Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating an artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) global level where all countries are considered as a monolithic group; and (b) cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using a nonlinear autoregressive recurrent neural network with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with the objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by finetuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSE) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.

The La Oroya metallurgical complex reveals a process of structural or power pathology, where economic and environmental social policies lead to a citizenry without systemic freedom, characterized by environmental contamination (PAMA executed on average 67%, some processes with 0%) and sanitary (plumbosis 8.39 to 10.28 μg / dL), the economic dependence of this industry is also observed, which caused the weakening of the communities to maintain autonomy over their own destinies.The Doe Run Peru, operated the metallurgical complex, creating added value to the extractive-export chain of mineral concentrate, but also took advantage of the legal loopholes, the little coordination between the State institutions and the little authority of the supervisory institutions to get the most out of it, complying with the law in some cases, but without moral quality in some others, such as health in the oroinos.Government institutions must have strong links that provide a normative framework with prospects with sustainable development, where the beneficiary is society and not only certain interest groups. The economic benefits of the metallurgical complex operation are multiple, which begin with labor, the purchase and sale of materials and services, the collection of taxes and energy.

In the ongoing Covid-19 pandemic, if a preventive restriction (PR), intended to arrest the transmission of the virus, is effective we expect a decrease in the rate of transmission. If an effective PR is lifted or relaxed, the rate may show some increase. We test this expectation in the history of PR imposition and relaxation in all countries based on available public database. We found marginal or no negative correlation between standing stringency index of PR and change in slope of the local curve. A change in stringency index was significantly negatively correlated with change in slope, but change in stringency of PRs could explain only 6.1 percent of the variance in rates of transmission. The distribution of slope changes after imposing versus after relaxing PRs was highly overlapping with only a tail consisting of 4.5 % PR impositions being clearly non-overlapping with PR relaxation. Non-parametrically, only 9.4% of PR impositions were associated with a reduction in the slope above the expectation of a null hypothesis. In brief, globally, preventive restrictions have played a very small role in the pandemic process over the one year period. This feedback needs to be considered in making policy for disease prevention in the further course of the pandemic as well as in any future threats of respiratory disease epidemics.

Tropical island countries are often highly populated and deliver immense ecosystem service benefits. As human wellbeing depends on these ecosystems proper management is crucial in the resource-rich tropical lands where related research is less. Though the ecosystem service and biodiversity studies are a promising path to inform the ecosystem management for these mostly developing countries published evidence of using ecosystem service studies in decision-making is lacking. The purpose of this study is to provide an overview of ecosystem services and related research in Sri Lanka examining trends and gaps and how these studies are conceptualized. Out of considered 139 peer-reviewed articles majority of articles 42.4% were terrestrial and forest related while coastal ecosystems were considered in 34.5% of studies. In most studies, the ecosystem service category was provisioning (33.8%) followed by regulatory service (30.9%). Studies investigating and quantifying ecosystem services, pressures on ecosystems, and their management were fewer compared to studies related to biodiversity or species introduction. Moreover, studies investigating the value of ecosystem services and biodiversity to the communities or involvement of stakeholders in the development of management actions regarding the ecosystem services were rare in Sri Lanka and intense focus of future studies in these aspects are timely and necessary.

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

Small Island States (SIDS) are among the nations most exposed to climate change (CC) and are characterised by a high degree of vulnerability. Their special nature means there is a need for more studies focused on the limits to CC adaptation on such fragile nations, particularly in respect of their problems and constraints. This paper addressed a perceived need for research into the limitations of adaptation on SIDS, focusing on the many restrictions which are unique to them. The main research question raised by this study was that how and to what extent the challenges by human activities (e.g., agriculture and tourism) posed to coastlines of SIDS could be addressed. This paper identified and described the adaptation limits they have, by using a review of the literature and an analysis of case studies from a sample of five SIDS in the Caribbean and Pacific regions (Barbados, Trinidad and Tobago, Cook Islands, Fiji, Solomon Islands, and Tonga). The findings of this research showed that an adaptable SIDS is characterised by awareness of various values, appreciation and understanding of a diversity of impacts and vulnerabilities, and acceptance of certain losses through change. The implications of this paper are two-fold. It explains why island nations continue to suffer from the impacts of CC, and suggest some of the means via which adequate policies may support SIDS in their efforts to cope with the threats associated with a changing climate. This study concluded that, despite the technological and ecological limits (hard limits) affecting natural systems, adaptation to CC is not only limited by such complex forces, but also by societal factors (soft limits) that could potentially be overcome by more adequate adaptation strategies.

The road traffic injuries risk factors such as driving offenses and average speed are concerns for health organizations to reduce the number of injuries. Without any comprehensive view of each road, one cannot decide about the effective policy. In this manner, the data-driven policy will help to improve and assess the decisions. The count data near the road of two airports is surveyed for investigating the time-varying speed zones. The descriptive statistics, ANOVA, and functional data analysis were used. The hourly data of traffic counts for four different locations at the entrance of the two airports, international and domestics, were collected for one the year 2018 to 2019.The hourly pattern of driving offenses for each road was assessed and the to and from airport roads had different peaks (<0.05). The hour, weekdays, type of airport, direction and their interactions were statistically significant (<0.05) for the chance of driving offenses. The speed average during the day was statistically different (<0.5) by the number of different types of vehicles. The traffic count data is a great resource for decision making in safe driving subjects such as driving offenses. With functional data analysis, we can analyze them to get the most of the characteristics of this data. The airports are public places with high traffic demand in all countries that yields the different pattern of traffic transportation, therefore we extract the factors that affect the driving offenses. Finally, we conclude that conducting a time-varying speed zone near the airports seems vital.

Policy induced decline of human mobility has been recognised to be effective in controlling the COVID-19 spread especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling data of confirmed COVID-19 cases with Google mobility data in Australia, we present a state-level empirical study to: 1) inspect the temporal variation of COVID-19 spread and the change of mobility adherent to social restriction policies; 2) examine the extent that different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and 3) analyse the time-lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time-lag effect on growth rates, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between mobility and COVID-19 spread varies across space and time, and subjects to the types of mobility. Thus, it is important for governments to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.

Open campus policies that grant access to the off-campus food environment influence U.S. high school students’ exposure to unhealthy foods, yet predictors of these policies are unknown. Policy holding and built (walkability), food (access to grocery stores), social (school-to-neighborhood demographic similarity), and organizational (policy holding of neighboring schools) environment data were collected for 200 Oregon public high schools. These existing data derived from the Oregon School Board Association, WalkScore.com, 2010 Decennial Census, 2010-2014 American Community Survey, Supplemental Nutrition Assistance Program, TDLinex, Nielson directories, U.S. Department of Education, National Center for Education Statistics, and Common Core of Data. Most (67%) of Oregon public high schools had open campus policies. Logistic regression analyses modeled open campus policy holding as a function of built, food, social, and organizational environment influences. With health and policy implications, results indicate that schools’ walkability, food access, and extent of neighboring open campus policy-schools are significantly associated with open campus policy holding in Oregon.

Energy and Environment Tax is used globally as a means of environment policy. Energy and Environment tax plays an important role as a driving force for the conversion to environmentally friendly energy. The basic tax principles considered in the design of energy and environmental taxation increases the efficiency of policy instruments. The purpose of this study is to evaluate South Korea’s energy and environmental taxation based on tax principles, namely, equity, efficiency, simplicity, flexibility, and accountability and to suggest directions for improvement. This study applied a methodology that provides policy implications, such as reviewing existing literature and comparing energy and environmental taxes. Results of this study show that South Korea’s energy and environmental taxation is negative in terms of equity, simplicity, and accountability. South Korea’s current energy and environmental tax is regressive to income classes and complex tax structures and it does not objectively measure the impact of energy and environmental taxation. However, energy and environmental taxation is evaluated positively in terms of efficiency and flexibility because it meets the greenhouse gas reduction policy and operates a flexible tax rate. The results of this analysis provide policy implications for reorganizing South Korea’s energy and environmental taxation

Energy taxation is used globally as a means of energy policy. Energy tax plays an important role as a driving force for the conversion to environmentally friendly energy. The basic tax principles considered in the design of energy taxation increases the efficiency of policy instruments. The purpose of this study is to evaluate South Korea’s energy taxation based on tax principles, namely, equity, efficiency, simplicity, flexibility, and accountability and suggest directions for improvement. This study applied a methodology that provides policy implications, such as reviewing existing literature and comparing energy taxes. Results of this study show that South Korea’s energy taxation is negative in terms of equity, simplicity, and accountability. South Korea’s current energy tax is regressive to income classes and complex tax structures and it does not objectively measure the impact of energy taxation. However, energy taxation is evaluated positively in terms of efficiency and flexibility because it meets the greenhouse gas reduction policy and operates a flexible tax rate. The results of this analysis provide policy implications for reorganizing South Korea’s energy taxation.

In this study, the prevalent methodology for design of the industrial policy in developing countries was critically assessed, and it was shown that the mechanism and content of classical method is fundamentally contradictory to the goals and components of the endogenous growth theories. This study, by proposing a new approach, along settling Schumpeter's economic growth theory as a policy framework, designed the process of entering, analyzing and processing data as the mechanism of the industrial policy in order to provide "theoretical consistency" and "technical and Statistical requirements" for targeting the growth stimulant factor effectively.

In this paper we take China’s one child policy as an example and investigate its environmental impact. We develop a model for an economy using a standard overlapping generation model extended with human capital, endogenous fertility, and changing life expectancy. To model the environmental impact of economic activities, we use a modified IPAT model. We show that China’s one child has a very strong positive impact on the environment, particularly if we consider the whole human legacy.

It is well recognised that the mining industry in South Africa is highly rated for its substantial contribution to the country’s economic growth, including employment and infrastructural development. It is also known that mining and ore processing activities potentially pose a severe threat to public health and environmental well-being, in the way operations are carried out, mine wastes are disposed of (in dumps), local communities are relocated, mine management and the mining community in general, perceive established environmental standards and etiquette. This paper examines ethical practices and norms in the South African mining industry, with particular reference to the management of tailings dams. We analyse the modes of articulation of the country’s regulatory instruments for tailings management, and review the corporate social responsibility (CSR) approach of leading mining companies. Despite decades of research and resulting recommendations on tailings management, it is concluded that current legislations are largely ineffective, level of adherence by mine management and the mining community, low, and mechanisms for compliance monitoring, weak. New perspectives on legislative issues for unsolved problems in tailings handling are put forward, and directions for future research, indicated.

Globally, humans are struggling with the double threat of communicable and non-communicable diseases, which are presenting new challenges to public health. Public health problems are generally studied and addressed at primary, secondary and tertiary levels. Most effective results are seen with primary interventions. Public health is becoming more aware of the importance of environment-gene interactions in the ontology of health and disease using epigenetics. Epigenetics is the study of altered gene expression without change in base pairs. Be it physical, social, behavioral, or economic factors; they all influence quality of life and health of individuals and populations. That environments are changing the human health phenotype and these changed phenotypes are heritable is of concern for the future of the human race. Knowing the causes of non-communicable human diseases using epigenetics will contribute to the development of new policies to encourage prevention using primary public health initiatives. Research and application of epigenetics shows great promise for improving population health. Continued advances in epigenetics will enhance how we understand and address the way environments are affecting the human health phenotype. For some time, health systems have been and continue to be tertiary in nature. Epigenetic changes can provide information necessary to better understand how social determinants of health can be used to build societies focused on equitable health for all people, rather than continuing to focus on treatment of diseases in the tertiary phase that leads to health disparities. Understanding mechanisms of social determinants of disease, will allow society to evolve in a health-oriented rather than a disease-oriented world. For this reason, we must enhance and apply epigenetics (physical, social, behavioral, economic) research to policy development. We will discuss how bringing social determinants together with biology can be used as new tools for public health policy.

