Literature circles create an interactive and participatory learning atmosphere that greatly increases student participation in the classroom. Through literature circles, students can exchange ideas and gain knowledge from one another in a nurturing learning atmosphere. Students feel more at ease taking chances and voicing their opinions in the classroom when there is a strong sense of community among the students. This research study used a narrative literature review as a qualitative method. Relevant literature in this review showed that literature circles can increase students' reading passion and enthusiasm. Students are more likely to be engaged when they can select their own reading materials and facilitate discussions. Thus, by implementing literature circles, teachers may create a more engaging and encouraging learning environment in the classroom, which will ultimately improve student performance and foster a deeper understanding of literature.

Many businesses, including finance, want to both understand and utilize blockchain technology. However, there is no detailed systematic literature review (SLR) analyzing blockchain technology in finance in order to understand it. This study emphasizes in detail the possible applications of blockchain in finance, its technical features, benefits and challenges. According to the literature review, blockchain technology has the potential to improve the efficiency of the financial sector, reduce costs and increase transparency and security. Regulatory constraints as well as concerns over scalability and interoperability are barriers that need to be resolved. In order to fully understand the potential of blockchain technology, this SLR explores the current state of research on blockchain in finance. In addition to analyzing the technical features of blockchain, the study also details its current and potential application areas, benefits and challenges. This research analyses the use of blockchain in finance in view of its infrastructure, technology, benefits and challenges for further research and application areas. In the study, 54 articles were evaluated and 34 of them were used for SLR questions. The usage of blockchain in finance is examined from a variety of aspects in this SLR. The study provides answers to nine questions about its application areas, benefits, infrastructure, technology, consensus methods, permission types, and challenges. In some cases, it also gives the correlation relationship between the answers.

Security patterns encompass security-related issues in secure software system development and operations that often appear in certain contexts. Since the late 1990s about 500 security patterns have been proposed. Although the technical components are well investigated, the direction, overall picture, and barriers to implementation are not. Here, a systematic literature review of 240 papers is used to devise a taxonomy for security pattern research. Our taxonomy and the survey results should improve communications among practitioners and researchers, standardize the terminology, and increase the effectiveness of security patterns.

Anonymous communications networks were born to protect the privacy of our communications, preventing censorship and traffic analysis. The most famous anonymous communication network is Tor. This anonymous communication network provides some interesting features, among them, we can mention user’s IP location or Tor Hidden Services (THS) as a mechanism to conceal the location of servers, mainly, web servers. THS is an important research field in Tor. However, there is a lack of reviews that sump up main findings and research challenges. In this article we present a systematic literature review that aims to offer a comprehensive view on the research made on Tor Hidden services presenting the state of the art and the different research challenges to be addressed. This review has been developed from a selection of 57 articles and present main findings and advances regarding Tor Hidden Services, limitations found, and future issues to be investigated.

Drive tourism (DT) have become an attractive way of tourist destination for an increasing number of visitors along driving routes. This flow of visitors has made sustainability a major issue that is, the way by which tourism development ensure economic benefits for local communities and preserves local identity, along the route, without compromising the environmental resources. Many studies focused the topic of DT, mainly the analysis of a particular angle, either be economic sustainability, e.g., advantages of the ones related to economic and environment sustainability [e.g., 2,4,5,10], such as the impact of tourists along the route environment. Nevertheless, little attention has been paid to the social consequences of DT in the local entrepreneurial environment and ensuing over enhancing of their cultural representativeness in terms of authenticity. Our aim is to summon these points of view and achieve, through a systematic literature review, a clear and integrative picture of the driving tourism impacts in terms of sustainability along the routes throughout local communities. A systematic literature review was performed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. This systematic literature review sought to consolidate knowledge on the subject. In order to illustrate the link between major categories and their corresponding trends, authors used VOSviewer scientific software. The gathering of existing knowledge around the three components of sustainability highlighted the importance of community involvement and collaboration among DT stakeholders to ensure a trade-off between the protection and promotion of DT routes. Opportunities for future studies are suggested.

In recent years, increasing attention has been paid to individuals organizing themselves and managing food systems in an ‘alternative’ and more sustainable way. Such emerging food initiatives are most commonly known as ‘Alternative Food Networks’ (AFNs). However, there is an ongoing debate concerning the extent to which AFNs facilitate social, economic and environmental change. There are criticisms of the overall sustainability promise of AFNs related to sufficiency of impact, possible counter effects and relevance of impacts. Because often empirical studies only focus on specific sustainability issues or AFNs, it has been difficult to develop more robust theories about the relations between diverse AFNs arrangements and sustainability. Thus, the aim of this paper is to contribute towards reducing this knowledge gap through a systematic literature review on AFNs in relation to sustainability. We summarize main methodological approaches, types of AFNs studied and sustainability dimensions addressed in literature to date. Findings serve as reference to propose opportunities for future research regarding sustainability in AFNs.

Land-use planning review seems relatively lower in publication rate and in coverage of content. This review contributes its part in two dimensions. First, it assesses ability of the popularly growing bibliometric method in tracking the real contribution of publications. Then it summarizes developments in the land use planning literature in three themes - general literature path building, land use planning context, and development of methods. It is observed that bibliometric method rewards information carriage paper more than the original contributors. Key planning context gaps include detachment of the general goal-oriented objective formulations from the basic land use allocation theories and models and certain urban land use optimization objectives even contradict the original though of sustainable city. Key research frontiers include: linking basic land use allocation and utility theories in urban land use planning; shifting the current urban land use planning from spatial optimization to activities into optimizing flow resources to available spatial configurations; evaluating existing built environment for optimality; transferring knowledge from rural land-use planning to urban land use planning. In method development, the key frontier would be advancing the current loosely coupled methods into more integrated systems.

