area of Jiamusi City, Suihua City and Mudanjiang City. The results of the study provide experience in realizing rural revitalization according to local conditions. The new spatial pattern of urban–rural development provides an important reference for formulating land use policies, optimizing urban–rural land allocation and realizing integrated urban–rural development strategies.

The construction time of concrete structures in hydraulic tunnels is long, the construction environment is complex, and there are many influencing factors. The requirements for construction quality are high, not only to meet the strength requirements, but also to meet the design requirements of erosion resistance, crack resistance, and seepage resistance according to its specific operating environment. Therefore, evaluating the construction quality of concrete structures in hydraulic tunnels is of great significance. Considering the randomness and fuzziness of factors affecting the construction quality of concrete structures in hydraulic tunnels, this paper proposes a comprehensive evaluation model based on Combined Weighting (CWM) and Uncertainty Measurement Theory (UM). The IAHP method and CRITIC method are used to determine the subjective and objective weights of evaluation indicators, combined weighting is based on the principle of minimum entropy, and the UM method is used to evaluate the construction quality level. Finally, taking a hydraulic tunnel as an example, its construction quality grade is calculated to be III according to the evaluation model proposed in this paper, which matches with the engineering reality, and a comparative study is made with the mixture element topology theory at the same time. It is verified that the evaluation model can scientifically and reasonably evaluate the construction quality level of concrete structures in hydraulic tunnels.

As companies increasingly undergo digital transformation, the role of talent management pro-cesses becomes pivotal in enhancing overall organizational performance. The research addresses the significance of talent management in corporate digital transformation, examining whether variations in the digitalization of these processes can be attributed to company size. A qualitative approach was employed, utilizing a questionnaire, collecting responses from 202 organizations across diverse sectors. Findings reveal disparities in digitalization throughout the talent man-agement process, with pronounced presence in the attracting, selecting, and rewarding phases, but diminishing in deployment and development, further declining in planning. A positive cor-relation between company size and adoption of specific digital platforms was observed. Larger enterprises exhibit greater utilization of digital platforms in talent deployment and development. Moreover, corporate communication tools are consistently utilized in the rewarding phase, irre-spective of company size. These findings offer practical insights for organizations to optimize their digitalization strategies based on their scale, thereby contributing to more effective and tailored digitalization endeavors. The uniqueness of this research lies in its exploration of the in-fluence of company size on the digitalization of talent management processes and its potential to explain variations across different stages of these processes.

The authors argue that despite significant numbers of foreign workers present in the Russian labor market Russia remains unattractive for highly skilled foreign workers. The economic crisis the country has faced since 2014 has resulted in a further outflow of foreign nationals from OECD countries. So Russia has to look for employees among newcomers from the former Soviet states, the majority of whom come from Central Asia. Russian politics with regard to immigration is characterized by the collision between “geopolitical” and domestic policy rationales. On one hand, seeking to maximize its influence in the post-Soviet space Russia provides preferential conditions of employment for citizens of partner countries in the framework of the Eurasian Economic Union. On the other hand, the Kremlin is afraid to liberalize its approach to immigration and the integration of immigrants through fear of losing popularity among the electorate. The second substantial feature of Russian immigration politics is an extreme level of securitization of migration issues. The government considers these issues primarily through a policing lens. One cannot claim that the Russian state does not take any steps to liberalize “migratory regulation”; however, the effect of these measures is being vastly reduced by new restrictions. In addition, liberally designed laws do not bring the expected results due to the corrupt practices that pervade the whole of migration regulation.

This paper considers the theoretical framework of the consumption-based asset-pricing model and derives successive approximations of the modified basic pricing equation using Taylor series expansions of the investor’s utility function during the averaging time interval Δ. For linear and quadratic Taylor approximations we derive new expressions for the mean asset price, mean payoff, their volatilities, skewness and amount of asset that delivers max to investor’s utility. We introduce new market-based price probability determined by statistical moments of the market trade values and volumes. We show that the market-based price probability results zero correla-tions between time-series of n-th power of price pn and trade volume Un, but doesn’t cause statis-tical independence and we derive correlation between time-series of price p and squares of trade volume U2. The market-based treatment of the random trade price describes impact of the size of market trade values and volumes on price probability. Predictions of the market-based price probability at horizon T should match forecasts of statistical moments of the trade values and volumes at the same horizon T. The market-based price probability emphasizes direct dependence on random properties of market trades.

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics, and thermodynamic parameters of peanut shell using TGA under atmospheric air. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1. Pre-exponential factors using FWO range from 2.19×106 to 8.06×107 s–1, and for KAS range from9.72×105 to 2.25×107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤ ±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

Monitoring the status and dynamics of desertification is one of the most important parts of combating desertification. In this study, 30m high-resolution information on land desertification and restoration in the HRB was extracted from the land cover database. The results indicate that land desertification coexists with land restoration in the HRB. At different periods, the area of land restoration is much larger than the area of land desertification in the HRB, and the HRB has been in a process of land restoration. Upstream of the HRB, there is a continuing trend of increasing land desertification associated with overgrazing in a context where climate change favors desertification reversal. In the middle and lower reaches, although both climate variability and human activities favor land desertification, the process of land desertification in the middle and lower reaches is still being reversed and land restoration dominates. The implementation of the Eco-Environmental Protection Project and desertification control measures, especially the EWDP, is contributing to the reversal of desertification in the middle and lower reaches of the HRB. However, the EWDP has indirectly led to the lowering of the water table in the middle reaches, resulting in local vegetation degradation. Therefore, there is therefore an urgent need to transform the economic structure of the middle reaches to cope with water scarcity and land desertification.

Strategic intelligence covers the examination of what impacts and influences the business and the related SWOT analysis, (strengths, weaknesses, opportunities, and threats mapping). Through this research, leaders will be able to properly allocate and re-route resources, identify areas of improvement, and ensure that strategic initiatives are aligned with the organization's mission. Strategic intelligence is, therefore, effective through the use of critical thought and data-driven decisions and seeing the outcomes of different positioned alternatives. It must also form and support a culture of cooperation and open communication within the organizations, stimulating employees' inputs and learning curves. The article's subject is the necessity for strategic intelligence, a crucial competence for leaders, managers, and companies striving to remain competitive, to be utilized and best leveraged in today's volatile and dynamic business contexts. It helps the leadership turn proactive, foresee trends, and make correct, agile decisions that enforce companies' long-term growth and success. This study follows a research design that includes a thorough literature review and bibliometric research, executed via VoSViewer, illustrating the concept of strategic intelligence from a leadership point of view as a driver of competitive advantage. Further, the article points out that the limitations are acknowledged because the literature on the matter is limited, as strategic intelligence is relatively new to the business sector; moreover, more research is required to fully understand and use the potential of strategic intelligence in business growth. By overcoming these limitations and continuing to study this concept, businesses can gain a competitive edge and make informed decisions that fuel their success in an ever-evolving market. As a result, this study contributes to developing strategic intelligence in leadership and business and paves the road for further research and applications of strategic intelligence theories in organizational contexts.

In order to investigate the size distributions and seasonal variations of carbonaceous aerosols (OC and EC), the carbonaceous species were collected and then analyzed by using a 9-stage Anderson-type aerosol sampler and DRI Model 2001A Thermal/Optical Carbon Analyzer on the typical industrial city Nanjing in Yangtze River Delta, China in the summer, autumn and winter of 2013 and spring of 2014. OC, EC, SOC and POC exhibited obvious seasonal variations, with the highest level in winter (39.1±14.0, 5.7±2.1, 23.6±11.7 and 14.1±5.7 μg•m^-3) and the lowest level in summer (20.6±6.7, 3.3±2.0, 12.2±3.8 and 8.4±4.1 μg•m^-3), and were mainly centralized in PM_1.1 in four seasons. The concentrations of OC in PM_1.1 varied in the order of winter > autumn > spring > summer, while EC ranked in the order of autumn > winter > summer > spring. In the PM_1.1-2.1 and PM_2.1-10, the concentrations of OC and EC decreased in the sequence of winter > spring > autumn > summer. The size spectra of OC, EC and SOC had bimodal distributions in four seasons, except for EC with four peaks in summer. The size spectra of POC varied greatly with seasons, exhibiting bimodal distribution in winter, trimodal distribution in spring and summer, and four peaks in autumn. The OC/EC ratios were 7.0, 6.3, 7.6 and 6.9 in spring, summer, autumn and winter, respectively, which demonstrated the abundance of secondary organic aerosols in Nanjing. The sources of carbonaceous aerosol varied significantly with seasons, and were dominated by vehicle exhaust, coal and biomass burning in PM_2.1, and dominant by dust, coal and biomass burning in PM_2.1-10.