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 work aims to explore the impact of side loads, drill-pipe tool-joint (DP-TJ) speed (RPM), and mud type on the austenitic stainless steel SM2535-110 casing wear characteristics. Actual field drill pipe tool joints, casings, and drilling muds are used in this study. The results of the study show that under both types of lubrication, the wear volume increased with radial load and DP-TJ speed. SM2535-110 casing specimens tested under oil-based mud (OBM) lubrication had higher casing wear volumes than those obtained under water-based mud (WBM) lubrication. This unexpected behavior is mainly due to the increase in the surface hardness of the casing specimens tested under WBM. The results also show that the specific wear factor (K) values of specimens tested under WBM are in general 2 to 4 times higher than those obtained under OBM. While K values under WBM increase with both the side load and RPM, those under OBM show a sharp decrease with RPM. This behavior under OBM is due to this lubricant’s higher viscosity and the change of lubrication regime from thin film to thick film lubrication at higher RPM. Scanning electron microscopy (SEM) and the digital microscopic imaging (DMI) of SM235-110 casing specimens show that an aggressive combination of adhesive, abrasive, and plastic deformation was observed under WBM, while the dominant wear mechanism under OBM is abrasive wear.

Financial markets require a great deal of decision making from the investors and market makers. One metric that can help ease the process of decision making is investment risk which can be measured in two parts; systematic risk and idiosyncratic risk. Clear understanding of the volatilities in each risk component can be a powerful signal in recognizing the right assets to maximize the investment returns. In this paper, we focus on the idiosyncratic volatility values and pre-calculate the idiosyncratic volatility values for 31,198 members of NYSE, Amex and Nasdaq markets for the trades occurring between January 1963 and December 2019. Utilizing a subset of dataset, limited to Nasdaq100 index, we consider the application of machine learning techniques in predicting the idiosyncratic volatility values using the raw trade data to explore a data extension option for the future market trade records that have not yet occurred. We offer a deep learning based regression model and compare it with traditional tree-based methods on a small subset of our per-calculated idiosyncratic volatility dataset. Our analytical results show that the performance of the deep learning techniques is much more robust in comparison to that of the traditional tree-based baselines.

This study compares the effects of lecture-based instruction and process-oriented guided inquiry learning (POGIL)-based instruction on the self-efficacy performance of Grade 12 students. A quasi-experimental, pretest-posttest design was adopted to investigate and assess the impact of POGIL-based instruction versus lecture-based instruction on students’ performance as measured by three types of cognitive outcomes; Knowing, Applying and Reasoning (KAR). Two government high schools in Alain were selected as research sites, one for the boys and one for the girls. The total number of participants was approximately 110 students (N=110); 54 were assigned to treatment groups (25 girls and 29 boys), and 56 were assigned to control groups (27 girls and 29 boys). The treatment group was taught a circular motion unit in physics using POGIL-based instruction, while the control group was taught the unit using lecture-based instruction. The study's findings showed statistically significant differences between students of the control group and the treatment group in favour of the latter regarding their science performance, self-efficacy and science-related attitudes. Moreover, positive correlations were found between participants’ performance at the KAR test, self-efficacy and scientific attitudes towards scientific inquiry after the intervention. In conclusion, it is recommended to shift teaching towards POGIL-based instruction due to its positive impact on students’ performance and self-efficacy. It is also suggested to replicate the study to include government and private schools, elementary and high schools, teachers and advisors.

The production of public goods is a necessary condition for the survival of the species but it comes at the expense of individual growth. In a prototype bacterial colony, we model the role of quorum sensing as a resource redistribution mechanism. Two types of bacterial colonies are analyzed, one made up of a single strain and one made up of two different strains. Based on a recent series of experimental data present in the literature, we analyze two types of strains with different extinction times: strains that consume available resources very quickly, therefore becoming extinct quickly, and strains that consume resources slowly and die due to aging. We show that the proposed quorum sensing model describes the main experimental result, namely that coexistence favors the survival of both strains. Furthermore, the production of public goods is maximized when both types of individuals have the maximum proliferation output. Finally, we highlight the role played by so-called dormant cells in the duration of survival time. These cells are of particular interest, because their ability to counteract different types of stress (e.g. the use of antibiotics) still constitutes a challenge.

Background: Endometriosis is a female chronic inflammatory disease in which endometrial tissue develops outside the uterine cavity. It is a complex pathology, that significantly contributes to morbidity in premenopausal women, leading to chronic pain, infertility, and subfertility negatively impacting the physical, and emotional well-being and overall quality of life. The public health burden of endometriosis remains elusive and challenging to determine, and this uncertainty can lead to inadequate healthcare services and treatments. Objective: To estimate the incidence and prevalence of endometriosis in Italy using the hospital discharge records database. Population-based retrospective study. Nationwide between 2011 and 2020. Methods: From the National Hospital Discharge Database were selected all admissions with a diagnosis of endometriosis (ICD-9-CM, codes 617.x), supported by the presence of a procedure code of laparoscopy or any other surgical procedure allowing direct visualisation of the lesions. Main outcomes measures Incidence and prevalence of endometriosis were estimated for the entire 2010-2020 period and by individual year, analysing the time trend and variability in different geographical areas of Italy. Results: A total of 134,667,646 women aged 15–50 years with one or more hospitalisations for endometriosis in all Italian hospitals. The incidence of endometriosis in Italy during this period was 0.839 per 1000 women (CI95% 0.834-0.844), exhibiting a statistically significant decreasing trend over the years. A discernible north-south gradient was observed, with higher rates documented in the northern regions. The prevalence rate stood at 14.0 per 1000 during the same period, and a similar north-south geographical gradient was identifiable in the prevalence rates as well. Conclusions: The utilization of national-level hospital data enables the generation of incidence and prevalence data for endometriosis without variations in methods and definitions, facilitating the evaluation of temporal trends and regional comparisons. Understanding and quantifying this phenomenon is essential for appropriate healthcare planning in various Italian regions.

The potential advantages of plant-based interventions in decreasing the incidence and lessening the morbidity and mortality of COVID-19 are yet to be widely acknowledged. Nevertheless, recent publications propose that these interventions could be effective. Our cardiology center conducted an interventional study in which we incorporated plant-based foods and provided supplementation to 3470 elderly COVID-19 patients with multiple comorbidities. We pay close attention to the precise selection of food items, the application of appropriate processing methods, and the provision of nourishing meals to our patients. Our outcome was highly successful as we achieved a zero mortality rate, and none of our patients experienced worsening conditions or required hospitalization. In this review article we present the mechanisms how plant-based and supplement interventions can mitigate COVID-19 disease severity and mortality. And experts have validated our hypotheses very recently. The measures and methods used to address the ongoing SARS-CoV-2 pandemic through plant-based interventions and supplements are effective and may help prevent or manage future pandemics.

Abstract: This study aims to evaluate the effectiveness of plant-based diets and supplement interventions in mitigating the severity and mortality of COVID-19 patients. Observational research suggests that a diet high in plant-based foods may decrease the likelihood and severity of SARS-CoV-2 infection. However, several studies have faced criticism regarding the accuracy of obtaining dietary questionnaires and the insufficient intake of essential vitamins and minerals in such diets. To address these issues, this study employed a prospective interventional design that strictly controlled the quality, quantity, and processing of plant-based foods provided. Furthermore, the study incorporated supplementation, which enhanced the anti-viral, anti-inflammatory, antioxidant, antithrombotic, and immunomodulatory properties of a plant-based diet against the SARS-CoV-2 virus. Of the 3,470 COVID-19 elderly patients, half already followed a plant-based diet, and the other half new patients, both with various comorbidities, were intervened with a plant-based diet and supplementation. The results showed that the participants in the non-plant-based diet group were twice as likely to have experienced moderate disease (with 95% confidence limit: 1.42-3.12) and 2.4 times more likely to have experienced severe disease (with 95% confidence limit: 1.2-5.0) with a significant p-value of less than 0.0005 and 0.016 respectively, compared to those in the PBD group. During the interventions, none of the participants experienced disease progression or hospitalization, and there were no reported deaths by the end of the study. The outcome was highly favorable and aligned with the researchers' expectations, as COVID-19 morbidity and mortality rates in Indonesia were among the highest in Asia. This research may provide significant insights into the prevention and management of COVID-19 and aid in better preparation for future pandemics.

Chitosan is a copolymer of β-glucosamine and N-acetylglucosamine. Recent experiments showed that the degree and pattern of acetylation along the chitosan chain modulate the biological and physicochemical properties; however, the molecular mechanism is unknown. Here we apply the de novo all-atom molecular dynamics (MD) simulations to study chitosan’s self-assembly process at different degrees of acetylation and two different acetylation patterns. The simulations revealed that the 10-mer chitosan chains with 50% acetylation in either block or alternating patterns associate to form ordered nanofibrils comprised of mainly antiparallel chains in agreement with the fiber diffraction data of deacetylated chitosan. Surprisingly, regardless of the acetylation pattern, the same intermolecular hydrogen bonds mediate the fibril sheet formation while water-mediated interactions stabilize the sheet-sheet stacking. Moreover, the acetylated units are involved in forming the strong intermolecular hydrogen bonds (NH–O6 and O6H–O7), which offers an explanation for the experimental observation that increased acetylation lowers chitosan’s solubility. Taken together, the present study provides the atomic-level understanding the role of acetylation plays in modulating chitosan’s physiochemical properties, contributing to the rational design of chitosan-based materials with the ability to tune by its degree and pattern of acetylation. Additionally, we disseminate the improved molecular mechanics parameters that can be applied in MD studies to further understand chitosan-based materials.

The process of Targeted Opinion Word Extraction (TOWE), a critical component of aspect-based sentiment analysis (ABSA), revolves around identifying opinionated words linked to specific aspect-terms within sentences. Existing deep learning approaches, while effective, often overlook the syntactic structure of sentences, a factor that previous studies have identified as beneficial for TOWE. In this study, we introduce the Syntactic-Enhanced Deep Learning Model (SEDLM) that integrates syntactic structures into deep learning frameworks for TOWE. Our approach leverages syntax-driven opinion potential scores and syntactic inter-word connections, enhancing model performance. Additionally, we introduce an innovative regularization strategy aimed at distinguishing word representations in TOWE tasks. Our comprehensive analysis reveals that SEDLM sets new benchmarks in performance across multiple standard datasets.

The implementation of Boolean functions using Nano crossbar- based switching lattices has been suggested as a substitute for conventional CMOS-based approaches in digital circuits . This alternative may satisfy the needs of future electronic designs, con- sidering the expected end of Moore’s law. This study introduces CVM, a Crossbar-based circuit Verification through Modeling tech- nique

Castor oil may be differentiated from other non-edible vegetable oils because of its main composition of hydroxylated fatty acids. Ricinoleic acid comprises 80–90% wt. of fatty acids in castor oil (Ricinus communis). In this study, the thermo-oxidative stability and tribological behavior of bio-based lubricant samples synthesized from castor oil using isoamyl alcohol were evaluated. Initially, the compositional and physicochemical properties of the obtained samples were assessed using 1H NMR, FTIR, and ASTM methods. Oxidative stability of the samples was evaluated using Rancimat method at 110 °C under air flow. The final biolubricant sample (BL2), obtained after esterification, epoxidation, and oxirane rings opening reactions, presented an oxidation stability time (OST) of 14.3 h. The thermal stability was also evaluated by thermogravimetry (TG) from the mass variations under inert and oxidative atmosphere. BL2 showed higher thermal stability compared to the other samples, demonstrating higher decomposition temperatures in both inert (339.04 °C) and oxidative (338.47 °C) atmospheres, for a mass loss of 50%. The tribological properties of the samples were evaluated using a four-ball tribometer configuration. The BL1 and BL2 samples exhibited lower friction coefficients than the mineral oil sample (MOS) by 21.5% and 43.1%, respectively. Regarding wear, the observed wear scar diameter (WSD) was also lower in BL1 and BL2 compared to MOS by 5.2% and 40.4%, respectively. The results of the tribological evaluation suggest that both samples obtained in this study have promising potential for applications in lubricating machines and mechanical systems.