Cultural tourism in Tanzania presents a diverse tapestry of traditions, varied ethnic groups, and historical accounts. This article aims to pinpoint areas for further exploration in the cultural tourism sector of Tanzania and analyze their potential impacts. The study conducted a systematic review of the literature following established inclusion criteria as well as the Preferred Reporting Items for Systematic Reviews and meta-analysis guidelines. A total of 21 articles focused on Tanzania Cultural Heritage Tourism from sources such as Google Scholar and web databases were examined, revealing several research gaps, including theoretical, contextual and methodological aspects. Furthermore, the research offers insights into theoretical implications and recommends avenues for future studies that could advance the field by addressing these knowledge gaps providing valuable direction to new researchers interested in exploring these specific areas as well as practitioners seeking a comprehensive understanding of various aspects related to Tanzania's cultural heritage tourism

Copernicus is Europe's space-based Earth monitoring asset, which consists of a complex set of systems that collect data from different sources: remote sensing satellites (RS) and in-situ sensors such as ground stations, airborne and marine sensors. This study was originally prepared for the needs of the Czech agricultural community, where we provided an in-depth analysis of articles related to Earth observation in precision agriculture. At a later stage, we extended this study by comparing the recommendations of the European EO4Agri project and scientific articles published in MDPI. We had two important objectives, one was to validate the results of the EO4Agri project and the other was to look for gaps in current research and community needs. To recognize the importance of using Sentinel 1 data, we also added a specific analysis of methods for data fusion of Sentinel 1 and Sentinel 2 data.

The paper's objectives are to identify the main benefits, limitations, and challenges facing using Blockchain technology in the Supply Chain Management (SCM). To explore the factors that affect the adoption and application of Blockchain technology in SCM. The study uses a systematic literature review methodology to analyze and compare selected related articles published between 2016 and 2022 on the usage of Blockchain technology in the SCM. Several studies showed that there are many benefits to using Blockchain technology in SCM such as enhanced security, confidentiality, traceability, transparency, data accuracy, privacy, efficiency, accountability, and trust. At the same time, there are many limitations and challenges like scalability, interoperability, legal (regulatory) issues, high implementation and maintenance costs, standardization and information, lack of trust in technology, high energy consumption, limited awareness, integration with current systems, and privacy. Blockchain technology has the potential to revolutionize various industries, but there are still several issues that need to be addressed to fully realize its potential. Understanding the benefits and difficulties of applying Blockchain technology in different industries, including the SCM, is essential in determining its effectiveness and the different strategies needed to assess its application and implementation.

This paper aims to provide a systematic review of the literature on school effectiveness, with a focus on identifying the main factors that contribute to successful educational outcomes. The research question that this paper aims to address is: What are the main factors of school effectiveness? The research was interested in several descriptors such as school, effectiveness/efficiency theories, effectiveness/efficiency research, and factors. Studies were reviewed through two databases: JSTOR and ERIC (published within the 2016-2022 period). The paper defines several categories that are exposed within school effectiveness research. Within these categories, various factors that affect the students’ outcomes and the defined effectiveness at school are listed. As the results show, the issue of school effectiveness is a multifaced challenge as the effectiveness of schools is a complex concept that can be measured through various indicators such as academic achievement, student engagement and teacher satisfaction. The review of school effectiveness has revealed that several factors contribute to effective schools, such as strong leadership, effective teaching practices, a positive school culture and parental involvement. Additionally, school resources, such as funding and facilities, can impact school effectiveness, particularly in under-resourced communities.

In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use AI and ML to assess credit risk, analyzing large volumes of information. We posed research questions about algorithms, metrics, results, data sets, variables, and related limitations in predicting credit risk. We searched renowned databases to answer them and identified 52 relevant studies with the credit industry microfinance. Challenges and approaches in credit risk prediction using ML models we identified, difficulties with the implemented models such as the black box model, the need for explanatory artificial intelligence, the importance of selecting relevant features, addressing multicollinearity, and the problem of the imbalance in the input data. By answering the questions, we identified that the Boosted Category is the most researched family of ML models; the most commonly used metrics for evaluation are Area Under Curve (AUC), Accuracy (ACC), Recall, precision measure F1 (F1), and Precision; Research mainly uses public data sets to compare models, and private ones to generate new knowledge when applied to the real world. The most significant limitation identified is the representativeness of reality, and the variables primarily used in the microcredit industry are related data to the demographic, the operation, and payment behavior. This study aims to guide the developers of credit risk management tools and software towards the existing offer of ML methods, metrics, and techniques used to forecast it, thereby minimizing possible losses due to default and guiding risk appetite.

Distance learning has assumed a relevant role in the Educational scenario. The use of Virtual Learning Environments contributes to obtain a substantial amount of educational data. In this sense, the analyzed data generate knowledge used by institutions to assist managers and professors in strategic planning and teaching. The discovery of students’ behaviors enables a wide variety of intelligent services for assisting in the learning process. This article presents a literature review in order to identify the intelligent services applied in distance learning. The research covers the period from January 2010 to May 2021. The initial search found 1,316 articles, among which 51 were selected for further studies. Considering the selected articles, 33% (17/51) focus on learning systems, 35% (18/51) propose recommendation systems, 26% (13/51) approach predictive systems or models, and 6% (3/51) use assessment tools. This review allowed to observe that the principal services offered are recommendation systems and learning systems. In these services, the analysis of student profiles stands out to identify patterns of behavior, detect low performance and identify probabilities of dropouts from courses.

