The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest to incorporate technologies and methods to determine these homogeneous zones. A case study was conducted in a 3.3 ha vineyard located near Évora, South of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture, pH, organic matter -OM, phosphorous -P2O5, potassium -K2O, sum of the exchange bases -SEB; and cation exchange capacity -CEC) which were determined from 20 soil samples taken in the different MZs. Additionally, validation was also performed using Rasch measures, which were defined based on the formula-tion of the objective and probabilistic Rasch model, integrating the information from the afore-mentioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ. The use of ECa constitutes an efficient technological tool for implementing site-specific man-agement in viticulture, which allows for the improvement of decision-making processes by con-sidering the inherent spatial variability of the soil.

Gaucher Disease's (GD) pathophysiology generates anesthetic concerns in Total Hip joint Arthroplasty (THA), and due to its rareness, data on perioperative risks is scarce. This 22-year study at a large reference center addresses anesthetic management and perioperative outcomes in GD. This retrospective-cohort study assessed anesthetic success and safety in 30 THA patients, comparing them with a control-matched group. Data on clinical characteristics, perioperative events, and outcomes were collected. The primary outcome was difficult anesthesia-initiation incidence. Secondary outcomes were difficult intraoperative course and hemodynamic management, and the development of postoperative-complications. The age, sex, weight, body mass index, primary-to-revision hip arthroplasty ratio were similar in both groups. The mean age was 48±13 years. Ten arthroplasties were revision while twenty were primary. There was no significant difference at all-type anesthesia first initiation attempt success. No particular preference by staff anesthetists for general anesthesia or neuraxial procedures was observed. The GD group showed significantly higher mean intraoperative packed red blood cell units administered (0.73 vs 0.18);(p= 0.038)), higher intraoperative and postoperative platelet transfusion incidence (5/30 [16.7%] vs. 0/56 [0.00%];p=0.004) and (3/30 [10%] vs 0/56 [0%];p=0.040) and longer mean recovery-room length-of-stay (426±412 vs 175±140;p=0.004). Postoperative complications were not significantly different.

This study examines the unique circumstances surrounding state-owned equity participation in non-state-controlled enterprises in China. Specifically, this study examines the impact of state-owned equity participation on the environmental, social, and governance (ESG) performance of non-state-controlled enterprises. Focusing on A-share listed firms on the Shanghai and Shenzhen Stock Exchanges and using data from 2013 to 2021, empirical testing shows that state-owned equity participation can significantly improve the ESG performance of non-state-controlled enterprises, with this conclusion remaining reliable after a series of robustness tests. Top management incentives is a mediating mechanism for state-owned equity participation in enhancing ESG performance. This study also finds that when state-owned equity participates in large enterprises or companies with a high degree of digital transformation, the effect on ESG performance is greater than that of small to medium-sized enterprises (SMEs) or enterprises with a low level of digital transformation. The findings of this study add to the current body of the existing field of research on the factors influencing corporate ESG performance and the impact of state-owned equity on corporate non-financial performance.

The aim of the current study was to develop and evaluate the therapeutic potential of apocynin (APO) loaded pH-sensitive nanoparticles (NPs) based transdermal hydrogel for management of rheumatoid arthritis (RA). Slightly modified nanoprecipitation technique was used for preparation of polymeric nanoparticles. Optimization was done through design expert software. Optimized APO-NPs were loaded into carbopol-934 based hydrogel as final dosage form and further studied for physicochemical properties. Optimized APO-NPs formulation had a minimum particle size 63.44 nm, polydisperibility index 0.161, and zeta potential -15mV with a maximum encapsulation efficiency of 89%. In-vitro and ex-vivo studies of APO-NPs based hydrogel was performed at pH 5.5 (pH of normal skin) and 6.8 (pH of inflammed joint) showed a pH-responsive sustained drug release and increased penetration in comparison to free APO based hydrogel. The stability studies of APO-NPs based hydrogel were done to strengthen the potential use of the prepared formulation through transdermal route. Assessment and therapeutic efficacy of the prepared pH-sensitive nanocarriers system was evaluated in chronic inflammatory RA mice model. Parameters associated with chronic inflammation were investigated including behavioral changes and histopathological, and radiological x-rays images of joints of mice paws. In-vivo study depicts improvement in behavioral parameter, decline in synovial hyperplasia and bone structure restoration. In conclusion, APO loaded pH-sensitive NPs based transdermal is a promising carrier system that can effectively manage RA.

This retrospective observational study describes the results of an ad-hoc designated prevention protocol aimed at containing the spread of the scabies infestation among healthcare workers (HCWs) of a large University Hospital in Italy. The outbreak started on October 2022 and a preventive protocol was set up thanks to a multidisciplinary approach. HCWs at high scabies risk were defined as subjects working in UOs with more than five confirmed cases of scabies, close contacts of a confirmed case of scabies, or HCWs with signs and symptoms of the disease. All cases of at high scabies risk underwent a dermatological examination and the infested HCWs were suspended from work until definitive healing. Mass prophylactic treatment was established for all HCWs working in UOs with more than five confirmed cases of scabies. Until March 2023, out of 183 screening dermatological examinations, 21 (11.5%) were diagnostic for scabies. We obtain a prevalence of scabies of 2.6% (21/800) and a duration of the outbreak of 14.7 weeks. Statistical analysis shows a significant association between scabies and being a nurse and have an allergy to dust mites. We obtained a low prevalence of scabies infection, limiting the duration of the outbreak and the related economic burden.

The last decade was characterized by the reduction of hospital beds throughout Europe. When facing Covid pandemic, this has been an issue of major importance as hospitals were seriously overloaded with an unexpected growth in demand. The dichotomy formed by the scarcity of beds and the need for acute care was handled by the Bed Management (BM) function. This study explores how BM was able to help the solidness of the healthcare system, managing hospital beds at best and recruiting others in different set-tings as intermediate care, in a large Local Health Authority (LHA) in central Italy. Ad-ministrative data show how the provision of appropriate care was achieved recruiting approximately 500 beds belonging to private healthcare facilities affiliated with the re-gional healthcare system and exercising at best the BM function. The ability of the system to absorb the extra demand caused by Covid was made possible using intermediate care beds, which allowed to stretch the logistic boundaries of the hospitals, and by the promptness of Bed Management in converting beds in Covid beds and reconverting them and timely managing internal patient logistic, thus creating space according to the healthcare demand.

Abstract: Five patients with standard medical treatment-resistant symptoms of skin lesions, ear infections, allergic rhinitis, nasal congestion, asthma, heartburn, and failure to thrive were success- fully treated with an integrative medicine assessment and integrative medicine treatment approach. The integrative medicine assessment method of autonomic response testing enabled the identifica- tion of nickel sensitivity as a common element in these patients. It guided the use of the integrative medicine therapies of low dose immunotherapy, gamma linoleic acid supplementation, chelation, dietary nickel restriction, and removal of nickel containing dental and cosmetic appliances. A chart review of 151 patients indicated a strong association of nickel and the simultaneous presence of skin lesions.

Education is one of the most important tools available to policymakers and non-governmental bodies to promote a change in the behavior of society and to address the climate crisis, in line with the 4^th and 13^th Sustainable Development Goals of the United Nations 2030 Agenda. Project-based learning (PBL) addresses real and global challenges and allows the academic and professional formation of students. As part of the reflection stage of the educational action research method using the Business Canvas Model (BMC), pedagogic deficiencies were identified in the PBL and a didactic proposal was elaborated to emulate the interaction of students with the ecosystems of society. A prototype for improving the management of organic manures as soil amendments was initially developed, to provide the students with a quick start on the first steps of the proposed project. In the 10 sessions designed for the PBL (Make it happen!), the students elaborate a more sophisticated artifact in response to the demands of potential clients, as per the outcomes of the primary market research (5^th session). Active teaching methods and tools, such as a modified template of the BMC with the Rumsfeld’s matrix, aid the metacognition of students and their competences development. In a double session of the PBL, the primary market research is organized with key stakeholders of the agroindustry to enquire about the feasibility of the implementation of the technological solution and the logistics at farm level. Finally, the evaluation relies on the suitability of the upgraded prototype to respond customers’ demands.

The paper analyses the national DK-model Hydrological Information and Prediction (HIP) system and HIP portal viewed as a ‘Digital Twin’ and how the introduction of real-time dynamic updating of the DK-model HIP simulations can give room for plug-in sub-models with real-time boundary conditions made available from a HIP portal. The possible feedback to a national real-time risk knowledge base during extreme events (flooding and drought) is also discussed. Under climate change conditions, Denmark is likely to experience more rain in winter, more evapotranspiration in summer, intensified cloudbursts, drought, and sea level rise. These challenges have been addressed as part of the Joint Governmental Digitalization Strategy 2016-2020 for better use and sharing of public data about the terrain, water, and climate to support climate adaptation, water management, and disaster risk reduction. This initiative included the development of a new web-based data portal (HIP portal) developed by the Danish Agency for Data Supply and Infrastructure (SDFI). GEUS delivered 5 terra-byte of hydrological model data to the portal with robust calibration methods and hybrid Machine Learning (ML) being key parts of the deliverables. The paper discusses the challenges and potentials of further developing the HIP Digital Twin with ‘plug-in Digital Twins’ for local river basins including feedback to the national level.

Due to nutritional benefits and perceived humane ways of treating the animals, the demand for antibiotic-free pastured poultry chicken has continued to be on a steady rise. However, despite non-usage of antibiotics in pastured poultry broiler production, antibiotic resistance (AR) is reported in zoonotic poultry pathogens. However, actors that drive multidrug resistance (MDR) in pastured poultry are not known. In this study, we used machine learning and deep learning approaches to predict farm management practices, and physicochemical properties of feces and soil that drive MDR in zoonotic poultry pathogens. Antibiotic use in agroecosystems is known to contribute to resistance. Evaluation of the development of resistance in environments that are free of antibiotics such as the all-natural antibiotic-free, pastured poultry production systems described here is critical to understand the background AR. We analyzed 1,635 preharvest (feces and soil) samples collected from forty-two pastured poultry flocks and eleven farms in the Southeastern United States. CDC National Antimicrobial Resistance Monitoring System guidelines were used to determine antimicrobial/multidrug resistance profiles of Salmonella, Listeria and Campylobacter. A combination of two traditional machine learning (RandomForest and XGBoost) and three deep learning (Multi-layer Perceptron, Generative Adversarial Network, and Auto-Encoder) approaches, identified critical farm/environmental variables that drive multidrug resistance in poultry pathogens, in broiler production systems that represents background resistance. This study enumerates management practices that contribute to AR and recommendations to potentially mitigate multidrug resistance and prevalence of Salmonella and Listeria in pastured poultry.

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.

This research was conducted to understand changes of physicochemical properties of fruits of three apple cultivars as influenced by stage of maturity and packaging types over storage period of three weeks. The research was designed to replicate practices by the producers and along the value chains and to assess the fruit quality under the conditions of the major markets in the region. All the measured physicochemical parameters significantly varied with the cultivars, maturity stage at harvest and packaging types. Higher firmness was recorded for the samples harvested about two weeks before the optimal maturity, usually practiced by significant number of producers to gain market advantage. Lower total soluble solids corresponded to the early harvested samples regardless of cultivars and packaging types. The firmness was observed decreasing over the storage periods whereas the total soluble solids increased, which is associated to improving sensorial quality for the early harvested cultivars as the soluble solids are mainly sugars. The early harvesting resulted in fruits of inferior desirability including extreme hardness, firmness and low total soluble solids that may have high sourness and less sweet taste. Awareness creation for the producers on the quality and advantages of harvesting their produces at optimal maturity and practicing good postharvest management is required.

The management of patients with spinal muscular atrophy type 1 (SMA1) is constantly evolving. In just a few decades the medical approach has switched from an exclusively palliative therapy to a targeted therapy, transforming the natural history of the disease, improving survival time and quality of life, and creating new challenges and goals. Many nutritional problems, gastrointesti-nal disorders and metabolic and endocrine alterations are commonly identified in patients af-fected by SMA1 during childhood and adolescence. For this reason, a proper pediatric multidis-ciplinary approach is then required in the clinical care of these patients, with a specific focus on the prevention of most common complications. The purpose of this narrative review is to provide the clinician with a practical and usable tool about SMA1 patients care, through a comprehensive insight into the nutritional, gastroenterological, metabolic and endocrine management of SMA1. Considering the possible horizons opened thanks to new therapeutic frontiers, a nutritional and endo-metabolic surveillance is a crucial element to be considered for a proper clinical care of these patients.