Innovation is an essential key factor in the technology development history. Past research on innovation focused more on the innovation behavior of technology, but seldom described knowledge assets which also influence innovation behavior greatly. The effect of knowledge assets attribute and result on disruptive innovation is therefore regarded as the research topic in this study, where disruptive innovation is divided into outbound and inbound to combine combination-embeddednessandmajor business specificityof knowledge assets as the research model. Manufacturing enterprises in China are proceeded the questionnaire survey, and 173 valid copies are collected. The empirical analysis shows that combination-embeddedness of knowledge assets presents significantly positive effects on major business specificity and outbound innovationof an enterprise but reveals remarkably negative effects on inbound innovation. Enterprises are suggested to constantly accumulate knowledge assets with low major business specificity before disruptive innovation in order to reduce ineffective inbound innovation.

Digital transformation process gained significant research interest over the past years especially when related with achievements in sustainability goals. Even though there exist growing research regarding various aspects of digital transformation and sustainability procedure, a more detailed analysis is needed in different national environments. Proposed study empirically analyzes the Greek managers’ perspective for the relationship between digital management intensity and environmental performance. Almost 60 Greek senior managers from various organizational sectors were interviewed, while a synthetic index already developed from previous studies was used. Results indicate that Greek companies are not fully exploit digital technologies to further develop their environmental practices. Digital transformation strategy is contributing effectively to environmental strategies in the case of reducing emissions of waste and avoid environmental accidents, while in the rest of cases emerging technologies play a less important role and not as a part of an holistic digital strategy.

Pyrethroid pesticides (PYRs) as the third most widely used pesticides, following organophosphorus and carbamate pesticides, which are of significant importance in the analysis and detection of vegetables. However, the current pretreatment technology for PYRs confronts challenges of difficult separation and low enrichment efficiency, resulting in a cumbersome and time-consuming pretreatment process with poor selectivity. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed to simultaneously purify and enrich five PYRs in vegetables, with the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. The COF-SiO2@Fe3O4 was prepared by a simple solvothermal conditions method, using Fe3O4 as magnetic core, benzidine and 3,3,5,5-tetraaldehyde biphenyl as two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on extraction efficiency was investigated to optimize the MSPE conditions, including adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography-mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg-1 (1.00–100 μg·kg-1 for bifenthrin and 2.5–100 μg·kg-1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg-1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg-1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promising prospects for the determination of PYRs in real samples.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of professional nurses in maintaining service standards under new governance.We conducted the study at sub-district health-promoting hospitals using a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes. We collected data from 340 nurses and 400 patients using structured questionnaires. We divided the questionnaires into seven sections, which captured a range of metrics such as the personal data of nurses, hospital service activities, and leadership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality. We used paired t-tests to compare performance metrics before and after the administrative transfer, one-way ANOVA to assess variability among different service units, and binary logistic regression to identify key determinants of service quality in our statistical analysis. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited minimal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities. This could contribute to improved healthcare delivery across restructured health systems.

Wide bandgap semiconductors-based photocatalysts are usually limited by their low solar energy conversion efficiency due to their limited absorption solar wavelength, surface’s fast recombination of photoelectron–hole pairs and low charge-carrier mobility. Here we report a new stepwise solution synthesis for making a new photocatalytic core/shell of titanate nanowire/reduced graphene oxide shell (or titanate/rGO) 1D-nanocomposite. The new core/shell nanocomposite maximized the specific surface area, largely reduced the charge transfer resistance and reaction energy barrier, and significantly improved the absorption of the visible light. The core/shell nanocomposites’ large on/off current ratio and rapid photo-responses boosted the photocurrent by 30.0%, the photocatalysis rate by 50.0%, and the specific surface area by 16.4%, when comparing with the pure titanate nanowire core. Our numerical simulations support the effective charge separation on the new core-shell nanostructure, which can help further advance the new photocatalysis.

Oedaleus decorus asiaticus, Calliptamus abbreviatus, Angaracris rhodopa, and Myrmeleotettix palpalis are the main grasshoppers that harm the natural grassland in the Hexi Corridor. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers habitats and to assess their distribution under current and future climate change conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, 61 occurrences of O. decorus asiaticus, 68 occurrences of A. rhodopa, 58 occurrences of C. abbreviatus, and 92 occurrences of M. palpalis were recorded by GPS, and the distribution of suitable habitats for O. decorus asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis were predicted under current and future climatic scenarios using a MaxEnt model. The average AUC and TSS values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a potential distribution area of 1.44×104, 1.43×104, 1.29×104, and 2.12×104 km2, accounting for 15.3, 15.2, 13.7, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the east-central part of Zhangye City, the western part of Wuwei City, and the western and southern part of Jinchang City, with areas of 0.35×104, 0.29×104, and 0.20×104 km2, accounting for 3.7, 3, and 2.2% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32×104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of O. asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis was predicted to decrease.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

Enhancement of orthodontic tooth movement (OTM) through local administration of biofunctional molecules has become increasingly significant, particularly for adult patients seeking aesthetic and functional improvements. This comprehensive systematic review analyzes the efficacy of various biofunctional molecules in modulating OTM, focusing on the method of administration and its feasibility, especially considering the potential for topical application. A search across multiple databases yielded 36 original articles of experimental human and animal OTM models, which examined biofunctional molecules capable of interfering with the biochemical reactions that cause tooth movement during orthodontic therapy, accelerating the OTM rate through their influence on the bone metabolism (Calcitriol, Prostaglandins, Recombinant human Relaxin, RANKL and RANKL expression plasmid, growth factors, PTH, osteocalcin, vitamin C and E, biocompatible reduced graphene oxide, exogenous thyroxine, sclerostin protein, a specific EP4 agonist (ONO-AE1-329), carrageenan and herbal extracts). The results indicated a variable efficacy in accelerating OTM, with Calcitriol, Prostaglandins (PGE1 and PGE2), RANKL, growth factors and PTH, among others, showing promising outcomes. PGE1, PGE2 and Calcitriol experiments had statistically significant outcomes in both human and animal studies, and, while other molecules underwent only animal testing, they could be validated in the future for human use. Notably, only one of the animal studies explored topical administration, which also suggests a future research direction. This review concluded that while certain biofunctional molecules demonstrated potential for OTM enhancement, the evidence is not definitive. The development of suitable topical formulations for human use could offer a patient-friendly alternative to injections, emphasizing comfort and cost-effectiveness. Future research should focus on overcoming current methodological limitations and advancing translational research to confirm these biomolecules' efficacy and safety in clinical orthodontic practice.

This study explored the intricate nexus between public service provision and land use planning, with a specific focus on the conservation of local plant species in Tambon Khao Phanom, Amphoe Khao Phanom, Krabi Province. Rooted in commitment. The research framework encompasses three fundamental activities: resource survey and collection, resource conservation and utilization, and resource development planning for public services, emphasizing land use planning for local plant species conservation. This multidisciplinary approach integrates the one-map method and draws data from the Department of Land Development to formulate a comprehensive land utilization plan that optimizes land use for biodiversity conservation. This study underscores the critical synergy between public service delivery and land use planning, highlighting their collective potential to advance community well-being and sustainable development.

The reviews usefulness has been the aim of several research studies. However, results regarding the significance of usefulness determinants are often contradicting, thus decreasing the accuracy of reviews’ helpfulness estimation. Also, bias in user reviews attributed to differences e.g. in gender, nationality, etc., may result into misleading judgments thus diminishing reviews’ usefulness. Research is needed for sentiment analysis algorithms that incorporate bias embedded in reviews, thus improving their usefulness, readability, credibility, etc. This study utilizes fuzzy relations and fuzzy synthetic evaluation (FSE) in order to calculate reviews’ usefulness by incorporating users’ biases as expressed in terms of reviews’ articulacy and sentiment polarity. It selected and analysed 95.678 hotel user reviews from Tripadvisor, for five nationalities. The findings indicate that there are differences among nationalities. The British are most consistent in their judgments expressed in titles and review documents. The British and the Greek review titles suffice to convey any negative sentiments. The Dutch use fewer words in their reviews than the other nationalities. This study suggests that fuzzy logic captures subjectivity which is often found in reviews, and it can be used to quantify users’ behavioral differences, calculate reviews usefulness, and provide the means for developing more accurate voting systems.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study, conducted from 1 March 2023 to 31 March 2024 at sub-district health-promoting hospitals in Thailand, aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of profes-sional nurses in maintaining service standards under new governance. Utilizing a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes, we collected data from 340 nurses and 400 patients through structured questionnaires. These questionnaires were divided into seven sec-tions, capturing metrics such as the personal data of nurses, hospital service activities, and lead-ership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality and conducted paired t-tests to compare performance metrics before and after the admin-istrative transfer. One-way ANOVA was used to assess variability among different service units, and binary logistic regression helped identify key determinants of service quality. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited mini-mal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities, potentially contributing to enhanced healthcare delivery across restructured health systems.