This study aims to understand the contents of debriefing performance in simulation education and its results by comprehensively examining the learning performance of the education ac-cording to the difference in the debriefing methods employed in domestic and overseas nursing simulation training. This is a literature review conducted to identify the effect of debriefing of simulation nursing practice education. The existing literature was found in electronic databases using Pubmed, Embase, MEDLINE complete, PsycINFO, Web of Science, CINAHL, the Cochrane Library, KoreaMed, National Discovery for Science Leaders, and Research Information Sharing Service and the key words were “nurse,” “nursing student,” “simulation,” “simulator,” “stand-ardized patient,” “debriefing.” Finally, 32 studies were analyzed. All the studies were conducted from 2012 to 2021. A total of 11 RCT, 17 quasi-experimental studies, 3 mixed method studies and 1 pilot study were identified. The debriefing process used media, structured questionnaires, and a method of teaching or peer-led debriefing. The outcome variables that were statistically significant were skill, performance, knowledge, problem-solving competency, critical thinking disposition, clinical judgement, self-confidence, satisfaction, and debriefing quality evaluation. It is necessary to educate the debriefers who are responsible for strategy development and meeting effective debriefing goals.

The Industry 4.0 represents new era of production, characterized by a deep integration between digital technologies and physical systems. Cyber physical systems, cyber resilience protection and workers' safety are key elements of this transformation. To ensure the benefits of Industry 4.0 realized in a secure way, it is crucial to focus on workers' safety, cyber resilience protection and human-centric and CPS systems security and privacy. However, to fully realize the potential of Industry 4.0, it is important to address these challenges and ensure that the benefits of digitalization are balanced with the needs of workers and the protection of critical infrastructure. The concept of Industry 5.0 is emerging as the next step in this evolution, emphasizing the importance of sustainability, human-centered design, and a focus on creating a better future for all.

External audit reliance issues on the internal audit function (IAF) are increasingly important in financial auditing, yet its application in audit engagements lags behind other applications. Despite the belief that audit reliance will shape auditing in the future, limited and intervalley publications explore this transformative potential. This paper investigates the increasing importance of external audit reliance issues in financial auditing. It investigates the use of the IAF in external audit reliance decisions and its potential to enhance audit quality, process transparency, and stakeholders' credibility. Through a systematic literature review of 68 scientific articles from 1984 to 2022, factors influencing external auditors' dependence on the IAF are analyzed, including IAF work quality, assistance type, organizational factors, customer pressure, and business risk. The review highlights the IAF's crucial role in improving financial reporting integrity and external audit effectiveness. However, the challenges that allowed external auditors to decide whether to rely on the works of IAF like limited disclosures and accessible data hinder assessing IAF reliance effects, leading to information asymmetry that may impact stakeholder confidence. The paper discusses implications, limitations, and future research directions to explore technology adoption and optimize audit practices, promoting transparency in the audit process.

The videofluorographic study is indicated for diseases potentially causing dysphagia and aspiration, such as gastrointestinal reflux disease, cancers of the oropharynx and esophagus, and certain neurologic diseases needing swallowing assessment. The study is designed to survey the anatomy and physiology of swallowing to diagnose any swallowing impairment and is standardized using scales such as the Modified Barium Swallow Impairment Profile (MBSImP). The procedure requires the patient to swallow a barium contrasted bolus which helps to visualize and obtain a real-time result. There are certain complications of the procedure including radiation exposure which requires necessary safety protocols to be followed.

Agricultural Big Data is a set of technologies that allows responding to the challenges of the new data era. In conjunction with machine learning, farmers can use data to address different problems such as farmers' decision-making, crops, weeds, animal research, land, food availability and security, weather, and climate change. The purpose of this paper is to synthesize the evidence regarding the challenges involved in implementing machine learning in Agricultural Big Data. We conducted a Systematic Literature Review applying the PRISMA protocol. This review includes 30 papers, published from 2015 to 2020. We develop a framework that summarizes the main challenges encountered, the use of machine learning techniques, as well as the main technologies used. A major challenge is the design of Agricultural Big Data architectures, due to the need to modify the set of technologies adapting the machine learning techniques, as the volume of data increases.

The runtime environment is an important concern for self-adaptive systems (SASs). Although researchers have proposed many approaches for developing SASs that address the issue of uncertain runtime environments, the understanding of these environments varies depending on the objectives, perspectives, and assumptions of the research. Thus, the current understanding of the environment in SAS development is ambiguous and abstract. To make this understanding more concrete, we describe the landscape in this area through a systematic literature review (SLR). We examined 128 primary studies and 14 unique environment models. We investigated concepts of the environment depicted in the primary studies and the proposed environment models based on their ability to aid in understanding. This illustrates the characteristics of the SAS environment, the associated emerging environmental uncertainties, and what is expressed in the existing environment models. This paper makes explicit the implicit understanding about the environment made by the SAS research community and organizes and visualizes them.

