One of the main challenges of the globalization became the increased destabilization and frequent economic crises. In general, managing an economic crisis is a particularly difficult task for any economy (developed or developing, and regardless the size). In the context of globalization, the process faces additional challenges. On the one hand, the world economy witnessed a shift from traditional purely economic instruments to more financial mechanisms of economic development. Indeed, the liberalization of the economy since the 1990s complicated the traditional trends of the world market development, resulting in significant fluctuation of the growth rates between different countries and regions. To respond to this evolution, governments and international organizations changed well-established strategies. For example, financial sector found itself given expanded role in economic development, with, different financial mechanisms used as key variables to evaluate an economic growth. On the other hand, the increased role of financial sector in a globilised world, increased financial relations among individual states and thus, interdependences. This “financial globalization” causes important fluctuations in the system and, as a result, causes instability in socio-economic development. Thus, an economic crisis of any important economy soon becomes a global issue (financial crisis of 2008, economic crisis of 2020).The recent global economic crisis due to the Covid-19 world pandemic, appeared to be unique for several reasons. First, it highlighted the transnational and origin-specific nature of the crisis. Second, it appeared to be the first case when non-economic factors caused a major economic crisis. As a result, this crisis turned out to be particularly difficult to predict and to manage. In this case, the main strategy of the global post-crisis rehabilitation became the restoration of the economy's predictability and ensuring its ability to obey the classical principles. According to the Organic Law on "Economic Freedom" of the European Union (2011), any factor which increases the equilibrium amount of output is reflected in the economic rehabilitation plan. Such exogenous factors are primarily fiscal mechanisms, i.e. - Reduction of taxes and increase of state expenditures. This crisis caused important structural problems with their effects on public expenditures (especially health expenditures, to the public expenditures, economic growth, price stability and budget balance) in both, developed and developing countries. Nearly every state declared an increase in public debt, inflation, and unemployment rates, while an important decrease was shown in growth rates and capital outflows. As the crisis due to the world pandemic was radically different from previous economic crises, it was difficult to manage it efficiently at the initial stage. It was complicated to forecast the scenarios of the unknown crisis with non-standard nature which was more linked to epidemiologic factors than objective economic law. The dynamics of crisis resolution depended on correct forecasting and effective implementation of global, but especially country-based reforms. More importantly, this crisis showed the important role of individual states to manage the global crisis. The traditional function of a government to ensure country’s socio-economic growth and security, increases in an extraordinary environment, such as sharp economic fluctuations and crises. In such contexts, the centralized management functions are sharply activated. The global pandemic processes have updated the economic essence of the state. The large scale of the latest economic crisis due to the world pandemic has determined the need for mutually coordinated development of anti-crisis plans of different countries. In today's dynamic landscape, modern global systems are redefining the standards and priorities of national economic policies. The economic status of countries is changing significantly as a result of their participation in these systems. As a result of these changes, today's global economy is marked by the proliferation of regionalism and the emergence of spatial economic frameworks. Thus, classical economic concepts are evolving, giving rise to a new model known as economic nationalism. This paradigm shift is generating new risks, which are increasing in severity and scope. The overriding objective of economic policy is now to ensure and predict stable development. Reflections are underway to meet the challenges of economic equilibrium and its social and institutional sustainability.In addition to the decentralization of the unified governance system, the global economy is characterized by the activation of centralized governance elements within individual countries. This requires the development of new norms for global cooperation and the careful balancing of national integration and development factors. The question of government's influence on the economy and the delegation of its powers becomes relevant once again. Effective coordination of public administration is based on the principle of decentralized government, which is a key element of a democratic model of society and facilitates the transfer of management tools to the public. The key objectives of this research are focused on the optimal distribution of state functions and the study of hierarchical principles of territorial organization within the country, fiscal mechanisms for the distribution of powers, as well as the particularities of the structuring of the spatial economy and its budgetary provisioning mechanisms.The example of the last two economic crisis showed that contemporary anti-crisis strategies should reflect several considerations. First, it becomes impossible to develop a single unified model of crisis management. Even in the context of important economic and financial globalization, the current decentralization and new spatial economic processes make it necessary to find a balance between the local priorities and global interests. Second, the role of non-economic crisis-causing factors increases compared to economic determinants. That is why international and country-based reforms should aim at not only economic rehabilitation, but also on the social, cultural and environmental restorations. Third, it becomes difficult to correctly predict the consequences of the crisis and thus, the effects of the anti-crisis strategy. Consequently, the success of the post-crisis rehabilitation of the countries' economies depends significantly not only on the effective realization of their own plan, but also, in general, on the specificities of the global economy and on the ability of the world markets to overcome the negative consequences of a crisis. In this context, the development of complex post-crisis platforms and state post-crisis strategies is the priority. The most effective component in the anti-crisis strategy is the monetary instruments of economic management. As for the determinant of successful functioning of economy, the priority should be given to the regulation of exchange rate, interest rate and inflationary processes. A state anti-crisis programs should reflect the crisis prevention strategy, which, on its turn, should differentiate the economic functions of the state and crisis management mechanisms according to the specific trends of given processes. It should aim at gaining stable development of the economy. Additionally, an anti-crisis plan should reflect the role of the society in the development process and its mental changes under crisis conditions. The state should be responsible for establishing and monitoring anti-crisis management mechanisms, financial recovery of the country and formation of correct relations. It is especially important to ensure economic security, to stabilize the development process and standard of living, to support the private sector and small entrepreneurship, to increase economic freedom, to ensure effective distribution of labor and capital, and others. All strategies of the anti-crisis platform should be focused on social results, as it should contribute to a fair distribution of income and to poverty reduction.

At the beginning of 2023 the Italian former prime minister, the former health minister and 17 others including the current president of Lombardy region, were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government’s response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse pandemic data of Italy and Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers.

The increasing demand for sustainable products and services has become a constant requirement by the different stakeholders in an organization. Higher Education Institutions (HEI) have a crucial role in training conscious and competent professionals to lead these changes. Chemical analyses laboratories bring together the proper mix, where the adoption of mature and efficient management systems proves to be crucial not only to better train the institutions´ human resources but also to cooperate in recruiting research projects and other services to benefit society. Maturity models assist in the needed stages for sustainable growth to take place. This paper proposes a Maturity Model based on standardized norms to guide adjustments related to quality, risks, safety, and environment of chemical analyses laboratories in public higher education institutions. This research was done in four stages: theoretical research about Maturity Models, sustainability, and integrated management systems; survey with laboratories; case study at a chemical analyses laboratory of an HEI; and structuring and validating a maturity model. As a result of this, the model includes eight dimensions (Strategy, Leadership, Management, Operations, Continuous Improvement, Sustainability, Culture, and Integration), 31 subdimensions, and 204 management practices to assess and guide chemical analyses laboratories to sustainable maturity levels.

Diabetes self-management education helps to improve health outcomes, quality of life and to reduce expenses for diabetic patients. This systematic review aimed to examine the effectiveness of diabetes self-management education used for newly diagnosed patients with type 2 diabetes (T2DM). A review of studies that have researched the use and the impact of health education in newly diabetic patients with T2DM was implemented. A literature search was conducted using the electronic database of Pub MED, Walters Kluwer, Cochrane Library, Elsevier, JSTORE between January 2017 – November 2022. The data on participants and intervention characteristics were extracted by two reviewers independently. We found 789 studies and after selection of PRISMA flow chart we selected 19 studies, including 2512 newly diagnosed adult T2DM. Biomedical results presented the pooled effect of HbA1c -0.64%, FBG -0.32. The evaluation of emotional and social results and behavioral effects has been evaluated respectively in 10 and 9 studies. The education and support of recently diabetic patients help to improve biomedical, psychosocial, and behavioral results. This intervention must be ongoing to maintain healthy behaviors

The use of artificial intelligence technologies may help companies obtain the optimal use of resources and accomplish more activities with an increase in productivity by 40%. With access to real-time data and the ability to learn from patterns and behaviors, AI can perform these routine tasks more efficiently. Ambient intelligence, Ami, is one of the applications of artificial intelligence, which is called artificial environmental intelligence, which is a concept that focuses on using technology to create an environment that is intelligent and responsive to the needs of its users. This technology has the potential to revolutionize disaster response and management, which in turn facilitates access to necessary information and resources. necessary vitality in the event of a crisis. It may use ambient intelligence to create a network of sensors that can detect and respond to changes in the environment. So that this network can be used to monitor the environment for potential disasters, such as floods, fires and earthquakes. Sensors can also be used to detect changes in temperature, humidity, and other environmental factors that may indicate a potential disaster. This information can then be used to alert emergency responders and provide them with the information needed to respond quickly and effectively. Ambient intelligence can also be used to create a comprehensive database of resources and information that can be accessed in times of crisis. This database may include information about the location of shelters, medical facilities, and other resources that can be used to assist those affected by a disaster. It may also provide information about the condition of roads, bridges, and other infrastructure that may be affected by a disaster. This information can be used to inform response and management decisions, helping to ensure that resources are used in the most efficient way possible. Ambient intelligence can be used to create a communication platform between emergency responders and those affected by a disaster. This platform can also be used to provide updates on the emergency situation, in addition to providing information about available resources to those affected. This can help ensure that those affected by a disaster can access the resources they need in a timely manner.

In the last ten years, plasma waste treatment has gained increasing prominence as a technology in response to growing challenges in waste disposal and the recognition of opportunities for generating valuable by-products. The efficiency and outcomes of this process are intricately linked to the characteristics of the plasma involved, such as plasma enthalpy and heat flux. We employed an experimental radio frequency inductively coupled plasma (RF-ICP) torch operating at atmospheric pressure to generate plasma. Utilizing optical emission spectroscopy (OES), we measured plasma parameters, specifically the effective electron temperature (Teff) and plasma density (ne), while varying argon gas flow rates and RF powers. Our investigations revealed that both flow rate and RF power exert significant control over plasma parameters, and we observed an unusual phenomenon within this range of discharge pressures. Consequently, both the plasma's enthalpy and the heat flux it generates are influenced by variations in both flow rate and RF power.

This paper aims to propose improvements for plastic waste management in Salvador – the Brazilian third most populated metropolis – via Partial Least Squares Structural Equation Modeling (PLS-SEM). All indicators, constructs, and hypotheses regarding collection, sorting, recycling, and disposal in the proposed PLS model were derived from the literature review, and the dependence of the performance construct on efficiency, effectiveness, municipality's socioeconomic aspects and municipality infrastructure is evaluated. Academic and practitioner publics were surveyed, and after analysis in both SmartPLS and RStudio software, suggestions for improvement regarding plastics recycling rate, market maturity, and infrastructural aspects for optimized reverse logistics were made. Since almost double the minimum number of respondents answered the survey questionnaire and the PLS-SEM statistics showed that the modeling presents consistency, the discussion is relevant. The model can and will evolve, but examples of suggested improvement are the installation of Deposit-Return Systems (DRS) in parks, streets, and avenues for increasing selective collection and the direct purchasing of waste from residents by municipal administration, compensating them with vouchers for food. The model can be a basis for other cities worldwide sharing analogous characteristics. By considering it, organizations can contribute to both reduced Greenhouse Gas (GHG) emissions and reduced terrestrial pollution.

Aquaculture by-products can be compromised an important liming material of increasing soil pH and soil fertility. The aim of this research was to assess the effect of mussel shells on soil pH, on organic matter and on soil nutrients. In this study a pot experiment was carried out at the De-partment of Ichthyology and Aquatic Environment (University of Thessaly, Greece). A acidic soil (pH 4.26) amended with 6 different proportions of mussel shell (0.0, 0.1, 0.3, 0.5, 1, 3 and 6%) in two different grain sizes (Fine powder (>1 mm) and Coarse powder (1-2 mm)), resulting in 13 treatments. According to the results, it was observed that pH, organic matter, Available P and Exchangeable K increased. Specifically, the highest pH values observed at 6% rate. Available P and Exchangeable K achieved the highest content at 6% Fine powder treatment, 46.2 and 190.1 mg kg-1, respectively. Similarly, organic matter had the highest value in 6% Fine powder pots (2.27%). Moreover, Total N concentration varied from 0.11 to 0.14 but no statistically significant different was noticed between the treatments. In conclusion, mussel shells can compose a promising liming material in the agriculture section.

Enzymes are biological molecules produced by living entities for carrying out biological processes. The application of enzymes for waste treatment has been gaining pace commercially to solve concerns related to agricultural residues, wastewater, replacement of synthetic processes with natural ones, etc. The application of enzymes for waste management has been an environmentally reliable and sustainable process. Treatment of waste with enzymes such as xylanase, proteases, hydrolases, cellulose, peroxidases, chitinases, laccases, etc. has been studied to be effective. These enzymes act upon the waste products and transform them into biodegradable forms that can be recycled, reused and converted to value-added products. They have wide applications and utility as it has been an effective approach, economically cheaper and sustainable techniques. Application of such enzymes for waste management would be beneficial for reducing the quantity of waste, diminishing the negative effects of waste and pollution on the environment, and would be beneficial in bio-converting the waste products into alternate sources of energy. The current chapter focuses on different types of enzymes, their applications for waste management, and their limitations. This chapter also emphasizes the usage of some prominent microorganisms, their secreted enzymes and their proposed mechanisms of action involved with the degradation of the waste products.