This study aims to understand the global environment of COVID-19 management and guide future policy directions after the pandemic crisis. To this end, we analyzed a series of the World Economic Forum’s COVID-19 response reports through text mining and network analysis. These reports, written by experts in diverse fields, discuss multidimensional changes in socioeconomic situations, various problems created by those changes, and strategies to respond to national crises. Based on 3,897 refined words drawn from a morphological analysis of 26 reports (as of the end of 2020), this study analyzes the frequency of words, the relationships among words, the importance of specific documents, and the connection centrality through text mining. In addition, network analysis helps develop strategies for sustainable response to and management of national crises through identifying clusters of words with a similar structural equivalence.

The present article proposes a complete framework for Supply Chain Strategy (SCS) analysis that is adapted to the specific characteristics of the agrifood chain, thereby facilitating management of the former. As a specific case of analysis, the horticultural supply chain, originating in Spain and ending with the European consumer, is analyzed, taking as a reference the marketing companies at origin (mainly social economy companies, i.e.; cooperatives). In addition, a survey of marketing companies is conducted to possibly determine which explicit cooperative growth strategies may include horizontal and vertical collaboration relationships with other members of the chain. The aim is to analyze with whom the cooperative collaborates within the supply chain and the key points of such collaboration. A model analyzing the influence of collaboration on company performance is also considered. The results reveal that, in recent years, aspects related to quality and health have been surpassed and replaced by the concept of sustainability within a framework of collaboration with customers. In any case, it becomes evident that there is a need to expand collaboration within the chain by incorporating the supplier of the supplier, with the aim of making the chain more profitable.

: A strong financialtransaction is an important factor in organizational triumph and sustainability, and it is elucidated in the revised student handbook of the University that can be found on page 96 rules 1 to 5. This study assessed the registered students organizations' profile in terms of its type, registration, years of establishment, functions, and designations of student leaders and advisers. The financial practices or internal control system manages their organizational finances and the problems encountered by the student organizations and eventually proposed a manual of operation for students and youth organization's internal control system. This research used the descriptive design with the aid of questionnaire; data gathering through quota sampling from 57 student leaders and advisers of different student organizations of NEUST. Findings showed that most organizations had their constitution and by-laws but kept only as files and renewal requirements. Some provisions were not known to the officers, mostly were registered more than five years in operation; however, in terms of functions of officers and advisers, the results showed that some functions were not done by the officers who supposed to do it like the auditors who serve as treasurers also, the PRO as the record keeper and the presidents who handled finances and collections and as well as disbursements of funds. Generally, the organizations' financial activities were deemed to be "good", especially budgeting and cash receipt, due to the implementation of "no collection and no tuition fee policy". The researchers concluded that the absence of the proper internal control systems and manual of operation and lack of proper transfer of financial records from the previous sets of officers were the serious problems that should be addressed. Moreover, the student organizations' internal control system could still be improved if there is proper training and supervision in accounting operation.

This article discusses the implementation of the Water Framework Directive (WFD) in the Netherlands and intends to show how law and politics combine in river basin management. Initially, the implementation of the WFD in the Netherlands was approached as a technical and administrative issue, handled by water quality and ecology experts, but in 2003 this approach was broken open by the agricultural sector, who were worried about stricter regulation. Subsequently, the environmental objectives of the WFD were set as low as possible and they are not used in authorising individual projects. Yet, in 2015 of the European Court of Justice determined that the environmental objectives have binding effect and that Member States have to refuse authorisation for projects that endanger the achievement of these objectives. In the future, the European Court of Justice and national courts may force the Dutch government to change its approach. They may only do so because and as long as they enjoy sufficient social and political support and function relatively independently. The article concludes that, to understand river basin management fully, one has to open up the black box of water law and become a kind of water lawyer.

Opioid analgesics are effective pain therapeutics but cause various adverse effects and addiction. For safer pain therapy, biased opioid agonists selectively target distinct m opioid receptor (MOR) conformations, while the potential of biased opioid antagonists has been neglected. Agonists convert a dormant receptor form (MOR-m) to a ligand-free active form (MOR-m*), which mediates MOR signaling. Moreover, MOR-m converts spontaneously to MOR-m* (basal signaling). Persistent upregulation of MOR-m* has been invoked as a hallmark of opioid dependence. Contrasting interactions with both MOR-m and MOR-m* can account for distinct pharmacological characteristics of inverse agonists (naltrexone), neutral antagonists (6b-naltrexol), and mixed opioid agonist-antagonists (buprenorphine). Upon binding to MOR-m*, naltrexone but not 6b-naltrexol suppresses MOR-m*signaling. Naltrexone blocks opioid analgesia non-competitively at MOR-m*with high potency, whereas 6BN must compete with agonists at MOR-m, accounting for ~100-fold lower in vivo potency. Buprenorphine’s bell-shaped dose-response curve may also result from opposing effects on MOR-m and MOR-m*. In contrast, we find that 6b-naltrexol potently prevents dependence, below doses affecting analgesia or causing withdrawal, possibly binding to MOR conformations relevant to opioid dependence. We propose that 6b-naltrexol is a biased opioid antagonist modulating opioid dependence at low doses, opening novel avenues for opioid pain therapy and use management.

Global pandemic COVID-19 is in stage 4 of widespread local transmission in Bangladesh- the country which did not have a noteworthy health policy and legislative structures to combat COVID-19 like a pandemic. Early strategic planning and groundwork for evolving and established challenges are crucial to assemble resources and react in an appropriate timely manner. This article, therefore, focuses on the public perception of comparative lockdown scenario analysis and how they may affect the sustainable development and the strategic management regime of COVID-19 pandemic in Bangladesh socioeconomically. Response from 159 respondents was collected via a purposive sampling survey method through a questionnaire, and 54 statements were collected for scenario analysis. Datasets were analyzed through a set of statistical techniques including Principal Component Analysis (PCA), hierarchical Cluster Analysis (CA), Pearson’s correlation matrix (PCM), Linear regression analysis (LRA), and psychometric characteristics were included in the Classical Test Theory (CTT) analysis. There were good associations among the lockdown scenarios and response strategies to be formulated. A strong significant positive relationship was observed between people who will start moving towards regular life and the formal and informal economic activities will be started in lockdown scenario 1(r=0.671, p<0.01). The scenario one describes how the death and infection rate will increase if Govt withdraw the partial lockdown before 40 to 50 days. Scenario 2 outlines people’s movement will enable low-level community transmission of COVID-19 with the infection and death rate will increase slowly (r=0.540, p<0.01). Moreover, there will be less supply of necessities of daily use with a price hike (r= 0.680, p<0.01). Scenario 3, full lock down will reduce the community transmission and death from COVID-19 (r=0.545, p<0.01). Moreover, along with the other problems gender discrimination and gender-based violence will increase rapidly (r=0.661, p<0.01). Form regression analysis, due to full lockdown, the formal and informal business, economy and education sector will be hampered severely (R=0.695), there was a strong association between the loss of livelihood and unemployment rate will increase due to business shutdown (p<0.01) and poor communities both in urban and rural areas will be affected severely (p<0.01).All these will further aggravate the humanitarian needs of the most vulnerable groups in the country in the coming months to be followed which needs to be dealt with proper response plans. It will undoubtedly affect the targets of global sustainable development goals (SDGs) of 2030 and all other development targets.

The paper presents a new vision on the energy consumption management in the case of the Small and Medium Enterprises (SMEs), integrated into an advanced decision support platform, with technical and economic benefits on increasing the energy efficiency, which contains modules for database management, profiling, forecasting, and production scheduling. Inside each module, Artificial Intelligence and Data Mining techniques were proposed to remove the uncertainties regarding the dynamic of technological flows. Thus, the data management module includes the Data Mining techniques, that extract the technical details on the energy consumption needed in the development of production scheduling strategies, the profiling module uses an original approach based on clustering techniques to determine the typical energy consumption profiles required in the optimal planning of the activities, the forecasting module contains a new approach based on an expert system to forecast the total energy consumption of the SMEs, and production scheduling module integrates a heuristic optimization method to obtain the optimal solutions in flattening the energy consumption profile. The testing was done for a small enterprise from Romania, belonging to the domain of trade and repair of vehicles. The obtained results highlighted the advantages of the proposed decision support platform on the decrease in the intensity of energy consumption per unit of product, reduction of the purchase costs, and modification of the impact whom the energy bills have on the operational costs.

This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

DC residential distribution system (RDS) consisted by DC living home will be a significant integral part in the future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between main grid and demand sides. The utilization of distributed generations (DGs) requires an economic operation, stability, environmentally friendly in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through centralized energy management system (CEMS), but a control approach to implement and ensure DG output voltages to various DC buses in DC RDS. Based on data collection, prediction and a certain objection, the expert system in CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage is aligned with the command of unit power schedule. In this work, a DC RDS is as a case study to demonstrate the process, the RDS is associated with unit economic models, cost minimization objective is proposed to achieve based on real-time electrical price. The results show that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency.

Scholars in the field of environmental economics have extensively examined the relationship between foreign direct investment (FDI) and economic growth. However, they have often failed to consider the crucial roles played by technological innovation and financial development in determining environmental costs. The rapid economic growth and urbanization witnessed in BRICS countries have led to a substantial increase in energy demands, resulting in significant environmental degradation. This study aims to investigate the impact of financial development (including measures such as broad money, domestic credit to the private sector, FDI, and green technological innovation) on carbon emissions in BRICS countries using data from 2001 to 2023. The results of the study demonstrate a strong cross-sectional dependence among the countries in the panel. The Augmented Mean Group (AMG) estimator reveals a negative and statistically significant long-term relationship between broad money, FDI, green technological innovation, and CO2 emissions. On the other hand, domestic credit to the private sector shows a positive and significant association with carbon emissions. To determine the direction of causality, the study utilizes the Dumitrescu and Hurlin panel causality test. The findings indicate a non-directional long-term causality between financial development and CO2 emissions. However, a unidirectional causality is observed between green technological innovation and carbon emissions. Based on these findings, the study suggests that the development of industries, financial institutions, and technological innovation is crucial for attracting high-quality FDI in BRICS countries. However, it also highlights the significant contribution of these developments to environmental degradation, necessitating urgent policy responses.

According to the wide variety of internet of things (IoT) devices within smart environments, many challenges face conventional digital forensic investigation (DFI) in smart environments. Challenges in this environment include heterogeneity, distribution, and massive amounts of data, which exceed digital forensic (DF) investigators’ human capabilities to deal with all of these challenges within a short period of time. Furthermore, it significantly slows down or even incapacitates the conventional DFI process. With the increasing frequency of digital crimes, better and more sophisticated DFI procedures are desperately needed, particularly in such environments. Since machine learning (ML) techniques might be a viable option in certain situations, this paper presents the integration of ML into DF. It also explores the potential further use of ML techniques in DF in smart environments to reduce the hard work of human beings, as well what to expect from future ML applications to the conventional DFI process.

This study attempts to investigate a method for creating an index from mobility data that not only correlates with the number of people who relocate to a place but also has causal influence on the number of such individuals. By creating an index based on human mobility data, it becomes possible to predict the influence of urban development on future residential movements. In this paper, we propose a method called the travel cost method for multiple places (TCM4MP) by extending the conventional travel cost method (TCM). We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of a neighborhood. However, conventional TCM does not assume that the opportunity cost of travel time varies according to the departure place. In this paper, TCM4MP is proposed to estimate the opportunity cost of travel time with respect to the departure place. We consider such estimation to be possible due to the use of massive mobility data. We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of the neighborhood. Therefore, we consider that the opportunity cost of travel time has a causal influence on future residential mobility. In this paper, the validity of the proposed method is tested using the smart card data of public transportation in Western Japan. Our proposed method is beneficial for urban planners in estimating the effects of urban development and detecting the shrinkage and growth of a population.