The growing global interest in Circular Economy (CE) adoption by organizations has received considerable attention in academic literature. This review delves into the multifaceted aspects of CE transformation, assessing barriers, drivers, and potential research directions. It encompasses three main clusters: frameworks and definitions, barriers and drivers, and industry-specific research. Existing studies significantly contribute by unveiling strategies, frameworks, and innovative ap-proaches aiding CE transition. However, there's a notable focus on identifying barriers hindering CE implementation, revealing a critical need for effective solutions. Moreover, the review highlights the lack of CE frameworks in the service sector and insufficient awareness among Small and Me-dium Enterprises, necessitating deeper exploration. Despite the potential of digital technologies like Industry 4.0 in expediting CE transformation, comprehensive implementation strategies remain lacking. Noteworthy frameworks, such as circular business models and two-stage transformation models, offer practical pathways for CE adoption. Dynamic capabilities emerge as a crucial yet underexplored factor facilitating CE transition. Future research should delve into country-specific contexts, integrate digital technologies into industries, and explore the relationship between dy-namic capabilities and CE transformation, especially within small and medium-sized enterprises. While progress has been made in understanding CE principles' adoption, this review highlights research gaps that require attention for global sustainability and widespread CE practice imple-mentation.

The interest in spatial analysis has been growing in recent years, mainly due to communication technology advance, economic globalization, and the development of new statistical and econometric methods. The main aim of this article is to contribute to the dissemination of spatial econometric applications by presenting some basic theoretical aspects and a literature review of articles that address the socio-economic drivers that lead to environmental pollution. Three spatial regression models are reviewed here: the spatial lag model (SLM), the spatial error model (SEM), and the spatial Durbin model (SDM). A literature search was conducted using specific terms of interest in eight databases, from 1996 to February 2021, where 22 articles were considered for analysis. The results showed that most articles studied environmental problems in China. The most used exploratory spatial analysis model was Moran Index and the most used explanatory spatial analysis models were SDM and SLM.

Increasing the metacognitive abilities of chemistry students is an indisputable output of the teaching and learning process today. Collaborative problem based learning is a learning method that has been tested and proven to be applied, especially in Western countries in increasing the metacognitive abilities of students, but it is still very minimal applied in Asian countries, including Indonesia. Thus, this study was conducted to explore previous studies that examined collaborative problem-based learning in improving students' metacognitive abilities. The research design used in this study is a Systematic Literature Review with the requirements of the inclusion of articles on collaborative problem-based learning in improving the metacognitive abilities of chemistry students, accredited national and international publications between 2010 and 2020, full text, journal articles, and open access. The results of the exploration that were carried out found 102 articles, then the title and abstract were read into 20 articles, and 4 articles were read in full, which fulfilled all the stipulated inclusion requirements. The results of the systematic literature review conducted in this study provide empirical evidence of literacy that problem based learning improves the metacognitive abilities of chemistry students. However, most of research conducted still uses various instruments, which are not standardized and validated.

The shipbreaking industry is located predominantly in South Asian countries, and dismantles end-of-life ships to meet national steel demand. There are charges that this industry exploits local environmental, economic and social conditions to boost profits. The majority of this previous research often draws from a single disciplinary point of view that ignores or downplays complexities and trade-offs, precluding realistic policy improvement. Here we review 110 shipbreaking papers published in international peer reviewed journals that are indexed in SCOPUS, Science Direct and Google Scholar. We found that to date, shipbreaking research revolves around the coastal contamination of end-of-life ships waste over many other topics, and lacks critical interdisciplinary studies that explain trade-offs between environmental, social and economic factors that would better inform policy formulations for improvement of worker safety and environmental conditions. We propose a Life Cycle Sustainability assessment (LCSA) framework that could incorporate these trade-offs in a single analysis. We hope this review guides future studies towards more comprehensive sustainability measurement of shipbreaking activities.

This systematic literature review meticulously explores the complexities of technological innovation and entrepreneurship, with a particular focus on the strategies and management practices involved in new product development from an interdisciplinary standpoint. By conducting an extensive analysis of 323 key articles from 11 top-tier journals published between 2020 and 2023, the review delineates the current research trajectories within these fields, underscoring significant scholarly interest and development. The study particularly emphasizes the emergence of artificial intelligence-generated content technology since 2022 and critically assesses its influence on innovation processes and product development practices among both nascent entrepreneurs and well-established corporations. This emergent technology's role in shaping the competitive landscape and its potential to drive significant shifts in market dynamics are thoroughly examined.

Climate change is currently one of the main problems facing agriculture to achieve sustainability. It causes situations such as drought, increased rainfall, and increased diseases, causing a decrease in food production. In order to combat these problems, Agricultural Big Data contributes with tools that allow improving the understanding of complex, multivariate, and unpredictable agricultural ecosystems through the collection, storage, processing, and analysis of vast amounts of data from diverse heterogeneous sources. This research aims to discuss the advancement of technologies used in Agricultural Big Data architectures in the context of climate change. The study aims to highlight the tools used to process, analyze, and visualize the data and discuss the use of the architectures in the crop, water, climate, and soil management, especially to analyze the context, whether it is in Resilience Mitigation or Adaptation. The PRISMA protocol guided the study, finding 33 relevant papers. Despite the advances in this line of research, few papers were found that mention the components of the architectures, in addition to the lack of standards and the use of reference architectures, which allow the proper development of Agricultural Big Data in the context of climate change.