This study examines the impact of GenAI tools on the daily tasks of designers within corporations. It investigates both the operational changes and employee anxieties regarding job security. The research employs a qualitative approach: one without the use of ChatGPT and one with its use. The findings indicate significant improvements in operational experience and subjective perceptions across various tasks, as demonstrated through a user experience map. Moreover, the study highlights the potential of AI for enhancing managerial efficiency, streamlining workflows, and improving collaboration. However, it also addresses challenges concerning information authenticity, copyright protection, and professional identity. The goal of this study is to comprehend AI's current role in businesses, evaluate its effects on designers, and offer balanced recommendations that emphasize the integration of AI thinking into future corporate workflows from a human-centric perspective.

Adult patients with Autism Spectrum Disorder (ASD) exhibit a range of behaviours that can be disruptive to the medical care of themselves and other patients and as a result, are at higher risk of being sedated. The aim of the present study was to determine whether patients with ASD presenting to hospital for acute psychiatric crises re-ceive more sedative medications compared to similar patients without ASD. 43 adult patients with a previous di-agnosis of ASD who were referred to the mental health team at a single, large emergency department in metro-politan Victoria over the year of 2021 were identified and matched with an equal number of controls within the same cohort. Sedative medications were converted to diazepam and chlorpromazine equivalent doses and com-pared using repeated measures T-tests. Patients with ASD received 5.1mg more diazepam-equivalent benzodiaz-epines on average compared to matched controls (95%CI: 0.41-9.71). This difference was statistically significant (T=2.20, df=42, p=0.034). There was no significance difference in chlorpromazine-equivalent antipsychotic doses. Clinicians should be aware of the higher dose of sedatives, and consider other means of behavioural management in these patients.

This study utilizes the Random Forest technique to investigate risk management practices and concerns in Islamic banks using survey data from 2016 to 2021. Findings reveal that larger banks provide more consistent survey responses, driven by their confidence and larger survey budgets. Moreover, a positive link is established between a country's development, characterized by high GDPs and low inflation and interest rates, and the precision of Islamic banks' survey responses. Analyzing risk-related concerns, the study notes a significant reduction in credit portfolio risk, attributed to improved risk management practices, global economic growth, stricter regulations, and diversified asset portfolios. Concerns related to terrorism financing and cybersecurity risks have also decreased due to better enforcement of anti-money laundering regulations and investments in cybersecurity infrastructure and education. This research enhances our understanding of risk management in Islamic banks, highlighting the impact of bank size and country development. Additionally, it emphasizes the need for ongoing analysis beyond 2021 to account for potential COVID-19 effects and evolving risk management and regulatory practices in Islamic banking.

Sustainable Forest Management (SFM) can fully use forest resources and improve the economic, environmental and social sustainability of forest areas. Forestry enterprises play a crucial role in the implementation of SFM. To better play the role of forestry enterprises in implementing SFM, it is necessary to establish a comprehensive and reasonable performance evaluation model for SFM in forestry enterprises. However, the previous literature pays little attention to this research question. Taking the Triple Bottom Line (TBL) as a theoretical framework and the Montreal Process Criteria and Indicators (MP C&I) as a basis, this paper constructs an indicator system to evaluate the performance of SFM of forest enterprises from economic, social and environmental aspects. This paper applies the integrated MCDM method, i.e. the BWM method and the VIKOR method, to construct the methodological system for SFM performance evaluation of forestry enterprises. The effectiveness of this SFM performance evaluation model is then demonstrated through its application to a case study of forestry enterprises in China. Through the application of the model, this paper evaluates the enterprise's SFM performance over the five-year period 2017-2021 and proposes appropriate policy recommendations and improvements.

This article examines how digitalisation is impacting the management of IT. Phase 1 of the re-search focuses on the German automotive industry, and adopts a qualitative inductive approach, based on feedback from 19 semi-structured interviews with IT managers and professionals. Five key aspects of digitalisation are identified, and a new model for the management of IT is devel-oped. Phase 2 then reviews the deployment of digital technologies in eight organisations from other industry sectors and assesses the overall impact on the management of IT. The results suggest that the transition to new IT management structures in the German automotive industry may be the forerunner of a change process that will impact more widely in other industries, in particular where digital technologies are now embedded in an organisation’s products or services. The results also provide some new perspectives on the conceptualisation of digitalisation and digital transformation, and represent a contribution to the developing theory around new tech-nology deployment and IT management in the digital era.

Over the past several decades, the extensive use of pyrethroids has led to the development of resistance in many insect populations, including the economically damaging pest tarnished plant bug (TPB), Lygus lineolaris on cotton. To manage TPB resistance, several commercially formulated pyrethroid-containing binary mixtures, in combination with neonicotinoids or avermectin are recommended for TPB control and resistance management in the Mid-south USA. This study aimed to evaluate the toxicity and resistance risks of four formulated pyrethroid-containing binary mixtures (Endigo, Leverage, Athena, and Hero) on one susceptible and two resistant TPB populations which were field-collected in July (Field-R1) and October (Field-R2), respectively. Based on LC50 values, both resistant TPB populations displayed variable tolerance to the four binary mixtures, with Hero showing the highest resistance and Athena the lowest. Notably, the Field-R2 exhibited 1.5-3-fold higher resistance compared to the Field-R1 for all four binary insecticides. Moreover, both resistant TPB populations demonstrated significantly higher resistance ratios toward Hero and Leverage compared to their corresponding individual pyrethroid, while Endigo and Athena showed similar or lower resistance. This study also utilized the calculated additive index (AI) and co-toxicity coefficient (CTC) analysis, which revealed that the two individual components in Leverage exhibited antagonist effects against the two resistant TPB populations. In contrast, the two individual components in Endigo, Hero and Athena displayed synergistic interactions. Considering that Hero is a mixture of two pyrethroids which can enhance the development of TPB resistance, our findings suggest that Endigo and Athena are likely superior products for slowing down resistance development in TPB populations. This study provides valuable insight for selecting the most effective mixtures to achieve better TPB control through synergistic toxicity analysis, while simultaneously reducing economic and environmental risks associated with resistance development in the insect pest.

The current organisation is facing intensifying competition in the global business world with loads of challenges and tries to sustain itself in the market through innovation and cost-cutting. The scientific community has a growing interest in management to make a niche in the global competitive era. They have started focusing on the expediency of green human resource management (GHRM) to steer the way to excel the organizations and their employees for sustainability. Green HRM tries to build an organization that encourages employees to adopt environmentally friendly workplace behaviours and minimize costs. The aim of this study is to identify and analyse the comprehensive research advances made in the field of green human resource management through bibliometric analysis. The Scopus database has been used to conduct the research. A total of 551 documents were inferred from Scopus, considering the department time period, 2004 to 2023. The outcomes of the study shed light on the eminence of green HRM research, identifying prolific authors and co-authorship patterns, commonly used keywords, country-wise and organization-wise analysis, research themes, theoretical foundations and simple statistics. This comprehensive exploration has provided valuable insights into the concept of green HRM, its objectives, and its potential benefits for businesses and society as a whole.

The capital allocation framework proposed by [] presents capital allocation principles as solutions to particular optimization problems and provides a general solution of the quadratic allocation problem via a geometric proof. However, the widely used haircut allocation principle is not reconcilable with that optimization setting. In this paper we provide an alternative proof of the quadratic allocation problem based on the Lagrange multipliers method to reach the general solution. We show that the haircut allocation principle can be accommodated to the optimization setting with the quadratic optimization criterion if one of the original conditions is relaxed. Two examples are provided to illustrate the accommodation of this allocation principle.

For an enterprise, the most critical aspect of development is resource management, which has a significant impact on all aspects of the enterprise. Therefore, enterprises must pay attention to resource management allocation, which can better promote the sustainable development of the enterprise and obtain optimal benefits. In the production and development of modern enterprises, the acquisition of benefits also involves the allocation of resources in enterprise management. This paper proposed a benefit optimization scheduling algorithm based on a macroeconomic prediction model under auction mechanism and a grid resource scheduling algorithm driven by a benefit function to allocate resources reasonably. This article used macroeconomic forecasting models to fully understand the resource needs of various departments and the resources held by enterprises, and rationally allocate various resources in various departments. This can improve the work efficiency of various departments, thereby reducing the cost of the enterprise, and achieving optimal benefits for the enterprise. The experimental results in this paper showed that the cost of resource management allocation for the benefit optimization scheduling algorithm and the grid resource scheduling algorithm based on the benefit function driven under the auction mechanism was 105.6 yuan and 46.8 yuan respectively when the task volume was 125 under the multi user environment. The time allocated for resource management was 36.6s and 18.9s respectively. It can be seen that the efficiency function driven grid resource scheduling algorithm had a lower cost and time for resource management allocation, so the efficiency function driven grid resource scheduling algorithm can achieve enterprise efficiency optimization.

The way humans use natural resources and especially freshwater, reflects their relationship with nature. It also influences the conceptual Water Resources Management (WRM) model. A historical review shows that the interplay between Humans and Nature is diachronically in constant change between two opposites: conflict and cooperation. Lessons from the past 20.000 years indicate that the WRM model is a function of two main parameters: (1) socio-economics, and (2) climate conditions. Three different Eras of the Humans-Nature relationship have been distinguished: (1) Naturalistic: Nature dominating Humans during the Last Glacial Period (100-10) kyr BC, (2) Dualistic: Nature-Humans cooperation and competition from 10 kyr BC to 1800 AD, and (3) Anthropocentric: Humans dominating Nature from 1800 AD to now. Since 2000, the Integrated WRM (IWRM) model is promoted as state-of-the-art and remains anthropocentric producing huge externalities. Its assessment during the last 20 years has given mixed results and needs to be reformulated. The new model we suggest is based on the dialectical tool for conflict resolution. It unifies Humans and Nature and enhances the social dimension of WRM. After identifying conflicts between stakeholders and the natural laws (eristic part), opposite objectives are unified to harmonize Humans with Nature (dialectical resolution). A case study of flood mitigation illustrates the eristic-dialectical methodology.

This study’s primary goal was to conduct an analysis on the flood propensity of the Tabua (Ribeira Brava) drainage basin’s main watercourse. In addition to that, this study also recommends two different methodologies in order to mitigate flood’s impacts, namely by dimensioning a detention basin and adjusting the riverbed roughness coefficient. Regarding the study on the flood propensity, it was necessary to resort to geomorphological data, which was obtained when characterizing the watershed; that data was crucial to determine the expected peak flow rate, according to the Gumbel Distribution methodology and considering a 100 years return period, and to perform necessary tasks in the SIG ArcGIS software. Lastly, it was also analyzed the drainage capacity of this drainage basin’s river mouth, in order to conclude whether it would have the capacity to drain the total volume of rainwater if an extreme flood event was to happen. Indeed, the main results point out that this watershed’s river mouth doesn’t have the necessary drainage capacity to cope with an extreme event, for the return period that was considered. As a consequence of that, the two mitigation measures aforementioned were developed considering Tabua (Ribeira Brava) drainage basin’s specific features: the sizing of the detention basin was estimated through the Dutch Method and the Simplified Triangular Hydrograph Method, while the adjustment of the roughness coefficient was considered a valid solution to enhance the drainage capacity of this river mouth.

Since the COVID-19 pandemic, urban forest mountains have become important restorative environmental spaces, and demand-customized management based on users’ experiences is needed. We collected 21,557 data points from blogs from January 2020 to December 2021. For data analysis, keyword frequency, term frequency-inverse document frequency, and sentiment analyses were conducted using TEXTOM 4.0, and a semantic linkage network was established and analyzed using Gephi 0.92. In the analyses, the restorative environment components of “being away” “fascination,” “extent,” and “compatibility” were derived from users’ experiences. Fascination, which stems from natural objects such as rocks, valleys, and trails, was derived the most frequently, and being away and compatibility, representing leisure activities such as climbing and walking, formed the largest cluster in cluster analysis. Sentiment analysis revealed a high positive word rate of 91.6%, with favorable feelings accounting for 87.5%, whereas the proportions of joy and interest (12.5%) were relatively low. This study showed that leisure activities related to nature objects had a positive impact. However, joy and interest, which correspond to vitality, were relatively lacking in the restorative experience. To improve restorative experience quality, diversification of leisure activities should be promoted and customized management plans corresponding to restorative environment components developed.

The main issues of accounting reporting regarding goodwill are whether a firm’s management reliably conveys their private information about future earnings, and whether they disclose value-relevant and useful information to accounting users. In the current International Financial Reporting Standards (IFRS) regulations, the goodwill impairment test is based on management’s discretionary assessments. This study examines how goodwill impairment is reported under IFRS considering company- and industry-specific economic factors, proxies for earnings management, and macroeconomic crisis years. We extend previous research using Tobit and Logit regression, by employing a fixed-effects model. This approach is possible because of a panel data set comprising 449 of 600 active companies sampled from the STOXX Europe 600 index from 2005 to 2018. We find that goodwill impairments are largely concentrated in certain companies, industries, and years. The regression models show a significant negative correlation between companies’ return on total assets and goodwill impairments. Moreover, we discover that goodwill impairments have a significant positive correlation with goodwill intensity, debt ratio, and the proxy for reporting a one-off big bath charge. In addition, we find that the global financial crisis in 2008-2009 and the European debt crisis in 2011 differ significantly from other fiscal years

Major emergencies can have a devastating impact on society, becoming a catalyst for social disorder and unrest and a trigger for social or political change. In today's world of frequent emergencies, the emergency management capacity of local governments is key to promoting safe operations and maintaining stability in cities and towns. Aiming to explore the direction and focus of local government emergency management capacity building, this paper establishes a local government emergency capacity evaluation system based on the emergency management process and combines Gray-Dematel, a gray decision laboratory analysis method, and AISM, an adversarial explanatory agency model, to derive the importance and intrinsic relationship among emergency capacity indicators. The algorithm describes the importance degree of each indicator in the system and also helps better understand the intrinsic relationship among the indicators. The outcomes of this research can be used to outline directional suggestions for the development of local government emergency response capacity and provide a new theoretical basis for more effective construction of local government emergency response capacity.