This literature review paper delves into the synergies between Climate-Smart Agriculture (CSA) and the effective management of food losses. With the escalating challenges posed by climate change and the pressing need to address food security concerns, the intersection of these two critical domains becomes paramount for sustainable agricultural practices. The review explores existing research on the implementation of climate-smart agricultural techniques and their impact on mitigating food losses throughout the agricultural value chain. The paper synthesizes findings related to climate-resilient crop varieties, precision farming, water-use efficiency, and sustainable soil management, highlighting their contributions to reducing post-harvest losses and enhancing overall food security. In addition to summarizing current knowledge, this paper identifies gaps in the literature and proposes avenues for future research. This review serves as a foundation for researchers, policymakers, and practitioners seeking to contribute to the advancement of climate-smart agriculture and the reduction of food losses, paving the way for a more sustainable and resilient global food system.

Soft magnetic composites cores were produced by Spark Plasma Sintering (SPS) from Ni3Fe@ZnFe2O4 and NiFeMo@ZnFe2O4 pseudo-core-shell powders. In the Fe-Ni alloys@ZnFe2O4 pseudo-core-shell composite powders, the core is a large nanocrystalline Permalloy or Supermalloy particle obtained by mechanical alloying, and the shell is a pseudo continuously layer of Zn ferrite particles. The pseudo-core-shell powders have been compacted by SPS at temperatures between 500-700 ºC, with a holding time of 0 minutes. Several techniques were used for the characterisation of the powders and sintered compacts: X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, magnetic hysteresis measurements (DC and AC) and electrical resistivity. The electrical resistivity is stabilised at values of about 7·10-3 Ω·m for sintering temperatures between 600-700 °C and this value is 3 orders of magnitude higher than the electrical resistivity of sintered Fe compacts. The best relative initial permeability was obtained for the Supermalloy/ZnFe2O4 composite compacts sintered at 600 ºC, which decreases linearly for the entire frequency range studied, from around 95 to 50. Up a frequency of 2,000 Hz the power losses are lower than 1.5 W/kg. At the frequency of 10 kHz, the power losses are larger, but they remain at a low level. In the case of Supermalloy/ZnFe2O4 composite compact SPS-ed at 700 °C, the specific power losses are even lower than 5 W/kg. The power losses decomposition proved that intra-particles losses give the main part of the losses.

Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.

The coseismic surface three-dimensional deformation fields were significant for quantified the geometric and kinematic characteristics of earthquake rupture faults. Traditional geodetic techniques were constrained by their intrinsic limitations, such as InSAR, which could only extract far-field deformation fields due to its incoherence, and GNSS, which could only acquire deformations at discrete points. The recently developing optical pixel correlation technique based on high resolution remote sensing images could acquire the near-field coseismic horizontal deformation. In this study, the vertical displacement field of the 2022 Mw 6.6 Menyuan earthquake was obtained by differencing the pre- and post-earthquake DEMs from GaoFen-7 stereo satellite images. Further, the line-of-sight (LOS) and azimuthal (AZI) directions far-field deformations by InSAR, the horizontal near-field deformation by optical pixel correlation based on pre- and post-earthquake GF-2/7 images, and the vertical deformation by differencing the pre- and post-earthquake DEMs, were incorporated to comprehensively solve the complete three-dimensional deformation fields of the 2022 Mw 6.6 Menyuan earthquake. Firstly, the vertical displacement field by differencing DEMs indicated there were significant vertical displacements about 1 m at the bend region, which was induced by the local compressive stress. In addition, at the epicenter on the middle segment of ruptured Lenglongling fault (LLLF), the maximum lifting occurred on the southern sides of the main and secondary faults exceeded 2 m. Secondly, the three-dimensional deformation fields solved by multiple deformation data demonstrated that the near-field deformation field calculated by optical pixel correlation method could quantify the displacements distributed over the rupture fault zone, which were not available on the InSAR deformation maps. Finally, the surface 2D strain derived from the displacement maps calculated by optical pixel correlation revealed high strain concentration on the rupture fault zone. Our study focused on the complete surface three-dimensional deformation estimation from multiple far- and near-field deformation data, and provided a new perspective for a deeper understanding of the characteristics of coseismic surface deformation and the rupture pattern of the fault.

A case of low level windshear at Beijing Daxing International Airport is studied in the present pa-per. It is related to the synoptic scale/mesoscale changes of the airflow pattern over northern China. The shear was captured well by the Doppler LIDAR at the airport and timely alerts had been issued. This study considers the technical feasibility of forecasting the shear feature using a high resolution numerical weather prediction model with a lead time of several hours. It turns out that the shear feature could be forecast well, and is generally consistent with the actual observations. However, there are still discrepancies between reality and the simulation, such as the strength of the shear and persistency of the feature. More cases of windshear at Daxing airport would be studied in the fu-ture in order to understand the nature of windshear over there.

This study delves into the intricate interplay of economic growth components, specifically focusing on Consumption and investment in Saudi Arabia from 2000 to 2022. Employing vector error correction models and cointegration techniques, we analyze the short- and long-term dynamics within the relationship of Consumption, investment, and economic growth. Granger causality analysis is also used to discern these pivotal variables' causal connections. Our empirical analysis reveals a persistent long-term cointegration relationship among the variables, underscoring the enduring nature of their interdependency. Furthermore, our findings highlight Consumption and investment's statistically significant positive impact on economic growth. Notably, the short-term analysis unveils a stable model characterized by an annual adjustment to equilibrium of 100%.Moreover, the Granger causality study demonstrates unidirectional causal linkages between Consumption, investment, and economic growth. These findings hold substantial implications for policy formulation in Saudi Arabia. Policymakers must grasp the ramifications of burgeoning prosperity and evolving private consumption patterns on future environmental outcomes. Achieving sustainable long-term results necessitates equal emphasis on bolstering private Consumption and fostering other facets of economic growth.

Liquidity providers for asset-pair pools with constant value distri- bution, such as Balancer pools, experience some impermanent loss whenever there is price divergence in the tokens’ fiat values. In this paper, we model this impermanent loss for geometric mean invariant pools by deriving a function of two parameters. We analyze our function graphically, showing that unevenly distributed pools with large weighting disparities best mitigate the risk of impermanent loss. We conclude by providing a general protocol for liquidity providers to choose a suitable pool based on their risk tolerance and profit goals.

This paper delves into the dynamics of asset pricing within Bachelier’s market model (BMM), elucidating the representation of risky asset price dynamics and the definition of riskless assets. It highlights the fundamental differences between BMM and the Black-Scholes-Merton market model (BSMMM), including the extension of BMM to handle assets yielding a simple dividend. Our investigation further explores Bachelier’s term structure of interest rates (BTSIR), introducing a novel version of Bachelier’s Heath-Jarrow-Morton model and adapting the Hull-White interest rate model to fit BMM. The study concludes by examining the applicability of BMM in real-world scenarios, such as those involving environmental, social, and governance (ESG)-adjusted stock prices and commodity spreads.

The information of seismic damage of buildings in SAR images of different time phase, especially in SAR images after earthquake, is easily disturbed by other factors, which affects the accuracy of information discrimination. In order to identify and evaluate the distribution information of the seismic damage accurately and make full use of the abundant texture features in the SAR image. The conventional method of change detection based on texture features usually takes the pixel as the calculating unit. In this paper, a method of texture feature change detection of SAR images based on watershed segmentation algorithm is proposed. Based on the optimization of texture feature parameters, the feature parameters are segmented by the watershed segmentation algorithm, and the feature object image is obtained. This method introduces the idea of object oriented, and carries out the calculation of the difference map at the object level, Finally, the classification threshold value of different types of seismic damage types is selected, and the recognition of building damage is achieved. Taking the ALOS data before and after the earthquake in Yushu as an example to verify the effectiveness of the method, the overall accuracy of the building extraction is 88.9%, Compared with pixel-based methods, it is proved that the proposed method is effective.