The ability to decode words accurately at an early age strongly predicts reading competence later on. Decoding-challenged children may find it difficult to understand texts, which might impede their overall academic development. Strong word decoding skills accelerate the process of learning vocabulary and grammar rules in a variety of languages. The paper aimed to collect relevant literature regarding word decoding ability in the world of the language acquisition process. Policymakers and educators will be greatly impacted by realizing how crucial word decoding is to language learning. Providing targeted interventions for struggling readers, encouraging a positive reading culture, and explicitly teaching phonological and orthographic abilities are all essential components of effective reading education. Promoting decoding proficiency also requires making sure that people have access to excellent reading materials and tools. In order to enable learners to become great readers and communicators across linguistic and cultural boundaries, educators and policymakers should prioritize phonemic awareness from an early age and use effective teaching methodologies.

Matters relating to preservation of environmental resources and climate change, social inclusion and diversity, and open and sound governance have rapidly gained global attention. However, little is known about the construction industry in meeting the environmental, social and governance (ESG) criteria towards sustainable development. In this study, the purpose is to identify the key ESG indicators for construction development. A systematic literature review was undertaken using data from Scopus, PubMed, Google Scholar, JSTOR, ProQuest, and Web of Science. The results show some of the key ESG indicators as climate resilience and green construction activities (at the project level), and active stakeholder engagement and effective project governance (at the firm level) and meeting environmental and social regulation requirements (industry/national level). The limitation of the article is in the sample size of twenty-six journal articles with future expectation of increment as ESG gain more acceptance in the construction industry. This study will be significant for the design of practice framework and policies on ESG in the construction industry. Comprehensively, this study presents relevant ESG indicators for construction management and presents essential information for future research.

Background: In the functional data analysis (FDA), the hybrid or mixed data are scalar and functional datasets. The semi-functional partial linear regression model (SFPLR) is one of the first semiparametric models for the scalar response with hybrid covariates. Various extensions of this model are explored and summarized. Methods: Two first research articles, including “semi-functional partial linear regression model”, and “Partial functional linear regression” have more than 300 citations in Google Scholar. Finally, only 106 articles remained according to the inclusion and exclusion criteria such as 1) including the published articles in the ISI journals and excluding 2) non-English and 3) preprints, slides, and conference papers. We use the PRISMA standard for systematic review. Results: The articles are categorized into the following main topics: estimation procedures, confidence regions, time series, and panel data, Bayesian, spatial, robust, testing, quantile regression, varying Coefficient Models, Variable Selection, Single-index model, Measurement error, Multiple Functions, Missing values, Rank Method and Others. There are different applications and datasets such as the Tecator dataset, air quality, electricity consumption, and Neuroimaging, among others. Conclusions: SFPLR is one of the most famous regression modeling methods for hybrid data that has a lot of extensions among other models.

In the dynamic landscape of the telecommunications industry, understanding and mitigating customer churn is paramount for maintaining competitive advantage and sustaining revenue streams. This comprehensive literature review delves into the intricacies of customer churn prediction, a crucial aspect in fortifying the bond between telecom businesses and their customers. The review methodically analyzes 11 articles published between 2000 and March 2024, spotlighting the strategic role of Customer Relationship Management and the prevalence of high churn rates that necessitate a shift from customer acquisition to retention strategies. Furthermore, the review navigates through the challenges inherent in churn prediction, including the complexities of managing large, imbalanced, and noisy datasets and the intricacies involved in model selection and optimization. Despite these challenges, the paper highlights the superior capability of machine learning techniques in handling complex datasets to provide accurate predictions, albeit acknowledging their practical complexities. The main aim of the study is to provide an overview, serving as a knowledge base for researchers interested in machine learning techniques within the realm of telecommunications.

Indonesia has emerged as one of the leading producers and exporters of palm oil, as supported by data from the Central Bureau of Statistics in 2021, which indicate that Indonesian palm oil exports reached an impressive value of US$ 18.44 billion, or IDR 258 trillion, in 2020, marking an 18.43 percent growth compared to the previous year. Furthermore, the domestic market for palm oil and palm kernel oil remains substantial, despite improvements in export quantities. Various industries, including cooking oil refineries, specialty fats, shortening, margarine, bath soaps, and oleochemicals, present potential markets for palm oil (CPO) and palm kernel oil (PKO). The palm oil industry encompasses four related sub-sectors, namely growers, millers, refiners, and oleochemicals, forming an integrated value chain from upstream to downstream. The current focus on environmental, economic, and social sustainability is driving companies to adopt internal green activities and expand their efforts into sustainability supply chain management (SSCM). Implementing SSCM practices is often seen as economically beneficial, as research has demonstrated their positive impact on firm performance from a resource perspective. Within the palm oil industry, a wide range of green management applications are being utilized. This study aims to examine and highlight the existing sustainable management practices across the entire palm oil supply chain, with a particular emphasis on producing high-quality palm oil. To achieve this objective, the paper utilizes a systematic review methodology, The number of papers analyzed were 62 articles published which involves an extensive review of relevant literature to identify research trends, gaps, and issues. The study seeks to contribute to the body of knowledge by expanding the theory of organizational readiness in preparing globally competitive palm oil products. The research findings hold practical significance for practitioners and academics, providing a comprehensive roadmap for implementing green management applications at the organizational level in the palm oil industry's upstream-to-downstream chain.