This paper proposes a re-conceptualization of the port supply chain as a smart service system, according to the theory of the Service science. Starting from a short literature review about the port supply chain approach and the Service science, a new comprehensive framework is provided to better understand the seaport dynamics and the creation of competitive port supply chains. The methodology used is the case study approach. The authors examined the port of Salerno (Italy), and re-conceptualized it as a smart port service systems. Both theoretical and practical implications are provided to enrich the literature about the port supply chain and to support the port operators.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. Validated through extensive offline experiments and online deployments, the model significantly outperforms existing optimal benchmark methods on real datasets, improving the location deviation squared metrics and the top-three location prediction accuracy metrics. These research results provide important support to further promote the intelligent development of the logistics industry.

Because of ambiguous and widely debated observations concerning incidence trend and management of TC, we performed this analysis. We drew attention to some events, such as “cancer screening activity,” introduction of noninvasive follicular neoplasm with papillary-like nuclear features (NIFTP) to TC types, possibility of papillary thyroid microcarcinoma (PTMC) active surveillance (AS), occurrence of personalized medicine in TC management and finally COVID-19 pandemic time. Because of the opinion that all changes have been made mostly by PTC, we compared it to the rest of types of TC in terms of incidence, clinical and pathological characteristics and treatment. The prevalence of TC significantly increased from 5.15% in 2008 to 13.84% in 2015 and then significantly decreased to 1.33% in 2022 when the pandemic lasted (p<0.0001). A similar trend was observed for PTC, when the incidence significantly increased to 13.99% in 2015 and then decreased to 1.38% in 2022 (p<0.0001). At that time, the NIFTP category was introduced, and observation of PTMC began. The prevalence of FTC and MTC also increased until 2015 and then decreased. Significant differences in age, types of surgery, necessity of reoperation, pTNM, between PTCs and other types of TCs were observed. The average age was significantly lower in PTC patients than in patients with the remaining types of TC (p<0.0001). Four milestones, including NIFTP introduction, the possibility of PTMC AS, personalized cancer medicine and the COVID-19 pandemic, may have influenced the general statistics of TC.

This investigation delves into an examination of the growth dynamics observed in Central Taiwan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs This investigation delves into an examination of the growth dynamics observed in Central Tai-wan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs in Taiwan and Scotland, respectively, attracting numerous high-tech and startup enterprises. Various means facilitate the growth of industries and foster innovations in different industrial spheres. Important factors contributing to this growth include policy support, availability of research materials, and provision of infrastructure. This research paper compares the successful case studies of two industrial parks, along with their environmental and economic management strategies. It explores the management principles that ensure the sustainable development and economic growth of industrial parks, aiming to assist decision-makers and relevant stakeholders in evaluating the sustainable development planning of industrial parks.

Animals in human care are affected by stressors that can ultimately reduce fitness. When reproduction is affected, endangered species’ conservation programmes can be severely compromised. Thus, understanding factors related to stress and reproduction, and measures of related hormones, are important to ensure captive breeding success. Red pandas are endangered and populations in the wild are threatened with extinction. A global captive breeding programme has been launched to conserve the species with the goal of reintroduction. However there is little informaiton on how stressors impact reproductive aspects of the species. This study measured fecal glucocorticoid (fGCM), fecal progestagen (fPM) and fecal androgen (fAM) metabolite concentrations in 12 female and 8 male red pandas (Ailurus fulgens fulgens) at three zoos in northeastern India to determine predictors of adrenal and gonadal steroid activity and the influence of fGCM on reproduction. Results indicated that fGCM concentrations were higher in males than females, and positively correlated with number of visitors, while negatively related to frequency of feedings and enclosure area. Sex, visitor number, frequency of feeding, and enclosure area explained 67% of the variations in fGCM concentrations in the study population. Concentrations of fPM were positively associated with tree density in the enclosure, explaining 47% of the variation among females. For fAM, positive associations were found with frequency of feeding, but concentrations were negatively related to age and number of visitors; these three covariates explained 45% of the variation in fAM concentration among males. Comparison of fGCM with fPM showed a negative trend, indicating increasing adrenal hormones may decrease reproductive function among female red pandas. The study thus suggests that zoo management should consider increasing feeding frequency, providing larger enclosures with more trees, and regulating visitor numbers to reduce stress and increase reproductive fitness among red pandas.

Climate change causes weather extremes to rise in frequency and severity, which could have detrimental effects on human life, property and livelihood activity. There is significant uncertainty about the influences of anthropogenic climate change on the occurrence and severity of small-scale, sudden onset weather phenomena such as hailstorms and subsequent loss and damage. Yet, several studies indicate that there is an apparent stable connection between hailstorm activity and hailstorm damage. Severe hailstorm events are observed in Bangladesh in recent years, which are, in fact, rapid-onset disasters but low exposure in terms of giving government response and media consideration. Hence this study examines potential impacts and management strategies for loss and damage resulting from hailstorm events among smallholder farmers in Kurigram District's Phulbari Upazila of Bangladesh. Firstly, the direct and long term economic and non-economic loss and damage caused by the hailstorm on human well-beings and livelihoods were assessed. Then, the study evaluated the current adaptation, coping, management and response strategies at the institutional and community level in the context of such extreme events. Finally, a regulatory framework and implementation approaches had suggested achieving the country's resilience against disaster and climate change-induced loss and damage. Participatory Vulnerability Analysis, Key Informant Interviews and Sample Surveys accumulated the primary data for the study. In addition, secondary data were collected through analysis of literature, published and unpublished scientific articles and media reports, etc. This research outcome will help countries develop a guideline to address climate change and disaster-related loss and damage.

The rising world population has made it imperative to get rid of time-consuming and non-economical agricultural practices. Thus, advances in Internet of Things (IoT) technology have recently propelled significant advancements in agriculture, similar to several other sectors. Through the combination of IoT and Farm Management Information Systems (FMIS), field data can be automatically collected, stored, analysed and accessed by farmers in real-time. In this paper, we present Proof-of-Concept (PoC) IoT circuit and FMIS web app for precision agriculture. The IoT circuit incorporates sensors, microcontroller and Wi-Fi module, which acquire and transfer field data to the FMIS web app. We designed and simulated the IoT circuit using Proteus, Arduino Uno, and Arduino Integrated Development Environment (IDE). The FMIS PoC web app was modelled with relevant Unified Modeling Language (UML) diagrams and Django (a Python framework) was employed to implement the app. Our simulation result illustrates how essentila field parameters can be monitored remotely and seamlessly by agriculture practitioners. It further provides a blueprint for real-time precision agriculture at scale and could serve as a learning aid for students in engineering and agricultural science.

The new climate law introduces a policy of sustainable construction, the assumption of which is the reduction of CO2 by the construction industry and the use of environmentally friendly materials, such as agricultural, mineral, and recycled waste, while limiting the consumption of natural resources. The article is a literature review that analyzes selected waste materials from various sectors of the economy that can be used as additives or partial substitutes for natural resources in the production of cement and in and cement building materials, the production of which reduces CO2 emissions, producing materials with high mechanical strength and environmentally friendly.

The current study assessed the influence of Anti Stripping Agents (ASA), Ground Tire Rubber (GTR) and waste polyethylene terephthalate (PET) on performance behavior of binder and Stone Matrix Asphalt (SMA) mixtures. Through this paper, the 85/100 penetration grade bitumen was utilized as original bitumen. Also, three liquid ASA’s (ASA (A), ASA (B), ASA (C)) were used as a mixture modifier. For this purpose, softening point, penetration, rotational viscosity, Dynamic Shear Rheometer, Multi Stress Creep Recovery (MSCR) and Linear Amplitude Sweep (LAS) tests were implemented to investigate the rheological properties of modified bitumen. For evaluating the behavior of modified mixtures several tests such as; Resilient Modulus, Tensile Strength, dynamic creep, wheel track and four-point beam fatigue tests were implemented. Based on MSCR test results, utilization of mentioned polymers enhanced the elasticity of bitumens and therefore the permanent deformation resistance of binders increases. Also by the addition of PET percentage, the rutting resistance improves. Results indicated that utilization of ASAs, PET and Crumb Rubber (CR) enhance the Resilient Modulus (Mr), Indirect Tensile Strength (ITS), rutting resistance, fatigue life and Fracture Energy (FE) of asphalt mixtures. Also based on results, modification of binder by PET/CR with a ratio of 50%/50% and ASA (B) have the highest fatigue life which indicates that this mixture has highest resistance against fatigue cracking.

High-strength wastewaters from a variety of sources, including the food industry, domestic septage and landfill leachate, are often hauled to municipal wastewater treatment plants (WWTPs) for co-treatment. Due to their high organic loadings, these wastewaters can cause process upsets in both the WWTP’s liquid and solids treatment trains and consume organic treatment capacity, leaving less capacity available to service customers in the catchment area. A novel pre-treatment method, the Waste Activated Sludge-High Rate (WASHR) process, is proposed to optimize the co-treatment of high-strength wastewaters. The WASHR process combines the contact stabilization and sequencing batch reactor processes. It utilizes waste activated sludge from the municipal WWTP as its biomass source, allowing rapid start-up. Bench scale treatment trials of winery wastewater confirm the WASHR process can reduce loadings on the downstream WWTP’s liquid treatment and solids treatment trains. A case study approach is used to confirm the economic viability and environmental sustainability of the WASHR process compared to direct co-treatment using life cycle cost analyses and greenhouse gas emissions estimates.

One of the biggest problems that the Dominican Republic has had in recent decades is the efficient management of solid waste produced by the population. This problem has worsened in recent years due to the decrease in available areas for the construction of sanitary landfills, the lack of recycling culture in the population, the deficiency in waste collection, and the scarce legal controls aimed at preserving water and air and soil, among other factors. The objective of this study was to explore the management of solid waste by the population and the municipality of Puñal, province of Santiago, to evaluate and analyze the situation and generation of solid waste, municipal solid waste management services, and the attitudes of the population regarding recycling projects and waste management, to evaluate the viability and sustainability of the use organic waste for energy generation. A total of 275 households from 29 localities in the municipality of Puñal were surveyed, which allowed for a significant population sample. According to the results obtained, the most significant type of waste produced by families is organic waste, followed by plastic waste and paper. Of the total organic waste produced in the municipality, 53% of solid waste is disregarded through the municipal waste collection system, while 47% is used as plant fertilizers or animal feed. On the other hand, most households receive the municipal waste collection service and pay for this service. The results of our research show that the implementation of an energy production system based on organic waste would be viable in the municipality of Puñal. However, a more efficient waste collection system would be necessary and the development of programs and projects that allow all households to participate in the system.

Vehicle routing is a critical factor in municipal solid waste (MSW) collection planning and operations. Poor routing can introduce inefficiencies and cause targeted levels of services or performance to be missed irrespective of the level of resource application. Trial and error approaches have been proven to be not the best in the planning and prediction of expected performance. This study explores various Geographic Information System (GIS) tools and analysis techniques, and how they can be applied to optimizing vehicle routes in light of challenging site conditions. Using Adentan West residential area, suburb of Accra Ghana as a case study, current performance of the trial and error method was measured and a GIS computer model was used to evaluate various optimization scenarios to determine the level of savings that can be made. Field measurements were taking with Global Positioning System (GPS) devices for waste collection activities in areas with varying characteristics and conditions, and data analysed for one selected vehicle operating four days per week. It was found that, for a scenario where only the bin collection order was optimized while route selection was restricted by the ArcGIS Network Analyst, 2.6% of travel distance and 2.21% of travel time were saved. For the second scenario where only the route selection was optimized while order of bin collection was restricted, 4.1% and 1.5% of travel distance and time respectively were saved. For a third scenario where both the order of collection and route selection were together optimized, 10.9% and 3.7% of travel distance and time respectively were saved. Lastly, by regrouping all the bins for daily collection, 4.5% and 1.2% of travel distance and time respectively were saved. The results demonstrated that there is always room for optimization of solid waste collection routing irrespective of site constraints and other challenges that the nature of bin distribution pose to drivers. In developing countries like Ghana, where there is high demand for services in the face of limited road network access, application of GIS in optimization of routes will guide providers in planning and subsequently make more savings in fuel consumption, vehicle maintenance and cost of man-hours.