ESG (Environmental, Social, and Governance) responsibility fulfillment increasingly affects enterprise valuation. Although researchers debate about the precise effects, the prevailing view suggests a linear relationship between ESG performance and enterprise value. This study introduces a novel ESG responsibility performance metric through the Regulated Intermediary Model to delve into this relationship within the Chinese context. Our findings reveal an inverted U-shaped relationship between ESG performance and enterprise value, with financing constraints having a significant moderating effect. These findings remain robust after employing instrumental variables to mitigate potential endogeneity. Heterogeneity analysis demonstrates that this inverted U-shaped relationship is particularly pronounced in non-polluting and non-state-owned enterprises. Moreover, a comparison between equity and debt financing mechanisms underscores that improved ESG performance is associated with lower cost of equity financing, thereby enhancing enterprise value. Financial institutions are encouraged to leverage innovative financial instruments to diversify enterprise financing channels and alleviate financing constraints of enterprises that fulfill their ESG responsibilities.

This study is centred on Insecurity and Electoral Administration in Nigeria. Elections are the leading mechanism for selecting governments and a cardinal feature of democratisation. The quest for fair representation, development, good governance, inclusiveness and a true sense of belonging has been the driving force for election. The conduct of credible elections remains one of the thorny and fundamental issues in a democracy. The trajectory of electoral administration in Nigeria is long and tortuous; it precedes independence and is punctuated by the elite's scheming and cunning, electoral fraud, gimmicks and violence. Nigeria has had its fair share of insecurity from diverse sources such as banditry, insurgency, recurring violent religious crises, ethnic, resource and poverty-induced militancy, and crises occasioned by the clamour for self-determination. This has left the electoral management body in a quandary and has undoubtedly imperilled the administration of elections in Nigeria and equally accentuated the temerity for a holistic approach in reversing the trend and engendering the right atmosphere for the administration of elections. This study depends mainly on secondary sources and uses qualitative means in data analysis. It is revealed in this study that violence and various degrees of interruptions have taken the front burner in the democratisation process and are one of the dangerous dimensions in electoral administration; electoral politics remains one of the remarkable principal bases of clashes, political failure and social dislocation, Elections and their administration are some of the most complicated, time-sensitive activities undertaken by any country which will be exacerbated by insecurity. Democratic elections are successful when the electorate can make informed decisions; when faith in the process is sustained; when fraud is disincentivised, detected and punished. When insecurity is whittled down, mitigated or eradicated. The need for electoral security can never be overemphasised.

The famous Capital Asset Pricing Model (CAPM) takes into account only business risk. In practice, companies use debt financing and operate at non–zero levels of leverage. This means that it is necessary to take into account the financial risk associated with the use of debt financing along with business one. The purpose of this paper is to simultaneously take into account the business and financial risk. A new approach to CAPM has been developed that takes into account both business and financial risk. We combine the theory of CAPM and the Modigliani–Miller (MM) theory. The first is based on portfolio analysis and accounting for business risks in relation to the market (or industry). The second one (the Modigliani–Miller (MM) theory) describes a specific company and takes into account the financial risks associated with the use of debt financing. The combination of these two different approaches makes it possible to take into account both types of risks: business and financial ones. We combine these two approaches analytically, while Hamada did it phenomenologically. Using the Modigliani–Miller (MM) theory, it is shown that the Hamada’s model, first model, used for this purpose half a century ago, is incorrect. In addition to the renormalization of the beta–coefficient, obtained in the Hamada model, two additional terms are found: the renormalized risk–free return and the term dependent on the cost of debt kd. A critical analysis of the Hamada model was carried out. The vast majority of listing companies use debt financing and are levered, and the Hamada model is not applicable to them in contrast to a new approach applicable to leveraged companies. Implemented a new approach to specific companies. A comparison of the results of the new approach with the results of the conventional CAPM is shown. Two versions of CAPM (market or industry) are considered.

International cooperation and food diplomacy play a pivotal role in addressing global challenges to food security. This study explores the effectiveness of Indonesia's international partnerships and diplomatic strategies in bolstering its food security amidst global uncertainties. The research employs a mixed-methods approach, combining qualitative analysis of policy documents and interviews with key stakeholders, alongside quantitative data on food production and trade. Our findings indicate that Indonesia has benefited significantly from technical and financial assistance through collaboration with organizations such as FAO, ASEAN, and bilateral agreements with countries like Japan and China. These partnerships have facilitated the adoption of advanced agricultural technologies, improved infrastructure, and enhanced human resource capacities. However, challenges remain, including bureaucratic inefficiencies and dependency on food imports, which pose risks to sustainable food security. The study concludes that while international cooperation has provided critical support, Indonesia must further streamline its policy implementation processes and reduce its reliance on imports by fostering local production. Strengthening research and development collaborations and actively participating in global forums are also recommended to ensure long-term resilience and food sovereignty. This research provides valuable insights for policymakers and stakeholders aiming to develop effective strategies to navigate the complexities of global food diplomacy and cooperation.

Recently, environmental degradation has become an international issue due to the extensive economic activities around the globe. This aspect demands the policymakers' and new researchers’ emphasis. Hence, the present article examines the impact of corporate social responsibilities (CSR) to community and environment on the environmental performance (ENP) of the manufacturing industry in China. The article also investigates the mediating role of green innovation and environmental strategy among CSR to community, CSR to environment and ENP of manufacturing industry in China. The article gets the primary data from the selected employees of the manufacturing industry using questionnaires. The article also tests the data's validity and reliability, and association among variables using smart-PLS. The outcomes indicated that CSR to environment has a positive association with ENP. The outcomes also revealed that green innovation and environmental strategy significantly mediate among CSR to community, CSR to environment and ENP. The article guides the policymakers in making policies related to improve ENP using CSR to environment and green innovation.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

Businesses now formally enter the phase of "think power differentiation and gap" in response to the new economic climate. While AI, big data, empowerment via the internet, and other aspects of the digital economy help to improve technical capabilities and save operating costs, they also push businesses to innovate their strategies at a faster rate. Enterprises are strategically choosing to de-enterprise, moving from focusing on a single business functioning benefit to building an ecosystem of platform services that will give them a competitive edge. Additionally, the organization's structure is evolving continually from a vertical model to a curved working style, in order to achieve this, businesses must recognize the importance of data analysis in day-to-day management and operations, encourage the development of an organizational atmosphere that is driven by data, fully utilize digital technology, modularize areas or production links that perform related tasks, and encourage the reform of organizational structures. By streamlining the output of the product or service to the external community while also enhancing the company's financial performance model, switching from process-to result-oriented evaluation, and putting in place a customized authority and accountability framework. Replace outcome-focused evaluation with process-focused evaluation, and create a customized incentive scheme that balances power, accountability, and rewards.

A new class of nano-cube core-shell heterostructures containing Ag coating on the top of WO₃ was fabricated. Physical vapor deposition was used to produce WO₃ based nano-heterostructures. All kind of wet toxic chemical process was avoided to make the process simple and contaminant free. Sputtering of WO₃ and a subsequent thermal annealing process was done to create nano-cubes of WO₃. After that, sputtering of Ag was performed to form the Ag-WO₃ core-shell nano-heterostructures (CSNH). The CSNHs were characterized using field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), X-ray diffraction analysis (XRD) and UV-vis spectroscopy. The morphologies, elemental analysis, interfaces, crystallinity, phases, and chemical compositions were analyzed. The bottom-up growth of WO₃ nanocubes was studied using different time periods at 900°C. Ag coating was also studied before and after annealing. Finally, an optical property (band gap) was also analyzed using Tauc plot derive from absorption spectra. The tailoring the band gap of WO₃ from ~2.9eV to ~ 2.45 eV was observed while Ag-WO₃ CSNH formed.

A new method in which completely eliminated the negative value of the scattering power is proposed in this paper. Primarily, here are presented the Freeman-Durden decomposition of the scattering powers, which are computed by using the coherency matrix elements with rotation and without rotation. Secondly, this paper investigates the reasons of the occurrence of negative values of the scattering powers. Then using the modification like in algorithm proposed by Yamaguchi for G4U, it was applied for the algorithm of Freeman-Durden decomposition to eliminate negative values. In this research, Radarsat-2 radar remote sensing data were used, which are acquired for study area Yushu County, Qinghai province, China. At the end, the comparison results of Yamaguchi G4U and a modified Freeman-Durden decompositions were presented.

Through analysis of the constituent components of the observation data from 12 geoe-lectric field stations located approximately 600 km form the epicenter of the Jishishan Ms6.2 earthquake, this study reveals that during earthquake preparation and occurrence, the geoelec-tric field at each station exhibit non-uniform variations. These variations are characterized by significant decreases or increases in correlation coefficients between different azimuths (δxy) and between long and short polar distances within the same azimuth (δxx). Additionally, there are discrete or extruding changes observed in the dominant azimuth angles of the telluric field at the stations, ranging approximately from 40° to 90°. These anomalies indicate local site effects and exhibit quasi-synchronous temporal characteristics. The study found that stations located in regions with intense tectonic activities, such as Menyuan and Jingtai, experience more significant anomalous changes influenced by the tectonic activities of the Qaidam-Qilian Mountain block. When multiple stations with anomalous changes are used to determine the earthquake epicenter, earthquakes often occur within or near the intersection area of the predicted ranges of these sta-tions. The specific time of earthquake occurrence shows no clear relationship with the locations or tectonic activities of the stations.