In this paper, a fuzzy logic-based energy management system and multi-port quasi-z-source converter are proposed that utilizes hybrid renewable energy sources. The system ensures that each energy source module can be used individually by employing fuzzy logic to define power modes. This approach also helps prevent switching losses resulting from extra switching of the source modules. Also, the proposed energy management does not have a mathematical model, so applicability is simple and it is suitable for different multiple input topologies. The Mamdani fuzzy inference system can be designed to capture the nonlinear behavior of the system because of the linguistic rules. Moreover, by adopting the quasi-z-source network to the end of the multi-port converter, the switching losses of the multi-port modules have been significantly reduced. The simulation results are obtained using MATLAB Simulink, and the experimental results are obtained by connecting the circuit to MATLAB Simulink via an Arduino Due.

Since the early 21st century, the globalization trend and technological innovations have changed the ways and speed of market growth. Rapid market expansion and the pressure for firms to achieve sustainable business growth via mergers and acquisitions have become the norms for acquiring the necessary competencies, expanding market shares and business integrations. This study explains the factors that correlate to the IJM's financial performance based on the market dynamics in recent years. This case study is a qualitative approach employing systematic review and content analysis. As a result, firms begin to diversify or venture into the business segments that might be related to or complement their core businesses, intentionally or unintentionally, which eventually evolved into the conglomerate form. This case study provides a financial performance analysis of IJM Corporation Berhad's success and challenges from its conglomerate business model. The fact that a well-diversified firm will have better risk management in the event of an economic downturn is also a primary driver for firms to embark on a corporate diversification strategy. This case study reveals IJM's conglomerate model has been successful during its rapid business growth; however, it has shown signs of diminishing in recent years.

Biological invasions are a human-induced environmental disturbance that can cause major changes in ecosystem structure and functioning. Located in the northeastern Mediterranean basin, the Aegean Sea is a hotspot of biological invasions. Although the presence of alien species in the Aegean has been studied and monitored, no assessment has been conducted on their cumulative impacts on native biodiversity. To address this gap and identify the most highly impacted areas and habitats and the most impactful invasive species in the Aegean, we applied the CIMPAL index, a framework developed for mapping the cumulative impacts of invasive species. Coastal habitats showed stronger impacts than the open sea. The highest CIMPAL scores were four times more frequent in the South than in the North Aegean. Shallow (0-60 m) hard substrate was the most heavily impacted habitat type, followed by soft substrates and seagrass meadows. We identified Caulerpa cylindracea, Lophocladia lallemandii, Siganus spp. and Womersleyella setacea as the most im-pactful species across their range of occurrence in the Aegean but, ranking varied depending on the habitat and impact indicator applied. Our assessment can support marine managers in prioritizing decisions and actions to control biological invasions and mitigate their impacts in the Aegean Sea.

: Border management serves as a crucial control checkpoint for governments to regulate the quality and safety of imported food. In 2020, the ensemble learning prediction model EL V.1 was introduced to Taiwan's border food management. This model primarily assesses the risk of imported food by combining five algorithms to determine whether quality sampling should be performed on imported food at the border. In this study, a second-generation ensemble learning prediction model, EL V.2, was developed based on seven algorithms to enhance the "detection rate of unqualified cases" and improve the robustness of the model. The chi-square test was employed to compare the efficacy of "pre-launch (2019) random sampling inspection" and "post-launch (2020–2022) model prediction sampling inspection". For cases recommended for inspection by the ensemble learning model and subsequently inspected, the unqualified rates were 5.10%, 6.36%, and 4.39% in 2020, 2021, and 2022, respectively, which were significantly higher (p=0.000***) compared with the random sampling rate of 2.09% in 2019. The prediction indices established by the confusion matrix were used to further evaluate the prediction effects of EL V.1 and EL V.2, and the EL V.2 model exhibited superior predictive performance compared with EL V.1, and both models outperformed random sampling.

This paper presents an improved SOC estimation method for lithium ion batteries in Electric Vehicles using Bayesian optimized feedforward network. This innovative bayesian optimized neural network method attempts to minimize a scalar objective function by extracting hyperpa-rameters (hidden neurons in both layers) using a surrogate model. Furthemore, the hyperparameters are built and data samples are trained and validated. The performance of the proposed deep learning neural network is evaluated. Two reasonable size data samples are ex-tracted from Panasonic 18650PF Li-ion Mendeley datasets that are used for training and valida-tion. RNN and LSTM neural network algorithms offer the common core property of retaining past information and/or hidden states for better SOC estimation. However, the feature of this pro-posed method is the inclusion of Bayesian optimization that chooses optimal double layer hidden neurons. Analysis of results shows that Bayesian optimized feedforward algorithm with average MAPE (0.20%) is the lowest and is the best selection compared with average MAPE for other five deep learning algorithms. In the last quarter of fuel gauge, where fuel anxiety is severe, feed-forward with Bayesian Optimization algorithm is still the best selection (with MAPE of 0.64%).

Browsing of wild ungulates can have profound effects on the structure and composition of forests. In the Swiss National Park, the density of wild ungulates including red deer (Cervus elaphus), ibex (Capra ibex), and chamois (Rupicapra rupicapra) is exceptionally high due to strict protection and the absence of large predators. We examined count data of larch (Larix decidua), cembra pine (Pinus cembra), spruce (Picea abies), upright mountain pine (Pinus mugo subsp. uncinata), and mountain ash (Sorbus aucuparia) of four sampling years between 1991 and 2021 and modelled how different topographic and location factors affected the probability of browsing on saplings of larch, cembra pine, and spruce. Despite the high density of wild ungulates, the numbers of saplings and young trees increased over the past 30 years. The probability of browsing on saplings was highest for larch at a height of 10 – 40 cm and increased with increasing elevation. In our study area, open grasslands are mainly located above the tree line, which might explain the positive correlation between elevation and the probability of browsing. Other factors like exposition and slope, available food resources and disturbance by humans did not have clear effects on the probability of browsing.

In the chemical processing industries, sensors for pumps are among the most commonly used machinery. Condition-based maintenance (CBM) and prognosis health management (PHM) determine the most cost-effective time to overhaul pumps. In order to determine the status of the pump, a signal-emitting accelerometer is employed. Stationarity-based feature extraction from amplitude signals is used to process the signal. Utilizing the time-domain function, multiple statistical results were produced. Eight fault codes were classified using support vector machine method. The enormous amount of data points necessitated the use of feature selection. In terms of accuracy, precision, recall, and F1 score, the Chi-square feature selection method exceeds other approaches.

The research objects are the tax and budgetary policies of the Russian Federation. In this research, financial (budgetary) risks are understood as a decrease in the balance of the state (national) budget resulting from a reduction in revenues or an increase in expenditures. This research considers production in the main sectors of the economy as a key factor of financial risk in the COVID-19 pandemic. The research aims to analyze the main directions of the budgetary and tax policy of the Russian Federation aiming at supporting the economy and the population during the spread of COVID-19, which is especially relevant in connection with the expected recession in a number of sectors of the economy and a decrease in the level of employment and, accordingly, the well-being of citizens. In these conditions, it is necessary to adjust the budgetary and tax policy to preserve the state’s social obligations and expand social and economic support for businesses and citizens to smooth out the negative consequences of the impact of restrictive measures. The authors applied systemic and institutional approaches and statistical methods. The main results of the research reflect the need to (1) implement support measures (tax and budgetary incentives) for small and medium-sized enterprises, on which the crisis provoked by the COVID-19 pandemic has had the most destructive impact, and (2) to expand the volume of budgetary financing of social programs for financial risk management of the Russian economy during the COVID-19 pandemics.

Kubernetes (K8s) defines standardized APIs for container-based cluster orchestration so it becomes possible for application managers to deploy their applications in a unified manner across different cloud providers. A practical problem is however feature incompatibility between different K8s vendors, who offer commercial K8s products based on the open-source K8s distribution. A large number of documented features in this open-source distribution are optional features that are turned off by default, but can be activated by setting specific combinations of parameters and plug-in components in configuration manifests for the K8s control plane and worker node agents. However, none of these configuration manifests are standardized, giving K8s vendors the freedom to hide the manifests behind a single, more restricted, and proprietary customization interface. Therefore some optional K8s features cannot be activated consistently across K8s vendors and applications that require these features cannot be run on those vendors. In this paper we present a unified, vendor-agnostic feature management approach that bypasses the proprietary customization interface of K8s vendors in order to consistently activate optional K8s features across a federation of clusters hosted by different Kubernetes vendors. We describe vendor-agnostic reconfiguration tactics that are already applied in industry and cover a wide range of optional K8s features. Based on these tactics, we design and implement an autonomic controller for declarative feature compatibility management across a cluster federation. We found that the features configured through our vendor-agnostic approach have no impact on application performance when compared with a cluster where the features are configured using the configuration manifests of the open-source K8s distribution. Moreover, the maximum time to complete reconfiguration of a single feature is within 100 seconds, which is 6 times faster than using proprietary customization interfaces of mainstream K8s vendors such as Google Kubernetes Engine. However, there is a non-negligible disruption to running applications when performing the reconfiguration; this disruption impact does not appear using the proprietary customization methods of the K8s vendors. Therefore, our approach is best applied in the following three use cases: (i) when starting up new K8s clusters, (ii) when optional K8s features of existing clusters must be activated as quickly as possibly and temporary disruption to running applications can be tolerated or (iii) when proprietary customization interfaces do not allow to activate the desired optional feature.

The purpose of this study was to model the impact of mentoring on women’s work-life balance. Indeed, this study considered mentoring as a solution to create a work-life balance of women. For this purpose, semi-structured interviews with both mentors and mentees of Tehran Municipality were conducted and the collected data were analyzed using constructivist grounded theory. Findings provided a model of how mentoring affects women's work-life balance. According to this model, role management is the key criterion for balancing work-life of women. In this model, antecedents of role management and the contextual factors affecting role management, the constraints of mentoring in the organization, as well as the consequences of effective mentoring in the organization are described. The findings of this research contribute to the mentoring literature as well as to the role management literature and provide recommendations for organizations and for future research.

Global crop yield and food security are being threatened by phytophagous insects. Innovative methods are required to increase agricultural output while reducing reliance on hazardous synthetic insecticides. It appears to be quite effective at reducing production costs and boosting farm profitability to use the ground-breaking CRISPR-Cas technology to create plants that are insect resistant. In contrast, this new technique can modify an insect's genome to either produce gene drive or get beyond an insect's tolerance to various insecticides. This paper reviews and critically discusses the use of CRISPR-Cas genome editing technology in long-term insect pest management. The emphasis of this review is on the prospective uses of the CRISPR-Cas system for insect stress management in crop production by creating genome-edited crops and insects. The potential and difficulties of using CRISPR-Cas technology to reduce pest stress in crop plants are critically examined and discussed.

The paper deals with the design of a systematic procedure for implementing strategy changes into internal business processes for a project-oriented production type of organization. In the first part of the contribution, a summary of the theoretical starting points for the field of strategic management and change management is presented. In the second part, the contribution deals with the analysis of the current situation in the area of the impact of the change of strategy on the management of business processes. In the last part, the proposal of the procedure for implementing strategy changes into internal business processes and the verification results are presented. The proposed procedure includes steps where the selection and verification of key performance indicators at individual levels of management plus the quantification of the impact of the change in strategy on the processes takes place. The management can thus monitor and evaluate the chosen processes in accordance with the fulfilment of the chosen strategy of the company. The last chapter presents the verification of the proposal for the systematic introduction of changes into the processes.

Disabled children on the one hand have a wide range of impairments that translate into functional limitations but at the same time they possess various talents and capacities. These are manifested into the dynamics of society and the environment that they interact with. This article discusses disaster management with disabled children as a focus group. Disaster, disability and its management is discussed in the context of international practices in general and suited to India in particular. The research follows a review of the recommendations of the United States National Commission on Children and Disaster. In addition to this Disaster Medicine as one approach to Disaster Management concerning disabled children has been explored. The research concludes that the understanding of particular issues of Children with disabilities as one stakeholder, their capacity to engage and a shift in mindset and power relations in which they can contribute to disability inclusive disaster management are fundamental to disability-inclusive DRR.