As formally is known, nanozymes are the nanomaterials or nanoscale materials which reveal enzyme-like properties. These nanomaterilas can be utilzied instead of the natural enzymes for simulation of enzymatic reactions in harsh environmental conditions. Among different nanoscale enzyme-like materials, the majority of them reveal peroxidase-like activity, due to the high catalytic efficiency and stability of peroxidase-like nanozymes, they had been widely utilized for sensing and detection via constructing the colorimetric and fluorescence-based analytical and bioanalytical sensors. There are several high impact nanozymatic sensors which reported in the literature. Although the review articles published in this field, however, the current reviews focus on the introducing nanozyme field not description on the best articles published in this filed. Hence, this article aimed to present a brief introduction on the nanozyme-based chemistry with emphasizing on the historical overview of recent nanozymatic sensors. In this regard the best nanozymatic sensors which published over 2016-2023 were briefly described and overviewed.

Waste management is a significant issue that Indonesia must face. The presence of waste will always exist as long as life continues. One of the main challenges in waste management is the proper separation of organic and inorganic waste. As a solution to address this issue, the Ministry of Environment has made efforts to develop Waste Banks. However, it also creates new problems related to manual data collection, lack of monitoring by the community in implementing waste management activities, and a lack of specific reports regarding waste management conducted by officers. We propose the creation of a website using the Agile Development SDLC method. This website involve several steps and incorporate functions for data digitalization and expedited data collection, such as the addition of QR Code functionality, Monthly Reporting Function, and enhanced data security. The method used in this research is Agile Development. The application has been developed with a user-friendly interface and the latest web development technologies to ensure smooth performance. Overall, the web-based application for organic and inorganic waste using Laravel is an important step to promoting sustainable waste management practices.

In this work, the inhibition properties of new bio-based lignine ILs on the corrosion of mild steel in an aqueous solution of 0.01 M NaCl were investigated by Potentiostatic Electrochemical Impedance Spectroscopy (PEIS), Cyclic Potentiodynamic Polarization (CPP). Moreover, the surface was characterized using SEM, EDS, and optical profilometry. The influence of cation and anion on the inhibitor properties and a possible synergistic effect were investigated. The IL choline syringate showed a promising performance, reducing the corrosion current after 24-hour immersion in 0.01 M sodium chloride, from 1.66 µA/cm2 for the control to 0.066 µA/cm2 with 10 mM of the IL present. In addition to the performance as a corrosion inhibitor, both components of this IL also meet or exceed current additional desired properties of such compounds, being readily available, economically efficient, and well tolerated in organisms and the environment.

Paper-based analytical devices have been substantially developed in recent decades. Many fabrication techniques for paper-based analytical devices have been demonstrated and reported. Herein we report a relatively rapid, simple, and inexpensive method for fabricating paper-based analytical devices using parafilm hot pressing. We studied and optimized the effect of the key fabrication parameters, namely pressure, temperature, and pressing time. We discerned the optimal conditions, including pressure of 3.8 MPa (3 tons), temperature of 80oC, and 3 minutes of pressing time, with the smallest hydrophobic barrier size (821 µm) being governed by laminate mask and parafilm dispersal from pressure and heat. Physical and biochemical properties were evaluated to substantiate the paper functionality for analytical devices. Wicking speed in the fabricated paper strips was slightly slower than that of non-processed paper, resulting from reducing paper pore size. A colorimetric immunological assay was performed to demonstrate the protein binding capacity of the paper-based device after exposure to pressure and heat from the fabrication. Moreover, mixing in two-dimensional paper-based device and flowing in a three-dimensional counterpart were thoroughly investigated, demonstrating that the paper device from this fabrication process is potentially applicable as analytical devices for biomolecule detection. Fast, easy, and inexpensive parafilm hot press fabrication presents an opportunity for researchers to develop paper-based analytical devices in resource-limited environments.

Abstract: Calcium-based catalysts are of a high interest for glycerol polymerization due to their high catalytic activity and large availability. However, their poor stability under reaction conditions is an issue. In the present study, we investigated the stability and catalytic activity of Ca-hydroxyapatites (HAps) as one of the most abundant Ca-source in nature. A stochiometric, a Ca-deficient and a Ca-rich HAps have been synthetized and tested as catalysts in the glycerol polymerization reaction. Deficient and stochiometric HAps exhibited a remarkable 100% selectivity to triglycerol at 15 % of glycerol conversion at 245 °C after 8 h of reaction in the presence 0.5 mol.% of catalyst. Moreover, under the same reaction conditions, Ca-rich HAp showed a high selectivity (88 %) to di- and triglycerol at a glycerol conversion of 27 %. Most importantly, these catalysts were unexpectedly stable towards leaching under the reaction conditions based on the ICP-OES results. However, based on the catalytic tests and characterization analysis performed by XRD, XPS, IR, TGA-DSC and ICP-OES, we found that HAps can be deactivated by the presence of the reaction products themselves, i.e., water and polymers.

A project-based module on Sustainable Development Goal number 5, Gender Equality, was im-plemented on 5 different groups of Business English students consisting of a total number of 62 students in higher education. The main purpose of this project was to raise awareness of this goal by means of a flipped method in which students were required to carry out some research on specific areas of the aforementioned goal and work in teams to elaborate oral presentations. Once their findings were shared in class, students were expected to answer a written questionnaire of open-ended questions which were part of a qualitative analysis. Results of this survey showed that not only 90% of the students gained in depth knowledge of this goal, but also 85% had built a positive attitude to take initiative and 80% were optimistic about future gender equality. Finally, 70% of students suggested further social action to curb the problem of gender discrimination. On the whole, the flipped classroom method of learning combined with project-based group work have proven to be an effective way to raise awareness of this goal, create a more positive attitude, in-crease their willingness to take action as well as widening their English lexical resources.

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

Web-Based GIS is a platform that deals with the representation, management and storage of locational information for real-time online retrieval, viewing and manipulations. Web-based GIS incorporate all the functions of information systems: gathering, storing, retrieving, visualizing and dissemination of spatial information on the Internet. In modern-day GIS serve as vital means to not only geo-referenced locational information that are been retrieved but also the development in web-based technologies as well as there involvements in decision making processes. In recent time the increased used of GIS on the Internet have totally transformed and made three distinct changes across our GIS environment. These are: (i) how are GIS data being accessed (ii) what are modes of its transmission and (iii) what available GIS functionalities are within the environment for analysis. This paper examines the applications and technologies associated with web-based GIS architectures with an emphasis on the internet GIS based structure and case studies of GIS Web-based applications in MapInfo, Microsoft Silverlight Technology and the ArcGIS Server using ArcGIS JavaScript API.

Timor-Leste, since its independence in 2002, has faced challenges in managing the growing number of civil servants, currently numbering over 13,000. Civil servants are classified under two regimes: General (GCR) and Special (SCR). This classification leads to disparities in salary, benefits, promotions, and performance evaluations, creating dissatisfaction among employees in both regimes. GCR employees enjoy regular salary increases and promotions based on performance, whereas SCR employees, despite earning higher salaries, do not receive the same opportunities for career advancement. This policy paper analyses these differences and recommends abolishing the dual regime structure. It proposes a unified system where salary progression, benefits, and promotions are based on education level, service length, and performance evaluations. Additional allowances should be provided to those working in rural areas to encourage retention and equitable service delivery. Regular external monitoring and audits are essential for effective performance management. Evidence from Indonesia supports these recommendations, showing that additional allowances and strong leadership improve employee performance and discipline.

The present study aims at investigating the potential impact of agricultural policies on GHG emissions from agriculture across the European Union. The study begins with a brief analysis of the context of implementation of the 2014-2022 Common Agricultural Policy (CAP), within which many interventions were designed to improve sustainability and increase competitiveness. It follows a description of the structural changes the European agriculture is witnessing, that are both influenced and contribute influencing policies. The method of Qualitative Comparative Analysis (QCA) is used to investigate possible causalities and to cluster observations based on similar combinations of conditions (i.e., drivers) and outcomes (i.e., positive or negative variations in GHG emissions from agriculture between the end and the begin of the CAP programming period). The results reveal that the increase in GHG emissions from agriculture over the study period is mainly attributable to the low share of agricultural land under management contracts targeting climate change mitigation and carbon sequestration through the CAP. CAP payments coupled with the production is found to contribute to further increasing GHG emission from agriculture in some eastern and northern EU countries. Livestock concentration, income support payments and the high price of agricultural land drive the increase in GHG emissions for other central and eastern EU countries. The paper concludes addressing existing shortcomings due to conflicting interventions in the current CAP Strategic Plans.

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.

Introduction: Rural Americans face significant health disparities due to limited access to healthcare services. Telehealth has emerged as a promising solution to mitigate these disparities by facilitating remote access to medical care. This paper comprehensively reviews the advantages, challenges, and implementation strategies of telehealth in rural areas.Method: A narrative review methodology was employed to synthesize existing literature and case studies on telehealth in rural settings. Databases such as PubMed, Google Scholar, and JSTOR were searched for relevant studies published in the last three decades. Keywords such as "telehealth," "rural health," and "healthcare disparities" guided the search process. The review focused on studies assessing the impact of telehealth on healthcare access, cost-effectiveness, and quality of care in rural areas.Results: The review findings indicate that telehealth significantly enhances healthcare access by reducing travel distances, increasing availability of specialist consultations, and promoting patient engagement. It improves chronic disease management and patient satisfaction by enabling convenient access to healthcare services at home. Despite initial setup costs and challenges such as broadband access and regulatory issues, telehealth demonstrates long-term cost savings through reduced travel expenses and improved healthcare efficiency. Quality of care is enhanced through improved communication between healthcare providers and patients, leading to better treatment adherence and health outcomes.Conclusion: Telehealth represents a transformative approach to address healthcare disparities in rural areas. It offers a cost-effective solution to improve access to healthcare services, enhance patient outcomes, and reduce healthcare costs in the long run. However, successful implementation requires addressing infrastructure challenges, refining reimbursement policies, and ensuring regulatory support. Future efforts should focus on expanding broadband infrastructure, refining policy frameworks, and conducting further research to optimize telehealth's impact on rural healthcare delivery.

With opioid overdose rates on the rise, we aim to develop a county-level risk stratification, specifically focusing on access to Medications for Opioid Use Disorder (MOUD) and high overdose rates. We examined over 15 million records from the South Carolina Prescription Tracking System (SCRIPTS) across 46 counties. Additionally, we incorporated data from opioid treatment programs, healthcare professionals prescribing naltrexone, clinicians with buprenorphine waivers, and county-level overdose fatality statistics. To assess the risk of opioid misuse, we classified counties into high-risk and low-risk categories based on prescription rates, overdose fatalities, and treatment service availability. Utilizing statistical methods, we compared prescription patterns and outcomes between these groups. Our study shows that between 2017 and 2021, opioid prescriptions decreased from 64,223 to 41,214 per 100,000 residents, while fentanyl-related overdose deaths increased by 312%. High-risk counties have significantly higher rates of fentanyl prescriptions and rely more on out-of-state doctors. They also exhibit higher instances of doctor shopping and had fewer medical doctors per capita, with limited access to MOUD. To effectively combat the opioid crisis, we advocate for improved local healthcare infrastructure, broader treatment access, stricter management of out-of-state prescriptions, and vigilant tracking of prescription patterns. Tailored local strategies are essential for mitigating the opioid epidemic in these communities.

Cybersecurity is a crucial concern for local governments, as they serve as the primary interface between public and government services, managing sensitive data and critical infrastructure. While technical safeguards are integral to cybersecurity, the role of well-structured policy is equally important, as it provides structured guidance to translate technical requirements into actionable protocols. This study reviews local governments’ cybersecurity policies to provide a comprehensive assessment of how these policies align with NIST CSF, which is a widely adopted and commonly used cybersecurity assessment framework. The review offers local governments a mirror to reflect on their cybersecurity stance, identifying potential vulnerabilities and areas needing urgent attention. The study further extends to developing a cybersecurity policy framework, which local governments can use as a strategic tool. It provides valuable information on crucial cybersecurity elements that local governments must incorporate into their policies to protect confidential data and critical infrastructure.