The NW-SE trending dextral strike-slip faults on the north side of the Tian Shan play an important role in accommodating the crustal shortening, which mainly includes the Karatau fault, Talas-Fergana fault, Dzhalair-Naiman fault, Aktas fault, Dzhungarian fault (also named Bolokenu-Aqikekuduk fault) and Chingiz fault. The classic viewpoint is that the strike-slip fault is the adjustment product caused by the difference of the crustal shortening from west to east. Another viewpoint attributes the dextral strike-slip fault to large-scale sinistral shearing. The Alakol Lake Fault is situated along the northern margin of the Dzhungarian Gate, stretching for roughly 150 km from Lake Ebinur to Lake Alakol. Our team utilized aerial photographs, Satellite Stereo-imagery, and field observation to map the distribution of the Alakol Lake fault. Our findings provided evidence supporting the assertion that the fault is a dextral strike-slip fault. In reference to its spatial distribution, Lake Alakol is situated in a pull-apart basin that lies between two major dextral strike-slip fault lines: the Chingiz and Dzhungarian faults. The Alakol Lake Fault serves as a connecting point for these two faults, resulting in the formation of a mega NW-SE dextral strike-slip fault zone. According to our analysis of the dating samples taken from the alluvial fan, as well as our measurement of the displacement of the riser and gully, it appears that the Alakol Lake fault has a dextral strike-slip rate of 0.8-1.5mm/yr. The strike-slip rate of the Alakol Lake fault is comparatively higher than that of the Chingiz fault in the northern region (~0.7 mm/yr), but slower than that of the Dzhungarian fault in the southern (3.2-5 mm/yr). The Chingiz-Alakol-Dzhungarian fault zone shows a gradual decrease in deformation towards the interior of the Kazakhstan platform. We contend that the rate of deformation observed is better explained by the crustal shortening adjustment model, rather than the large-scale sinistral shearing model.

In the rapidly evolving field of real estate economics, the prediction of house prices continues to be a complex challenge, intricately tied to a multitude of socio-economic factors. However, traditional predictive models have often overlooked the spatial interdependencies that play a vital role in shaping housing prices. This study applies Graph Neural Networks (GNNs) on Open Statistics Knowledge Graphs to model spatial dependencies and predict house prices across Scotland’s 2011 data zones. To this end, integrated statistical indicators are retrieved from the official Scottish Open Government Data portal. The three representative GNN algorithms employed - ChebNet, GCN, and GraphSAGE - demonstrate higher prediction accuracy than traditional models, including the tabular-based XGBoost and a simple Multi-Layer Perceptron (MLP). In addition, local and global explainability are employed to increase transparency and trust in the predictions made by the most accurate GNN - GraphSAGE. The global feature importance is determined by a logistic regression surrogate model while the local, region-level understanding of the GNN predictions is achieved through the use of GNNExplainer. Explainaibility results are compared with those from a previous work that applied the XGBoost machine learning algorithm and the SHapley Additive exPlanations (SHAP) explainability framework on the same dataset. Interestingly, both global surrogate model and the SHAP approach underscored the Comparative Illness Factor, a health indicator, and the ratio of detached dwellings as the most crucial features in the global explainability. In the case of local explanations, while both methods showed similar results, the GNN approach provided a richer, more comprehensive understanding of the predictions for two specific data zones.

The need for effective bridge asset management in Indonesia has become crucial. Currently, the number of bridge assets in Indonesia is continuously increasing, parallel to the rising budget allocations for infrastructure development in the road and bridge sectors to enhance regional connectivity more efficiently. This situation places demands on asset managers to work harder and possess expertise in bridge asset management. However, the reality reveals persistent issues related to the incapacity of bridge asset managers in various regions to manage their assets effectively. This raises the question of whether asset managers have the intention to implement asset management or what factors might drive their appeal to have an intention towards effective asset management. To address these questions, a survey was conducted involving asset managers and experts to evaluate the current state of bridge asset management in Indonesia. The research findings provide insights into the relationships among factors such as budget, data, policy, resources, and system that associated with bridge asset management and the intention of an asset manager. The model's solutions show that data and system are anticipated to achieve effective and efficient implementation of bridge asset management. It is hoped that this research will assist asset managers in Indonesia in enhancing their intention towards better bridge asset management.

Composite fiber materials are superior materials due to their high strength and light weight. Composites reflect the properties of their constituents, which is proportional to the volume fraction of each phase. There are different fiber reinforcement types and each affects it’s flexural, tensile and compression strength. When selecting a composite for a specific application, the forces excreted on the composite must be known in order to determine the reinforcement type. Unidirectional fiber reinforcement will allow very strong load resistance but only in one direction where as a random orientated fiber reinforcement can resist less load but can maintain this quota in all directions. These materials are said to be anisotropic. Certain composite fibers, taking into consideration there weights, are physically stronger than conventional metals. This research deals with the analysis of three composite materials with different reinforcement types, volume fraction and phase content. It was found that material A (glass epoxy) was the strongest in the longitudinal direction with a flexural strength of 534 MPa in the longitudinal and 420 MPa in the transverse direction. The flexural stresses of material B (glass silicone) and material C (glass polyester) where both found in the 120 to 135 MPa range. Differences were due to their differences in matrix composition and reinforcement type.

Background: Leishmaniasis is a significant global public health issue that is caused by parasites from Leishmania genus. With limited treatment options and rising drug resistance, there is a pressing need for new therapeutic approaches. Molecular chaperones, particularly Hsp90, play a crucial role in parasite biology and are emerging as promising targets for drug development. Objective: This study evaluates the efficacy of 17-DMAG in treating BALB/c mice from cutane-ous leishmaniasis through in vitro and in vivo approaches. Materials and Methods: We assessed 17-DMAG cytotoxic effect on bone marrow-derived mac-rophages (BMMΦ) and its effects against L. braziliensis promastigotes and intracellular amastigotes. Additionally, we tested the compound's efficacy in BALB/c mice infected with L. braziliensis via intraperitoneal administration to evaluate the reduction of lesion size and de-crease of parasite load in the ears and lymph nodes of infected animals. Results: 17-DMAG showed selective toxicity [selective index=432) towards Leishmania amastigotes, causing minimal damage to host cells. The treatment significantly reduced lesion sizes in mice and results in parasite clearance from ears and lymph nodes. It also diminished in-flammatory responses and reduced the release of pro-inflammatory cytokines (IL-6, IFN-g, TNF) and the regulatory cytokine, IL-10, underscoring its dual leishmanicidal and anti-inflammatory properties. Conclusion: Our findings confirm the potential of 17-DMAG as a viable treatment for cutaneous leishmaniasis and support further research into its mechanisms and potential applications against other infectious diseases.

The objectives of this study was to assess the impact of a reproductive approach in high-yielding nulliparous and parous Holstein cows on the interestrus interval, estrus detection rates, conception rates, and pregnancy rates. The strategy involved giving GnRH on day 5 following artificial insemination (AI). For nulliparous cows, there appears to be no noticeable effect of GnRH therapy on the interestrus interval. In both groups, nearly all of the cows exhibited an 18–25-day cycle interval (P < 0.05). In the 18–25 day cycle period, the untreated multiparous cows exhibited the highest proportion (P < 0.05), while the treated group demonstrated the highest proportion (P < 0.05) in the 26–35 day cycle interval. The study found that the conception rate was higher in repeat breeder nulliparous and 3+ lactation treated Holstein cows compared with untreated ones. However, the cumulative heat detection rate, pregnancy rate and conception rates were similar in both groups (P > 0.05). Also, this study found that in the hottest months of the year, this therapeutic approach can't counteract the negative effect of heat stress in high-yielding dairy cows. Thus, it is not advised of using the hormonal method to create supplementary corpus luteum across the herd.