COVID-19 has become a part of everyone's day-to-day life, since the outbreak in 2019 the novel coronavirus disease (COVID-19) has caused more than 4.5 million deaths with over 200 million cases reported globally. Currently, the number of infections and deaths are gradually lowering in different countries however the underlying challenges still exist. COVID-19 threatens human life, social functioning and development. Although numerous studies have been carried out in the past to highlight the key challenges very limited studies have been conducted from an ordinary person's viewpoint. In the fight against COVID-19, humanity has been pushed to a level which cannot be accepted where establishing that balance is a priority. This study focuses on highlighting the common issues faced by the ordinary public in the current era. Five key areas were identified to be the most essential; education, technological adaptation, transportation, mental health and gender-based violence (GBV).

Threats emerging from microplastics pollution in the marine environment have received much global attention. This review assessed sources, fate, and impacts of microplastics in marine ecosystems and identified gaps. Most studies document ubiquity of microplastics and associated environmental effects. Effects include impacts to marine ecosystems, risks to biodiversity, and threats to human health. Microplastic leakage into marine ecosystems arises from plastic waste mismanagement and a lack of effective mitigative strategies. This review identified a scarcity of microplastics mitigation strategies across different stakeholders. Lack of community involvement in microplastic monitoring or ecosystem conservation exists due to limited existence of stakeholder co-management initiatives. Although some management strategies exist for controlling the effects of microplastics (often implemented by local and global environmental groups); a standardized management strategy to mitigate microplastics in coastal areas is urgently required. There is a need to identify focal causes of microplastic pollution in the marine environment through further environmental research. This would extend to creating more effective policies as well as harmonized and extended efforts of educational campaigns and incentives for counteraction and plastic waste reduction, while mandating stringent penalties for polluting the marine environment. This will help reduce microplastic leakage into the environment.

This paper discusses the use of a participatory approach to assess the level of understanding of the Water-Energy-Climate Change nexus in South Africa. The aim is to facilitate the development of well-coordinated, systematic, and holistic strategies for efficient management of the nexus and its implications in the country. The assessment was guided by the broader Integrated Water Resource Management framework, which promotes a participatory approach in the administration of water resources. The paper argues that despite the reasonable level of understanding of WECC, there is still a lack of integrated policy development and planning among key stakeholders. This is exacerbated by limited coordination and consultation among these stakeholders, particularly policymakers. This necessitates the urgent adoption of holistic and systems thinking approaches, and the promotion of collaboration among different stakeholders mandated to manage WECC sectors. Until such approaches are adopted, the WECC nexus will continue to impede the country’s socio-economic development and environmental wellbeing.

Low back pain (LBP) is a leading cause of disability. It significantly impacts the patient’s quality of life, limits their daily living activities, and reduces work productivity. To reduce the burden of LBP, several pharmacological and non-pharmacological treatment options are available. This review summarizes the role of heat therapy in the management of LBP. First, we outline the common causes of LBP, then discuss the general mechanisms of heat therapy on (LB)P, and finally review the published evidence regarding the impact of heat therapy in patients with acute or chronic non-specific LBP. This review demonstrates that continuous, low-level heat therapy provides pain relief, improves muscular strength, and increases flexibility. Therefore, this effective, safe, easy-to-use, and cost-effective non-pharmacological pain relief option is still relevant in modern clinical practice.

The leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of ecosystems productivity and related climate, topography, and edaphic impacts. The spatio-temporal changes of LAI were assessed throughout Ardabil Province, a host of relevant plant communities within the critical ecoregion of a semi-arid climate. In a comparative study, novel data from Google Earth Engine- GEE was tested against traditional ENVI measures to provide LAI estimations. Besides, it is of important practical significance for institutional networks to quantitatively and accurately estimate LAI at large areas in a short time and using appropriate baseline vegetation indices. Therefore, LAI was characterized for ecoregions of Ardabil Province using remote sensing indices extracted from Landsat 8 Operational Land Imager (OLI), including Enhanced Vegetation Index calculated in GEE (EVIG) and ENVI5.3 software (EVIE), as well as Normalized Difference Vegetation Index estimated in ENVI5.3 software (NDVIE). Besides, a new field measurement method, i.e., the LaiPen LP 100 portable device (LP 100), was used to evaluate the accuracy of the derived indices. Accordingly, the LAI was measured on June and July 2020 in 822 ground points distributed in 16 different ecoregions-sub ecoregions having various Plant Functional Types (PFTs) of the shrub, bush, and tree. The analyses revealed heterogeneous spatial and temporal variability in vegetation indices and LAIs within and between ecoregions. The mean (standard deviation) value of EVIG, EVIE, and NDVIE at Province scale yielded 1.1 (0.41), 2.20 (0.78), and 3.00 (1.01), respectively in June, and 0.67 (0.37), 0.80 (0.63), and 1.88 (1.23), in that respect in July. The highest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June are found in Meshginshahr (1.40), Meshginshahr (2.80), and Hir (4.33) ecoregions and in July are found in Andabil ecoregion respectively with values of 1.23, 1.5, and 3.64. The lowest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June were observed for Kowsar (0.67), Meshginshahr (1.8), and Neur (2.70), ecoregions and in July were for Bilesavar ecoregion respectively with values of 0.31, 0.31, and 0.81. High correlation and determination coefficients (r>0.83 and R2>0.68) between LP 100 and remote sensing derived LAI were observed in all three PFTs (except for NDVIE-LAI in June with r=0.56 and R2=0.31). On average, all three examined LAI measures tended to underestimation compared to LP 100-LAI (r>0.42). The findings of the present study can be promising for effective monitoring and proper management of vegetation and land use in Ardabil Province and other similar areas.

The impact that new technologies have on all aspects of our lives, work, and businesses is significant and growing over time. Blockchain and artificial intelligence, among other innovative technologies, are having a profound effect on practically all business functions, including most human resources (HR) tasks. The HR sector is currently facing a variety of challenges as HR departments invest many hours in vetting candidates' applications and authenticating records to decrease the chances of imperfect recruiting. Nowadays, more technologically based processes are utilised for talent search, selection and management, as well as for accumulating, retaining, and integrating new talents into a company. These HR practices are far more effective compared to traditional methods but can also be more expensive if the transactional costs are considered. This paper consists of two parts. Following an introduction, the first part discusses the trust and confidentiality that can be attained, while the second part examines security, fraud prevention and the productivity gained from using blockchain technology in HR activities. Finally, there is a concluding section, discussing the implications of blockchain technology for firms who choose to employ it.

: The purpose of this research was to verify the importance and performance of crisis management in Korean fitness center using Importance-Performance Analysis (IPA). For this study, 304 fitness center executives and managers in Seoul and Gyeonggi region were selected as from March 21 to May 17, 2020. Frequency analysis was performed using SPSS 24.0 and exploratory factor analysis was conducted to verify the validity and reliability. Priority analysis and IPA analysis were performed to compare the mean values, and the following results were obtained. First, in the first quadrant, there were 6 attributes besides keep social distancing between employees and customers. Second, in the second quadrant, there were four attributes in addition to regular disinfection of the gymnasium. Third, in the third quadrant, there were 6 attributes besides maintain furniture clean. Third, there were 6 attributes other than maintaining furniture clean in the third quadrant. Fourth, in the fourth quadrant, there are three attributes in addition to the restriction of face-to-face meetings. The conclusion is as follows. First, equip supplies for prevention of covid19, keep social distance, and check government support policies. Second, analyze of economic support policies, and research on their application methods. Third, Prepare various non-face-to-face communication methods and Untact(non-contact) marketing strategies. Fourth, make a checklist for factors with relatively little importance.

Background: Laryngopharyngeal reflux (LPR) is a common disease in otolaryngology characterized by an inflammatory reaction of the mucosa of the upper aerodigestive tract caused by digestive refluxate enzymes. LPR has been identified as etiological or favoring factor of laryngeal, oral, sinonasal or otological diseases. In this case-series, we reported atypical clinical presentation of LPR in patients presenting in our clinic with reflux. Methods: A retrospective medical chart review of 351 patients with LPR treated in the European Reflux Clinic in Brussels, Poitiers and Paris was performed. In order to be included, patients had to report atypical clinical presentation of LPR, consisting of symptoms or findings that are not described in reflux symptom score and reflux sign assessment. The LPR diagnosis was confirmed with 24-hour hypopharyngeal-esophageal impedance pH-study and patients were treated with a combination of diet, proton pump inhibitors and alginates. The atypical symptoms or findings had to be resolved from pre- to posttreatment Results: From 2017 to 2021, 21 patients with atypical LPR were treated in our center. The clinical presentation consisted of recurrent aphthosis or burning mouth (N=9), recurrent burps and abdominal disorders (N=2), posterior nasal obstruction (N=2), recurrent acute suppurative otitis media (N=2), severe vocal fold dysplasia (N=2), and recurrent acute rhinopharyngitis (N=1), tearing (N=1), aspirations (N=1) or tracheobronchitis (N=1). Abnormal upper aerodigestive tract reflux events were identified in all of these patients. Atypical clinical findings resolved and did not recur after an adequate anti-reflux treatment. Conclusion: LPR may present with various clinical presentations including mouth, eye, tracheobronchial, nasal or laryngeal findings, which may all regress with an adequate treatment. Future studies are needed to better specify the relationship between LPR and these atypical findings through analyses identifying gastroduodenal enzyme in the enflamed tissue.

The disastrous 2017 fire season in Portugal lead to widespread recognition of the need for a paradigm shift in forest and fire management. We focused our study on Alvares, a parish in central Portugal which had 60% of its area burned in 2017, with a large record of historical. We evaluated how different fuel treatment strategies can reduce wildfire hazard in Alvares, through i) a fuel break network with different priorities and ii) random fuel treatments resulting from stand-level management intensification. To assess this, we developed a stochastic fire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast, and center-east areas of the parish that are very often associated with high fire line intensities. The different fuel treatment scenarios decreased burned area between 12.1-31.2%, resulting from 1%-4.6% increases in annual treatment area, and reduced 10%-40% the likelihood of wildfires larger than 5000 ha. On average, simulated burned area decreased 0.22% per each ha treated, and effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.

Clearly policy makers should consider the impacts of any decisions they might make before making them. Science can provide estimates of various economic, ecologic, environmental, and even social impacts of alternative policies, impacts that determine how effective any particular policy will be. These impact estimates can be used to compare and evaluate alternative policies in the search for identifying the best one to implement. Among all scientists providing inputs to policy making processes are analysts who develop and apply models that provide these estimated impacts and, possibly, their probabilities of occurrence. But just producing them is not a guarantee that they will be considered by policy makers. This paper discusses ways scientists, including systems analysts, can effectively contribute to and inform those involved in making water management decisions. Brief descriptions of a variety of past and on-going water management policy making processes illustrate both some successes and failures of science informing policy.

Rice wheat cropping system prevailed in more than fifty percent areas of rice belt of central and upper Punjab. In this area yield of wheat is curtailed every year due to late harvesting of rice crop. In addition to this, lack of machinery for direct sowing of wheat into combine harvested rice is a major limitation for timely wheat sowing due to presence of heavy straw load dropped by the combine harvester. A field experiment was planned and executed during two consecutive years 2017-18 and 2018-19 at Agronomic Research Station Farooqabad to evaluate the various stubble management techniques for the sowing of wheat in a rice-wheat cropping system. The Experiment consist of four treatments Happy seeder (Zero tillage), conventional sowing without burning of rice stubble, Rotavator two times, and Conventional sowing with the burning of rice stubble. The trail was arranged as a Randomized Complete Block Design with four replications having a net plot size of 8 m x 20 m. The Treatments have significant effects on Plant height, Number of productive tillers, 1000- grain weight, and grain yield. Maximum plant height (94.74 and 94.25 cm), numbers of productive tillers/m2 (324.00 and 322.25), 1000-grain weight (36.35 and 36.20 g), grain yield (3780 and 3613 kg/ha), and benefit-cost ratio (2.54 and 2.43) were recorded from the treatment happy seeder (Zero tillage) during both years respectively. It is concluded that the sowing of wheat with a happy seeder (Zero tillage) is an appropriate technique in the rice-wheat cropping system by protecting the environment and soil health from the burning of rice stubbles.

Background: The purpose of this study was to evaluate and compare the performance of health, safety and environmental management of civil, traffic and urban services contractors in the 18th district of Tehran municipality in 2015-2016. Methods: This is an applied, longitudinal, descriptive-comparative study. The statistical population of this study was construction contractors, urban services and traffic in the municipality of district 18 of Tehran in the years 2015-2016. from 52 contractors, 18 construction contractors, 21 utilities contractors and 13 traffic contractors, respectively, were selected using census method. the research instrument consisted of periodic direct observation and completion of the HSE standard checklist by researchers. Data were analyzed using Kruskal-Wallis nonparametric test by SPSS software.Results: The HSE performance of all contractors (civil, utilities and traffic) was acceptable and the results of Kruskal-Wallis test showed that the HSE performance of contractors at the second visit of 2015 and the first visit of 2016 was significantly different in favor of civil contractors )p <0.01), but there was no significant difference between the first and third visits of 2015 and the second and third visits of 2016 (p> 0.05). visits in six periods indicate HSE Civil Contractors status increased from 100% unfavorable to 88.88% acceptable level and 11.11% good level, and in the case of civil service contractors who initially had 95.23% in an unfavorable situation and 4.76% in a favorable situation achieved 100% acceptable performance, and finally, the traffic contractors, who were 100% unfavorable, were upgraded to 100% acceptable. Conclusion: According to the findings of the study, it seems that the supervision of municipality inspectors on HSE performance of contractors can be effective in improving and strengthening the commitment to HSE requirements, therefore, it is suggested that periodical visits be made to the municipal contractors.