Municipal landfills play a vital role in disposing of the solid waste from a community. One of the biggest challenges landfill management face is when the available storage space is being reduced faster than the rate that was planned for. This shortening of the landfill lifecycle impacted the city of Wilmington, Delaware when it was found that their landfill had lost 11 years of its projected lifespan and would reach fully capacity within the next decade. In order to remedy the situation six alternative solutions were devised, with each having different costs (capital, operating, and transport) and varying lengths of landfill extension. This research used the principle of optimization via a LINDO program to determine which solution would achieve the longest landfill extension for the minimum total cost. Other constraints placed on the program include reducing the waste being sent to the landfill and to achieve a minimum of 25 additional years for the landfill. The calculated solution produced a cost reduction of $232.64 million dollars and 3.2 additional years of operation from the option that was eventually chosen by the landfill authority.

The EASY-NET network program (NET-2016-02364191 - Effectiveness of Audit and Feedback (A&F) strategies to improve health practice and equity in various clinical and organizational set-tings), piloted a new and more structured A&F strategy. This study compared the effectiveness of the new strategy versus the periodic publication of indicators alone in improving the appropri-ateness and timeliness of emergency health interventions in patients with Acute Miocardial In-farction (AMI) and ischemic stroke in the Lazio Region. Efficacy was evaluated according to a prospective quasi-experimental design of pre-post (2021-2022) intervention type with control group. The exposed are hospitals in the Lazio Region where professional teams voluntarily par-ticipated in the intervention. The control group is involved only in the usual reporting activities. Effectiveness analysis was conducted at the patient level. Regional health information systems were used to calculate process and outcome indicators. The effectiveness of the intervention was assessed with Difference In Difference models, comparing pre-post intervention periods between exposures and controls. Estimates were calculated in terms of the difference in percentage points (pp) between absolute risks. Sixteen facilities for the IMA pathway and 13 for the stroke pathway joined the intervention. The intervention reduced the proportion of 30-days readmissions after a hospitalization for ischemic stroke by 0.54 pp in the exposed patients with a significant difference of -3.80 pp (IC95% -6.57; -1.03; 5453 patients, 63.7% cases) in the exposed compared to controls. There were no statistically significant differences attributable to the implemented A&F interven-tion in the other indicators considered. The results show, for the first time in Italy, the impact of A&F interventions in an emergency setting using aggregated data from hospitals involved in the Lazio Region emergency network.

Signal preprocessing and feature extraction are two important and necessary steps of data analysis. In signal analysis, typically these two steps are implemented through multiple algorithms. Moreover, the significant parameters in most algorithms are set empirically. We have developed an algorithm that can preserve and highlight characteristic waveforms while attenuating non-feature waveforms. The parameters in the algorithm are set through difference analysis. We have conducted experiments on both clinical and open-source ECG data, obtaining effective test results.

Green and Roasted coffee oils are products rich in bioactive compounds, such as linoleic acid and diterpenes cafestol and kahweol, being a potential ingredient for food and cosmetic industries. An overview of oil extraction techniques most applied for coffee and their influence on the oil composition is presented. Both green and roasted coffee oil extractions are highlighted. Pressing, Soxhlet, microwave, and supercritical fluid extraction were the most used techniques used for coffee oil extraction. Conventional Soxhlet is most used on lab-scale, while pressing is by industry. Supercritical fluid extraction has also been evaluated due to the goal of increasing the coffee oil diterpenes content. One of the highlighted activities in Brazilian agribusiness is the industrialization of oils due to their increasing use in the formulation of cosmetics, pharmaceuticals, and foods. Green coffee oil (raw bean) has desirable bioactive compounds, increasing the interest of private companies and research institutions in its extraction process to preserve the properties contained in the oils.

Background: The main objective of this study is to develop a customized metatarsophalangeal implant for the treatment of various conditions affecting this specific joint. This approach involves replacing the joint with a custom implant designed specifically to fit each patient's unique anatomical structure. The need for custom implants stems from the obvious lack of size variety available, which presents a major challenge when, the search for the ideal size implant can be a hard task, also when considering the possibility of extensive modification of the bone to adapt it to the available implant. This adaptation, often synonymous with bone reduction, can cause significant post-operative pain for the patient and impact healing time. Methods: A comparative study of modeling software was carried out to select the perfect software, by defining and comparing the relevant criteria. Similarly, the different biomaterial options were examined and compared to select the one best suited to this project, mentioning the imaging modality used to determine the types of images used for our approach. Finally, the 3D printers used in this work were represented, highlighting their technical characteristics. Findings: A resin metatarsophalangeal implant prototype was created using 3D modeling and reconstruction software and tools. Interpretation: Reconstruction and 3D modeling techniques are revolutionizing implant creation, offering customized solutions for patients suffering from metatarsophalangeal joint disorders caused by a wide range of diseases. These results have significant implications for disability management and rehabilitation, encouraging further exploration and progress.

Breast cancer has become the most diagnosed cancer in women globally with 2.3 million new diagnosis each year. Accurate early staging is essential for improving survival rates with metastatic spread from loco regional to distant metastasis decreasing rates by 50%. Current guidelines do not advice the routine use of Positron Emission Tomography (PET)-Computed Tomography (CT) in staging of early breast cancer in the absence of symptoms. However, there is a growing body of evidence to suggest that PET-CT used in this early stage can benefit the patient by improving staging and as a result treatment and outcome as well as psychological burden without increasing costs to the health service. Ongoing research in PET radiomics and artificial intelligence is showing promising future prospects in its use in diagnosis, staging, prognosticatication and assessing response to treatment in breast cancer. Furthermore ongoing research to address current limitations of PET-CT by improving techniques and tracers is encouraging.

The genetic potentials of rice cultivars will need to be expressed to their fullest if global rice production is to be expanded enough by 2050 to meet the increased demand of expanding population while the availability of land and water per capita dwindles. New and ‘improved’ rice varieties have contributed greatly to increased production over the past 50 years, but the rate of rice yield increase based on genetic changes has declined in recent decades compared with the early years of the Green Revolution. In fact, many rice consumers continue to prefer to consume ‘traditional’ rice varieties (referred to also as local, native, unimproved, or indigenous) because of their taste, aroma, texture, and other qualities. Further, many farmers prefer to cultivate these varieties because of their better adaptation to local climatic and soil conditions and their evolved resistance to endemic stresses. The practices that comprise the System of Rice Intensification (SRI), including transplanting rice seedlings at a young age, wide spacing between plants, keeping the soil well-aerated rather than inundated, and enhancing soil organic matter, provide traditional rice varieties with micro-environments that are more favorable for the expression of their genetic and agronomic potentials. Interactions among rice plants, soil characteristics, water, energy, and other inputs improve the phenotypic and physiological performance of rice plants. This paper considers how the cultivation of traditional rice varieties with SRI methods can raise yields, reduce farmers’ costs of production, and generate higher incomes, while contributing to the conservation of rice biodiversity.

Hemodialysis (HD) patients experience significant psychological stress related HD. Coping strategies are utilized to help these patients cope with this stress. Prevalence of different types of coping strategies in relation with differential levels of HD-related stress scores and by demographics were assessed. HD patients aged 18 years and above who were seeking regular treatment in a specific HD-unit of a hospital in the upper Midwest, were surveyed between March 2020 and July 2020. Descriptive statistics, correlational analyses, and regression analyses were performed. Females could be expected to have emotional coping scores 8 units greater than males, as B = 8.017 for sex in the model, p =.000. Females could be expected to have coping scores 6.4 points higher than males when adjusted for stress levels, as: B = 6.351, p =.001 for sex in the model. For each 1point increase in Stress Score, the Coping Score could be expected to: increase 6.8 points when adjusted for Sex, where B = 6.751 and p =.000. Increased prevalence of emotional pre-occupation was only observed among female patients which increased with the increase in stress. Psychological interventions in female HD patients should be strongly considered in addressing emotional pre-occupation coping.

Sporothrix brasiliensis is the most pathogenic species, responsible for the Brazilian cat-transmitted sporotrichosis hyperendemics. In this scenario, investigation of pathogen-host interaction can provide relevant information for future treatment strategies. To this end, the invertebrate Galleria mellonella has proven to be a suitable alternative to evaluate the virulence of pathogenic fungi since the insect immune system is similar to the mammalian innate immune response. The aim of this work was to investigate phenotypic and molecular aspects of the immune response of G. mellonella throughout the S. brasiliensis infection. Hemocyte density and the evolution of the fungal load were evaluated. In parallel, RT- qPCR expression analysis of genes encoding antimicrobial peptides (Gallerimycin and Galiomycin) and stress management genes (C7 Contig 15362 and C8 Contig 1910) was conducted. Fungal load and hemocyte densities were proportionally increasing simultaneously to the deleterious morphological events and larvae mortality. Gallerimycin, C7 Contig 15362, and C8 Contig 19101 genes were positively regulated (p&lt;0.05) at distinct moments of S. brasiliensis infection, characterizing a time-dependent and alternately modulated profile. Galiomycin gene expression remained unchanged. Our results contribute to the future proposal of potential alternative pathways to treat and, consequently, control S. brasiliensis zoonosis, a major public Health in Latin America.

While biologic originators’ patents are expiring, biosimilars are emerging to take their place, offering significant cost savings to healthcare systems. Many challenges still need to be addressed in the clinical practice of inflammatory bowel disease (IBD). A global survey was organized to highlight physicians’ current knowledge and beliefs and to gain insight about their practical management and remaining concerns and obstacles associated with starting a biosimilar, switching from an originator to a biosimilar, or switching from one biosimilar to another (multiple switches and reverse switching). Fifteen physicians with expertise in the field of IBD from 13 countries attended a virtual international consensus meeting to develop practical guidance regarding biosimilar adoption worldwide, considering the survey results. Consensus was reached on 10 statements regarding biosimilar effectiveness, safety, indications and rationale, multiple switches, therapeutic drug monitoring of biosimilars, non-medical switching and future perspectives.

In this research, a new conceptual framework introduced to analysis of water security. Using the exponential, logistic growth model, and employing the historical population of Tabriz city from 1956 to 2016, the future period (2022-2100) population predicted. Pearson Correlation, Spearman's Rho and Kendall's rank coefficients were used for analyzing correlation between population and water consumption. In addition, the amount of city water demand in the future period predicted using the ordinary least square model. Then, water stress and water scarcity indices calculated for Tabriz city in the future period. Results indicated that the mathematical population growth models are very suitable for prediction of city population. There was a significant positive correlation between the city population and water demand. In addition, the amount of water demand will proportionally increase with rising number of population. Finally, linear and quadratic equations presented for city water demand based on the city population number. It can be concluded that Tabriz city will be faced with severe water stress in the future period. The proposed new method in this study can be used for other different cities of the world. Also, Results will be helpful for decision makers in optimum management of urban water resources.

Background: Caregivers of asthmatic children have poor knowledge of proper asthma man-agement practices in Nigeria. The objective of this study was to examine the knowledge, attitudes, and practice behaviors of caregivers in the management of asthma in children under age 5 in Oyo State, Nigeria, using the Health Belief Model. Methods: While a mixed method was used in the original research, this brief describes the quantitative method used in this study to evaluate caregiver’s asthma management practices A 55-item questionnaire investigating childhood asthma knowledge, attitude, and practice was administered during child welfare clinic visits to 118 caregivers. To gain insights into caregivers’ beliefs about asthma management practice behavior, focus group discussions were conducted among two groups of 10 caregivers. Data were analyzed using the IBM SPSS Version 25.0. Statistical significance was set at p < 0.05 and 95% CI. Result: More than 70% of caregivers knew that asthma is associated with airway inflammation and about 90% knew that Flu infections triggered asthma attacks in their children. Overall, 70% of caregivers from the focus group discussions found preventive measures including avoidance of common triggers like dust and smoke, wearing warm clothes in cold weather, environmental sanitation, regular visits to the clinic, and medication adherence helpful. Similarly, caregivers reported the use of quick-to-relieve OTC drugs rather than seeking medical attention. Caregivers with higher income (OR = 3.0; 95% CI = 1.558-5.778; P = 0.001) were 3.0 times more likely to practice proper asthma behavior than those with a lesser income. Conclusion: Despite having moderate knowledge of asthma, caregivers of asthmatic children had wrong perceptions and inadequate knowledge about preventive and treatment options. An optimal public health approach is needed to identify and target underserved communities that suffer poorer asthma outcomes and improve caregivers’ knowledge and skills in asthma management practices. The need to pay more attention to the proper management of childhood asthma among caregivers in underserved populations cannot be overemphasized.