Metaverse has become an emerging trend for both academia and industry, and it seems to concern the next generation of the Internet. Although it is still in its grassroots, metaverse is estimated to bring disruption to people’s lives. One of the effects concerns the generation of new value oppor-tunities that don't exist in real life. These new types of value as well as their impact on people's lives must be explored. In this respect, this paper utilizes literature evidence to define the value types of metaverse, which are circulated with experts from the focus group on metaverse of the Interna-tional Telecommunications Union. Results uncover economic, public, and social values that metaverse generates, which can ensure its financial viability and the community's social sustaina-bility. The economic value sources come from both the industrial and the commercial sectors, while the public values concern citizen empowerment and government efficiency. The social values of metaverse concern employment growth, and the provision of immersive experiences in enter-tainment and education environments. Finally, this paper critically reviews their role for envi-ronmental, economic, and social sustainability. The literature review indicated that metaverse can on the one hand, enhance sustainability but on the other hand, it can cause environmental impact.

In this research, the primary goal was to investigate the relationship between strategic planning and organizational performance in Iraq's manufacturing context. The study's primary data sources were 360 manager respondents. The structured questionnaire was used to collect primary data from manufacturing firms located throughout Iraq. To analyze the result, the researcher used descriptive statistics, correlation, and multiple regression analysis. SPSS version 16 software was used to conduct data analysis. The result reveals that the process of strategic planning has a beneficial effect on financial performance. Environmental scanning has a statistically significant positive effect on a company's non-financial performance. Management participation and planning formality positively and statistically significantly affect a business's non-financial performance at the 10 percent level. The domain of strategy and technique has not impacted the company's non-financial performance.

Waterbomb structures are origami-inspired deformable structural components used in new types of robots. They have a unique radially deployable ability that enables robots to better adapt to their environment. In this paper, we propose a series of new waterbomb structures with square, rectangle, and parallelogram base units. Through quasi-static axial and radial compression experiments and numerical simulations, we prove that the parallelogram waterbomb structure has a twist displacement mode along the axial direction. Compared with the square waterbomb structure, the proposed optimal design of the parallelogram waterbomb structure reduces the critical axial buckling load-to-weight ratio by 55.4% and increases the radial stiffness-to-weight ratio by 67.6%. The significant increase in the radial stiffness-to-weight ratio of the waterbomb structure and decrease in the critical axial buckling load-to-weight ratio make the proposed origami pattern attractive for practical robotics applications.

Hazelnut shells (HS), scientifically known as Corylus avellana L. shells, are a waste produced in companies that process nuts. The main objective of this study was to find an efficient way to maximize the chemical potential of HS by solubilizing the hemicelluloses, which could then be used to recover sugars and at the same time increase the lignin content of this material in order to produce adhesives or high strength foams. In order to optimize the pre-hydrolysis process, two different temperatures (160 and 170 C) and times varying from 15 to 180 min were tested. All the remaining solid materials were then liquefied by polyalcohols with acid catalysis. The chemical composition of hazelnut shells was determined before and after the pre-hydrolysis. All the process was monitored by FTIR-ATR by determining the spectra of solids and liquids after pre-hydrolisis and liquefactions steps. The highest solubilization of hazelnut shells was found for 170 C and 180 min, resulting in a 25.8% solubilization. Chemical analysis after the hydrolysis process showed a gradual increase in the solubilization of hemicelluloses as both the temperature and time of the reactor were increased. Simultaneously, the percentages of α-cellulose and lignin in the material also increased with rises in temperature and duration. FTIR-ATR allowed for the detection of significant spectral changes in the hazelnut shells from their initial state to the solid residue and further into the liquefied phase. This confirmed that pre-hydrolysis was effective in enhancing the chemical composition of the material, making it more suitable for the production of adhesives or polyurethane foams with enhanced mechanical strength.

Background and Objectives: The purpose of this study was to investigate whether early surfactant administration affects the status of ductus arteriosus (DA) in preterm infants ≤32 weeks of gestational age (GA) within 24 hours of birth. Materials and Methods: It is a prospective study conducted from March 15, 2022, to November 15, 2023, in a tertiary academic center. In-born infants ≤ 32 weeks of gestation (n = 88) were enrolled. The study group was further divided into surfactant (n=44) and non-surfactant (n=44) subgroups. Results: 76% of the preterm infants who received surfactant therapy (RRR = 0.839) recorded an increase in Kindler Score at 24 hours of life (1-RR = 1-0.24 = 76%). Surfactant administration was significantly associated with decreased pre-ductal diastolic pressure (29.9 mmHg vs. 34.8 mmHg, p=0.0231), post-ductal diastolic pressure (28.7 mmHg vs. 32.2 mmHg, p=0.0178) pre-ductal MAP (41.6 mmHg vs. 46.5 mmHg, p=0.0210) post-ductal MAP (41.0 mmHg vs. 45.3 mmHg, p=0.0336). There were no significant changes in ductus arteriosus parameters at 24 hours of life. Conclusions: Early surfactant administration does not affect the status of ductus arteriosus in preterm infants ≤32 weeks of gestational age at 24 hours of life.

Smart City has emerged as the mainstream paradigm for urban governance innovation, sustainable development, and strategy upgrades, which is drawing attention from scholars worldwide. However, current frameworks for Smart City assessment remain incomplete and simplistic. In is paper, 30 national or provincial capitals in China were selected and we designed a tri-dimensional SPI model—Social, Physical, and Information Space—for smart city spatial development assessment. Utilizing methods such as entropy weighting, coupled coordination degree models, and the Dagum Gini coefficient, this study assesses the spatial development and coupled coordination of 30 cities from 2011 to 2019. Finally, by means of BP neural networks, the study examines the contribution of each indicator to the spatial coupled coordination. The results indicated that with a narrowing disparity in development speeds among different regions, the spatial coupled coordination development level of smart capitals in China has steadily increased, presenting a pattern of staggered distribution. Moreover, the IS subsystem plays the most significant role in coupled coordination. The significance of this research lies in its tri-dimensional spatial perspective of the spatial development and coupled coordination differences of the Smart City, providing evidence-based support for the regional layout and optimization in China.

The emergence of Distributed Ledger Technology (DLT) in the past decade has challenged our imagination to discover new, innovative and disruptive solutions to problems in domains ranging from finance and healthcare to supply chain and smart cities. However, the enormous energy consumption that has been observed in some of the most successful DLT applications raises the question of their long term sustainability. This article reviews the standardization efforts of the International Telecommunications Union (ITU) to provide guidelines to regulators and policy makers for making informed decisions on the applicability and sustainability of DLT architectures from the point of view of energy consumption.

This article presents a description of a new method for solving the factorization problem, based on the gradient descent algorithm. This approach demonstrates significant improvements in efficiency compared to traditional methods proposed in previous research. This article describes a new method for solving the factorization problem, based on the gradient descent algorithm, and demonstrates the transition from algebraic methods to approaches based on functional analysis. The proposed approach not only improves the efficiency of solving the problem but also allows the application of computational algorithms of functional analysis, opening new possibilities for research and optimization.

Background and Objectives: This study aimed to evaluate the histological and biochemical ef-fects of capsaicin on implant osseointegration and oxidative stress. Materials and Methods: Male Wistar albino rats weighing between 250 and 300 grams were used in this study. Twenty-four rats were randomly divided into three equal groups: implant + control (n= 8), implant + capsai-cin-1 (n= 8), and implant + capsaicin-2 (n= 8). 2.5 mm diameter and 4 mm length titanium im-plants were surgically integrated into the corticocancellous bone parts of the femurs. In the treatment groups, rats were injected intraperitoneally with 25 mg/kg (implant + capsaicin-1) and 50 mg/kg (implant + capsaicin-2) of capsaicin. No additional applications were made in the con-trol group. Three rats in totally were died during and after the experiment, as a result of the an-alyzes performed on 21 animals. Results: The highest total antioxidant status value was found in capsaicin dose 2, according to the analysis. The control group had the highest total oxidant status and oxidative stress index values, while group 2 of capsaicin had the lowest. After analysis, we found that there was no observed positive effect on osteointegration in this study (p> 0.05), alt-hough the bone implant connection was higher in the groups treated with capsaicin. Conclusi-ons: A positive effect on osteointegration was not observed in this study. This may be due to os-teaclast activation. However it was found that it has a positive effect on oxidative stress. Osteo-clast activation may be the cause of this phenomenon. Capsaicin was found to have a positive effect on oxidative stress (p

Catastrophic mass flows originating from the high mountain cryosphere often cause hazard cascades. With increasing human activities in the alpine region and the sensitivity of glaciers, snow and permafrost to climate warming, the cryospheric hazard risks tend to be more active in the Tibetan Plateau(TP). The remoteness and inaccessibility of high mountain regions make the remote sensing technology the most effective approach for monitoring and investigating the cryospheric hazards. Exploring the evolution process and impact of ice avalanches and subsequent hazards are crucial to understand drivers and nature of mass flow process chain in order to prevent and mitigate potential hazard consequences. In this study, the glacier and ice-rock avalanches occurred in Arutso and Sedongpu basins in Tibet were investigated on the basis of Sentinel-2 time-series images and in-situ investigation, the evolution process of these events were reconstructed, and impacts and driving factors were analyzed. The massive Chamoli rock-ice avalanche occurred in February 2021 in the western Himalayas was also reviewed using using same methods. The study shows that Arutso glacier No. 53 (Arutso-53) avalanche completely melted away in July 2018 after two years from occurrence to final disappearance, while Arutso glacier No. 50 (Arutso-50) avalanche completely melted by the end of August 2023 after lasting for seven years. Four large-scale ice-rock avalanche and debris flow events in the Sedongpu basin in 2017 and 2018 not only had significant impacts on the river flow, landscape and geomorphologic shape in the basin, but also caused serious disasters in the basin and downstream. In March 2021, a small-scale ice-rock avalanche and debris flow event occurred again in the Sedongpu basin. The glacier and ice-rock avalanches occurred in Tibet area were mainly induced by climate warming, heavy precipitation and seismic activity, which acting on specific topographic and geomorphic structure of glacier properties in the high mountain regions. Catastrophic hazard events originating from the high-elevation glacier and ice-rock collapses in the mountain cryosphere and subsequent hazard cascades in the TP and Himalayas highlight the importance of mountain hazard monitoring, early warning systems and sustainable mountain development.