There are uncertainties associated with every phase of the stock assessment process, ranging from the collection of data, assessment model choice, model assumptions and interpretation of risk to the implementation of management advice. The dynamics of fish populations are complex, and our incomplete understanding of those dynamics (and limited observations of important mechanisms) necessitate that models are simpler than nature. The aim is for the model to capture enough of the dynamics to accurately estimate trends and abundance and to provide advice to managers about sustainable harvests. The \textit{status quo} approach to assessment modelling has been to identify the `best' model, based on diagnostics and model selection criteria, and to generate advice from that model, mostly ignoring advice from other model configurations regardless of how closely they performed relative to the chosen model. We review the suitability of the ensemble modelling paradigm to more fully capture uncertainty in stock assessment model building and the provision of advice. We recommend further research to evaluate potential gains in modelling performance and advice from the use of ensemble modelling, while also suggesting revisions to the formal process for reviewing models and providing advice to management bodies.

Risk assessment management have been a hot topic for the researchers since a very long time. Software risk management is an important part of project management as it contains the identification, analysis, estimation and monitoring of different risks present in the system. This helps developers in decision making while assessing the problems that could arise in the software systems. Risk management is very complex in large scale system as these systems have very complex development. The paper describes risk management techniques for large scale system. Furthermore we have provided a detailed comparative analysis of these techniques with commonly identified risks in software systems and have provided a systematic order for risk management process to ensure risk mitigation.

Corporate Sustainability (CS) literature has gone through a period of intense development. The moment is favorable to gathering these contributions to consistently advance the state of the art in CS and, also, discuss them to apply in real contexts. The main objective of the paper is to systematize, through a systematic literature review using content analysis of the 30 most cited articles from 2007 to 2017, the guiding pillars of CS management. The systematic search for papers was carried out in Scopus and Web of Science and the initial screening of the papers was assisted by the coding software MAXQDA 2018, through which the authors structured and analyzed their main insights, contributions and conclusions. After getting acquainted with the sample, an in-depth reading of the texts was conducted and 60 CS elements were identified. The elements cited in the relevant literature were grouped into 6 pillars related to Corporate sustainability strategy; Corporate governance; Human resources management; Knowledge and innovation management; Measurement, disclosure and independent assurance; and Management systems and Integrated management systems. The discussion of CS management pillars presented in this study provides understanding to researchers and managers on the main aspects that make up the integration of this construct in the companies, especially from a management point of view.

In this study, the decision-making process management of forest tending in the forestry business is decentralized, and forest tending decision-making activities at different points in time are integrated by decision makers at different geographical locations. The decision-making process was analyzed and optimized from a system perspective. Based on the optimized decision-making process, a forest tending business group decision support system (FTGDSS) was established. We first reviewed and discussed the characteristics and development of the forest tending business and forestry decision support system. Business Process Modeling Notation was used to draw a current state flow chart of the forest tending business, to identify and discover important decision points in the process of tending decision-making. We also analyzed the content and attributes of each decision point, and described the system structure, functional framework, knowledge base structure, and reasoning algorithm of FTGDSS in detail. Finally, FTGDSS was evaluated from the two dimensions of the technology adoption model. FTGDSS integrates different levels of time-space decision-making activities, historical tending data, business plans, decision-makers' management tendencies into the decision-making process and automatically extracts decision-making data from the forest business process management enterprise resource planning system (Smartforest) that improves the ease of use of the decision support system (DSS). It also improves the quality of forest tending decisions, and enables the DSS to better support multi-target management strategies.

A long-term investigation of D. suzukii dynamics in wild blueberry fields from 2012 - 2018 demonstrates relative abundance is still increasing seven years after initial invasion. Relative abundance is determined by physiological date of first detection and air temperatures the previous winter. Date of first detection of flies does not determine date of fruit infestation. The level of fruit infestation is determined by year, fly pressure, and insecticide application frequency. Frequency of insecticide application is determined by production system. Non-crop wild fruit and predation influences fly pressure; increased wild fruit abundance results in increased fly pressure. Increased predation rate reduces fly pressure, but only at high abundance of flies, or when high levels of wild fruit are present along field edges. Male sex ratio might be declining over the seven years. Action thresholds were developed from samples of 92 fields from 2012 - 2017 that related cumulative adult male trap capture to the following week likelihood of fruit infestation. A two-parameter gamma density function describing this probability was used to develop a risk-based gradient action threshold system. The action thresholds were validated from 2016-2018 in 35 fields and were shown to work well in two of three years (2016 and 2017).

Power system decentralization has been an emerging topic for the past decade in an effort to improve power quality and environment protection via increased integration of renewable energy sources. Towards these objectives, decentralized microgrids have been proposed and thoroughly investigated in terms of technical capabilities and economic performance. In fact, the planning and actual operation of small-scale, decentralized microgrids has started in countries such as Canada, Japan, USA, UK and other countries. It is expected that the research in this area will progress and eventually take over the existing paradigm of large-scale power generation in the future. These small-size decentralized microgrids could be connected with nearby microgrids under normal operating conditions, but under special events, such as natural or man-made disasters, they would be disconnected and run in islanded mode. Under such high impact – low probability events, the microgrid must have resiliency to successfully re-connect with other microgrids and the main grid. In this paper, an Energy Management System (EMS) for a microgrid having a resiliency function, allowing to operate under islanded mode after an accident, is proposed. The proposed tool, called Resilient Energy Management System (ResEMS), aims at procuring reserve power into the microgrid’s Battery Energy Storage System (BESS) effectively, by importing it from the nearby connected power system. The accident is assumed to be a predictable natural disaster, which means that the accident occurrence time, duration and level of damage can be estimated. The proposed ResEMS has been applied to a microgrid comprising of a BESS, a diesel generator and several photovoltaic devices. The simulation results verify its beneficial operation.

Crop production is a major livelihood activity of smallholders in Ethiopia. However, it is often characterized by low performance. In an effort to improve crop production, a series of agricultural extension programs have been running in Ethiopia since the 1950s. Nevertheless, the performance of agriculture is still low. In this study, it is argued that the limited attention given to cropland allocation methodologies is one of the major causes of low performance of crop production and increased environmental degradation. This study used linear programming to examine the role and impacts of cropland allocation methods on performance of crop production. The data for this study was drawn from household survey of 75 randomly selected households combined with focus-grouped discussion, key informant interview, and secondary data. In the current conventional cropland allocation, households were not able to meet their household consumption. The average profitability of farms under current practice was found significantly below than estimated optimal level of profit that could be realized using linear programming. In addition, it uncovered that low performance of crop production (in terms of meeting household consumption demand and profitability) is the primary cause that limited the effort of households to participate in environmental and natural resource management. This study suggests the use of linear programming-based cropland allocation to enhance the profit performance of smallholder crop production, meeting household consumption requirement, and thereby promote sustainable utilization of natural and environmental resources.

The unsustainability of the services related to water, sanitation and hygiene in informal settlements in Sub-Saharan Africa services is deeply embedded in current societal and governance structures, cultures and practices; it is context-dependent and involves numerous actors with different interests. The field of sustainability transitions research addresses such persistent and large scale societal challenges, with transition management being one of its widely applied governance approach. By drawing on an analysis of the root causes of unsustainability and unreliability of WASH services in three case studies in Sub-Saharan Africa (Arusha-Tanzania, Dodowa-Ghana, Kampala-Uganda), we explore how a transition management approach can be designed to support a transition towards sustainable Water, Sanitation and Hygiene (WASH) in Sub-Saharan Africa. We distinguish the following contextual dimensions related to the unsustainability of WASH services: a) Multiplicity of WASH practices, structures and arrangements, b) Governance capacities for WASH services and maintenance, c) Landownership for sustainable access to WASH, d) Public participation in decision-making related to WASH, e) socio-economic structures governing access to WASH. These dimensions prompt the identification of conceptual and application challenges for transition management. Based on these challenges, recommendations were formulated for the design of a prescriptive transition management process that is not only functional but also emancipatory of character.

The number of green buildings has increased to address the global environmental crisis. However, green buildings face risks resulting from new materials and methods. In addition, these buildings are expected to perform at higher levels than traditional ones. The objectives of this study are to identify the possible risk factors for architects developing green building projects in South Korea and to assess risk mitigation measures. To attain this goal, fourteen risk factors and twelve mitigation measures were identified from a comprehensive literature review. A questionnaire survey was administered to architects practicing green building design. Findings revealed the ‘adoption of new technology and processes’ was the largest difference between green and traditional building projects. This study identified ‘financial risk,’ ‘design changes,’ and ‘client’s goal uncertainty’ as the top three risk factors in green building design. Additionally, the survey proposed the four most effective risk mitigation measures for green building projects: (1) ‘contract indicating each party’s roles, liabilities and limitations clearly’; (2) ‘utilizing integrated design process’; (3) ‘understanding client’s goal in green building projects’; and (4) ‘improving communication and coordination among stakeholders.’ There are a few studies focusing on the architects’ perceived risk concerning green building projects; however, this study expands the knowledge and fills the literature gap. Additionally, this study provides a comprehensive understanding of critical risks and mitigation measures that can benefit South Korea’s green building design practice through better risk management.

We propose a new Mamdani fuzzy rule-based system in which the fuzzy sets in the antecedents and consequents are assigned in a discrete set of points and approximated by using the extended inverse fuzzy transforms, whose components are calculated by verifying that the dataset is sufficiently dense with respect to the uniform fuzzy partition. We test our system in the problem of spatial analysis consisting in the evaluation of the liveability of residential housings in all the municipalities of the district of Naples (Italy). Comparisons are done with the results obtained by using trapezoidal fuzzy numbers in the fuzzy rules.

Information regarding the cost of a construction project is available to the investor and project participants in order to determine the subsequent success of a project, given that the information they collect has an impact on the decisions they make. Cost calculations, especially in the initial phase of a project, often generate large errors. This paper presents the new approach based on a combination of the Case Based Reasoning method (CBR) with the originally selected criteria for the description of a construction project (as a result of Pearson correlation coefficient and Spearman's rank correlation coefficient) and Building Information Modeling (BIM) technology. The CBR method fulfils expectations for a simple and fast system supporting the cost estimation process. It does not require any specialist knowledge, so it will be comprehensible to cost estimation practitioners. The BIM-based model gives the opportunity for the calculation of quantity take-offs and enables the use of the information contained in the BIM model in the cost estimation process. In order to prepare the model an appropriate relational database had to be developed. With extensive research, a database of 173 construction projects, including the construction of a sports field, was obtained. There were 14 variables defined originally by authors; however, only 10 (as a result of the correlation analysis) were used for the calculation. Data related to the project were collected in the BIM model. Results estimating the project’s unit price, using the CBR method, were presented and discussed. The Mean Absolute Estimate Error was used to evaluate the model.

Project portfolio configuration (PPC) is an important approach to maintain the sustainable development of enterprises and achieve organizations’ strategy. However, the synergetic efficacy of PPC which determines the degree of the project's strategic objectives achieved is a fuzzy problem and hard to be measured. To solve this problem, this paper takes the data envelopment analysis (DEA) as the tool to measure the efficacy of PPC under deterministic conditions. First, a portfolio evaluation index system which takes financial indicators and non-financial indicators into consideration is developed based on the review of the literature; Second, an evaluation model based on DEA is built to reduce the number of decision making-unit with the perspective of synergetic theory; Then, a computational experiment is studied to verify the feasibility of this proposed model. The results of this computational experiment show that this model can effectively narrow scope of decision-making, improve the decision-making level and provide a reference to decide the DEA effective project portfolio decision-making unit. To our knowledge, this study is the first time to apply the notion of synergetic efficacy and DEA to the PPC domain. It is hoped that this paper may shed lights on any further study about PPC and enterprise competitiveness of sustainable development.

The purpose of this paper is to provide empirical evidence to water policy-makers and the evaluation of the application of economic instruments such as price and other factors affecting demand, they contribute to improved decision-making around water management in the Biosphere Reserve El Vizcaino, Mexico. It was estimated a dynamic function with average price specification and other price perception specification. The findings show that consumers react to average price perceived and not the marginal price; long-run price elasticity is higher than short-run and both elasticities are inelastic. Elasticities inelastic with rising prices generate high incomes to improve water planning, supply quality and expand service coverage. The results suggest that the level of knowledge of users on the price is key to take into account restructuring rates in a scenario where the consumer has asymmetric information and themselves achieve goals of economic efficiency, social equity and environmental sustainability.

The problem of low soil fertility and limited research in agricultural data driven tools, may lead to low crop productivity which makes it imperative to research in applications of high throughput computational algorithms such as of machine learning (ML) for effective soil analysis and fertility status prediction in order to assist in optimal soil fertility management decision-making activities. However, difficulties in the choice of the key soil properties parameters for use in reliable soil nutrients analysis and fertility prediction. Also, individual ML algorithms setbacks and modelling expert implementation procedures subjectivity, may lead to exploitation of worst fertility level targets and soil fertility status targets classification models performance reported variations. This paper surveys state-of-affair in ML for agricultural soil nutrients analysis and fertility status prediction. Prominent soil properties and widely used classical modelling algorithms and procedures are identified. Empirically exploited fertility status target classes are scrutinized, and reported soil fertility prediction model performances are depicted. The three pass method, with mixed method of qualitative content analysis and qualitative simple descriptive statistics were used in this survey. Observably, the frequently used soil nutrients and chemical properties were organic carbon, phosphorus, potassium, and potential Hydrogen, followed by iron, manganese, copper and zinc. Predominant algorithms included Random Forest, and Naïve Bayes, followed by Support Vector Machine. Model performances varied, with highest accuracy 98.93% and 98.15% achieved by ensemble methods, and the least being 60%. Interdisciplinary ML related researchers may consider using ensemble methods to develop high performance soil fertility status prediction models.