Polymyalgia rheumatica (PMR) is the most common inflammatory rheumatic disease among people over the age of 50 and occurs with symptoms such as musculoskeletal pain and stiffness in the neck, shoulders and hips. To date, corticosteroids represent the cornerstone of PMR treatment, although it is well known that their prolonged use is associated with several adverse effects, making it crucial to find therapeutic alternatives to their use. The purpose of this case report was to describe the effectiveness of 10 whole-body cryostimulation (WBC) sessions on a 74-year-old woman suffering from PMR. An improvement in disease impact, fatigue, pain, quality of sleep and total physical activity was observed after WBC. Moreover, the patient reduced her daily drug intake by 67% following WBC treatments. Given the increasing prevalence of PMR and considering the side effects that drug treatments can lead to, WBC could represent a valuable adjuvant and well-tolerated alternative for the treatment of PMR.

Depression and obesity are highly comorbid with one another, with evidence for bidirectional causal links between each disorder and a shared biological basis. The available evidence suggests that genetic factors play a major role in influencing both the occurrence of comorbid depression and obesity, their courses, and their response to existing treatments. The current paper is a scoping review of studies that have evaluated the contribution of specific genetic variants to the comorbidity between obesity and depression. Based on a search of the PubMed and EMBASE databases, 28 studies were included in this review, covering 54 candidate genes. Positive associations were identified for fourteen genetic loci (AKR1C2, APOA5, COMT, DAT1, FTO, KCNE1, MAOA, MC4R, MCHR2, NPY2R, NR3C1, Ob, PCSK9 and TAL1). Replicated findings across two or more independent samples were observed for the FTO and MC4R genes. Many of these gene products represent novel molecular targets for the pharmacological management of obesity which are not pharmacologically influenced by existing anti-obesity or antidepressant medications. The implications of these associations for future drug development are discussed, with an emphasis on recent evidence on the polygenic architecture of comorbid depression and obesity, and on a precision medicine approach to these conditions.

Background: Stress among prison inmates is a neglected psychological health issues, but this phenomenon seems worse in Ghana’s prisons. This study examined the stress levels, predictors and management strategies utilized among inmates at Ankaful Prison Complex. Method: This survey sampled 1,160 inmates using the census approach at the Ankaful Prison Complex with a self-developed questionnaire for the data collection. Frequency counts, one-way ANOVA, and multiple regression analysis were applied to the data. Results: The findings indicate that more than half of the inmates were moderately or highly stressed. Specifically, inmates at the Maximum-Security Prison were the most stressed, followed by Annex Prison, Communicable Disease Prison, and the least, Main Camp Prison inmates. Inmate engagement in exercises, sporting activities, visit and chat with colleagues, and family connectedness outside the prison were stress management strategies. Inmates’ self-reported stress levels were influenced by the prison of custody and state of depression. Conclusion: The moderate to high stress levels identified among inmates of Ankaful Prison Complex are influenced by person-environment factors. Management of Ankaful Prisons Complex is encouraged to initiate health screening services for inmates on common mental health challenges like stress and promote functional stress reduction interventions to improve prisoners’ mental health and overall wellbeing

This paper presents a new information technology platform specially tailored for infrastructure asset management of urban water systems operated by water utilities of lower digital maturity level, developed in the scope of DECIdE research project. This platform aims at the integration of different data from the water utilities with several information systems and the assessment of the system performance, in terms of water losses, energy efficiency and quality of service by using developed tools (i.e., water and energy balances and key performance indicators). This platform was tested with data from five small to medium size Portuguese water utilities with different maturity levels in terms of technological and human resources. Obtained results are very promising since the platform allows to assess the systems performance periodically which constitute an important part of the infrastructure asset management for small and medium-sized water utilities

This study provides an insightful overview of community-participatory governance and conflict management as instruments for utilizing resources for development in Sub-Saharan Africa (SSA). SSA is a region rich in natural resources but prone to conflict. The study is conceptual and critically engages the application of community governance and conflict management strategies that SSA countries need to adopt. The study praises the notion that community governance is characterized by recognizing and accepting intercultural diversity and creating a democratic institution for promoting good governance and conflict management in SSA. The study recommends that good community governance is required to drive local communities' development, growth, and transformation into a sturdy, innovative, and productive society capitalizing on opportunities. The study voice for the amalgamation of appropriate models and theories of governance cogently in the context of SSA due to the heterogeneity of communities. Therefore, to resolve conflict, conflict management, resolution, and transformation strategies are necessarily needed to accomplish a viable peace to maintain and sustain development.

The present era of the Internet of Things (IoT) having intelligent functionalities in solving problems pertaining to realtime mission-critical systems has brought an immense revolution in diverse fields including healthcare and navigation systems. However, to the best of our knowledge, the potential of IoT has not been fully exploited yet in the field of the energy sector. We argue that there is an immense need to shift the traditional mission-critical electric power system architecture to IoT-based fully orchestrated architecture in order to increase efficiency, as billions of investment is reserved for the energy sector globally. Since network orchestration deals with auomating the interaction between multiple components involved to execute a particular service, therefore, scheduling the relevant processes within strict deadlines becomes the core pillar of the architecture. The mission-critical systems with urgent task execution often suffer from issues of missing task deadlines. In this study, we present a novel IoT task orchestration architecture for efficient energy management of a nanogrid system that focuses on minimizing the use of nonrenewable energy resources and maximizing the use of renewable energy resources. Moreover, major components of IoT task orchestration such as task mapping and task scheduling are also enhanced using NLP and PSO optimization modules. The proposed task scheduling algorithm incorporates the optimized surplus time, and efficiently executes the energy management-related tasks contemplating to their types. The study utilizes sensors to obtain data from physical IoT devices, including photovoltaic (PV), Energy Storage System (ESS), and diesel generator (DG). The performance of the proposed model is evaluated using data set of nanogrid houses. The outcomes revealed that IoT-task orchestration has played a pivotal role in efficient energy management for nanogrid mission-critical system. Furthermore, the comparison with state-of-the-art scheduling algorithms showed that the task starvation rate is reduced to 16% and 12% when compared with RR and FEF algorithms, respectively.

The increase in the number of firms manipulating financial reports has misled shareholders' investment decisions and resulted in an indelible blot on foreign investors’ trust. Due to earnings management (EM) practice, managers' inefficiency, and lack of transparency in Iraq companies. This study tested the influence of the corporate governance mechanisms (CG), (board independence, audit committee, meeting frequency) on EM based on agency theory, as well, to link between EM and firm's performance (FP) in Iraqi listed companies and the impact of moderating role of corporate social responsibility (CSR) based on the Stakeholder Theory. The study's sample consists of 65 companies for the 2013-2018 financial years. Data were collected mainly from the annual reports (secondary data) of the Iraqi listed firms. This study uses the M-score model to detect EM practices as practical techniques in detecting earnings manipulation practices. The panel static model estimators. Hence, this paper adds to the CG literature from the perspective of stakeholder theory using Iraq's unique industrial environment. Based on the research results, policy-makers might use the study‘s findings to recognize the essential roles of several CG mechanisms in alleviating the opportunistic practices in Iraq. Further, companies should also be encouraged to enhance the CSR disclosure quality.

Odontogenic infections are infections of the orofacial structures arising from dental disease. Despite its preventability, it exerts a significant burden on healthcare infrastructure worldwide. Our study explored the various different microbiological, social, and epidemiological characteristics of 103 cases of odontogenic infections at our regional center which demonstrated specific predilections for the young and middle-aged, those with diabetes mellitus, African American/Black and Hispanic ethnicities, posterior teeth, left-sided dentition, and male gender. However, nuances and exceptions to these trends were also seen with specific groups that may complicate treatment.

Background: Cutaneous malignant melanoma (CMM) is one of the most aggressive types of skin cancer. Currently, innovative approaches such as target therapies and immunotherapies have been introduced in clinical practice for the treatment of metastatic CMM. Data of clinical trials and real life studies that evaluate the outcomes of these therapeutic associations are necessary to establish their clinical utility. The aim of this study is to investigate the types of oncological treatments employed in the real-life clinical management of patients with advanced CMM in several Italian centers which are part of the Clinical National Melanoma Registry (CNMR), and the oncological outcomes obtained. Methods: CNMR collects data of patients with a histologically confirmed diagnosis of primary CMM treated in one of the 38 Italian institutions (hospitals, research institutes, etc.) participating in the network. Melanoma-specific survival and Overall survival were calculated. Kaplan-Meier curves and medians of OS and 95% CI are presented overall and by immunotherapy and target treatments. The Log-rank test compared curves by treatments. Multivariate Cox regression models were used to estimate the hazard ratios adjusting for confounders and other prognostic factors. Results: The median follow-up time was 36 months (range 1.2-185.1). 787 CMM were included in the analysis with completed information about therapies.Global immunotherapy showed a significant improved survival compared with all other therapies (p=0.001). 75% was the highest reduction of death reached by nivolumab/pembrolizumab immunotherapy (anti-PD1 HR=0.25 95% CI 0.14-0.42), globally immunotherapy was significantly associated with improved survival, either for anti-CTL A4 monotherapy or combined with anti-PD1 (HR=0.47;95% CI 0.33-0.66 and HR=0.26; 95% CI 0.15-0.46, respectively). Conclusions: The nivolumab/pembrolizumab and the combination of ipilimumab can be considered the best therapy to improve survival in a real-world-population. The CNMR can complement clinical registries with the intent of improving cancer management and standardizing cancer treatment.

Some of the European countries affected by COVID-19 have not learned from previous experience in China. Italy did not learn from China and Spain did neither learn from China nor from Italy. Confinement in Spain was postponed due to pressure from economic interests and traveling of infected people, especially from Madrid to the beaches in South-East Spain, was allowed. Strict confinement and border closure came late, when the curve of infected people and the death toll already had the worse trend worldwide. Tests to SARS-CoV-2 RNA detection by PCR, were first unavailable and, later, faulty and/or detecting antibodies and not the virus itself. Instead of mobilizing research laboratories for making tests, and instead of making masks and ventilators, mediatic scientists asked for money for controversial clinical trials and for obtaining a vaccine. In this scenario, common sense indicates that ad hoc measures should be taken at the end of confinement in order to minimize pain. The chain of errors should be avoided in the management of next pandemics by designing Good Practice Rules (GPRs). In addition, post-confinement measures should be implemented as soon as possible to be ready for SARS-CoV-2 return next season. In this sense a longitudinal study in the most affected cities (Madrid, Barcelona, Vitoria and Pamplona) should be performed with the primary objective of detecting carriers with no symptoms, to stratify patients according to symptoms, and to early detection of virus reappearance. Also relevant is to sequence as many viruses as possible to detect possible variants; there are still patients that are PCR positive.

Since the late 1980s the idea of sustainable development has been gaining widespread recognition as a guiding framework for policies on development and the environment. However, the concept of sustainable development has received a number of criticisms, including its over-emphasis on meeting human needs through economic growth, as well as its failure to recognize dynamic human-environment interactions. In response to these shortfalls, the concepts of resilience and adaptive governance have emerged as alternative perspectives for pursuing sustainable development. Resilience in social-ecological systems emphasizes the capacity of coupled human-environment systems to deal with change while continuing to develop. Adaptive governance relies on diverse and nested institutional mechanisms for connecting actors across multiple scales to manage conflicts and uncertainties in ecosystem management processes. However, the ethical dimensions of resilience and adaptive governance have not received enough attention. A promising ethical perspective for guiding policies on human-environment interactions is the philosophy of deep ecology which highlights the need for recognition of the intrinsic values of all living things, as well as the nurturing of ecological and cultural diversity. We argue that an integration of the principles of deep ecology and adaptive governance provides a complementary set of ethical principles and institutional attributes that offers better prospects for pursuing sustainable development in the era of the Anthropocene. The implications of this integrative agenda include: adoption of a holistic conception of dynamic human-environment interactions; recognition of diverse knowledge systems through an anti-reductionist approach to knowledge; promotion of long term sustainability through respect for ecological and cultural diversity; and embracing decentralization and local autonomy. We further illustrate this integrative agenda using the management of protected areas as a case study.