Maximum likelihood estimation (MLE) is a popular method for parameter estimation in both applied probability and statistics but MLE cannot solve the problem of incomplete data or hidden data because it is impossible to maximize likelihood function from hidden data. Expectation maximum (EM) algorithm is a powerful mathematical tool for solving this problem if there is a relationship between hidden data and observed data. Such hinting relationship is specified by a mapping from hidden data to observed data or by a joint probability between hidden data and observed data. In other words, the relationship helps us know hidden data by surveying observed data. The essential ideology of EM is to maximize the expectation of likelihood function over observed data based on the hinting relationship instead of maximizing directly the likelihood function of hidden data. Pioneers in EM algorithm proved its convergence. As a result, EM algorithm produces parameter estimators as well as MLE does. This tutorial aims to provide explanations of EM algorithm in order to help researchers comprehend it. Moreover some improvements of EM algorithm are also proposed in the tutorial such as combination of EM and third-order convergence Newton-Raphson process, combination of EM and gradient descent method, and combination of EM and particle swarm optimization (PSO) algorithm.

This study presents a critical literature review on the models of users' adoption of blockchain applications in supply chains. This review pertaining to blockchain technology adoption by supply chain stakeholders is significant as it is a pre-requisite for the technical sustainability of blockchain technology in supply chains. Through a critical literature review, the previous studies related to technology adoption models were analyzed to explore practices brought about by blockchain applications for supply chain management. This study examined the suitability of the existing models (e.g., the technology-organization-environment (TOE) framework, task technology fit (TTF), unified theory of acceptance and use of technology (UTAUT)) of technology adoption for blockchain applications in supply chains and came up with a new unified model, namely, TOE-TTF-UTAUT. This review provides implications for a more appropriate research design using mixed methods. When adopting the TOE-TTF-UTAUT model in a study, two phases of research using mixed methods can be performed. The first phase is an exploratory sequential design in which a qualitative approach to explore the TOE and supply chain task constructs is followed by a quantitative approach using a survey and quantitative analyses to investigate the factors affecting blockchain adoption in supply chains. The second phase adopts explanatory sequential design in which the quantitative findings from the first phase are reviewed for follow-up by qualitative interviews to obtain explanations.

Recent years have witnessed significant advances in reinforcement learning (RL), which has registered remarkable success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving, involve the participation of more than one single agent, which naturally fall into the realm of multi-agent RL (MARL), a domain with a relatively long history, and has recently re-emerged due to advances in single-agent RL techniques. Although, typically, the communication protocol between agents is manually specified and not altered during training, recently, some papers have shown signs of trying to emerge a communication between agents on the one hand and, on the other hand, to understand what is exchanged between agents. So, there is a growing body of literature on this topic which includes qualitative and quantitative studies and the ones that apply mixed methods. This study presents the scoping review of the methodological strategies undertaken in a total of 16 research articles. The results present the critical appraisal of quantitative methods in terms of validity and reliability and for qualitative methods considering four trustworthiness factors. In the end, relevant insights are further explored with implications and reflections on how they can benefit one's research in the field.

The objective of this study is to investigate the correlation between the advancement of flood research and the utilization of Geographic Information Systems (GIS) and multi-criteria evaluation techniques, both from a theoretical and practical standpoint. Additionally, this research seeks to identify potential ways to address the aforementioned relationship. The present study employs a thorough literature review methodology. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, a total of 28 papers were identified and included in the analysis, as they fulfilled the predetermined criteria. The findings of the study indicate that current research pertaining to the utilization of Geographic Information Systems (GIS) and multicriteria evaluation in flood control mostly centers around five key areas, namely natural factors, technical considerations, institutional factors, socio-economic factors, and financial factors. However, the aforementioned studies have identified specific areas of focus, including natural factors pertaining to climate, technical factors related to infrastructure, institutional factors concerning flood management strategies, socio-economic factors associated with demographics, and financial factors pertaining to financial obligations. However, there is a limited amount of existing research that specifically addresses flood management in developing nations. Therefore, it is anticipated that this study can serve as a valuable resource for future research endeavors, particularly in informing decision-making processes pertaining to the establishment of priorities in flood control plans. The primary subject of this study pertains to flood management occurrences within developing nations.

Bus services play a significant role as the main public transportation, especially in urban areas throughout the years. Since bus services compete greatly with other types of public transportation, such as e-hailing service and private vehicles, they have recently attracted scholars to conduct many relevant studies. However, most past research studies in the Asian region were not focused on engineering, social science, and Internet of Things (IOT). This present study concentrated on the service quality of bus services in Asia by using systematic literature review of articles. This study conducted a review based on previous studies, specifically on the service quality of performance. Several previous studies were selected by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRIMSA) approach. SCOPUS and Science Direct were chosen as the main journal database. By using this method, 41 articles were selected for further analysis. This study was merely focused on three primary themes, such as study approach, stakeholder, and service quality attributes. Advanced analysis on these primary themes was used to formulate another 18 sub-themes. All themes and sub-themes which reflected the significant impacts of service quality towards bus services were discussed in detail. This study had addressed several qualities of bus services of bus performance towards improvement of urban transportation polices. Lastly, several recommendations that could provide necessary knowledge and information for future research were presented.

Food insecurity is an economic and social condition that involves individuals having limited or uncertain access to healthy food. Despite the well-intentioned efforts of both governmental and not-for-profit organizations in addressing food insecurity, well over one-in-ten households in the U.S., the wealthiest nation in the world, experience food insecurity every year. This literature review covered several government programs and research interventions designed to address food insecurity. Results from the review highlight how the Supplemental Nutrition Assistance Program (SNAP), The Emergency Food Assistance Program (TEFAP), and not-for profit food banks have demonstrated success in improving food insecurity. However, the prevalence of food insecurity among U.S. households has fluctuated without any sustained decreases that achieve a food insecurity rate that remains below 10 percent of the population. Food waste, which refers to food that is edible yet discarded at the retail or consumption phases, is rampant in the U.S., as approximately 30 percent (66.5 million tons) of edible food is wasted after leaving the farm every year. Food waste prevention efforts that involve rescuing edible, nutritious food and redistributing it to individuals who are food insecure can promote both environmental- and public health through simultaneous reductions in food waste and food insecurity.