The 2030 global agenda of the United Nations emphasizes peace, human rights, gender equality, partnership, and women's empowerment. It balances the social, economic, and environmental dimensions of sustainable development. The SDG framework was designed to be integrated and indivisible, making the interconnections of 17 Goals and 169 Sustainable Development Goals Targets (SDTs) more complex that need extensive and intensive investigative research. Recent studies have increased on the interrelationships of SDGs, but none of these have focused on integrating Climate Change (CC), Sustainable Forest Management (SFM), and Information and Communication Technology (ICT), also known as CSI Nexus. This study aims to investigate and identify the 169 SDTs linked to CC, SFM, and ICT and assesses the significance of the relationships between these variables. The alignment of SDTs to CSI Nexus was identified through clustering and mapping techniques. The result argued that 56 SDTs are directly connected within CC+SFM+ICT, 16 within CC+SFM, one within SFM+ICT, and 51 within ICT+CC. Our result suggests that CC is significantly associated with SFM; however, ICT has no significant association with CC and SFM. It further asserts that the ICT and SFM have minimal influence on the SDG 2030 framework. The proposed CSI Nexus and SDTs Integration Framework was a science-informed guide for priority-setting, policy coherence, and decision-making supporting the 2030 Sustainable Development Goals. This study does not include interactions, network analysis and visualization, simulations, and modeling between SDG targets.

This study examines the balancing between urban transportation security and supply chain efficiency amid global disruptions like the COVID-19 pandemic, attacks on maritime lanes, and geopolitical conflicts. The authors combine bibliometric network analysis and natural language processing (NLP) to review scholarly literature from 2017 to 2023. This approach identifies and visualizes evolving thematic trends. Findings reveal a shift towards integrating advanced technologies such as blockchain, AI, and IoT to enhance security without compromising efficiency. This study highlights the significance of integrating urban planning principles and sustainable practices to enhance transportation security and supply chain efficiency within urban environments. Actionable insights for policymakers and supply chain managers emphasize the adoption of integrated, technology-driven security solutions to foster resilient and sustainable supply chains. This research contributes to academic discourse by refining the understanding of evolving priorities in transportation security and supply chain management, offering both theoretical and practical implications for secure and efficient global supply chains.

To meet the calls of the International Labor Organization and National Institutes of Occupational Safety and Health, this paper discusses how to build Occupational, Health, Safety (OSH), and Well-Being competence by expanding education to non-traditional undergraduate disciplines. The authors provide (1) theoretical background on why this would benefit society as a whole, (2) learning theory strategies for teaching OHS and Well-being outside of traditional majors, (3) case studies of how this can occur in undergraduate classes and (4) opportunities and challenges for the future.

This work investigates how to balance the electricity supply and demand in a carbon-neutral northern Europe. Applying a cost-minimizing electricity system model including options to invest in eleven different flexibility measures, cost-efficient combinations of strategies to manage varia-tions are identified. The results of the model are post-processed using a novel method to map the net load before and after flexibility measures are applied to reveal the contribution of each flexi-bility measure. The net load is mapped in the space spanned by the amplitude, duration, and number of occur-rences. The mapping shows that, depending on cost structure, flexibility measures contribute to reduce the net load in three different ways; 1) by reducing variations of long duration but low amplitude, 2) by reducing variations of high amplitude but short duration and low occurrence or 3) by reducing variations of high amplitude, short duration and high occurrence. It is found that cost-efficient variation management is achieved by combining wind and solar power and by combining strategies (1-3) to manage variations. The cost-efficient combination of strategies de-pends on electricity system context where electricity trade, flexible hydrogen and heat production (1) manage the majority of variations in regions with good conditions for wind power while sta-tionary batteries (3) are the main contributors in regions with good conditions for solar power.

In its 8th Malaysia Plan (MP*), the Malaysian government has given nanotechnology development a high priority and has been made a Strategic Research (SR) programme. Consequently, an exhaustive and long-term approach is essential. Additionally, specific laws are required to provide an optimal health and safety environment for workers. Consequently, the current study intends to assist Malaysian policymakers in promoting improved safety, risk assessment, and management for nanotechnology workplaces, as well as drafting a comprehensive policy for the recently released DOSH guideline in 2018. Utilizing a unique methodology, this study evaluated the assessment and management of nanotechnology health and safety risks in Malaysia using the international risk governance council (IRGC) framework. In addition to document analysis, n = 20 semi-structured interviews were conducted with representatives of several nanotechnology platforms to collect data that was then analyzed thematically. The research evaluated current workplace safety regulations and laws. Consequently, we propose a future dynamic strategy for Malaysian nanotechnology with more favourable upgrades supported by increased concentrations in the following areas: I policy creation, ii) comprehensive management system, iii) knowledge transfer, and iv) infrastructure management. In addition, the findings highlight the need of cross-sectional communication in bridging existing gaps. This study laid the groundwork for a more systematic and comprehensive health and safety strategy.

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

Hybrid reverse osmosis electrodialysis systems make it possible to obtain solutions with a higher concentration of components compared to single electrodialysis treatment, i.e. more efficient separation of brine and pure water. The article proposes experimental and pilot-industrial studies of a hybrid membrane system operation using industrial wastewater for the disposal of liquid waste from an ion-exchange chemical-desalting water treatment plant of a thermal power plant, followed by a calculation of economic efficiency and an analysis of the environmental feasibility of their use. The developed technological scheme offers separate processing of acidic and alkaline waste regeneration solutions using calcium carbonate reagent and desalination on baromembrane and electromembrane units to obtain clean water and dry residue. The hybrid system includes a booster filter press and an evaporator. The hybrid system makes it possible to provide a thermal power plant with a "zero discharge" with a minimum consumption of reagents and electricity, as well as return all water from wastewater to the power plant cycle.

We investigate the human sustainability of ICT and management changes using a French linked employer-employee survey on organizational changes and computerization (COI). We approach the human sustainability of changes through the evolutions of work intensity, skill utilization and the subjective relationship to work. We compare in the private sector and the State civil service the impacts of ICT and management changes on the evolution of these three dimensions of work experience. We find that when ICT and management changes are intense, they are positively associated in the public sector with work intensification and new knowledge. In the private sector ICT and management changes increase the use of skills, but at a rate decreasing with their intensity and without favoring the accumulation of new knowledge. However, their impacts on the subjective relationship to work are much stronger, with public sector employees expressing discouragement as well as the feeling of an increased effort-reward imbalance when private sector employees become more committed. We tested that the self-selection of employees, the specific sources and paths of changes and the implementation of performance pay did not explain this divergence. We identify two partial explanations: one is related with employee turnover in the private sector, the other one with the role of trade unions. These results suggest that the human sustainability of ICT and management changes depends on their intensity and on how their implementation takes into account the institutional context of the organization.

Red mud (RM) is a residue obtained from the production of alumina. It contains a high concentration of metal oxides and waste concentrated sodium hydroxide solution (pH = 13). To increase the value of RM, an environmentally friendly process of transesterification using waste cooking oil (WCO), MeOH and concentrated sodium hydroxide solution (CSHS) from aluminum production was proposed. Triglycerides of WCO reacted with MeOH at 60 oC to yield mixtures of fatty acid methyl esters (FAMEs) in the presence of 2.03% (w/w) CSHS/WCO using the CSHS (0.204 mol L-1, predetermined by potentiometric titration) from aluminum production by the Bayer process or with the addition of 0.68% (w/w) fabric softener (3% w/w cetyltrimethylammonium chloride in solution) as a phase transfer (PTA) agent. The addition of PTA to the catalyst resulted in a better yield of the products (greater than 98% yield). A simplified mechanism is presented to account for the experimental results.

Biochar application to the soil can improve soil quality and nutrient leaching loss. Recent studies have reported that surficial application of biochar to stored swine manure can reduce emissions of odorous compounds and reduce the volatilization loss of ammonia. Our working hypothesis was that the biochar-treated manure application to the soil would decrease nutrient leaching from manure and increase plant-available nutrients. The study objectives were to evaluate the impact of biochar-treated swine manure on soil total C, N, and other major and minor nutrients. Three biochars (i) neutral pH red-oak (RO), (ii) highly alkaline autothermal corn (Zea mays) stover (HAP), and (iii) mild acidic Fe-treated autothermal corn stover (HAPE) were incubated with swine manure for a month. The biochar-manure mixture was applied in triplicate to soil columns with application rate determined by the P₂O₅-P content in manure or manure-biochar mixtures after the incubation. The ammonium (NH₄⁺), nitrate (NO₃^-), and reactive P concentrations in soil column leachates were recorded for eight leaching events. Soil properties and plant-available nutrients were compared between treatments and control manure & soil. Manure-(HAP&HAPE) biochar treatments significantly increased soil organic matter (OM) and increased soil total C, N, and improved soil bulk density. Concentrations of KCl-extractable NH₄⁺ and NO₃^- significantly increased in HAPE column leachates during this 4-week study and in the soil after the experiment. A significant reduction in soil Mehlich3 Cu was also observed for the manure-HAPE mixture compared with the control. Overall, the manure-biochar incubation enabled biochar to sorb nutrients from manure, and the subsequent manure-biochar mixture application to soil improved soil quality and plant nutrient availability in comparison to conventional manure application to soil. This proof-of-the-concept study suggests that biochars could be used to solve both environmental and agronomic challenges and further improve the sustainability of animal and crop production agriculture.

In air quality management, at urban and regional levels, road transport remains the cornerstone of residential, commercial, and industrial activities, and the vehicle exhaust emissions maintain the position of one of the key contributing sources. In Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads, contribute to as much as 50% of particulate matter pollution in a year. So, having access to a vehicle exhaust emissions inventory that is reliable and replicable is critical for air quality management and this exercise starts with access to vehicle stock numbers. These numbers are typically obtained from vehicle registration databases, traffic surveys, and other governmental records, and often require time consuming data cleaning protocols before they can used for emissions and pollution baseline analysis. This paper provides a cleaned and open-access vehicle stock database, as registered and in-use fleet, for the period covering 1993 and 2018, for all India and states, along with an estimate of age-mix of the vehicles using survival functions.

Fog computing is a potential solution to overcome the shortcomings of the cloud computing processing of IoT tasks. These drawbacks can be high latency, location awareness and security, and it is attributed to the distance between IoT devices and servers, network congestion and other variables. Although fog computing has evolved as a solution to these challenges, it is known for having limited resources that need to be consciously utilised, or any of its ad-vantages would be lost. Computational offloading and resource management are critical concerns to be considered to get maximum benefit of the available resource at fog computing systems and benefit from its advantages. Computational offloading and resource management are important issues to be considered to get maximum benefit of the available resource at fog computing systems and benefit from its advantages. In this article, in vehicular traffic applications, we introduce a dynamic online offloading scheme that involves the execution of delay-sensitive ac-tivities. This paper proposes an architecture of a fog node that enables a fog node to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to solve an optimisation problem aimed at minimising overall delay, improving throughput, and minimising energy consumption at the fog layer, while maximising the use of resource-constrained fog nodes. Compared with other benchmarks, our approach can reduce the delay by up to 95.38% and reduce energy consumption by up to 67.71% in fog nodes. Additionally, this approach enhances throughput by 71.08%.

Ecosystem surveillance monitoring is critical to managing natural resources and especially so under changing environments. Despite this importance, the design and implementation of monitoring programs across large temporal and spatial scales has been hampered by the lack of appropriately standardised methods and data streams. To address this gap, we outline a surveillance monitoring method based on permanent plots and voucher samples suited to rangeland environments around the world that is repeatable, cost-effective, appropriate for large-scale comparisons and adaptable to other global biomes. The method provides comprehensive data on vegetation composition and structure along with soil attributes relevant to plant growth, delivered as a combination of modules that can be targeted for different purposes or available resources. Plots are located in a stratified design across vegetation units, landforms and climates to enhance continental and global comparisons. Changes are investigated through revisits. Vegetation is measured to inform on composition, cover and structure. Samples of vegetation and soils are collected and tracked by barcode labels and stored long-term for subsequent analysis. Technology is used to enhance the accuracy of field methods, including differential GPS r plot locations, instrument based Leaf Area Index (LAI) measures, and three dimensional photo-panoramas for advanced analysis. A key feature of the method is the use of electronic field data collection to enhance data delivery into a publicly-accessible database.Our method is pragmatic, whilst still providing consistent data, information and samples on key vegetation and soil attributes. The method is operational and has been applied at more than 704 field locations across the Australian rangelands as part of the Ecosystem Surveillance program of the Terrestrial Ecosystem Research Network (TERN). The methodology enables continental analyses, and has been tested in communities broadly representative of rangelands globally, with components being applicable to other biomes. Here we also recommend the consultative process and guiding principles that drove the development of this method as an approach for development of the method into other biomes. The consistent, standardised and objective method enables continental, and potentially global analyses than were not previously possible with disparate programs and datasets.