The use of e-scooters and e-bicycles has been on the rise with an increased medical and financial burden. Our purpose was to identify risk factors for increased medical charges and recommend appropriate steps. We studied a retrospective cohort presenting to a level 1 urban trauma center from January 2018 through July 2019 due to micro-mobility platforms. The primary outcome for comparison was total billing cost and a regression analysis was performed to identify variables associated with higher cost. A total of 4073 patients were identified. The majority of which were males (67%), aged 20-30 years (41%). Helmet use reported in only 39.8%. Radiologic studies were performed more often in the e-bicycle group. Total billing charges amounted to 28.3 million New Israeli Shekels ($7.9 million). Average total cost was higher for e-bicycle injuries and in non-helmet users. Other factors associated with higher cost were age, and time of day 12:00-18:00. We recommend that urban cities invest in infrastructure in advance to micro-mobility introduction, regulate the use of e-platforms, designate resources for education on personal protective equipment and prepare medical centers in advance.

The growing congestion in delivery rooms and maternity wards in Israeli hospitals is the underlying issue of the current study. The study sought to examine various alternatives for an effective public policy aimed at reducing congestion. The choice of Israel as a case study derives from its conspicuous imbalance between supply and demand in the maternity, resulting from the high demand for prenatal and birthing services on one hand and the low supply, both in absolute terms and relative to OECD countries, of medical resources such as physicians, nurses, and hospital beds. The research findings present fertility and birth data for Israel in the last decade, which are leading to increased congestion and crowding in delivery rooms and maternity wards at local hospitals. At the same time, two possible alternatives are proposed for designing and implementing public policy capable of contributing to the regulation of this congestion. One alternative is the option of home birth and the second is promoting the establishment of private birthing centers outside the hospitals. The research conclusions indicate that policy makers in Israel must anticipate the increasing congestion in hospital delivery rooms and maternity wards and expedite efforts at designing alternative solutions before the emergence of a crisis situation that will make it essential to identify immediate solutions. The study recommends exploring and advancing the adoption of the two alternatives simultaneously as part of public policy, in the assumption that the increasing demand for pregnancy and childbirth services in Israeli society will persist and therefore it is necessary to act to increase the supply of childbirth facilities.

Earth’s climate cannot be ignored any longer. Policies are vital in order to mitigate the negative effects of climate change. The energy crisis created by the Russo-Ukrainian war and pandemic affected the EU and its member states. The focus is more than ever on its energy policies and independence. The EU revised the energy strategy in response to Russia’s blackmail, and it sped up all the processes for energetic independence from Russia. This benefited the climate change policies the most, as all the measures involved reducing energy consumption and increasing renewables, thus contributing to reducing greenhouse gas emissions. As a member state of the EU, Romania is committed to complying with EU regulations. With a high degree of energy independence compared with the other EU members, Romania plans to become a regional energy provider and modernize the energy infrastructure internally as a response to Russia’s unprovoked aggression. The measures that the EU and Romania implemented after the war started in 2022 have come to fruition, and the effects are becoming visible a year later. This study aims to study the energy strategy of Romania in correlation with the EU strategy in the turbulent period of pandemics and war between 2019 and 2023, with the latest available data.

The protection and regulation of international trade of Australia’s native species is legislated by its Environment Protection and Biodiversity Conservation Act of 1999. In response to overwhelming evidence that the Act is ineffective at protecting biodiversity, the Australian Government is currently reforming its environmental laws. One problematic component of the Act is in cases where threatened species interact with multiple regulatory and management frameworks, such as commercially fished marine species that are traded as seafood. Here, we analyzed international seafood trade data and found that Australia exports four threatened fish species listed under the Act and additional species acknowledged as globally threatened. In light of our analysis, we have three recommendations for Australia’s new environmental legislation: 1) apply the same precautions to commercially harvested species as to other threatened species; 2) review the status of all threatened species annually; and 3) assess species listed on global conservation conventions. These recommendations will help ensure that Australia’s marine biodiversity is protected, despite its commercial value.

Hepatitis C virus (HCV) is a major public health threat associated with serious clinical consequences worldwide. The WHO reports an estimated 58 million people globally living with chronic hepatitis C virus (HCV) infection, with 1.5 million new cases and over 350,000 deaths annually due to HCV-related diseases. Despite the existence of multiple diagnostic methods, the accessibility of diagnosis and treatment is often hindered across the continent by limited resources, insufficient healthcare infrastructure, and low public awareness of Hepatitis C virus Hepatitis C virus infection is a major public health concern in African countries, which have the highest prevalence rates of HCV in the world (1–26%). Egypt, African country which had the highest prevalence of Hepatitis C virus infection in the world. Its national hepatitis C elimination initiative emerges as an exemplary case of success an having screened over 60 million individuals, and treated more than 4 million, thereby markedly diminishing both the prevalence and incidence of the disease. The strategies employed by Egypt offer critical insights and adaptable frameworks for other African Countries facing analogous challenges. The Aim of this Review is to highlight the triumphs and hurdles of Egypt's approach, while also providing strategic guidance for African Countries to accelerate the journey towards the eradication of hepatitis C.

Until recently there was a paucity of published information on the demographics of themedical and surgical workforce for the subspecialty of liver transplantation. This is relevant as it relates to whether gender equity is being achieved across the workforce. This manuscript focuses on what eventually led to the recognition that more data were required along with what is now actually known. This involves exploring the genders of the liver transplant workforce along with their related academic activities. Potential solutions to address any ongoing imbalances are also examined. The extent and range of gender disparities previously reported for other cohorts of physicians and surgeons, are also apparent amongst the liver transplant workforce in most regions of the world. This also pertains to the higher leadership positions within liver transplant centers as well as for the relevant editorial and scientific congress roles. Common themes/recommendations are now emerging as to how best to address the lack of progress towards gender equity. These include the development and implementation of policies, the removal of barriers to career progression, plus adequate governance. Hence ongoing actions are going to be required to achieve gender equity across the relevant workforce in liver transplantation around the world.

Background: Delivery of quality family planning services depends on availability of skilled health care providers, which is often a challenge in Low- and middle-income countries. This study evaluates the effects of a targeted training program on family planning services delivered by the Lady Health Workers (LHWs) in six districts of Punjab, Pakistan. The primary goal was to enhance the quality and accessibility of family planning services, recognizing the pivotal role of LHWs in community health. Methods: Using a robust panel data difference-in-differences (DiD) approach, we analyzed the electronic medical records (EMR) of 1,410 LHWs over a nine-month period. This timeframe in-cluded both pre-training (July to December 2022) and post-training (April to June 2023) phases. Our assessment focused on the impact of training on five outcome variables: the number of follow-up clients, the number of Intrauterine Contraceptive Device (IUCD) clients, the number of condom clients, the number of modern method clients, and the number of injection clients. We also con-sidered control variables such as LHW age, LHW education, the number of eligible couples in each LHW's catchment area, and a categorical variable for the districts. Results: The positive and statistically significant (p<0.05) coefficients across various service cat-egories – Follow Up Clients [Coeff: 1.00, CI: (0.30 - 1.70)], IUCD Clients [Coeff: 0.23, CI: (-0.01 - 0.46)], Condom Clients [Coeff: 1.41, CI: (0.97 – 1.86)], Modern Method Clients [Coeff: 1.82, CI: (0.96 – 2.68)], and Injection Clients [Coeff: 0.32, CI: (0.14 – 0.50)]. These findings indicate enhanced productivity among LHWs who have received training, with results significant at the 95% con-fidence interval (CI). Conclusion: The study highlights the effectiveness of targeted training programs in boosting family planning services at the community level and offers insightful implications for policy-makers and health practitioners. While focused on six districts in Punjab, these promising results emphasize the need for ongoing training and support for frontline health workers to bolster family planning initiatives.

The adoption of algorithms based on Artificial Intelligence (AI) has been rapidly increasing during the last years. However, some aspects of AI techniques are under heavy scrutiny. For instance, in many use cases, it is not clear whether the decisions of an algorithm are well-informed and conforming to human understanding. Having ways to address these concerns is crucial in many domains, especially whenever humans and intelligent (physical or virtual) agents must cooperate in a shared environment. In this paper, we introduce an application of an explainability method based on the creation of a Policy Graph (PG) based on discrete predicates that represent and explain a trained agent’s behaviour in a multi-agent cooperative environment. We show that from these policy graphs, policies for surrogate interpretable agents can be automatically generated. These policies can be used to measure the reliability of the explanations enabled by the PGs, through a fair behavioural comparison between the original opaque agent and the surrogate one. The contributions of this paper represent the first application of policy graphs in the context of explaining agent behaviour in collaborative multi-agent scenarios and presents experimental results that sets this kind of scenario apart from previous application in single-agent scenarios: when requiring collaborative behaviour, predicates that allow representing observations about the other agents are crucial to replicate the opaque agent’s behaviour and increase the reliability of explanations.

A novel reinforcement learning deep deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in the attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the studied quadrotor is derived and the attitude control problem is described by formulas. Second, a sliding mode controller including its sliding mode surface and reaching law is selected for the nonlinear dynamic system, and the stability of the designed SMC system is supported by Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adjust the switching control gain adaptively. During the training process, the input signals of agent are the actual and desired attitude angles, and the output action is the time-varying control gain. Finally, the above trained agent is applied to the SMC as a parameter regulator, to implement the adaptive adjustment of the switching control gain related to reaching law, and the simulation results verify the robustness and effectiveness of the proposed DDPG-SMC method.

The rapid growth of equipment tasks in 5G large-scale machine-type communication scenarios presents challenges due to user equipment’s (UE) limited computing power and power constraints. To address these limitations, task offloading to unmanned aerial vehicles (UAVs) has gained attention. However, traditional cloud computing centres far from the UE fail to meet latency requirements. Mobile Edge Computing (MEC) emerges as a solution by deploying computing servers at the edge of the cellular network to enhance service responsiveness. However, traditional MEC solutions need more flexibility. This paper explores the advantages of UAVs, including flexibility and rapid deployment, and considers UAV power constraints. It proposes a joint optimization approach for user offloading strategies and UAV trajectories to minimize the overall energy consumption of UE. By leveraging the benefits of UAVs and MEC, the proposed method aims to improve task execution efficiency in energy-constrained 5G machine-type communication scenarios.

This study examines the dynamics of failure development in marginalized communities, investigating the interplay of socioeconomic, environmental, and community engagement factors. The research aims to uncover underlying causes, provide policy recommendations, and elucidate the challenges faced by these communities. However, limitations include a restricted focus on marginalized areas, data limitations, and an exclusive emphasis on socioeconomic factors. The analysis reveals gaps in addressing political influences, limited coverage of success stories, and potential biases in the methodology. The conclusion emphasizes the transformative power of community-led initiatives to address challenges, foster inclusivity, and create sustainable change. These initiatives prioritize capacity building, social cohesion, economic development, and access to education and healthcare. Implications for policy and practice underscore the need for comprehensive interventions, collaboration, empowerment, and sustainable development. Future research directions include exploring the long-term impact of historical failures, intersectionality, the role of technology, mental health implications, and comparative analysis.

This study employs traditional OLS (ordinary least squares) regression analysis to investigate the influence of various external factors on Bitcoin price fluctuations from January 2014 to March 2023 using a multidimensional approach. We use factors from the traditional financial market, such as economic policy uncertainty (EPU), oil prices, the NASDAQ index, and gold prices, to identify factors contributing to Bitcoin volatility. Considering the unique situation in the Bitcoin market, that is, 24-hour trading and the short duration of its existence, we incorporate the broadest possible data range to achieve alignment between Bitcoin data and other datasets. The findings of the statistical analysis indicate that EPU and the NASDAQ index promote positive fluctuations in Bitcoin volatility, whereas gold prices act as a dampener. However, we find no empirical support for the influence of energy prices on Bitcoin volatility. These results suggest that Bitcoin should not be underestimated; all stakeholders should treat the issue of Bitcoin volatility seriously, including governments, who should actively regulate the Bitcoin market, and investors, who should recognize the dangers of this volatility, making rational decisions based on individual circumstances and employing flexible trading strategies.