We present a hierarchical reinforcement learning (RL) architecture that employs various low-level agents to act in the trading environment, i.e. the market. The highest level agent selects among a group of specialised agents, and then the selected agent decides when to sell or buy a single asset for some period. This period can be variable according to a termination function. We hypothesized that due to different market regimes, more than one single agent is needed when trying to learn from such heterogeneous data, and instead, multiple agents will perform better, with each one specialising in a subset of the data. We use $k-means$ clustering to partition the data and train each agent with a different cluster. Partitioning the input data also helps model-based RL (MBRL), where models can be heterogeneous. We also add two simple decision-making models to the set of low-level agents, diversifying the pool of available agents and thus increasing overall behaviour flexibility. We perform multiple experiments showing the strengths of a hierarchical approach and test various prediction models at both levels. We also use a risk-based reward at the high level, which transforms the overall problem into a risk-return optimization. This type of reward shows a significant reduction in risk while minimally reducing profits. Overall, the hierarchical approach shows significant promise, especially when the pool of low-level agents is highly diverse.

Amid the array of challenges prompted by the COVID-19 pandemic, the policy response of governments proved vital. The U.S. states pursued varied policy approaches that demonstrated distinct divergences in impact. Particularly, contrasting state contexts produced markedly assorted frameworks for the delivery of public health services, which indicate potential effects for COVID-19 policy implementation. Using the rates of COVID-19 vaccinations as a measure of policy execution, the purpose of this study is to examine the political and administrative influences contributing to differences in COVID-19 public health policy outcomes among the U.S. states. Ordinary least squares (OLS) regression models included data sources of nationally representative information pertaining to state public health attributes of politics and administration during the height of the pandemic and vaccine campaign. The findings suggest that state political and fiscal orientations display significant associations with COVID-19 vaccination disparities, while other administrative indicators did not. The results signal important policy implications for the politics-administration dynamic within the COVID-19 pandemic and offer further understanding toward the roles of federalism and governance in future public health emergencies.

This article presents a comprehensive framework for valuing financial instruments subject to credit risk. In particular, we focus on the impact of default dependence on asset pricing, as correlated default risk is one of the most pervasive threats in financial markets. We analyze how swap rates are affected by bilateral counterparty credit risk, and how CDS spreads depend on the trilateral credit risk of the buyer, seller, and reference entity in a contract. Moreover, we study the effect of collateralization on valuation, since the majority of OTC derivatives are collateralized. The model shows that a fully collateralized swap is risk-free, whereas a fully collateralized CDS is not equivalent to a risk-free one.

In this study, I extend the Fama and French five-factor asset pricing model with a sixth factor, namely, carbon risk, to investigate its impact on equity returns. To measure carbon risk, a new factor ‘pollutant minus green,’ is developed using the difference between the weighted average returns of pollutant and green firms across 51 developed and emerging countries across four categories—North America, Europe, Emerging Markets, and the Asia Pacific. The results reveal that North America, Europe, and Asia Pacific markets have a carbon risk premium that gets eliminated in small-cap firms. The carbon risk factor is further tested in left-hand side (LHS) test asset portfolios and found to be more pronounced with size-effect anomaly; specifically, small stock firms report greater declining average returns because of more exposure than the mega-cap stocks to carbon dioxide emissions. Furthermore, size-effect anomaly prevails with profitability and investment factors across firms. Therefore, high profitability, as well as high investment small firms, show a greater decline than the big stock firms in average returns when their carbon dioxide emissions increase. The asset pricing model evaluation is carried out through the Gibbons, Ross, and Shanken test. The six-factor model directed at capturing carbon risk patterns in average equity returns performs better than the three-factor and five-factor models of Fama and French (1993 and 2015) in the majority of categories under 3x3 sorting and compete with both Fama and French model under 2x4x4 sorted LHS portfolios. The finding of this study offers various useful applications for investors, policymakers, brokers, corporations, governmental pollution abatement institutions, and other stakeholders who wish to obtain carbon risk premium.

Sentinel-1A/B radar remote sensing data were applied for the first time to determine the sixth nuclear test, its underground explosion h-bomb location and affected zone in North Korea, on September 3, 2017. Location of epicenters nuclear test were found according to line-of-sight displacement images via its maximum value. Line-of-sight displacement images were obtained by processing in the GMTSAR package in the VirtualBox virtual machine of the Linux Ubuntu 16.04 operation system. In this research, three scenes Sentinel-B data with descending orbits were considered, one after and two before the event (the nuclear test date) scene were used.

This article described the technology of determining earthquake epicenter with radar remote sensing on the example of Sentinel-1A/B. To determine the epicenter of the earthquake, the Earth's crust displacements were analyzed using radar remote sensing data obtained for the ascending and descending flight orbits. Coordinates of Earthquake epicenters were found according to line-of-sight displacement images via its maximum value. Displacement of the Earth's crust was obtained by processing in the GMTSAR package in the VirtualBox virtual machine of the Linux Ubuntu 16.04 operation system. Two earthquakes that occurred in 2020 were studied to determine the accuracy of finding epicenters using the ascending and descending orbits Sentinel-1A/B. These earthquakes occurred in Western Xizang, China, and Doganyol, Turkey. The maximum deviation from the officially registered epicenter coordinates was 15.38 km for Doganyol and 3.2 km for the Western Xizang earthquake. The negative displacement was 90 mm for Doganyol and 50 mm for Western Xizang.

Dry intrusion is an important mid-latitude atmosphere phenomenon within the upper troposphere and lower stratosphere. It is always found to be related to the cyclogenesis, rainstorm, as well as convection generation and precipitation enhancement. Since the atmosphere environment for any of these above-mentioned weather is terribly complicated, those preexisting popular schemes which takes no account of water vapor may not suitable for detecting the dry intrusion related to these weathers. With regard to the merits and demerits of the current preexisting schemes, a new scheme based on Fengyun-2E geo-stationary satellite data is presented in this study to detect the atmospheric dry intrusion. The scheme is set up based on the statistical relationship between water vapor at high level troposphere, the general moist potential vorticity, ozone concentration and upper-level jet. After using the total amount of ozone and ozone profile operational products retrieved by Fengyun-3 Polar Orbiting Meteorological Satellites and the potential vorticity calculated by ECMWF Interim data for validation, this scheme is applied to analyze two typical middle-latitude weather processes. One is the famous Beijing extreme rainfall of 21 July 2012 and the other is a hailstorm occurred on the eastern China during March 19, 2014. A good application effect in both cases suggests that our new method of detecting dry intrusion is feasible and can be helpful in middle-latitude disastrous weather monitoring and forecasting.

This study explores the elements that influence consumer vegetarian diet choices in parts of South Korean provinces. The study examines these explanatory variables: ethical-animal-welfare, health, environment, social issues , mood-emotion, and religious-beliefs with vegetarianism serving as the dependent variable. The Likert scale data from 264 respondents were analyzed using logistic regression analysis. Results show that health, ethical-animal-welfare ideals as well as environmental concerns emerge as significant variables influencing the decision to embrace a vegetarian diet. This shows that consumers (international students) in Korea are becoming more aware of and concerned about health, ethical and sustainable dietary choices. Secondly, health plays a crucial role in the vegetarian diet selection, indicating that health-conscious people are more inclined to choose a vegetarian lifestyle. Religious belief and mood have various degrees of influence on the vegetarian diet decision. The findings of this study have consequences for consumer behavior, marketing managers, and decision-makers. Businesses in the food industry, in particular, can gain from catering to the needs and tastes of consumers that prioritize ethical-animal welfare ideals, as well as those that value health and environmental sustainability. Creating and advertising vegetarian and vegan choices in local restaurants can effectively attract and serve this specific target demographic.