Understanding the vulnerability of areas and the likelihood of specific disasters, particularly earthquakes, is one of the most important issues in Iran. One of the major concerns in Iran is the resilience of rural communities. The present study is devoted to spatial analysis of risk in rural areas and the evaluation of preparedness in the rural districts of the city of Abhar. In particular, this study evaluates the resilience to earthquakes. The research was conducted in two parts in which the first part has used the VIKOR Multiple criteria decision making model as well as the employment of this model in the ArcGis. The second part of the study used field studies, in the form of questionnaires, to evaluate the readiness of the local population against the risks of earthquakes. Four indicators, individual, physical, economic abilities and access, were assessed. The population included rural districts, where statistical samples were villagers. Results of the spatial analysis indicated that 15 villages are in the high-risk areas, 24 villages were in the medium-risk areas and all other villages were in low-risk areas. In terms of readiness of the locals, the results indicated a lack of planning with regards to the four mentioned indicators.

The Android-based IoT platform just like the existing Android provides an environment that makes it easy to utilize Google's infrastructure services including development tools and APIs through which it helps to control the sensors of IoT devices. Applications running on the Android-based IoT platform are often UI free and are used without the user’s consent to registered permissions. It is difficult to respond to the misuse of permissions as well as to check them when they are registered indiscriminately while updating applications. This paper analyzes the versions of before and after an application the update running on the Android-based IoT platform and the collected permission lists. It aims to identify the same permissions before and after the update, and deleted and newly added permissions after the update were identified, and thereby respond to security threats that can arise from the permissions that is not needed for IoT devices to perform certain functions.

Culex quinquefasciatus is an important target for vector control because of its ability to transmit pathogens that cause disease. Most populations are resistant to pyrethroids and often to organophosphates, the two most common classes of active ingredients used by public health agencies. A knockdown resistance (kdr) mutation, resulting in a change from a leucine to phenylalanine in the voltage gated sodium channel, is one mechanism contributing to the pyrethroid resistant phenotype. Enzymatic resistance has also been shown to play a very important role. Recent studies have shown strong resistance in populations even when kdr is relatively low which indicates factors other than kdr may be larger contributors to resistance. In this study, we examined on a statewide scale (over 70 populations), the strength of the correlation between resistance in the CDC bottle bioassay and the kdr genotypes and allele frequencies. Spearman correlation analysis showed only moderate (-0.51) and weak (-0.29) correlation between the kdr genotype and permethrin and deltamethrin respectively. The frequency of the kdr allele was an even weaker correlate. These results indicate, in contrast to Aedes aegypti, assessing kdr in populations of Culex quinquefasciatus is not a good surrogate for phenotypic resistance testing.

This study explores the transformative impact of machine learning on predictive analytics within supply chain management. As supply chains become increasingly complex and dynamic, traditional methods of forecasting and management are proving inadequate. Machine learning offers advanced algorithms capable of analyzing vast datasets to uncover patterns and trends that enhance decision-making processes. This research investigates how machine learning improves demand forecasting accuracy, optimizes inventory management, strengthens supplier relationships, and enhances risk management. The study employs a qualitative approach, analyzing data from industry case studies and expert interviews to identify key themes and challenges associated with the adoption of machine learning. Findings reveal that machine learning significantly improves forecasting precision, reduces inventory costs, and enables proactive supplier and risk management. However, challenges such as ensuring data quality, acquiring specialized skills, integrating new technologies with existing systems, and addressing ethical considerations are critical. The study also highlights the potential of emerging technologies like blockchain, IoT, and 5G to further enhance machine learning applications in supply chain management. This research contributes to a deeper understanding of how machine learning can drive innovation and efficiency in supply chains, while also addressing the hurdles that organizations must overcome. The results underscore the need for a balanced approach that incorporates technological advancements and ethical practices to fully leverage the benefits of machine learning.

The use of Physical Unclonable Functions (PUFs) linked to the manufacturing process of the electronic devices supporting applications that exchange critical data over the Internet has made these elements essential to guarantee the authenticity of said devices, as well as the confidentiality and integrity of the information they process or transmit. This paper describes the development of a configurable PUF/TRNG module based on Ring Oscillators (ROs) that takes full advantage of the structure of modern programmable devices offered by Xilinx 7 Series families. In this work, the increase in hardware efficiency of the proposed architecture is used with a double objective. On the one hand, perform an exhaustive statistical characterization of the results derived from the exploitation of RO configurability. On the other hand, undertake the development of a new version of the module that requires a smaller amount of resources while considerably increasing the number of output bits compared to other proposals previously reported in the literature. The design as a highly parameterized Intellectual Property (IP) module connectable through a standard interface to a soft- or hard-core general-purpose processor greatly facilitates its integration into embedded solutions, while accelerating the validation and characterization of this element on the same electronic device that implements it. The studies carried out reveal adequate values of reliability, uniqueness and unpredictability when the module acts as a PUF, as well as acceptable levels of randomness and entropy when it acts as a True Random Number Generator (TRNG). They also illustrate the ability to obfuscate and recover identifiers or cryptographic keys of up to 4 096 bits using an implementation of the PUF/TRNG module that requires only a 4×4 CLB array to accommodate the RO bank.

DIPA-CRISPR is a revolutionary gene editing technology that has set new benchmarks in precision and efficacy. It builds upon the CRISPR-Cas9 system, introducing unparalleled specificity and minimizing unintended effects. Its potential applications in addressing complex genetic disorders offer hope for more effective disease management. The integration of DIPA-CRISPR into gene therapy research signifies a monumental leap forward in medical science and biotechnology. This article explores the DIPA-CRISPR methodology, its core principles, and recent technological strides in refining the technique. It highlights the implications of these developments on the treatment of genetic conditions and discusses future prospects and innovations within the field. The transformative potential of DIPA-CRISPR in disease management and the broader spectrum of genetic engineering is underscored, heralding a new age of medical and scientific discovery. The emphasis on addressing both technical and ethical challenges underscores the complexity and responsibility that accompanies such powerful technological advancements. The future prospects of DIPA-CRISPR, from pest management to combating global infectious diseases and transforming oncology, underscore the need for continued innovation coupled with rigorous ethical oversight.

Discussions and practices on sustainability are actively underway around the world. In this social context, this study conceptualized ESG management values ​​focused on sports organizations, especially professional sports clubs in Korea. Utilizing Q Methodology, suitable for research on individual's subjectivity, we explored ESG management values accepted by consumers of Korean professional sports. As a result, the ESG management values were confirmed as follows: ‘Type I: Trust-Management Emphasis,’ ‘Type II: Local-Community Emphasis,’ and ‘Type III: Safety-Respect Culture Emphasis.’ While each of the three types accepted governance, social responsibility, safety, and respect culture as their main values, they tended to deny environment-related values. Accordingly, this study provided two discussions: ‘Professional sports consumers’ low awareness of the environment’ and ‘Reinterpretation of environmental values ​​among the ESG management values ​​of professional sports clubs’. In conclusion, the three types are significant in that (1) they well reflect the social and cultural context of Korean professional sports and consumers' perceptions, and (2) they provide a new perspective on the ESG management value of professional sports teams.

Federated learning (FL) has emerged as a crucial technology in today’s data-centric technological environment, enabling decentralized machine learning and safeguarding user privacy. This study introduces “Federated Operations (FedOps) Mobile,” a novel FL framework optimized for the dynamic and heterogeneous ecosystem of mobile devices. FedOps Mobile enhances traditional FL approaches for mobile devices by integrating real-time operational control and advanced on-device training capabilities using TensorFlow Lite and CoreML, addressing critical challenges in scalability, efficiency, and system heterogeneity. Our approach utilizes a wide range of devices, facilitated by intelligent client-selection mechanisms. This mechanism evaluates the capabilities and readiness of multiple devices per client to ensure fair and efficient network participation. The framework also utilizes remote device control for seamless task management and sustained engagement, enabling continuous learning without compromising the user experience. We conducted extensive experiments to validate the framework’s performance, focusing on three core aspects: operational efficiency, model personalization, and resource optimization in multi-device environments. The results demonstrate that the proposed method is effective for efficient client selection, energy consumption, and model optimization.

Cleidocranial dysplasia (CCD) – is an autosomal dominant skeletal dysplasia with a prevalence of 1 in 1 million individuals. This rare disorder is associated with clavicular hypoplasia or aplasia, delayed closure of fontanels, brachycephalic skull, delayed exfoliation of primary teeth , delayed eruption of permanent and, multiple supernumerary teeth, and morphologic abnormalities of maxilla and mandible. The purpose of this paper is to describe the multidisciplinary surgical, pediatric stomatologic and orthodontic treatment of CCD. A case of a young boy suffering from CCD along with the long-term management, is described in the present report. The patient was 8 years and 5 months old when first presented in the clinic and has been treated for another ten years by the interdisciplinary team comprised of the pediatric dentist, the orthodontist, and the maxillofacial surgeon. The report encompasses a detailed description of the clinical and radiographic findings as clinical, surgical, and orthodontic interventions. The treatment of such cases requires long-term management, close cooperation of specialists, and proper dental age assessment.

With the Sendai Framework (2015-2030) and the Paris Agreement (2015), the UN has been promoting at a global level, the priority objectives to protect the life and well-being of people, these documents of global consensus have scheduled in several countries, an extensive list of actions of responsibilities and commitments to the environment, to address natural disasters among those of greatest impact earthquakes and floods and among earthquakes (seismic activity). The materialization of the disaster is a natural or human-induced event, it manifests itself in permanent changes in society and by its origin it is classified as natural, anthropogenic (anthropogenic) and mixed, creating a worldwide problematic situation of immediate reaction. The attention and alert in the scientific community have been adding efforts, but in a disorganized way, with limited human and material resources and with globalized strategies still to be improved. The literature review of disaster risk management due to seismic activity, from 2008 to 2023, allows us to have updated information to identify the factors and deepen them, with the understanding, comprehension, and multidisciplinary knowledge. The selected researches that mention the factors (elements) that influence risk management of natural disasters due to seismic activity (RMNDDSA) allow us to know the advances and spaces to approach them, which constitutes the motivation to study the twenty-four (24) factors present in this type of disasters. The selected research articles indicate important advances that associate disaster risk management (DRM) and communication technology (ICTs). The technological means mentioned are well received and accepted by society, capable of detecting and communicating in real time seismic activity worldwide, with the help of social mobile networks, technological platforms, Twitter, Facebook, and others.

Diabetes management requires constant monitoring and individualized adjustments. This study proposes a novel approach that leverages digital twins and Personal Health Knowledge Graphs (PHKGs) to revolutionize diabetes care. Our key contribution lies in developing a real-time, patient-centric digital twin framework built on PHKGs. This framework integrates data from diverse sources, adhering to HL7 standards and enabling seamless information access and exchange. PHKGs offer a flexible and efficient format that supports various applications. As new knowledge about the patient becomes available, the PHKG can be easily extended to incorporate it. This dynamic approach fosters continuous improvement and facilitates the development of new applications. As proof of concept, we have demonstrated the versatility of our digital twin by applying it to different use cases in diabetes management. These include predicting glucose levels, optimizing insulin dosage, providing personalized lifestyle recommendations, and visualizing health data. By enabling real-time, patient-specific care, this research paves the way for more precise and personalized healthcare interventions, potentially improving long-term diabetes management outcomes.