The COVID-19 pandemic has resulted in an unprecedented acceleration in scientific production across multiple disciplines. The vast number of publications available makes it challenging for healthcare professionals and researchers to keep up with the current state of knowledge regarding COVID-19. This article presents covid19-help.org, a free expert-curated database designed to increase the availability of relevant original data related to COVID-19 treatment and prevention via immunization. To accelerate the process of identifying relevant original scientific publications and to simplify annotation of their content, the database uses our artificial intelligence in medical literature (AIM.lit) tool. The article provides an overview of the covid19-help.org database design, the criteria used to select publications, and the use of the AIM.lit tool. The database allows users to easily search and filter records, provides concise information on individual substances and their mechanisms of action, lists relevant original scientific publications with annotations, and offers links to external resources. The AIM.lit tool increases the speed of publication selection and extraction of basic relevant information, without compromising the validity of the data. The technology and experience gained from creating the covid19-help.org database and its tools could also be useful in other areas where scientific information organization is a challenge.

The modern technologies require the need to analyze the opportunities for improvement the integration of digital technologies in CSR activities in the context of added values be-tween business and science in perspective, incl. the future digital society. The main goal of this article is to identify the current state of research on the integration of digital technolo-gies in CSR activities in business, as well as to prepare recommendations for further re-search and practice. A systematic literature review and bibliometric analysis of 129 scien-tific articles published between 2014 to 2023 was performed. The bibliometric analysis was organized in two directions: descriptive and performance analysis, through which we can study the contribution of the analyzed objects to the given scientific area, and science mapping, which studies the relationships among them. The results indicate that the com-panies use more frequently artificial intelligence, blockchain, the Internet of Things and other technologies to increase the efficiency and impact of their CSR activities. In addition, this research reveals the basis of bringing forward the new trends for future publications, which shall upgrade and enrich the theory and practice.

Background: Shared value creation in Base of the Pyramid (BoP) communities is a crucial process towards building sustainable societies. BoP communities in developing countries represent more than four billion people who live on low incomes with limited access to basic products and services. Current or emerging technologies offer promising solutions for organisations pursuing manufacturing opportunities in BoP communities. This study seeks to explore the literature on how BoP communities may become active participants in sustainably manufacturing products using micro-manufacturing factories. The research question posed is: What are the core concepts that need to be taken into consideration for creating shared value through micro-manufacturing factories in BoP communities? Method: A Systematised Literature review (SLR) was completed following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) method for data selection criteria and analysis. The SLR is used to explore the state of literature with regards to creating manufacturing shared value in BoP communities with the objective to identify study gaps and to explore shared value creation concepts. Results: Literature indicates BoP initiatives that have pursued to engage BoP communities through various innovation strategies. The findings of the review is organised under three strategic pillars: Capability building strategy, Implementation process, and Growth strategy. The capability building strategy defines the users’ intention to create shared value in BoP communities with Micro-manufacturing factories (MMF). It is followed by the implementation process which guides the users to create manufacturing shared value in BoP communities. This is followed by a growth strategy to scale for impact.

Children’s learning of place value is critical to their future study of mathematics. However, its learning presents a huge challenge for many learners. As result they develop misconceptions and thencommit errors that become an encumbrance to their understanding of place value. It is therefore important to identify these misconceptions and their associated errors early and help children to overcome them. This article reports the findings from literature on what misconceptions learners display in the learning of place value and how they can best be supported to overcome them. The results show that despite the importance of this topic there are limited studies devoted to its research. The dearth of these studies creates a gap in the study of place value.

Anorectal malformations (ARMs) represent a wide spectrum of congenital anomalies of the anus and rectum, of which more than half are syndromic. Their etiology is highly heterogeneous and still poorly understood. We report a 4-year-old girl who initially presented with an isolated ARM, and subsequently developed a global developmental delay as part of an ARID1B-related Coffin-Siris syndrome (CSS). The co-occurrence of ARMs and CSS in an individual is unexpected since both diseases are very rare. A review of the literature enabled us to identify 12 individuals with both CSS and ARMs. Among these 12 individuals, 9 had a variant in ARID1A, 2 in ARID1B, and 1 in SMARCA4. This more frequent than expected association between CSS and ARM indicates that some ARMs are likely a rare consequence of CSS, especially for ARID1A-related CSS.

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, using machine learning, deep learning and neural networks. AI enables machines to learn from experience and perform human-like tasks. The field of AI research has been developing fast over the past five to ten years, due to the rise of ‘big data’ and increasing computing power. In the medical area, AI can be used to improve diagnosis, prognosis, treatment, surgery, drug discovery, or for other applications. Therefore, both academia and industry are investing a lot in AI. This review investigates the biomedical literature (in the PubMed and Embase databases) by looking at bibliographical data, observing trends over time and occurrences of keywords. Some observations are made: AI has been growing exponentially over the past few years; it is used mostly for diagnosis; COVID-19 is already in the top-5 of diseases studied using AI; the United States, China, United Kingdom, South Korea and Canada are publishing the most articles in AI research; MIT is the world’s leading university in AI research; and convolutional neural networks are by far the most popular deep learning algorithms at this moment. These trends could be studied in more detail, by studying more literature databases or by including patent databases. More advanced analyses could be used to predict in which direction AI will develop over the coming years. The expectation is that AI will keep on growing, in spite of stricter privacy laws, more need for standardization, bias in the data, and the need for building trust.