Whereas a vast literature exists on satellite-based mapping of rice paddy fields in Asia, where most of the global production takes place, little has been produced so far that focuses on the European context. Detection and mapping methods that work well in the Asian context will not offer the same performances in Europe, where different seasonal cycles, environmental contexts, and rice varieties make distinctive features dissimilar to the Asian case. In this context, water management is a key clue; watering practices are distinctive for rice with respect to other crops, and within rice there exist diverse cultivation practices including organic and non-organic approaches. In this paper, we focus on satellite-observed water management to identify rice paddy fields cultivated with a traditional agricultural approach. Building on established research results, and guided by the output of experiments on real-world cases, a new method for analysing time series of Sentinel-1 data has been developed, which can identify traditional rice fields with a high degree of reliability. This work is a part of a broader initiative to build space-based tools for collecting additional pieces of evidence to support food chain traceability; the whole system will consider various parameters, whose analysis procedures are still at their early stages of development.

Lithium batteries and an increasing focus on CO₂ reduction have become an integral part of daily life and business for many people. Boron and boron compounds have been widely studied together in the history and development of lithium batteries. With a broad examination of battery components and systems but a boron-centric approach to raw materials, this review seeks to summarize past and recent studies on the following: which boron compounds are studied in lithium battery, in which parts of lithium batteries, what improvements are offered for battery performance, and what improvement mechanisms can be explained. The uniqueness of boron and its extensive application beyond batteries contextualizes the interesting similarity with studies on batteries. The paper predominantly focuses on lithium-ion batteries (LIBs) but also mentions other lithium batteries. At the end, the article aims to predict prospective trends for future studies that may lead to the successful and extensive use of boron compounds on a commercial scale.

(1) Background: Prevention of acute cardiovascular events in patients with cardiovascular diseases (CVDs) requires promoting health-protective behaviors (e.g., physical activity) and preventing health-compromising behaviors (sitting). Digital health interventions provide much potential. Based on multiple behavioral change theory, an intervention (reCardial app) was evaluated, and the following hypotheses were tested: H1: Health behaviors (physical activity, sitting) and disease self-management (self-care maintenance, self-care confidence) are closely interrelated. H2: Change in health behaviors and disease self-management indicators over time is more pronounced in reCardial app-users. H3: In the intervention group, changes in systolic and diastolic blood pressure indicate a positive trajectory. (2) Methods: A study with the design of a randomized controlled trial over 12 weeks was conducted. 40 CVD-patients were randomized equally to the Intervention Group (35% women; Mage=60.6years) and Control Group (45% women; Mage=61.5years). (3) Results: Findings support H1 with significant correlations between health behaviors (r=0.45-0.63**), and disease self-management (r=-0.32-0.54**), H2 with Eta²=0.21 (not statistically significant) and H3 partially with d=0.101 for systolic blood pressure but not regarding diastolic blood pressure. (4) Conclusions: Replications are needed with larger samples and more objective measures. The app can help prevent and manage CVD by means of promoting health-protective behaviors and preventing health-compromising behaviors. Taking different behaviors into account can increase intervention effects and with that support of users.

This article explores the relationship between metabolic syndrome and cardiovascular disease, providing a comprehensive overview of its risk factors and prevalence. Metabolic syndrome, characterized by a cluster of interconnected risk factors, significantly increases the likelihood of developing cardiovascular disease and type II diabetes. The study, conducted over a one-year period, involved 117 patients with ages between 30 to 79 years old. Various elements such as gender, age, education level, background, smoking, alcohol consumption, dietary aspects, physical activity, and their contribution in developing the metabolic syndrome, were analysed.Central adiposity and high blood pressure emerged as prominent elements of the condition. The findings underscore the importance of a healthy lifestyle in the prevention and management of metabolic syndrome. Encouraging regular physical activity, maintaining a balanced diet, rich in fresh vegetables and fruits, and avoiding harmful behaviours, such as smoking or alcohol consumption, are essential in reducing the risk of metabolic syndrome and its associated cardiovascular complications. The study highlights the need for public health initiatives, as well as individualized preventive strategies to combat the rising prevalence of metabolic syndrome. Through promoting awareness of its risk factors and implementing effective interventions, healthcare professionals can contribute to better cardiovascular health worldwide. Further research in this area will continue to enhance our understanding of the metabolic syndrome and refine preventive and therapeutic approaches for its management.

In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.

Is it true that the nuclear technology applied to electric energy generation offers a clean, safe, reliable and affordable i.e. sustainable alternative? Yes it is, but its impact on the environment strongly depends on the implementation bearing residual risks due to a human factor, technical failures or natural catastrophes. A full response is therefore difficult and can first be given when the wicked multi-disciplinary problems get well formulated and “solved”. These problems have multi-dimensional nature lying at the interface between: necessary R&D effort, the industrial deployment and the technology impact in view of the environmental sustainability including the management of produced hazardous waste. This enormous complexity indicates that just a description of the problem might represent a problem. The paper proposes a holistic approach to assess the nuclear energy systems potential with respect to sustainable performance applying Multi-criteria decision analysis with a suitable objective tree and a multi-level criteria structure and examines the trading-off techniques for ranking of the alternatives. The framework proposes a multi-criteria and multi-stakeholders treatment which can be used as a pre-decisional support towards an implementation of nuclear fuel cycles adapted to national preferences and priorities. Proposed approach addresses some aspects of the environmental footprint of nuclear energy systems. Advanced nuclear fuel cycles, previously investigated by the NEA/OECD expert group WASTEMAN, are analyzed as a case study. Sustainability facets of waste management, resource utilization and economics are in focus.

The sustainable use of precious water resources requires effective water management. In the European Union, water management is mainly regulated by the Water Framework Directive (2000/60/EC), introducing an integrated river basin management approach. As EU directive, the legislation needs to be implemented in the Member States, entailing not only legal transposition, but also application and enforcement in Member States. One major instrument introduced by the Water Framework Directive is the environmental goal achievement obligation of art. 4 WFD, containing also a deterioration ban with several exemptions. This study compares transposition, application and enforcement of the exemption of permanent deterioration (art. 4 (7) WFD) in the context of the environmental goal achievement obligation regime in Lower Saxony (Germany) and the Netherlands. The study rests on a legal analysis of literature, policy documents and jurisprudence. Although based on the same EU directive wording and case law of the European Court of Justice, the deterioration ban and the exemption of permanent deterioration are implemented rather differently: While the deterioration ban is predominantly understood as planning obligation in the Netherlands, it became an important permit requirement in Lower Saxony since the Weser-ruling of the European Court of Justice.

in the following article I analyze the trend of cultural and creative employment in the Italian regions between 2004 and 2022 through the use of ISTAT-BES data. After presenting a static analysis, I also present the results of the clustering analysis aimed at identifying groupings between Italian regions. Subsequently, an econometric model is proposed for estimating the value of cultural and creative employment in the Italian regions. Finally, I compare various machine learning models for predicting the value of cultural and creative employment. The results are critically discussed through an economic policy analysis.

This study outlines a comprehensive examination of risks and hazards in three egg sorting and packing stations, covering the entire process from supplier selection and evaluation to egg delivery in chain stores. The analysis is conducted within the framework of Codex Alimentarius and GFSI-integrated food safety programs. Salmonella is the greatest significant threat. To enhance the Hazard Analysis of Critical Control Points (HACCP), preparatory programs were incorporated into the quality management system (QMS) by monitoring and assessing the biological, chemical, and physical threats according to Code Alimentarius and further integrated into GFSI food safety programs, including food authenticity and food defense. The procedure offered sophisticated preventive tools, hand-on at any time, for eliminating, reducing, or mitigating the risks encountered in egg packing and sorting facilities.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

The increasing importance of batteries in the 21st century and the challenges posed by the anticipated growth in end-of-life batteries, particularly in Europe, are addressed. Projections indicate a significant increase in battery waste, with a specific focus on the recycling of black mass (BM)—a complex and hazardous byproduct of the battery recycling process. The research employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to systematically analyze the hazardousness of BM derived from various types of batteries. The findings reveal the inherently hazardous nature of BM, classifying it under multiple hazardous properties (HPs) according to European regulations. The urgent need for a definitive legislative classification of the hazardousness of BM is emphasized, and the potential of innovative technologies and strategies to improve recycling performance while mitigating risks is highlighted. The research significantly contributes to understanding the complexities of BM recycling, providing a foundation for future advancements in this area and emphasizing the need for further exploration and economic feasibility analysis of recycling technologies.

The use of swine manure as a source of plant nutrients is one alternative to synthetic fertilizers. However, conventional manure application with >90% water and a low C:N ratio results in soil C loss to the atmosphere. Our hypothesis was to use biochar as a manure nutrient stabilizer that would slowly release nutrients to plants upon biochar-swine manure mixture application to soil. The objectives were to evaluate the impact of biochar-treated swine manure on soil total C, N, and plant-available macro and micronutrients in greenhouse-cultivated corn (Zea mays L.) and soybean (Glycine max (L.) Merr.). Neutral pH red oak (RO), highly alkaline autothermal corn stover (HAP), and mild acidic Fe-treated autothermal corn stover (HAPE) biomass were pyrolyzed to prepare biochars. Each biochar was surface-applied to swine manure at a 1:4 (biochar wt/manure wt) ratio to generate mixtures of manure and respective biochars (MRO, MHAP, and MHAPE). Conventional manure (M) control and manure-biochar mixtures were then applied to the soil at a recommended rate. Corn and soybean were grown under these controls and treatments (S, M, MRO, MHAP, and MHAPE) to evaluate the manure-biochar impact on soil quality, plant biomass yield, and nutrient uptake. Soil OM significantly (<0.05) increased in all manure-biochar treatments; however, no change in soil pH or N was observed under any treatment. No difference in soil ammonium between treatments was identified. There was a significant decrease in soil M3-P and soil NO₃^- for all manure-biochar treatments compared to the conventional M. However, the plant biomass nutrient concentrations were not significantly different from control manure. Moreover, an increasing trend of N and decreasing trend of P in the plant under all biochar-manure treatments than the controls were noted. This observation suggests that the presence of biochar is capable of influencing the soil N and P in such a way as not to lose those nutrients at the early growth stages of the plant. In general, no statistical difference in corn or soybean biomass yield and plant nutrient uptake for N, P, and K was observed. Interestingly, manure-biochar application to soil significantly diluted the M3-extractable soil Cu and Zn concentrations. The results attribute that manure-biochar has the potential to be a better soil amendment than conventional manure application to the soil.

Soil water infiltration is an important component of the hydrological cycle and it is best evaluated when the raindrop is impacted on the ground surface. For this reason, it is affected by changes in land use and occupation, and by the characteristics and physical-hydric properties of the soil. This study aimed to evaluate soil water infiltration in areas occupied with annual crops (soybean and corn) and pastures, in two watersheds of the Teles Pires River-MT, using simulated rainfall, physical models and principal component analysis. Infiltration rates were evaluated from simulated rainfall with an average intensity of 75 mm h-1, with 4 repetitions per region (upper, middle and lower) of the hydrographic sub-basins of the Caiabi and Renato rivers, and soil use with cover, without cover and disturbed. Soil tillage provided higher water infiltration rates into the soil, especially in pasture areas in the two hydrographic sub-basins. There were significant adjustments of the mathematical models to the infiltration rate data for all land use and land cover conditions. The soil attributes that most interfered with the infiltration rate were microporosity, soil density and total porosity in the crop areas of the middle Caiabi, and microporosity, clay content, total porosity and silt content in the areas farming at the source of the Renato River. The Horton and Philip models presented the best adjustments in the hydrographic sub-basins of the Renato and Caiabi and Renato rivers, being recommended for estimating the rate of water infiltration into the soil in different uses, coverages, and regions.

Providing safely-managed sanitation/hygiene requires key competencies for education, training, service delivery, enterprise development and management, product and infrastructure design and development, construction and installation, governance, financing, research, etc. These strategic sanitation capacities will have to be built from higher education’s academic and professional programmes structured and designed to produce skilled and knowledgeable professionals and practitioners. This study aims to investigate the quality of the sanitation/hygiene management content of Environmental Health programmes; the adequacy of the existing central curricula; and the perception of environmental health sanitation/hygiene-trained professionals to determine the next phase for building knowledge and capacity of sanitation professionals in Nigeria through higher education institutions. A multilevel mixed method concurrent study was used for sampling and data collection with a multilevel perception analysis to examine the perceptions of students, lecturers and graduate alumni as well as employers/supervisors and clients/service-users of sanitation/hygiene related graduates. The main findings of this paper show limited understanding of the concepts of contemporary issues of sanitation/hygiene management; the central/national teaching and curricula were found to be seriously out of date; and clients/service-users were dissatisfied with the skills and knowledge levels of the graduates. The study concludes by recommending a national sanitation management higher education pathway to guide the provision of integrated sanitation/hygiene management education at higher education institutions (HEIs), to build effective, efficient, competent, and sufficient workforce for the country.