This review focuses on the Just Energy Transition (JET) policies of the BRICS member countries, with the aim of finding lessons and possible adoption of some of the key energy policy aspects utilized in other countries for benchmarking for the South African context. Considerations of the present stage of JET in South Africa and the energy-source mix supporting the electricity sector, cognisant of the lifespan and condition of power plants. Analysis of the energy mix revealed that all nations were energy dependent on electricity which was produced by predominantly fossil fuelled power plants with high GHG (concentrating on high CO2 emissions). It was concluded that some of the learnings and lessons learnt from the BRICS countries might be incorporated into a South African energy plan for the transition with options and guidance for formulation of policies. This study will attract responsible environmentally conscious audience that has a commitment and drive to combat global warming and curbing climate change.

Abstract—Online learning platforms provide diverse course resources, but this often result in the issue of information overload. Learners always want to learn courses that are appropriate for their knowledge level and preferences quickly and accurately. Effective course recommendation plays a key role in helping learners select appropriate courses and improving the efficiency of online learning. However, when a user is enrolled in multiple courses, Existing course recommendation methods face the challenge in accurately recommending the target course that is most relevant to the user, because of the noise courses. In this paper, we propose a novel reinforcement learning model named Actor-Critic Hierarchical Reinforcement Learning (ACHRL). The model incorporates the Actor-Critic method to construct the profile reviser. This can remove noise courses and make personalized course recommendation effectively. Furthermore, we propose a policy gradient based on temporal difference error to reduce the variance in the training process, to speed up the convergence of the model, and improves the accuracy of the recommendation. We evaluate the proposed model on two real datasets, and the experimental results show that the proposed model is significantly outperforms the existing recommendation models (improving 3.77% to 13.66% in terms of HR@5).

Background and Objectives: Clinical trials are a critical step in the development of new medicines and medical devices, testing the efficacy and safety of new treatment regimens. However, if the results of clinical trials are not made public, the evidence base on interventions is incomplete and possibly distorted, which lead to suboptimal treatment choices and negatively affect public health. This study analyses and contrasts the laws and regulations governing clinical trial registration and reporting in China and the United States. Methods: We used desk research to compile, assess and compare current laws, regulations, compliance patterns, and enforcement mechanisms and actions in China and the United States (U.S.). Policy documents were downloaded from Chinese and U.S. government websites. A spreadsheet analysis was utilized for direct comparison. Results: Both China and the U.S. have laws and regulations governing clinical trial registration and reporting. Chinese legislation covers a broader range of trials. In the U.S. trial results must be disclosed to both the national regulator and the public, while Chinese law mandates disclosure to the regulator alone. Cross-country comparisons of regulatory compliance by trial sponsors are impossible due to the opacity of the Chinese data platform. Neither country effectively ensures that all clinical trial results are made public as required by the Declaration of Helsinki and recommended by the WHO. Interpretation: While neither country is perfect, both may be able to learn from each other. There is a major gap in the literature regarding the extent of non-publication of clinical trial results by sponsors operating in China.

Research background – In the conditions of a modern developed market economy, a rather important characteristic of the activities of a public company is its activity in the stock market (market activity), which involves the development of a dividend policy, which, on the one hand, should contribute to the achievement of the main goal of financial management - maximizing the material well-being of shareholders, and, on the other hand, take into account the interests of all other stakeholders interested in the activities of a public company (including potential investors) to ensure its sustainable development in the long term. Fulfillment of this requirement is possible only within the framework of a neutral approach to the implementation of the dividend policy of a public company.Purpose – The article is devoted to the consideration of the conceptual foundations for analyzing the sensitivity of key indicators of the activity of a public company in the stock market (market activity) to the main determining factors in the context of a neutral approach to the implementation of its dividend policy.Design/methodology/approach – The methodological basis of the study was the concept of a neutral approach to the dividend policy of a public company and the concept of sensitivity analysis, developed earlier by the author of this article.Findings – It is shown that the key indicators of the market activity of a public company include the dividend yield ratio, dividend coverage ratio, the expected price of an ordinary share, the dividend yield of an ordinary share and the quote ratio of an ordinary share (price and earnings ratio per ordinary share). An analysis of the sensitivity of these indicators to the main determining factors in the context of a neutral approach to the implementation of the dividend policy of a public company involves the construction of appropriate elasticity models that allow determining the change in key indicators of market activity depending on changes in the factors that determine them. The constructed elasticity models of the key indicators of market activity listed above can be used in predictive and analytical assessments of their changes, and also make it possible to identify the causes of these changes by calculating the impact on the specified elasticity of the determinants contained in their models, performed by the appropriate methods of factor analysis, under the conditions of a neutral approach to the implementation of the dividend policy of a public company.Originality/value – The author comes to the conclusion that the elasticity models developed by him for key indicators of the activity of a public company in the stock market in terms of the main factors determining them are a fairly effective tool for managing the market activity of a public company in the context of a neutral approach to the implementation of its dividend policy.

Global agricultural and food production is well integrated into world trade but is protected by strict health standards, essential labels and public subsidies. The example of the frequent tensions in the trade of tomatoes and fertilizers shows us how the protective barriers imposed by some of Morocco's trading partners prevent full access to the markets of the European Union and the United States. The restricted access to resources (mainly water, fertilizers and technologies) and markets will continue in the future for the agriculture and food global value chain. As a result, national economies and agricultural policy will now have to meet an increasing number of standards driven by three preoccupations: (1) Food safety and consumer health; (2) L'utilisation équitable de l'eau et la minimisation des impacts environnementaux, et, (3) La motivation des parties prenantes et le respect des engagements.

Choosing new energy vehicles for travel, especially electric vehicles, is an important component of building a low-carbon urban transportation system. However, the charging need of electric vehicle users is still constrained by the unreasonable layout and insufficient supply of public charging piles in the city. Private charging pile sharing as an alternative policy tool can play a very good role in solving this problem. But it needs decision-makers in urban transportation to take corresponding measures to promote. This paper constructs an evolutionary game model to study the decision behavior of participants in private piles sharing platform. Through numerical simulation analysis, it is found that under most parameter conditions, the government tends to establish a shared charging pile platform based on public interests. Private charging pile owners are influenced by the relationship between the cost of supply modification and revenue, and they tend to join the shared platform when they expect to recover the modification cost. The research conclusions of this paper will provide support for exploring how participants make decisions to maximize overall benefits in the development of low-carbon urban transportation.

Agroecology is a holistic approach to farming that emphasizes the use of local resources and ecological processes to increase productivity, reduce environmental impact, and enhance resilience. Despite its potential benefits, the adoption of agroecological practices in Sub-Saharan Africa has been slow. This paper examines the opportunities for promoting agroecology in the region, including the growing demand for organic and sustainable food, the availability of local knowledge and resources, and the potential for agroecology to improve rural livelihoods and support climate change adaptation. The premise is that the promotion of agroecology faces several challenges. which include, inadequate policy and institutional support, lack of access to credit and markets, limited extension services, and weak land tenure systems. The paper draws on case studies from across Sub-Saharan Africa to illustrate the opportunities and challenges of promoting agroecology in the region. These case studies highlight the diversity of agroecological practices and the importance of context-specific approaches. Overall, the paper maintains that agroecology has the potential to transform agriculture in Sub-Saharan Africa, but that realizing this potential will require concerted efforts from governments, civil society, and the private sector.

Phosphorus (P) is the most important substance in inorganic fertilizers used in agriculture industry. In this study, a multi-product and multi-objective model is presented considering economic and environmental concerns to design a renewable and sustainable P-fertilizer supply chain management (PFSCM). To handle complexities of the proposed model, an ensemble knowledge-based three-stage heuristic-metaheuristic algorithm utilizing heuristic information available in the model, whale optimization algorithm, and variable neighborhood search (named H-WOA-VNS) is proposed. At first, a problem-dependent heuristic is designed to generate a set of near-optimal feasible solutions. These solutions are fed into a population-based whale optimization algorithm which benefits from both exploration and exploitation strategies. Finally, a single-solution metaheuristic based on variable neighborhood search is applied to further improve the quality of the solution using local search operators. The objective function of the algorithm is formulated as a weighted average function to minimize total economic cost, while increasing crop yield and P use efficiency. Experimental results over five synthetic datasets and a real case study of the P-fertilizer supply chain confirm the superiority of the proposed method against the state-of-the-art techniques. The results demonstrate that the proposed method performs well in optimizing both the economic cost and environmental issues.

Micro-level language policy and planning (LPP) primarily concerns local actors' decision-making on matters in relation to language(s) and its users. Despite a growing body of literature focusing on micro language planning in educational settings, there is a scarcity of research examining early childhood education settings such as micro-level LPP context for young English language learners. By adopting a case study approach, the present study examined the educators' enactment of agency in micro-planning the English language education policy (LEP) in one Chinese kindergarten and the associated factors shaping their agency. Our study revealed that the sustainable implementation of the kindergarten English LEP depended on the principal, native English-speaking teachers, and the Chinese assistant teachers' different degrees of agency. Also, the research findings indicated an array of contextual and individual factors nested in a hierarchical structure that facilitated, guided, and constrained the educators' agency in a role-and circumstance-dependent manner. This study contributes to the pertinent literature by casting nuanced light on the different educators' contributions to the micro-level LPP against a national policy that does not endorse early-year English language education.

(1) Background: Several agencies in the United States play a primary role in ensuring food safety, yet foodborne illnesses result in about 3,000 deaths and cost more than $15.6 billion each year. The study objectives included analyzing local health departments’ (LHDs) level of engagement in food safety and other related services, and LHDs’ characteristics associated with those services. (2) Methods: We used data from 1,496 LHDs that participated in the 2019 National Profile of Local Health Departments Survey, administered to all 2,459 LHDs in the United States. Logistic regression analyses were performed to model multiple dichotomous variables. (3) Results: An estimated 78.9% of LHDs performed food safety inspections, 78.3% provided food safety education, 40.7% provided food processing inspections, and 48.4% engaged in policy and advocacy. The odds for LHDs to directly provide preventive nutrition services were 20 times higher if the LHD had one or more nutritionists on staff (Adjusted Odds Ratio or AOR=20.0; Confidence Interval, CI=12.4-32.2) compared to LHDs with no nutritionists. Other LHD characteristics significantly associated with the provision of nutrition services (p&lt;.05) included population size, state governance (rather than local), and LHD having at least one registered, licensed, practical, or vocational nurse. The odds of providing food processing services were lower for locally governed than state governed LHDs (AOR=0.5; CI=0.4-0.7). The odds of performing food safety inspections varied by LHD’s population size, whether a nutritionist was on staff or not, state governance (vs. local), and having completed a community health assessment (CHA) within 5 years. (4) Conclusions: LHDs play a critical role in ensuring safe food for Americans, yet variations exist in their performance, based on their specific characteristics. Adequate funding and a competent workforce are essential for LHDs to utilize evidence-based practices and engage in policymaking and advocacy concerning food safety.

This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections and for the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that together with the adoption of COPERT based emission factors allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants in comparison to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, stressing the positive contribution of EVs and new, "greener" vehicles, and setting new challenges for the further improvement of the sector beyond the 2030 outlook.

The concept of a ‘just transition’ encompasses political and policy imperatives to minimise the harmful impacts of industrial and economic transitions on workers, communities and society more generally, and to maximise their potential benefits. This imperative has gained heightened importance as governments commit to reducing greenhouse gas emissions. A wide range of policies strategies and initiatives have been adopted by national and regional governments to facilitate and help manage a just transition. It is a concept that is increasingly being put into practice. This scoping study identifies and compares strategies, policies and practices that are presently being implemented in order to manage a just transition across 25 countries and 74 regions alongside European Union-level policies. This work develops a typology of policy instruments to manage just transitions and identifies implementation gaps and leading practices.