This paper seeks to fill in the gaps of modern relativistic Cosmology by utilizing the total symmetry between space and time dimensions and re-interpreting the scale factor of the Universe as a gravitational potential generated by the mass/energy of the entire Universe as a whole. The gradient of this potential is along the cosmological time dimension through which the Universe is falling. This gradient gives us an arrow of time, we find explanations for why the Universe began expanding and why the expansion is accelerating without the need for a Cosmological Constant. In a finite time, the gradient will point in the opposite direction of time turning the expanding Universe into a collapsing one where it is shown that when placing the Schwarzschild metric in the dynamic Cosmological background, gravity becomes repulsive and things like would-be Black Holes become White Holes. The model naturally describes a Universe and an anti-Universe (consisting of antimatter) moving in opposite directions of time that collide at the end of collapse, annihilating and subsequently pair producing two new Universes as the cycle begins again. It is shown that the model's Hubble diagram fits the currently available supernova and quasar data. It is found that Dark Matter can perhaps be understood as ordinary matter that is not connected to us with null geodesics.

For most people, using social media to research products has become common. Despite previous research, there is a gap in understanding reviewers' product-related comments and how they lead to purchase intentions. In terms of contributions, this study analyses people's dependence on social media for product information in purchase intention while considering the moderating impact of risk and trust on the link between purchase intention and social media. The data were collected quantitatively using surveys. The sample consisted of 384 students. The study hypotheses were tested using the PROCESS macro after exploratory factor analysis and correlation analysis were conducted. Among those surveyed, it was confirmed that most people sought product-related comments on social media when seeking information about a product they might be interested in purchasing. It was also observed that the risk factor reduced the impact of other variables in the model presented in this study. In conclusion, this investigation is more reliable, and its outcomes benefit scholars, supervisors, merchants, and webmasters, for instance, in establishing a study for future research efforts and providing practical guidance that could boost promotional efforts and marketing activities, especially in this era of artificial intelligence.

Two novel core-shell composites SiO2@PMDA-Si-Tb, SiO2@PMDA-Si-Tb-phen with SiO2 as the core and terbium organic complex as the shell, were successfully synthesized. The terbium ion was coordinated with organic ligand forming terbium organic complex in the shell layer. The bi-functional organosilane ((HOOC)2C6H2(CONH(CH2)3Si(OCH2CH3)3)2 (abbreviated as PMDA-Si) was used as the first ligand and phen as the second ligand. Furthermore, the silica-modified SiO2@PMDA-Si-Tb@SiO2, SiO2@PMDA-Si-Tb-phen@SiO2 core-shell-shell composites were also synthesized by sol–gel chemical route. An amorphous silica shell was coated around the SiO2@PMDA-Si-Tb and SiO2@PMDA-Si-Tb-phen core-shell composites. The core-shell and core-shell-shell composites both exhibited excellent luminescence in solid state. The luminescence of core-shell-shell composites was stronger than that of core-shell composites. Meanwhile, an improved luminescence stability property for the core-shell-shell composites was found in the aqueous solution. The core-shell-shell composites exhibited bright luminescence, high stability, long lifetime, and good solubility, which may present potential applications in the field of bio-medical.

The present research focuses on the endogenous development theory and investigates the relationship between economic growth (dependent variable) and renewable energy consumption, technological innovation, and export diversification (independent variables) in seven emerging economies known as the E-7. Previous studies have examined these factors individually but have not explored their combined impact on the E-7 economies. Therefore, this study contributes to the existing literature on the effects of renewable energy consumption, technological advancement, and export diversification on economic development. The study analyses the dynamic connection among these variables in seven selected emerging countries: Brazil, China, Indonesia, India, Mexico, Russia, and Turkey. Panel data from 1990 to 2022 is utilized, and various methodologies, including panel cointegration, the PMG-ARDL estimator, and robustness tests such as FMOLS and DOLS, are employed. Empirical inferences are drawn using the Dumitrescu-Hurlin Panel Causality (DHC) test, and the long-run relationships among the variables are validated using the Westerlund residual cointegration tests. The results from the PMG-ARDL estimator show that renewable energy consumption, technological advancement, and export diversification have a significant and positive impact on economic expansion, confirming the validity of the endogenous growth model in the E-7 countries. The control variable of the financial sector has a positive but insignificant effect on economic growth, while trade openness has a negative and significant effect. The DHC test results indicate a neutral feedback effect of renewable energy consumption on economic growth. The findings also reveal a unidirectional causal relationship between technological innovation and economic growth. Overall, these findings provide valuable insights for economic policymakers in the E-7 countries. By removing barriers to renewable energy consumption, technological innovation, and export diversification, policymakers can promote sustainable economic development.

Cannabidiol (CBD) is a safe and non-psychotropic phytocannabinoid with a wide range of potential therapeutic antiinflamatory and antioxidant activity. Due to its lipophilicity, it is normally available dissolved in oily phases. The main aim of this work was to develop and characterize a new formulation of a microemulsion with a potential anti-inflammatory and antioxidant action for topical treatment of inflammatory skin disorders. The micro-emulsion system was obtained from a 20% CBD oil as hydrophobic phase, Labrasol/Plurol Oleique (1:1) as surfactant and cosurfactant (S/CoS) respectively and an aqueous vegetal extract obtained from S. ebulus L. ripe fruits, with a potential anti-oxidant and anti-inflammatory activity, as water phase. A pseudo-ternary phase diagram was elaborated, selecting an optimal proportion of 62% (S/CoS), 27% CBD oil and 11% water and, after testing its reproducibility, the aqueous phases were replaced by the vegetal hydrophilic extract. The defined systems were characterized in terms of conductivity, droplet size by laser scattering, compatibility of components by differential scanning calorimetry and rheological properties using a rotational rheometer. The designed microemulsion showed good stability and a slight pseudo-plastic behavior. The release properties of CBD from the oil phase and caffeic acid from the water phase of the microemulsion were studied by in vitro diffusion experiments using flow-through diffusion cells in comparison to a CBD oil and a microemulsion only with CBD as active substance. It was evidenced that the inclusion of the original oil in microemulsions did not provoke a significant modification of the release of CBD, incorporating the possibility of including hydrophilic active compounds in the formulation, stablishing an interesting strategy for the development of future formulations.

Hydrodynamic modeling and hazard mapping are essential tools for urban flood mitigation and spatial planning. Leveraging software like HEC-RAS (Hydrologic Engineering Center - River Analysis System) and ArcGIS, this study aimed to map flood-prone areas along the Jijia River in the Ungheni administrative unit of Iasi County. Human-induced environmental changes and global climate shifts have heightened flood risks worldwide, particularly in urbanized areas. Hydrological and hydraulic modeling anticipate and assess flood events, while hydrodynamic modeling accurately simulates flow propagation, in-forming flood extent, timing, and volume. Flood hazard maps offer essential insights into flooded areas, water depths, and velocities, assisting in risk assessment and mitigation strategies. Through the use of different scenarios, river modeling aims to accurately replicate real-world conditions. This study focuses on Ungheni commune in Iasi County, Romania, situated along the Prut River's eastern bank. Utilizing a combination of fixed-grid and irregular mesh elements in modeling al-lows for fine-tuning of flow details and optimization of simulation times. Model accuracy, particularly regarding peak river levels, hinges on hydrograph duration. While a 30-minute error is typically accepted, greater tolerances may apply to river basins with longer response times. The extraction and processing of model results, including maximum water depths, flood extents, and velocity maps, are facilitated by ArcGIS, providing valuable data for effective flood management strategies.

This article analyzes the perspectives of professional training of the public administration staff, from the viewpoint of the sustainability criteria, starting from the experiences of the online courses run in the last two years. In order to understand the nature, type and magnitude of the changes caused by the Covid-19 pandemic in the field of professional training for public administration, we performed a survey among public institution employees, by applying a questionnaire. The instrument included qualitative elements, to allow the framing of statistical results. The article is grounded on the hypothesis that the professional training activities in the last two years were organized preponderantly online and it aims to analyze the sustainability of the new teaching systems/methods. The limitations of the study are given by the fact that each administrative system has structure particularities and its own legal framework regarding the professional training of public administration staff, what makes that the model proposed cannot be applied in all countries. The study provides a model of online professional training for public administration staff, sustainable, based on the experience accumulated in the last two years.