The integration of Artificial Intelligence (AI) in dairy farm management through biometric facial recognition for cows is a significant stride in livestock management. This review critically evaluates the evolution, applications, and challenges of AI-driven biometric facial recognition in dairy farming. It emphasizes the role of this technology in enhancing individual monitoring of dairy cows, providing accurate health, behavior, and productivity tracking. Originally derived from human facial recognition systems, this approach utilizes distinctive bovine facial features for essential, non-invasive, real-time monitoring in large-scale operations. The progression of AI from elementary pattern recognition to advanced Convolutional Neural Networks (CNNs) and deep learning models marks a shift toward data-driven farming. This study addresses key challenges such as environmental variability, data collection hurdles, ethical concerns, and technological limitations. It also contrasts various AI models, spotlighting their unique strengths and practical utility in dairy farming scenarios. Despite these challenges, facial recognition technology holds promise for improving farm efficiency, animal welfare, and sustainable practices, highlighting the need for continuous research and development. The review concludes by advocating for future research focused on environmental adaptability, ethical AI application, cross-breed compatibility, and integration with other farming technologies. Ultimately, it underscores AI's transformative potential in modernizing dairy farming towards a more data-oriented, responsible agricultural future.

The emergence of digital twins (DTs) represents a recent advancement in technological processes that support the planning, construction, and oversight of constructed assets. A DT is essentially a digital model that facilitates simulations and two-way information exchange with its real-world counterpart (a physical twin), creating opportunities for data-driven decision-making. Despite the promising prospects of DTs, both the technology and the methodologies for developing them, as well as their potential applications, remain not fully understood in both academic and industrial contexts. This research explores the applications of DTs for the management of existing assets within the AEC/FM industry. The study presents the results of a comprehensive literature review that explores existing knowledge in this domain. The findings reveal that procedures for creating DTs are still in their early stages, emphasizing potential applications in asset management throughout their lifespan, facilitating sustainability upgrades, and supporting the maintenance and restoration of heritage assets. The review concludes by providing recommendations for future research in this evolving field.

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

Buildings are subject to intrinsic and extrinsic failures at all stages of the construction process, i.e., design to occupancy (i.e., use) as several failure types can affect them. There are three basic steps for researching building failures: listing, cataloging, and solving/deciding whether highlighting the least invasive and lowest cost intervention. Therefore, this research presents some methods used in construction for the intervention prioritization and seeks to illustrate the most suitable methodology for different settings failure x diagnosis x intervention. Therefore, the most traditional tools are shown: BASICO, SWIFT, FEMEA, AAF, and GUT matrix, where a critical assessment of the strengths and weaknesses is carried out. After that, a case study on maintenance services for the moisture on the building facades was performed. Finally, the GUT matrix and the FMEA method are the best results

(1) Background: Bronchial artery embolization has been shown to be effective in the management of neoplastic hemoptysis. However, knowledge of pulmonary artery embolization is lacking. To evaluate safety and efficacy of pulmonary artery embolization in patients presenting with hemoptysis related to lung tumors. (2) Methods: This retrospective study reviewed all consecutive patients with cancer and at least one episode of hemoptysis that required pulmonary artery embolization from December 2008 to December 2020. The endpoints of the study were technical success, clinical success, recurrence of hemoptysis and complications. (3) Results: A total of 92 patients were treated with pulmonary artery embolization (63.1 years ± 9.9; 70 men). Most patients had stage III or IV advanced disease. Pulmonary artery embolization was technically successful in 82 (89%) patients and clinically successful in 77 (84%) patients. Recurrence occurred in 49% of patients. Infectious complications occurred in 15 patients (16%). The 30-days mortality rate was 31%. At 3 years, survival rate was 3.6%. Tumor size, tumor cavitation and necrosis and pulmonary artery pseudo-aneurysm were significantly associated with recurrence and higher mortality. (4) Conclusions: Pulmonary artery embolization is an effective treatment to initially control hemoptysis in patient with lung carcinoma but recurrence rate remains high and overall survival remains poor.

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.

Fungal pathogens pose a major threat to food production worldwide. Traditionally, chemical fungicides have been the primary means of controlling these pathogens, but many of these fungicides have recently come under increased scrutiny due to their negative effects on the health of humans, animals, and the environment. However, the use of fungicides with less of an environmental impact tends to result in the development of resistance in populations of phytopathogenic fungi. Therefore, new environmentally friendly alternatives that provide adequate levels of disease control are needed to replace chemical fungicides—if not completely, at least partially. A number of alternatives to conventional chemical fungicides have been developed, including plant defence elicitors (PDEs), biological control agents (fungi, bacteria and mycoviruses), biofungicides, RNA interference (RNAi) methods, and resistance breeding. This article reviews the conventional and alternative methods available to manage fungal pathogens, discusses their strengths and weaknesses, and identifies potential areas for future research.

The main aim of this study is to examine the effects of Total Quality Management (TQM) practices (leadership of management, decision making, continuous improvement, customer focus, employee involvement, process management and relations with suppliers) on the financial and operational performance of hospitals in service industry. The data of the study were collected by the questionnaire prepared in the light of published studies and the suggestions of medical and administrative staff. Medical and administrative staff were chosen as target participants that reflect perspectives of hospitals. 1069 questionnaires were answered in 6 private and 26 public hospitals in the Marmara region in Turkey. The results claim that “customer focus” affects both operational performance as well as the financial performance of hospitals more than other TQM practices. While “process management” and “customer focus” explain the variance of financial performance significantly. “Process management” does not explain variance of operational performance.

The paper addresses the ongoing and continuous interest in photovoltaic energy systems (PESs). In this context, the study focuses on an isolated photovoltaic system with hybrid bat-tery-supercapacitor storage (HBSS). The integration of supercapacitors (SCs) in this system is of particular importance because of their high specific power density. In photovoltaic (PV) systems, multi-storage systems use two or more energy storage technologies to enhance system perfor-mance and flexibility. When batteries and supercapacitors are combined in a PV system, their benefits are maximized and offer a more reliable, efficient, and cost-effective energy storage op-tion. In addition, effective multi-storage power management in a PV system needs a solid grasp of the energy storage technologies, load power demand profiles, and the whole system architecture. In this work, battery-supercapacitor storage system (HBSS) is established by combining batteries and supercapacitors. The primary objective is to devise a novel management algorithm that ef-fectively controls the different power sources. The algorithm's purpose is to regulate the charge and discharge cycles of the HBSS, ensuring that the state of charge (SOC) of both batteries and supercapacitors remains within the desired range. The proposed management algorithm is de-signed to be simple, efficient, and light on computational resources. It efficiently handles the energy flow within the HBSS, optimizing the usage of both batteries and supercapacitors based on real-time conditions and energy demands. By maintaining the SOC of these energy storage components within the specified limits, the proposed method ensures their longevity and max-imizes their performance. Simulation results obtained from applying the management strategy are found to be satisfactory. These results show that the proposed algorithm maintains the SOC of batteries and supercapacitors within the desired range, leading to improved energy management and enhanced system efficiency.

Wastewater management in Bogor, Indonesia, faces significant challenges to achieving a sustainable state. The growth of self-help settlements which are sporadic, unplanned, unorganized, and very dense, has an impact on the government's difficulties in providing sustainable wastewater management services. The research aims to examine fast-growing areas of self-help settlements, identify critical elements as a basis for strategy, and map the roles and influence of stakeholders in managing fast-growing areas in self-help settlements based on domestic wastewater management. This research uses a case study approach. Data were collected through observation, interviews, and focus group discussions. Data in this study were analyzed using Mactor software. The result showed knowledge and understanding of the correct management of domestic wastewater are the basis for achieving the actors' goals. In an implementation, social capital is needed to increase community participation by providing incentives that can affect the management of domestic wastewater, and it is necessary to increase the capacity of actors to assist the community in managing domestic wastewater. Ease of implementation at the community level must be based on community-based planning with government assistance so that the community itself carries out the decision on the type of domestic wastewater management by considering the advantages and disadvantages of each wastewater management system.

The purpose of this paper is to propose a tool to measure the performance of a Strategic Asset Management Plan (SAMP) based on a Balanced Scorecard (BSC). The SAMP converts organizational objectives into asset management objectives, also specifies the role of the asset management system and brings support to achieve asset management objectives. The SAMP becomes the heart of the organization and integrates with long-term, medium-term, and short-term financial plans integrated with same term activity plans. In the SAMP, the balance among performance, costs and risks is also taken into consideration in order to achieve the organization’s objectives. On the other side, the SAMP is a guide to set the asset management objectives while describing the role of the Asset Management System (AMS) in meeting those objectives. While SAMP is the central figure of AMS, it is important to measure its performance and needs to be build and improved through an iterative process, what means that is not just a document, it is “the document”, and should be treated as a “living being” that needs to adapt to internal and external changes quickly. The BSC is an excellent tool where, through the appropriate Key Performance Indicators (KPIs), the progress can be measured, and is supported by four perspectives: Financial; Customer; Internal Process; and Learning and Growth.

Profitability is an underestimated concept in precision agriculture. In this research, a new module is developed within a pre-existing farm management system to assess the profitability of precision agriculture applications in extended crops. The module is regulated on a 5-meter spatial resolution, thus allowing scaling up of original and processed data on a zone-, field-, cultivar-, and farm-scale. A bottom-up approach, taking advantage of the full functionality of the farm management system, together with a flexible architecture and an easy-to-use interface, renders the new module an innovative commercial application.

Owners and managers of small and medium-sized enterprises (SMEs) have changed their perspective on risk management due to the current global negative threats in the business environment. If they want to be successful and ensure the financial performance of their business, they must accept a proactive approach to reducing strategic risks in connection with operational risks. The aim of the article is to identify and quantify the differences in operational risk management and its effect on the financial management of SMEs between four Central European countries. The statistical sample of SMEs consisted of 1,090 owners and top managers. Data collection was carried out through a questionnaire in the period December 2022-January 2023. Statistical hypotheses were evaluated with the application of correlation analysis and linear regression modelling. Empirical findings have confirmed that operational risk management has a significant positive impact on improving the profitability of the enterprise; on reducing the enterprise's indebtedness as well as in the context of reducing the enterprise's inability to pay its obligations. However, there are disparities in the perception of this influence between owners/managers with regard to the country in which they carry out their business activities. The findings are important for both national and multinational organizations and entities dealing with risk management in the business environment of small and medium-sized enterprises.

Deep brain stimulation (DBS) is an effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric diseases, and has been consolidated as a first-line tool in the last two decades. Closed loop deep brain stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real-time. This paper presents a CLDBS with 2 stimulation channels and 2 acquisition channels. Each channel has a low-noise amplifier (LNA) buffer in differential configuration to eliminate the DC signal component of the input. Energy management is efficiently done by the control and communication unit. The battery supports almost 9 hours with both the acquisition and stimulation circuits active. If only the stimulation circuit is used as an Open Loop DBS (OLDBS), the battery can hold sufficient voltage for 24 hours of operation. The whole system is low-cost and portable and therefore it could be used as a wearable.

Common bean (Phaseolus vulgaris L.) is an important crop for food security and for national economics for several countries worlwide. One of the most important factors of risk in common bean production is the fungal disease anthracnose caused by Colletotrichum lindemuthianum, which in some cases, causes complete yield losses; this kind of plant disease is usually managed through the application of chemical products such as fungicides, that are commonly not accepted by society, this rejection is based on the relationship of pesticides with health damage and environmental contamination. In order to help in solving this drawbacks, the present work propose the use of Electrochemically Activated Salt Solutions(EASS) as a safer pathogen control agent in crops due to it have shown an elicitor and biostimulant effect on plants such as tobacco and apple. With this background, this manuscript presented in vitro results of the evaluation of the inhibitory effect for multiple bean pathogens and in vivo results of EASS in the common bean-Colletotrichum pathosystem by in vitro evaluations of the inhibitory effect for multiple bean pathogens and in vivo evaluation of the infection severity and defense activation such as secondary metabolites production and antioxidant activity. EASS presence in growth media had strong inhibitory effect, at beginning of experiment, for some of the evaluated fungi. EASS showed effect against the development of the disease when applied in specific doses to prevent distress in plants.