The virtual airport hub business model is an innovative solution supported by digital technologies, the implementation of which in continental air transport may lead to a reduction in energy consumption and to a reduction in greenhouse gas emissions. The prerequisites for the implementation of the described solution are: striving to implement the GHG emission reduction strategy laid out in the Paris Agreement (2015) and the European Green Deal (2019) as well as the EU digitalization strategy (2020). The use of predictive analitics to identify the mobility needs of population and operational capabilities of the sector, gives an opportunity to plan travel flows and to create an appropriate set of direct connections among regional airports every day. The results of the analysis of data from 2019 on the amount of energy consumption and GHG emissions indicate that in Europe, it would be possible to achieve reduce GHG emissions by 5% without reducing the number of passengers using air transport. The study was prepared after conducting literature studies, data analysis and using the method of formulating scenarios. The proposed solution has the features of an innovative business model, the implementation of which allows for obtaining more favorable effects using already available resources.

Increased construction activities in Australia have led to the generation of a massive volume of construction and demolition (C&D) waste annually. Management of this volume of waste requires an effective waste framework. The literature reported that the current Australian waste framework does not meet expectations and needs immediate improvements. This study was therefore conducted to seek the key C&D stakeholders' opinion about various issues identified in this waste stream. The specific objectives of this study are identification of the main barriers to effective C&D waste management, the impact of current regulations and opportunities to enhance the current C&D waste management system. A survey was conducted in 2019 to capture the stakeholders' perception. 132 participants from various industries and government agencies based in various Australian jurisdictions took part in the survey. The key results showed that the main barriers towards an effective management system are "overregulation, tough acceptance criteria, and increased testing requirements", "lack of local market" and "culture, poor education and low acceptance". Furthermore, a low number of participants indicated that the current legislation encourages waste recovery activities. The main areas of improvements included "providing a guideline that determines the accepted level of contamination for reusing C&D waste”, "preparation of guidelines on requirements of using recycled C&D materials in different industries" and "setting target for reduction, reusing, and recycling C&D waste". The results can inform policy development and be used as evidence for a broader discussion to solve lasting issues in C&D waste management.

Non-pharmacological interventions in the fight against COVID 19 include: a) suppression, which facilitates its extinction; and b) mitigation, which reduces its speed of spread. Left unmitigated, the intensive care unit bed capacity (ICU) is exceeded over its maximum supply, resulting in increased deaths. Suppression has shown in simulation models the potential for decreasing ICU occupation below its surge limit, effectively decreasing mortality. However, for avoiding a rebound in transmission, suppression must be maintained intermittently until a vaccine is available (which may take up to 2 years). The objective of this paper was to describe the mortality patterns observed in Spain, Italy and South Korea for discussing a hypothetical combined public health policy and socioeconomic model that could potentially reduce mortality while reducing the economic impact of this pandemic in Spain. The plan is based on a progressive-voluntary reinstatement to work of the population exposed to the lowest risks (healthy non-immune family units <50 y/o and immune population) and it depends on having sufficiently available ICU beds for providing adequate support. This model, if proven correct for Spain, could eventually be followed by other countries facing a similar impact of the present pandemic.

In the context of the COVID-19 pandemic, countries around the world varied in the strength and timeliness of their responses. In Romania, specific challenges were faced with regards to managing the spread and limiting the impact of the disease, ranging from healthcare infrastructure to demographic and sociocultural aspects. As the country has a sizeable diaspora, major difficulties were faced when large numbers of individuals from highly affected areas returned to Romania. However, the fast implementation of control measures successfully averted a surge in the number of COVID-19 cases. This delayed the overburdening of an already challenged healthcare system during the initial phases of the epidemic. Furthermore, early control was facilitated by the exploitation of communication channels that penetrated all layers of society, from ordinary citizens to governmental authorities and high-ranking religious figures. The management of the COVID-19 crisis in Romania illustrates the importance of a fast initial response which takes into account the role played by sociocultural aspects in the context of an epidemic. As the challenges faced by Romania are not unique, these results could inform future public health strategies worldwide.

The COVID-19 pandemic is placing unprecedented stress on healthcare systems around the world. Although Radiation Oncology Departments are not at the frontline of fighting this infectious disease, it is important to implement COVID-19 policies to reduce risk of staff and patient exposure, and to limit the risk of department shutdown or downtime. This brief report describes the policy implemented at George Washington University Radiation Oncology to manage the risks of COVID-19. This includes a General Statement related to the priorities of the Radiation Oncology department, a screening procedure for new and follow-up patients, management policies for critical and non-critical patients with COVID-19 or under quarantine, a policy for the management of patients currently under treatment who are diagnosed or placed in quarantine, a clinical escalation action plan, guidelines for staff meetings and travel, and procedure management. This policy was implemented at George Washington University Radiation Oncology after the first case of COVID-19 was reported in Washington DC on March 7, 2020.

The School Fruit and Vegetables Scheme (SFVS) implemented by the European Union during 2009/10 aims to improve the diet of school children and to support agricultural markets and environmental sustainability. The objective of this study was to characterize the SFVS implementation in Spain (2009-2017). A descriptive, longitudinal, observational and retrospective study was carried out based on document analysis of annual strategies of the SFVS. We studied the average budget for the EU, the number of students enrolled, the cost of the SFVS by student and by day, the duration of the SFVS, the quantity of fruits and vegetables (FV) per student, the variety of FV, the inclusion of local, seasonal and organic foods, and the education activities (EA). The results were studied by autonomous community (AC). The budget increased from 7.4 million euros in 2009/10 to 14.4 in 2016/17. Since 2014/15, the increase came from EU funds, the number of students increased from 18% in 2009 to 20% in 2016. The quantity of FV went from 2,579 to 4,000 tons, duration increased from 9.8 to 19.6 days and the variety of fruits and vegetables increased from 20 to 21 and from 5 to 6 respectively. In AC there were important variations in EA, in the number of enrolled students (7.4% to 45.6%), in the cost per student (2.3€ to 28€) and in the duration in days (5.6 to 70 days). The inclusion of local, seasonal and organic foods was identified in 5 of the 8 years studied. The development and reach of the SFVS in Spain is still insufficient to influence dietary patterns and health in the school population. However, the SFVS has generated an economic market for agricultural production.

Emerging countries in Southeast Asia are facing considerable challenges in addressing rising motorisation and its negative impact on air quality, traffic, energy security, liveability, and greenhouse gas emissions. Indeed, even as initial policies to address these issues are being agreed and implemented, current trends are incompatible with sustainable development and long-term climate change targets. This paper presents a comparative analysis of the approach and status of sustainable, low-carbon transport policy in ASEAN countries and identifies differences and similarities, with the aim of helping assessment of feasibility of future policies and informing future studies on policy innovations and cross-country learning. The methodology is based on the taxonomy of policy components developed by Howlett and Cashore, and our data on comprehensive country studies for Indonesia, the Philippines, Thailand and Vietnam and interviews. We find that each country has a specific set of goals, objectives and targets that support sustainable transport, and, directly or indirectly, climate change mitigation. In terms of specific instruments and calibrations, which we analyse based on the Avoid-Shift-Improve approach, there are notable differences between the countries, for example in fuel economy policy.

A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of Agent-based Complex Systems—ACS science—has a significant potential to handle such challenges. The advantages of ACS science for sustainability are addressed by way of identifying the key elements and challenges in sustainability science, the generic features of ACS, and the key advances and challenges in modeling ACS. Artificial intelligence and data science promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.

Wearable assistant devices play an important role in daily life for people with disabilities. Those who are hearing impaired may face dangers while walking or driving on the road. The major danger is their inability to hear warning sounds from cars or ambulances. Thus, the goal of this study is to develop a wearable assistant device for the hearing impaired to recognize emergency vehicle sirens on the road using edge computing. An EfficientNet-based fuzzy rank-based ensemble model was proposed to classify seven audio sounds, including human vocalizations and emergency vehicle sirens. This model was embedded in an Arduino Nano 33 BLE Sense development board. The audio files were respectively obtained from the CREMA-D dataset and Large Scale Audio dataset of emergency vehicle sirens on the road, with a total number of 8756 files. The seven audio sounds included neutral vocalization, anger vocalization, fear vocalization, happy vocalization, car horn sound, siren sound, and ambulance siren sound. The audio signal was converted into a spectrogram by the short-time Fourier transform as the feature. When one of the car horns, sirens, or ambulance sirens was detected, the wearable assistant device presented alarms through vibration and messages on the OLED panel. The performances of the EfficientNet-based fuzzy rank-based ensemble model in offline computing achieved an accuracy of 97.1%, precision of 97.79%, sensitivity of 96.8%, and specificity of 97.04%. In edge computing, the results were an accuracy of 95.2%, precision of 93.2%, sensitivity of 95.3%, and specificity of 95.1%. Thus, the proposed wearable assistant device has the potential benefit of helping the hearing impaired avoid traffic accidents.

Graphene-based nanomaterials (GNMs), including graphene, graphene oxide, reduced graphene oxide, and graphene quantum dots, may have direct anticancer activity or be used as nanocarri-ers for antitumor drugs. GNMs usually enter tumor cells by endocytosis and can accumulate in lysosomes. This accumulation prevents drugs bound to GNMs from reaching their targets, sup-pressing their anticancer effects. A number of chemical modifications are made to GNMs to facili-tate the separation of anticancer drugs from GNMs at low lysosomal pH and to enable lysosomal escape of drugs. Lysosomal escape may be associated with oxidative stress, permeabilization of the unstable membrane of cancer cell lysosomes, release of lysosomal enzymes into the cytoplasm, and cell death. GNMs can prevent or stimulate tumor cell death by inducing protective autopha-gy or suppressing autolysosomal degradation, respectively. Furthermore, because GNMs prevent bound fluorescent agents from emitting light, their separation in lysosomes may enable tumor cell identification and therapy monitoring. In this review, we explain how the characteristics of the lysosomal microenvironment and the unique features of tumor cell lysosomes can be exploited for GNM-based cancer therapy.

This study was designed to extend the literature on multicomponent interventions for the children of deaf adults (CODA) population. This study used two evidence-based behavior intervention strategies: pre-session pairing (PSP) and independent group contingency (GC). These strategies have been successfully used to decrease off-task behavior in elementary school children with various abilities and diverse backgrounds. However, the research on multicomponent interventions has yet to examine their effects on the CODA population in inclusive classrooms. This study used a concurrent multiple baseline design across participants with an ABC sequence to examine teacher-implemented PSP with independent GC in reducing the off-task behavior of three CODAs in an inclusive classroom at a public elementary school. The results show that the intervention successfully decreased off-task behavior for all participating CODAs. The results suggest that CODAs can adapt to classroom rules and expectations when PSP and independent GC are systematically applied to them in classrooms.

Event-based vision is an emerging field of computer vision that offers unique properties such as asynchronous visual output, high temporal resolutions, and dependence on brightness changes to generate data. These properties can enable robust high-temporal-resolution object detection and tracking when combined with frame-based vision. In this paper, we present a hybrid, high-temporal-resolution, object detection and tracking approach, that combines learned and classical methods using synchronized images and event data. Off-the-shelf frame-based object detectors are used for initial object detection and classification. Then, event masks, generated per each detection, are used to enable inter-frame tracking at varying temporal resolutions using the event data. Detections are associated across time using a simple low-cost association metric. Moreover, we collect and label a traffic dataset using the hybrid sensor DAVIS 240c. This dataset is utilized for quantitative evaluation using state-of-the-art detection and tracking metrics. We provide ground truth bounding boxes and object IDs for each vehicle annotation. Further, we generate high-temporal-resolution ground truth data to analyze the tracking performance at different temporal rates. Our approach shows promising results with minimal performance deterioration at higher temporal resolutions (48 – 384 Hz) when compared with the baseline frame-based performance at 24 Hz.