UN Convention on Climate Change 2015 mandates reducing carbon footprint to reduce global warming. Considering environmental concerns, Electric Vehicles (EVs) spearhead the move towards green mobility. Niti Aayog (Indian Government) has envisaged an “EV only” scenario by 2030. Two wheelers dominate the Indian automobile industry with almost 80% market share. With the transportation sector accounting for 70% of world’s fossil fuels use, the need for a sustainable supply chain which addresses environment, economy and societal issues, has, of late, aroused interest in the business academic community and industries. Sustainability in business decision-making promotes efficiency, controls expenditure, enhances customer delight, increases sales and market share, optimises risk management strategy, and promotes profitability. This study intends to develop a conceptual framework after examining research gaps in sustainable supply chain management (SSCM) and allied topics like sustainability, green supply chain management, and vendor partnerships through collaborative efforts. Even the UN vide Goal 9 of sustainable goals pertaining to industry, highlights the importance of this framework.

Current research on smart cities is primarily focused on the area of applicability of information and communication technologies. However, in the context of a multidisciplinary approach, it is also necessary to pay attention to the resilience and converged security of individual infrastructures. Converged security represents a particular security type based on a selected spectrum of certain convergent security types of, assuming the creation of a complementary whole. Considering the outputs of the analysis of security breaches manifestations, this kind of security makes it possible to detect emerging security breaches earlier (still in the symptom stage), thus providing a more efficient and targeted solution suitable for building smart city infrastructure. In its essence, the article refers the practical application of the theoretical principles of converged security presented in the publication to a functional sample, deployed and tested in practical conditions of selected smart city infrastructure protection and resilience. Considering the nature of the practical application, the convergence of a wider spectrum of smart security alarm systems in the context of resilience assessment is defined. In the beginning, the general principles of security/ safety and the need for their convergence are presented. In this context, the mathematical model called Converged Resilience Assessment method is presented for better understanding. Subsequently, PSIM and SIEM systems are described as a technological concept that can be used for resilience assessment. The most beneficial part is the structural, process and functional description of the Converged Security and Information Management System (CSIM) using the concept of smart security alarm systems converged security.

Invasive alien plant species (IAPS) pose one of the most significant threats to native biodiversity. Swietenia macrophylla, or big leaf mahogany, is among the most threatening invasive plants in the Philippines. This article aimed to formally document the presence of S. macrophylla along the edges of Mt. Banahaw de Nagcarlan, a protected area on Luzon Island, Philippines. The study also sought to identify the management strategies being implemented by various government institutions for addressing big leaf mahogany and other invasive plants. A total of 1591 individuals of S. macrophylla were documented in mixed land-use areas and roadsides. These were found to have been introduced by the Department of Environment and Natural Resources in 1991 as a reforestation species. Fortunately, no individuals were observed beyond the buffer zone towards the protected area. The identification of management strategies for big leaf mahogany and other IAPS revealed that there is no established approach specifically addressing the presence of S. macrophylla at the site. However, some institutions advocate for the conservation of native plants through tree planting activities and educational campaigns. Furthermore, no collaborative efforts were observed among stakeholders and institutions. The results of this study highlight the urgent need for managing the S. macrophylla population. Planning and enforcement of strategies require collaborative efforts among stakeholders to prevent its entry into the protected area and ensure the preservation of native biodiversity.

Avian Influenza viruses (AIVs) has posed a significant pandemic threat since their discovery. This review mainly focuses on the epidemiology, virology, and pathogenesis, and treatments of avian influenza viruses. We delve into the global spread, past pandemics, clinical symptoms, severity, and immune response related to AIVs. The review also discusses various control measures, including antiviral drugs, vaccines, and potential future directions in influenza treatment and prevention. Lastly, by summarizing the insights from the previous pandemic control, this review aims to direct effective strategies for managing future influenza pandemics.

Debates on climate change challenges around the world are moving in favour of nature-based solutions (NBS) as potential mitigation and adaptation options. Mangroves and associated blue carbon ecosystems are nature-based solutions against sea level rise and other coastal hazards. As such, protecting the existing mangrove forests and restoration of the degraded areas is integral in this aspect. However, conventional mangrove restoration approaches in high-energy areas result in poor performance due to the removal of seedlings by waves. Here, we assessed the efficacy of using modified Riley Encasement Methods in the restoration of eroding intertidal areas of Gazi Bay, Kenya. Vegetation and soil baseline data were collected in 49 square plots of 100m2; established along belt transects perpendicular to the waterline. The following mangrove vegetation data was collected; species composition, tree height (m), and stem diameter (cm); from which the importance value index (IV), basal area and standing density (stems/ha) were derived. Sediment cores were made in the center of each square plot for carbon and grain size analysis. Mangrove (Rhizophora mucronata) planting adopted a randomized complete block design (RCBD) in which the planting area was divided into three blocks (A, B, C). Within each block, treatments (bamboo and different-sized PVC pipes) were randomly assigned locations. Results show that seedlings grown within PVC encasements had high survival and growth rates, surpassing bamboo and control groups. This implies that PVC pipes offer better protection from external factors. These findings are critical in highlighting potential enhancements for the effectiveness of PVC pipes in mangrove restoration. They also reinforce on the need to consider the incorporation of PVC encasements as an alternative mangrove restoration technique in high-energy locations.

In the traditional power system, customers respond to their primary electricity consumption pattern based on price or incentive to take additional advantages. By developing energy hubs (EHs) where electricity, heat, natural gas and other forms of energy are coupled together, all types of energy customers even the inelastic loads can participate in demand response (DR) program. This novel vision has led to the concept of "integrated demand response (IDR)". IDR programs (IDRPs) in EHs involve coordinating multiple DR activities across different energy systems, such as buildings, industrial complexes, and transportation networks. The main purpose of IDR is that multi-energy users can respond not only by shifting or reducing energy consumption from the demand side, but also by changing the type of energy consumed, in response to the dispatching center. The integration of IDRPs in EHs can help to reduce energy costs, improve grid stability, and increase the penetration of renewable energy sources (RES) in the power system. Moreover, by synchronizing DR activities across different energy systems, IDRPs can provide additional benefits, such as improved energy efficiency, reduced greenhouse gas emissions, and increased resilience to power outages and other disruptions. In this paper, we provide a review, assessment, and classification of fundamental principles, modeling techniques and optimization methods for IDR programs in EHs.

Working capital management (WCM) is critical because it affects a company's profitability, liquidity, and investment decisions, all of which have an impact on financial performance. As a result, effective and efficient working capital management is an essential component for commercial and service businesses. Given the importance of the commercial and services industries to the Kenyan economy, the goal of this research was to look into the impact of working capital management on the financial performance of these firms, particularly those listed on the Nairobi Securities Exchange (NSE), from 2003 to 2022. Working capital management was measured using the average age of inventory, average collection period, average payment period, and cash conversion cycle, whereas financial performance was measured using return on asset, return on equity, and net operating profit margin. Using panel regression analysis, the results showed that the average inventory age, average collection period, average payment period, and cash conversion cycle were all negatively related to financial performance for NSE-listed commercial and services firms. Based on the findings, it is recommended that Kenyan commercial and services firms adopt prudent optimal working capital management practices in order to improve firm financial performance and maximize shareholder wealth.

There is a need for strategic healthcare workforce planning to address shortages and ensure universal health coverage, aiming to optimize work-force per population ratio, distribution, and competencies. Amidst rising demands exacerbated by aging populations and events like the COVID-19 pandemic, strategic workforce planning becomes crucial for addressing healthcare inequalities by forecasting needs, bridging skill gaps, and adapting to changing demographics and care models. Israel has invested in strategic planning to tackle healthcare workforce challenges; however, globally there is insufficient planning informed by health labor market analysis, which hinders efforts to address healthcare inequalities. The paper reviews national policies in Israel, Australia, Germany, and Norway, ex-amining statistics and government publications to highlight strategic plan-ning considerations and address challenges in healthcare workforce plan-ning. This paper focuses both on the critical role of physicians in healthcare systems, and on the changing borders between healthcare professions and different national contexts which demand more context dependent strategic workforce planning. We highlight common themes among national policies, including the need for data collection, increasing the capacity of domestic training programs, and the need to address geographic maldistribution of physicians. Ultimately, we aim to guide policy in the development of a re-silient and sustainable healthcare workforce capable of meeting diverse community needs and promoting equity in healthcare services.

Hydrogen sulfide and ammonia are always a concern in the livestock industries, especially when farmers try to clear their manure storage pits. Agitation of manure can cause dangerously high concentrations of harmful agents such as H₂S and NH₃ to be emitted into the air. Biochar has the ability to sorb these gases. We hypothesized that applying biochar on top of manure can create an effective barrier to protect farmers and animals from exposure to NH₃ and H₂S. In this study, two kinds of biochar were tested, highly alkaline, and porous (HAP, pH 9.2) biochar made from corn stover and red oak biochar (RO, pH 7.5). Two scenarios of (6 mm) 0.25” and (12 mm) 0.5” thick layers of biochar treatments were topically applied to the manure and tested on a pilot-scale setup, simulating a deep pit storage. Each setup experienced 3-min of agitation using a transfer pump, and measurements of the concentrations of NH₃ and H₂S were taken in real-time and measured until the concentration stabilized after the sharp increase in concentration due to agitation. The results were compared with the control in the following 3 situations: 1. The maximum (peak) flux 2. Total emission from the start of agitation until the concentration stabilized, and 3. The total emission during the 3 min of agitation. For NH₃, 0.5” HAP biochar treatment significantly (p<0.05) reduced maximum flux by 63.3%, overall total emission by 70%, and total emissions during the 3-min agitation by 85.2%; 0.25” HAP biochar treatment significantly (p<0.05) reduced maximum flux by 75.7%, overall, total emission by 74.5%, and total emissions during the 3-min agitation by 77.8%. 0.5” RO biochar treatment significantly reduced max by 8.8%, overall total emission by 52.9%, and total emission during 3-min agitation by 56.8%; 0.25” RO biochar treatment significantly reduced max by 61.3%, overall total emission by 86.1%, and total emission during 3-min agitation by 62.7%. For H₂S, 0.5” HAP biochar treatment reduced the max by 42.5% (p=0.125), overall total emission by 17.9% (p=0.290), and significantly reduced the total emission during 3-min agitation by 70.4%; 0.25” HAP treatment reduced max by 60.6% (p=0.058), and significantly reduced overall and 3-min agitation’s total emission by 64.4% and 66.6%, respectively. 0.5” RO biochar treatment reduce the max flux by 23.6% (p=0.145), and significantly reduced overall and 3-min total emission by 39.3% and 62.4%, respectively; 0.25” RO treatment significantly reduced the max flux by 63%, overall total emission by 84.7%, and total emission during 3-min agitation by 67.4%.

This qualitative study explores the dynamics of supplier relationships among Italian restaurant managers, aiming to uncover the strategic practices and challenges in supplier relationship management (SRM) within the culinary industry. Through semi-structured interviews with a diverse sample of restaurant managers across Italy, the study examines how trust, communication, adaptive sourcing strategies, and innovation influence supplier interactions and operational outcomes. Findings reveal that trust-building is foundational to establishing reliable supplier partnerships, crucial for ensuring consistent delivery of high-quality ingredients essential for culinary excellence. Effective communication channels and negotiation techniques are pivotal in clarifying expectations, resolving conflicts, and fostering collaborative relationships with suppliers. Adaptive sourcing strategies, including diversification of supplier bases and local sourcing initiatives, enable managers to navigate market dynamics and meet consumer demands effectively. Innovation emerges as a catalyst for differentiation and sustainability in supplier relationships, with managers engaging in collaborative product development and embracing sustainability initiatives to align with consumer preferences and corporate values. Despite facing challenges such as pricing pressures, supply chain logistics complexities, and regulatory compliance, proactive management strategies and operational agility enable managers to mitigate risks and capitalize on opportunities in supplier management. Theoretical implications enrich understanding of SRM dynamics in the culinary sector, while practical implications suggest strategies for optimizing supplier relationships, enhancing operational efficiency, and sustaining competitive advantage. Future research could explore technological advancements, consumer trends, and longitudinal impacts of SRM practices on business performance within the restaurant industry.

This qualitative study explores supplier selection criteria from the perspectives of procurement professionals across diverse industries. Supplier selection is crucial for organizational efficiency and performance, influenced by factors beyond traditional cost considerations. The research aims to uncover nuanced criteria such as quality assurance, supplier reliability, innovation capability, sustainability practices, strategic alignment, relational dynamics, and risk management strategies. These criteria reflect a shift towards holistic evaluation frameworks that integrate economic, social, and environmental dimensions in procurement decision-making. Methodologically, the study employed semi-structured interviews with 30 procurement professionals, ensuring depth and diversity in perspectives. Thematic analysis was used to identify recurring themes and patterns, illuminating the complexities and strategic importance of supplier selection processes. Findings highlight the strategic role of suppliers in driving innovation, enhancing supply chain resilience, and supporting organizational goals. Moreover, the study underscores the significance of sustainable sourcing practices, ethical considerations, and effective supplier relationships in fostering long-term partnerships and mitigating operational risks. Practical implications suggest that organizations should adopt integrated approaches to supplier selection, leveraging data-driven insights and technological advancements to optimize decision-making. By prioritizing strategic alignment, fostering collaborative partnerships, and implementing robust risk management strategies, organizations can navigate uncertainties, capitalize on market opportunities, and sustain competitive advantage.