The effects of global warming combined with the progressive expansion of urbanization have considerably increased exposure to urban flooding and runoff widespread erosion risk, also causing shallow landslides and mud flows, respectively in urbanized areas of lowland and hill/foothill environments. Increasing urban flooding resilience has become a priority at virtually all levels of governance. The analysis of a different hazard scenarios, in which various hydro-meteorological conditions and management alternatives are examined, should act as the basis for the effective design and evaluation of interventions to improve urban flooding resilience. Turin Metropolitan Area (TMA), located in north-western Italy, represents a unique case due to its complex orography, with a mountainous sector in the west side and a flat or hilly part in the east side. During the warm season, these environmental conditions make the urban area prone to severe atmospheric convection causing frequent hailstorms and rainstorms of high intensity that may impact on urban infrastructures (i.e., drainage system and road network), thus requiring an adequate management as a key factor to reducing risk and losses. The urban areas of TMA are monitored by polarimetric Doppler weather radars and by a dense rain gauges network. Analyzing several case studies of urban flooding, this research work assesses the feasibility of a meteorological radar early warning system based on the identification of rainfall thresholds that characterize urban flooding, occurring in the lowlands, and the runoff erosion phenomena affecting the urbanized hills and foothills.

Tetranychid outbreaks have been detected since 2016 in southern highbush blueberries (SHB); however, it was not until 2019 when the southern red mite (SRM), Oligonychus ilicis (Acari: Tetranychidae) was confirmed as the pest causing severe bronzing and stunting, in multiple Florida and Georgia commercial blueberry plantings. There is little known about the management of SRM in SHB and only three miticides (fenazaquin, fenpyroximate, and acequinocyl), have recently been registered for use in SHB between 2019 and 2020. Similarly, there is no knowledge regarding the existence of natural enemies of SRM in SHB. This is the first report of naturally occurring predatory mites (Amblyseius sp. and Neoseiulus ilicis) associated with SRM in SHB. Predatory mites were recorded in treated bushes after evaluating the performance of seven miticides used to manage SRM populations including spiromesifen, acequinocyl, sulfur, sulfur + molasses, bifenazate, fenpyroximate, and fenazaquin. Miticide efficacy was rated based on the number of SRM recorded on collected leaves and plant damage ratings using an arbitrary index (from 0= no bronzing to 4= 100% bronzing). Additionally, the presence or absence of predatory mites per sample was recorded. Fenpyroximate used as the standard miticide, significantly reduced mite numbers seven days after application, as well as acequinocyl and fenazaquin. Only plants treated with fenpyroximate or fenazaquin showed significantly less bronzing compared with the control plants. Overall, fenpyroximate and fenazaquin demonstrated the best performance for managing O. ilicis on SHB and safe to naturally occurring predatory mites. Lastly, the level of growers’ awareness regarding SRM was assessed using surveys in 2020 to design adequate educational materials available to the grower community.

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.

Sustainability is essential for every business and organization, but how can it be achieved? This work is a study of sustainability based on the sufficiency economy philosophy, a valuable concept introduced by the Thai people. We apply it to the notion of sustainability in 400 agricultural community enterprise owners in Thailand, who participated in the study. An oblique rotation component analysis was performed, finding that the variables on the same side are related, and a confirmative component analysis with structural equation models was conducted. The results showed that the approach to applying the sufficiency economy philosophy among community enterprises consists of 11 components, as follows: 1) financial control, 2) planning, 3) member management, 4) morals, 5) prevention plan, 6) moderation, 7) knowledge and expertise, 8) market development, 9) care, 10) quality control and 11) value of investment. The confirmative component analysis with structural equation modeling was consistent with the empirical data. Agricultural community enterprises and entrepreneurs focus on the moral component, conduct business with honesty and avoid causing problems for others, value justice without taking advantage with diligence and adhere to moral principles in life, because all of the above will lead to sustainability in the future.

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 compelling effects of climate change on forests may have been underestimated in the past few decades in practical forestry. Although the first attempts to draw attention to this complex problem appeared almost half a century ago, the debate has been conceptual rather than experimental and applicative. At first glance, the con-cerns were mainly related to sustainable forest management (SFM) issues, which obviously needed attention. Over time, the effects of climate change have been mainly considered in the context of the SFM; they started from various and somewhat different scales and goals. Over time, more research and awareness of the im-portance of SFM under the pressure of climate change have led to the development of a clearer field that can be defined as ‘adaptive forest management’ - to climate change. One of the characteristics of this discipline is to be featured by the absence of univocal methods and / or objectives to be pursued but to identify, verify, and adapt methods to the various climatic and forest types and conditions found in the field. Therefore, this work shows some phases of forest planning and management concepts and criteria over time and recalls some innovative and / or adaptive methods related to the approach to forest planning and management under climate change

The wracks of Posidonia oceanica leaves on the sandy beaches of Calabrian region could be one of the most important defence against erosion processes. The management of Posidonia oceanica leaf litter in Italy has been realized through the mechanical removal and the transport in dumping areas of the beach-cast material. This solution, apparently simple and fast, produces a net loss of sediments from the sandy beaches and, therefore, a deficit in the sedimentary budget of coastline leading the coastal system to possible shore erosions. Instead, it could be better to keep these vegetable deposits on the place so to warrant a positive sedimentary budget and the tourist value of the regional beaches improving coastal tourism in the seaside resorts with bathing vocation.

Electronic Health Record (EHR) is being used in most healthcare institutions to preserve and share health records instead of a paper-based method. Data records must be exchanged amongst various parties and users' privileges to manage access to their records should also be provided. In addition to the basic standards of secrecy, confidentiality and integrity of information, these facts further demonstrate the need for interoperability and consumer control to access their personal data. Electronic Health Record (EHR) system faces issues of protection of data, trust and management issues. In recent Covid-19 pandemic, various applications, tools and websites were launched that stores records. Also, many personal records related to health need to be shared among different parties for early detection, contact tracing, monitoring and the future prediction that requires accurate and reliable data. Simultaneously, the citizens will be hesitant in providing their personal details due to privacy concerns and social stigma. Blockchain technology has arisen as a powerful technology that can offer the immutability, confidentiality and user access properties of stored information and provided distributed storage. This paper analyses the blockchain suitability in EHR and its further applications in efficient Covid-19 pandemic management.

Forest ecosystems are important providers of ecosystem functions and services belonging to four categories: supporting, provisioning, regulating, and cultural ecosystem services. Forest management, generally focused on timber production, has consequences on the ability of the system to keep providing services. Silviculture, in fact, may affect ecological structures and processes from which services arise. In particular, the removal of biomass causes a radical change in the stocks and flows of energy characterizing the system. Aiming at the assessment of differences in stored natural capital and ecosystem functions and services provision, three differently managed temperate forests of common beech (Fagus sylvatica) were considered: (1) a forest in semi-natural condition, (2) a forest carefully managed to get timber in a sustainable way and (3) a forest exploited without management. Natural capital and ecosystem functions and services are here accounted in biophysical terms. Specifically, all the resources used up to create the biomass (stock) and maintain the production (flow) of the different components of the forest system were calculated. Both stored emergy and empower decrease at increasing human pressure on the forest, resulting in a loss of natural capital and a diminished ability of the natural system to contribute to human well-being in terms of ecosystem services provision.

Statistical management policy and system plays significant role in development of any nation as it guides the planner to analyze the gaps, design programs and allocate budget in efficient manner. Globally, design and usage of statistical management system varies relying on country specific ability and resources availability. Government of Nepal has been managing database in individual as well as thematic manner. Policy wise, thematic database is in operation based on Statistics Act 1958 and individual database is in operation based on Birth, Death and Other Personal Related Events Registration Act 1976. Though civil registration related policies have been either updated or newly formed, sectoral statistic management related policy has not been updated since its first promulgation period (1958). With no policy supporting the consolidated statistical management system, government as well as non-government agencies has been investing millions of dollars annually to collect, compile and analyze individual related data and fulfill their respective objectives. It has forced the government services and performance to be paper-based, time-consuming and tedious thus creating dis-trust among citizen each passing day. Though, formulation of legal instrument promoted digital movement and mandated shift towards e-government modality, the process has been low. Theoretically, Technology Acceptance Model (TAM) state the need of having advanced and efficient technology to be in place in current setting to improve governance, efficiency, accountability, transparency and trust. Also, the same theory state the requirement of strong willingness and motivation from the users (government, non-government and citizen) to adopt the technology based policy and system. As the integrated statistical management policy emphasizes on technology-based system or digital system, the perspectives of Technology Acceptance Model also termed as Information System Theory aid in understanding the context, conceptualizing and addressing the needs with an establishment and implementation of digital system or technology based system. This policy paper applied the Technology Acceptance Model (TAP) to examine the underlying opportunities and challenges associated with an integrated statistical management policy. With existing gaps in existing policy, system and practice alongside an overview of opportunities and challenges, this paper recommends the need of stand-alone integrated statistical management policy to consolidate sectoral as well as civil related information through single system based on recommended policy.

Proper management of solar energy, as an effective renewable source, is of high importance toward sustainable energy harvesting. This paper offers a novel sophisticated method for predicting solar irradiance (SIr) from environmental conditions. To this end, an efficient metaheuristic technique, namely electromagnetic field optimization (EFO) is employed for optimizing a neural network. This algorithm quickly mines a publicly available dataset for non-linearly tuning the network parameters. To suggest an optimal configuration, five influential parameters of the EFO (i.e., N_Pop, R_rate, Ps_rate, P_field, and N_field) are optimized by an extensive trial and error practice. Analyzing the results showed that the proposed model can learn the SIr pattern and predict it for unseen conditions with high accuracy. Furthermore, it provided about 10% and 16% higher accuracy compared to two benchmark optimizers, namely shuffled complex evolution and shuffled frog leaping algorithm. Hence, the EFO-supervised neural network can be a promising tool for the early prediction of SIr in practice. The findings of this research may shed light on the use of advanced intelligent models for efficient energy development.

The objective of this study is to identify how demographic characteristics (gender, age, seniority at work, and educational level) are related to the entrepreneurial behavior of companies. To comply with the above, a quantitative, transversal, and non-experimental research was carried out, which consisted in applying an instrument to 262 managers of Small and Medium Enterprises (SMEs) in a northern city in Mexico. The collected information was analyzed in the software SPSS, version 26 with statistical testing by the Mann-Whitney and Kruskal-Wallis. The main findings dermore highly educated managers are those who contribute to this behavior of the studied companies, while gender and seniority at work are not differentiating elements in relation to the above. This research generates different possibilities of studies to be carried out in large companies from other sectors, as well as to include behavioral characteristics as study variables.

Due to the tremendous progress in the automotive industry, the growth of the urban population, the number of vehicles is increasing and this creates parking challenges. Intelligent parking management systems offer an optimal solution for finding empty parking space so that drivers can quickly find their car parking space. To solve these problems, it is necessary to design an intelligent parking system, in addition to providing comfort to drivers, which is also economically viable. This paper proposes an intelligent multi-storey car parking system with the help of RFID technology and examining user preferences that can effectively solve car parking problems. The proposed method is a multi-objective decision-making method to reduce the problem of car parking, which is called MODM-RPCP. Therefore, the proposed MODM-RPCP method can allocate the best space for their stopping place by using the decision-making system and based on the priorities considered by the users. The simulation results show that the MODM-RPCP reduces the average booking time more than 19.2% and 27.1%, and decreases the response time of central parking management server more than 20.1% and 29.78% compared to MOGWOLA and ODPP approaches.

This paper discusses devastating urban floods in the year 2019 that caused human and socioeconomic losses in many countries, including Iran. The main question addressed by this paper is the choice between two flood management models, namely, the optimal and nature-based flood management or the existing hazardous situation that damage the ecosystem and natural resources. The analysis of this paper will find the main responsible factors in the mentioned floods in Iran. For this reason, it examines the impacts of the existing flood management that neglects the ecosystems, environmental components, and nature. The method of this research includes theoretical studies, case studies with the help of structured interviews, and observations. A benchmarking technique compares the two alternatives. The comparisons use seven indicators abstracted from successful global experiences and local knowledge. Finally, this research presents a model for optimal flood management that is applicable everywhere in the world.