The recent covid crisis has proven important lessons for academia and industry regarding digital reorganization. Among fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and over. Moreover, drug development is a costly and time-consuming business, and only a minority of approved drugs return the revenue that exceeds the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper will review the most significant research on artificial intelligence in the de novo drug design for COVID-19 pharmaceutical research.

Maternal-child care is one of the foundations of primary health care. Nurses’ competency skills they have been taught. Community awareness is an important part of preventive healthcare, and nurses must be aware of the factors that impact the health of the community. This study examines the effectiveness of lecture-based instructions in maternal and child care and its implications to students' social competency skills and community awareness in Nursing Colleges in Nueva Ecija, Philippines. The researcher uses survey questionnaire and employed the descriptive design where fifteen (15) nursing students and five (5) teachers were purposively selected. The findings revealed that the weighted mean for the effectiveness of lecture based instruction in maternal and child care is 3.91 with verbal description of “Effective”, the effects of lecture based instruction in maternal and childcare to students’ social competency skills and community awareness got the weighted mean of 3.87 and interpreted as “very satisfactory” and the effectiveness of actual community-based instruction is very effective with weighted mean of 4.25 and is higher compare to lecture based instruction. The results also revealed that students and teachers were challenged in lecture-based instruction in maternal and chi8ldcare during distance learning. Recommendations for the enhancement of lecture-based instruction in maternal and childcare in social competency skills and community awareness were also made.

Over the last decade, a significant literature has emerged that advocates the potential of different Additive manufacturing (AM) technologies and printable polymeric materials. Nevertheless, large scale printing and complex geometric shapes, with curvatures and non-planar layer deposition, are a challenging process for the traditional gantry-based machine. The 3 degrees of freedom cartesian configuration restricted their capability to planar layered printing and restricted part dimensions. To date, many researchers have used industrial robots to overcomes this limitation. This review gives the reader a good overview of the FDM technique due to its scalability, cost efficiency and a wide range of material printability. A strong emphasis is laid on the PLA and PLA-based composites as promising materials for the FDM process applications. The second part of this paper links the successful use of these materials in the traditional printing process to large scale printing using the robot-based FDM process. This survey presents representative setups for robot-based AM and works that have been used these setups for non-planar material deposition. Finally, we conclude this paper by identifying opportunities for realizing new functional capabilities by exploiting robot-based AM, and we also present the future trends in this area.

Saccharomyces cerevisiae are a phenotypically diverse species that adapt to a wide variety of environments by exploiting standing genetic diversity and selecting for advantageous mutations. Glyphosate and copper-based herbicides/ fungicides affect non-target organisms, these incidental exposures can impact microbial populations. In this study, glyphosate resistance was found in the historical collection of yeast which was collected over the last century, but only in yeast isolated after the introduction of glyphosate. The highest glyphosate-resistant yeasts were isolated from agricultural sites. However, herbicide application at these sites was not recorded. In an effort to assess glyphosate resistance and impact on non-target microorganisms, yeast were harvested from 15 areas with known herbicidal histories, including an organic farm, conventional farm, remediated coal mine, suburban locations, state park, and a national forest. Yeast representing 23 genera were isolated from 237 samples of plant, soil, spontaneous fermentation, nut, flower, fruit, feces, and tree material samples. Saccharomyces, Candida, Metschnikowia, Klyveromyces, Hanseniaspora, and Pichia were other genera commonly found across our sampled environments. Managed areas had less species diversity and at the brewery, only Saccharomyces and Pichia were isolated. A conventional farm growing RoundUp Ready™ corn had the lowest phylogenetic diversity and the highest glyphosate resistance. The mine was sprayed with multiple herbicides including a commercial formulation of glyphosate; however, the yeast did not have elevated glyphosate resistance. In contrast to the conventional farm, the mine was exposed to glyphosate only one year prior to sample isolation. Glyphosate resistance is an example of the anthropogenic selection of nontarget organisms.

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins and carbohydrates in their seeds, distinctly dominate modern agronomic practice. Indeed, these plants play an essential role in the food industry and fuel production. Therefore, the seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, not only seed development and germination, but also age- and stress-related alterations in seed vigor, longevity, nutritional value and safety can be addressed by a broad panel of analytical, biochemical and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes, accompanying plant development, senescence and response to biotic or environmental stress. Among individual methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. Here we discuss the main methodological approaches employed by seed proteomics in the context of physiological changes related to seed development, ageing and response to environmental stress.

This paper presents an in-depth contextualized tutorial on Agricultural IoT (Agri-IoT), covering the fundamental concepts, assessment of routing architectures and protocols, and performance optimization techniques via systematic survey and synthesis of related literature. The negative impacts of climate change and the increasing global population on food security and unemployment threats have motivated the adoption of the wireless sensor network (WSN)-based Agri-IoT as an indispensable underlying technology in precision agriculture and greenhouses to improve food production capacities and quality. However, most related Agri-IoT testbed solutions have failed to achieve their performance expectations due to the lack of an in-depth and contextualized reference tutorial that provides a holistic overview of communication technologies, routing architectures, and performance optimization modalities based on users’ expectations. Thus, although IoT applications are founded on a common idea, each use case (e.g., Agri-IoT) varies based on specific performance and users expectations as well as its technological, architectural, and deployment requirements. Likewise, the agricultural setting is a unique and hostile area where conventional IoT technologies do not apply, hence the need for this tutorial. Consequently, this tutorial addresses these via the following contributions: (1) a systematic overview of the fundamental concepts, technologies, and architectural standards of WSN-based Agri-IoT, (2) an evaluation of the technical design requirements of a robust, location-independent, and affordable Agri-IoT, (3) a comprehensive survey of the benchmarking fault tolerance techniques, communication standards, routing and medium access control (MAC) protocols, and WSN-based Agri-IoT testbed solutions, and (4) an in-depth case study on how to design a self-healing, energy-efficient, affordable, adaptive, stable, autonomous, and cluster-based WSN-specific Agri-IoT from a proposed taxonomy of multi-objective optimization (MOO) metrics that can guarantee an optimized network performance. Furthermore, this tutorial established new taxonomies of faults, architectural layers, and MOO metrics for cluster-based Agri-IoT (CA-IoT) networks and a 3-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.

The cement industry has significant environmental impacts, stemming from natural resources extraction and fossil fuels combustion. Notably, carbon dioxide (CO2) emissions are a major concern associated with cement production. The cement industry emits 0.6 tons of CO2 per ton of cement production, which is around 8 % of the total CO2 emissions in the world. Meeting the 13th United Nations Sustainable Goals, cement plants aim to achieve carbon neutrality by 2050, resulting from reduction in CO2 emissions (change in the composition of cementitious materials) and the adoption of carbon capture and utilisation (CCU) technologies. A promising approach involves converting CO₂ into valuable chemicals and fuels, such as methanol (MeOH) through the power-to-liquid (PtL) technologies. In this process, CO2 captured from cement industry flue gas with hydrogen generated from renewable sources through electrolysis of water, catalytically transformed into renewable methanol (e-MeOH), offering a sustainable solution. To achieve this, it is crucial to advance the development of novel, highly efficient catalysts specifically designed for direct CO2 hydrogenation. In this sense, this review discusses recent developments and improvements in CO2 catalytic conversion, emphasizing catalyst performance, selectivity, and stability.

Background Postpartum hemorrhage (PPH) remains the leading cause of maternal mortality globally, necessitating focused attention from midwifery professionals. To mitigate severe complications and improve maternal outcomes, regular and effective training in PPH rescue techniques is essential. Aim To assess the efficacy of the combination of case-based learning (CBL) and problem-based learning (PBL) with simulation teaching methods to enhance the technical proficiency of midwifery trainees in managing PPH Methods This quasi-experimental study included 76 trainees who received PPH training at Peking University Third Hospital from March to July 2023; they were divided into two groups: the control group (n = 50), which followed traditional simulation training methods, and the research group (n = 26), which used a combination of CBL-PBL and scenario simulation. After training, all participants completed a questionnaire to evaluate their satisfaction with the training program and to measure improvements in clinical thinking, practical skills, relevant knowledge, team cooperation, and management abilities. Statistical analysis was conducted using unpaired t-tests and chi-square tests to compare the groups. Findings The combination of CBL-PBL with scenario simulation was found to be highly satisfactory compared with the traditional simulation training. This approach significantly enhanced self-assessed skills among midwifery trainees in the research group. Additionally, a majority of trainees expressed a preference for the inclusion of regular simulation exercises and detailed discussions on PPH cases in future training sessions. Conclusion Combining CBL-PBL with simulation practice is a more effective teaching method for PPH management training than traditional methods. Future studies should explore the implementation of regular PPH rescue skill training and its effectiveness in real clinical settings to substantiate these findings.

Driven by environmental sustainability concerns, the integration of biobased components in curtain wall systems is gaining traction in both research and the construction market. This paper explores the development and validation of a bio-based façade system within the Basajaun H2020 project. The project aimed to demonstrate the feasibility of introducing environmentally friendly bio-based components into the mature curtain wall façade industry. The paper focuses on identifying technological solutions for replacing key components such as profiles, insulation, and the tightness system with bio-based and less environmental impact alternatives presenting the results achieved in the façade system design of the Basajaun project funded by European Union. These solutions aimed at creating a bio-composite-based curtain wall façade that adheres to current building envelope standards and normative; to implement diverse façade typologies for vision panels, opaque sections, and integrated windows; to engineer the prefabrication process for industrialization, enabling wider market replication and simplified transport and installation. The results demonstrate that the Basajaun façade successfully integrates selected components and meets the performance requirements set by regulations. However, questions remain regarding the workability of bio-based profiles as a commercially viable, ready-to-market solution that can replace traditional aluminum profiles in the curtain wall façade industry.

This review aims to consolidate varied information regarding Port Scanning, and examine the tools, techniques, and detection algorithms used. It explores TCP SYN, Full TCP, UDP, and stealth scans, and shows their functions and abilities. Paired with these techniques, it also shows the tools that they can be used by, such as NMap, Zmap, and MASSCAN. It discusses the various detection techniques such as Signature and Anomaly based detection, and discusses the real world impact of this technology, while commenting on the legal and ethical issues posed.

This study reports the synthesis and characterization of novel per-fluorinated organic polymers with azo- and azomethine-based linkers using nucleophilic aromatic substitution. The polymers reveal variations in the fluorine content via the incorporation of decafluorobiphenyl and hexafluorobenzene linkers, which enhanced their hydrophobic nature. The rich fluorine polymers were slightly soluble in THF and have shown molecular weights between 4886 to 11948 g/mol. All polymers exhibit thermal stability in the range of 350-500°C, with varying thermal stability depending on the fluorine and nitrogen content. Conjugation of the polymers was confirmed through changes in the UV-Vis spectra, with a hypsochromic shift observed in all cases, more pronounced in azo-based fluorinated chains due to H-bonding on the nitrogen sites, chain conformations, and planarity. The optical band gap (Eg) of the polymers was determined from the UV-Vis data, with the Eg values of the azo-based fluorinated polymers being 1 eV higher than those of their corresponding linkers. The cross-linking formation was characterized by porosity measurements, with the azo-based polymer exhibiting the highest surface area of 770 m²/g with a pore volume of 0.35 cm³/g, while the open-chain azomethine-based polymer exhibited the lowest surface area of 285 m²/g with a pore volume of 0.0872 cm³/g. Porous structures with varied hydrophobicities were investigated as adsorbents for separating water-benzene and water-phenol mixtures and selectively binding methane/carbon dioxide gases from the air. The most hydrophobic polymers containing the decafluorbiphenyl linker were suitable for benzene separation, while the best methane uptake values were 6.14 and 3.46 mg/g for DAB-Z-1O and DAB-A-1O, respectively. DAB-Z-1h, with the highest surface area and rich in nitrogen sites, exhibited the highest CO₂ uptake at 298 K (17.25).

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. 3D pharmacophore models are powerful computational tools in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning will be highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

Industrial products e-commerce refers to the specific application of the e-commerce concept in the field of industrial products transactions. It enables industrial enterprises to conduct transactions via Internet platforms and reduce circulation and operating costs. Industry literature such as policies, reports and standards related to industrial products e-commerce contains abundant and crucial information. Through systematical analysis of the literature information, it is beneficial to explore and grasp the development characteristics and trends of the industrial products e-commerce. To study the characteristics and development status of industrial products e-commerce in China, literature comprising 18 policy documents, 10 industrial reports and 5 standards is deeply analyzed by employing text mining methods. Firstly, natural language processing (NLP) technology is utilized to pre-process the text data related to industrial products commerce. Then, word frequency statistics and TF-IDF keyword extraction are performed, and the results of word frequency statistics are visually displayed. Subsequently, the feature set is obtained by combining the manual screening method. The original text corpus is used as the training set by employing the skip-gram model in word2vec, and the feature words are transformed into word vectors in the multi-dimensional space. The k-means algorithm is used to cluster the feature words into groups. Moreover, the latent dirichlet allocation (LDA) method is also utilized to further group and discover the features. The research results based on text mining provide supportive decisions for uncovering the development characteristics and trends of industrial products e-commerce in China.

This study investigates the impact of Government Consumption (GC) on Saudi Arabia’s GDP during major economic crises from 1969 to 2022, with a focus on periods marked by fluctuations in oil and non-oil revenues. By integrating these revenue streams, the research provides a more comprehensive analysis of fiscal policy effectiveness during economic downturns. Using an Autoregressive Distributed Lag (ARDL) model, the study reveals the complex role of Government Consumption (GC) in stabilizing and stimulating the Saudi economy amidst revenue volatility.Key findings indicate that while GC does not significantly influence GDP in the short term, its long-term effectiveness varies across different crises. Specifically, GC has acted as a buffer against immediate economic shocks during certain crises while providing a stimulus for economic recovery in others. For instance, during the 2020 COVID-19 pandemic, timely fiscal measures significantly boosted GDP, underscoring the importance of adaptive and proactive fiscal policies. Conversely, the 2014-2016 oil price collapse demonstrated that GC alone was insufficient to counteract economic downturns, emphasizing the need for diversified revenue strategies.These findings underscore the dual role of GC in economic stabilization and recovery. During the COVID-19 pandemic, GC played a crucial role in both mitigating negative economic impacts and supporting recovery efforts, showcasing its effectiveness in times of global disruptions. This demonstrates GC's capability as an immediate buffer against economic shocks and a stimulus for economic recovery. In contrast, during the 2014-2016 oil price collapse, GC was less effective, indicating the limitations of relying solely on government spending without broader economic diversification. This highlights the necessity of diversified revenue strategies to complement fiscal measures for long-term economic resilience.The robustness of the findings was ensured through various diagnostic tests, including checks for autocorrelation, heteroskedasticity, and stationarity of residuals. The absence of significant autocorrelation and heteroskedasticity, along with the stationarity of differenced variables, confirms the validity of the econometric models used.The study contributes to the discourse on fiscal policy in oil-dependent economies by illustrating the critical role of diversified revenue strategies and adaptive fiscal measures in enhancing economic resilience. Recommendations are offered for policymakers to optimize fiscal strategies, ensuring robust economic recovery and long-term stability in volatile markets. This research highlights the necessity for Saudi Arabia to refine its fiscal policies towards greater economic diversification and stability.

The current green development in the context of public policy and industrial economy is difficult to fully match the new infrastructure process driven by massive data. Its connotation and exten-sion and the level of rule of law need to be deepened to ensure that data production, processing, circulation, elimination and other activities can get high-quality and sustainable development in the collaborative construction of hard facilities and soft environment in the new era. Based on the practical needs of data industry green development in key areas, we can resolve the legal risk of data industry green development from three aspects: improving the legal level of green public policy, clarifying the green legal benchmark of data industry development, and improving the green legal system of digital society. Then, it considers the design of environmental protection system based on hardware facilities and the structural and readable clean data system innova-tion of soft data industry development framework mode, so as to clarify the legalization scheme of data industry green development under the new infrastructure. Overall, achieving the green development of the data industry requires not only active attempts by China but also joint efforts by China and other countries.

Although promoting healthy eating is a policy objective, the controllability of dietary habits remains uncertain. The personal dietary patterns reflect many factors, of which some are relatively controllable for individual, and others are not. In this article, assuming that some sort of information about controllability of dietary habits is contained in the observed pattern of food consumptions, we focused on dietary pattern on its own. We introduced a statistical descriptive model for data on food frequency questionnaire, estimated strength of pairwise linkage between foodstuffs, and grouped foodstuffs by applying community detection to the networks of the estimated inter-food linkages. Those linkages represent co-movement of pairs of foods consumption. Furthermore, we demonstrated an analysis on the relationship between health of mind and dietary habits considering the aspect of controllability of dietary habits. Using an observational study in Japan, we obtained the following results: 115 foodstuffs were divided into 3 groups for both of genders, but the compositions were different by gender; in the analysis of mental health, some stress response items were associated with the dependence on some of those food groupings. As the grouping of foodstuffs based on our estimation depicted the internal structure of dietary habit that a healthy eating policy should regard as constraint, it follows that we should design the policy along the line with that grouping.

This paper aims to provide an evaluation of how Value Added Tax (VAT) policy alterations influence market liquidity, trading volume, and stock performance. To fill the existing literature gap on the direct effect of (VAT) adjustments on stock market dynamic, particulate within the banking industry. The study employs an event study methodology to analyse the immediate and medium-term effects on bank stocks listed in markets subject to a (VAT) adjustments. The core of the study analysis is anchored around two pivotal events, the initial application of (VAT) on 1st January 2018, and the subsequent (VAT) increase to 15% on 1st July 2020 using MATLAB R2022b. The study analysis encompasses the period immediately before and after the introduction and subsequent increase (VAT) in kingdom Saudi Ariba (KSA) employing an eleven sample comprises the (KSA) largest banks with a ±7 days window period from the event. The analysis revels that the imposition of 5% (VAT) lead a substation downturn in trading volume and stock returns of 9.5%, and 39.5%, subsequently. While when the (VAT) was increased by 15% the market exhibited a mixed but ultimately positive response of 3.3% trading volumes increases and 128.7% average stock return recovery.

Historically, urban development has always been centered on coastal areas – with access to waterbodies – seas, rivers and canals being a significant advantage for movement and trade. With most of the world’s megapolises located on coasts, land reclamation offers a solution for the expansion of city centers which are otherwise restricted by the coastline. The current understanding of urban regeneration and development on reclaimed lands is defined in this study, answering the basic questions of what, why and how. This study aims to assess the urban regeneration on reclaimed coastal land based on the principles of sustainable development defined by existing studies. The literature review establishes a theoretical framework and defines performance-based benchmarks identifying the spatial indicators of urban development. Composite indicators namely open space coverage, land use mix, percentage of coast for people, accessibility to public transportation and amenities, availability of pedestrian paths and cycling tracks and adequate road networks are considered for this framework. The conclusions are drawn based on the results of the analysis of spatial layout using GIS as a tool to map and empirically measure each indicator. The framework is validated using a major land reclamation project, West Bay, in the coastal urban area of ​​the city of Doha. The results determine that West Bay has achieved a good level of sustainability, although there are areas that could be enhanced to further improve the overall sustainability of urban development. These findings can serve as a guide for policymakers and various stakeholders for sustainable urban planning on reclaimed coastal lands.

Digital infrastructure is the basic guarantee for digital transformation, it is of practical significance to discuss how to effectively use digital infrastructure construction to promote the digital transformation of tourism enterprises. This paper examines the impact of digital infrastructure construction on tourism enterprises based on the "Broadband China" policy as a quasi-natural experiment. A-share tourism listed enterprises from 2010 to 2021 are studied using the double difference method. Findings indicate that digital infrastructure construction positively and significantly influences the digital transformation of tourism enterprises, driven by digital leadership and innovation capabilities. State-owned, small-scale, and high-growth tourism enterprises benefit more from this transformation. The results suggested that the state should develop differentiated digital infrastructure plans based on the specific conditions of different tourism enterprises. Additionally, tourism enterprises should enhance digital leadership and innovation capabilities through strategic changes and digital applications to amplify the impact of digital infrastructure on their transformation.

This article deals with a finite-source stock-dependent stochastic inventory system with heterogeneous servers and retrial facility. The system can store up to S number of items, and the lifetime of each item follows an exponential distribution. The primary customers arrive in a finite waiting hall from a finite source and get service from the multi-channel (c-heterogeneous servers). The customer’s arrival rate depends on the present stock level. Those customers who arrive while the waiting hall is full enter into the finite orbit. Also, customers in the waiting hall can become impatient and enter the orbit. The (s,Q) ordering policy is adopted for the replenishment of stocks. In the steady state, the joint probability distribution of a number of items in the inventory, busy servers, customers in the waiting hall, and orbit is computed. The comparative numerical analysis of heterogeneous and homogeneous servers on the expected total cost, the average number of customers in the waiting hall and orbit, the fraction of successful retrial rate, and the average impatient customer rate are also carried out.

This study contextualises the background of Japan’s “carbon neutrality and net-zero” (CNN) policy announced in October 2020, thereby identifying important changes in the country’s climate policy between 1990 and 2020. Using four research questions, four main findings were extracted from a narrative technique-based analysis of Japan’s policy documents related to CNN. The following are the findings: [i] the framing of climate change as a “climate crisis” by influential Japanese climate stakeholders was a key motivation for Japan to formally announce its CNN policy in October 2020, [ii] pressure from the international community and the political leadership of the Yoshihide Suga administration are essential factors that led the Japanese government to change its stance and announced this policy, [iii] Japan unintentionally delayed announcement of the policy until 2020 due to the concern among Japanese climate stakeholders about the problem of fairness in Kyoto Protocol’s emission reduction targets, and [iv] this delay was also due to Keidanren’s (or business sector) consistent opposition to the introduction of regulatory schemes. These results emerge for the first time in a study of Japan’s CNN politics, particularly in terms of the broader context of climate politics. Finally, we offer a possible explanation for Suga’s deliberate announcement of the CNN policy. This opens up space for future research to complement our study by providing important indicators on the trajectory of this important policy.

The German Constitutional Court’s climate verdict provides a re-interpretation of liberal- democratic core concepts and is highly relevant for liberal constitutional law in general – including EU and international law. The verdict accepts human rights as intertemporal and globally applicable; it applies the precautionary principle to these rights and frees them from the misleading causality debate. However, the court fails to address the most important violations of human rights, and it categorised climate policy as a greater threat to freedom than climate change. And the court does not make it clear that the Paris 1.5-degree limit implies a radically smaller carbon budget. Furthermore, little attention has so far been paid to the fact that the ruling implies an obligation for more EU climate protection, especially since most emissions are regulated supranationally. To be effective, the EU emissions trading system demands a reform, which should go well beyond the existing EU proposals to enable societal transformation to sustainability.

Abstract: The purpose of this study is to explore, from the perspective of government interven-tion, behavioral logic and game relationship among farmers, service organizations and the gov-ernment in the pest and disease control outsourcing system, as well as the endogenous motiva-tion of each subject. The results indicate that the stronger the willingness of each subject, the faster the stable state of joint pest and disease control among the three parties can be formed; In the case of implementing a single policy tool, the convergence rate of each party that imple-ments the regulatory policy alone is fast but may be unstable, while the rate is slow but more stable when a guidance- or incentive-based policy is solely applied; The effect of policy tool combination is much better than that of a single policy tool applied. The simultaneous imple-mentation of the three types of policy tools can form a policy system with both positive and negative mechanisms, which can maximize complementary and superposition effect.