Many pilot-based initiatives have been developed to promote awareness and use of climate information services among vulnerable smallholder farmers in Africa through million-dollar investments. However, despite their experimental nature, these pilot projects have been successful in raising participating farmers’ awareness and use of climate information services and they can inform transferrable good practices. Through a systematic literature review approach, this review sought to understand ways in which these past pilot projects have contributed to climate risk management in the context of smallholder farming and the factors that led to their success. Results showed that climate information services main contribution to climate risk management has been through facilitating farm level decision making. Factors that led to success of the pilots include: use of downscaled information; building institutional partnerships to add value to climate information; involving farmers through the co-designing and co-developing process; face-to-face way of communication; embedding pre-seasonal workshops in the activities of local institutions for sustainability; using diversity of communication channels to enhance reach among others. These factors can be borrowed as good practices to inform future efforts focused on increasing adoption of climate information services among a wider population beyond pilot project reach.

Background and introduction: Lung cancer is a prevalent and deadly disease globally. Non-small cell lung cancer (NSCLC) is the most common subtype, comprising 85% of cases; Case report: A 65-year-old ex-smoker man presented to our facility with nocturnal cough. Various investigations revealed that he had metastatic NSCLC, for which he underwent chemotherapy with cisplatin and gemcitabine, followed by immunotherapy with Nivolumab. He achieved a complete response to the therapy and has remained free from recurrence for over 7 years since the initial diagnosis; Discussion and Conclusion: The treatment of metastatic NSCLC remains a significant therapeutic challenge, but the implementation of new therapeutic techniques has expanded the possibilities of achieving complete and durable eradication of the disease.

There is an increased interest in the district-scale energy transition within interdisciplinary research community. Agent-based modelling presents a suitable approach to address variety of questions related to policies, technologies, processes, and the different stakeholder roles that can foster such transition. This state-of-the-art review focuses on the application of agent-based modelling for exploring policy interventions that facilitate the decarbonisation (i.e., energy transition) of districts and neighbourhoods while considering stakeholders’ social characteristics and interactions. We systematically select and analyse peer-reviewed literature and discuss the key modelling aspects, such as model purpose, agents and decision-making logic, spatial and temporal aspects, and empirical grounding. The analysis reveals that the most established agent-based models’ focus on innovation diffusion (e.g., adoption of solar panels) and dissemination of energy-saving behaviour among a group of buildings in urban areas. We see a considerable gap in exploring the decisions and interactions of agents other than residential households, such as commercial and even industrial energy consumers (and prosumers). Moreover, measures such as building retrofits and conversion to district energy systems involve many stakeholders and complex interactions between them that up to now have hardly been represented in the agent-based modelling environment.

Remittances are essential to economies in mountainous regions that face massive labour migration due to limited income generation and employment opportunities. In 2021, the share of remittances to GDP in the top 10 mountainous economies in the world was over 20%. Nonetheless, most are characterized by relatively lower GDP per capita and high poverty levels. Drawing a comparison with other mountainous areas, Phuthadjthaba, an emerging mountainous and border city of South Africa with Lesotho, faces similar out-migration and inferior socio-economic parameters. A global systematic literature review on the impact of remittances on livelihoods specifically targeting mountainous areas is missing. We, therefore, interrogate the role remittances can play in Phuthadijthaba. To inform our intended research, we seek to draw lessons from evidence on how migration and remittances affect mountainous communities globally. Accordingly, we carry out a systematic literature review (SLR) based on an updated Preferred Reporting Item for Systematic Reviews and Meta-Analysis (PRISMA) 2020 statement supported by Bibliometric (co-word) Analysis (BA) in VOSViewer. We collected data from Scopus and Dimensions websites and drew 165 publications, of which only 88 were included after exclusion and inclusion assessments. PRISMA results show that Mountain Research and Development, King Russell, and Nepal is the most productive and cited journal, the most productive and cited author, and the most researched country, respectively. Bibliometric analysis on keyword co-occurrences reveals women, agriculture, labour migration, land management, forest, and poverty, to be the research hotspots. In light of these findings, we proffer important recommendations to future researchers and policymakers.

The prolonged exposure to nicotine and the development of nicotine dependence have significant implications for cancer risk. Tobacco use, driven by nicotine addiction, is a major contributing factor to the development of various types of cancer. Smoking tobacco, in particular, has been strongly associated with an increased risk of lung cancer, as well as other malignancies. The harmful chemicals present in tobacco products, including carcinogens, can cause DNA damage and promote the initiation and progression of cancerous cells. This article presents a comprehensive literature review on the neurobiology of nicotine dependence and its implications for tobacco use treatment. Nicotine dependence is a complex phenomenon involving various neurobiological mechanisms. When nicotine enters the body, it binds to nicotinic acetylcholine receptors in the brain's reward circuitry, triggering the release of neurotransmitters like dopamine, serotonin, and norepinephrine. Over time, repeated nicotine exposure leads to neuroadaptive changes in the brain, resulting in increased motivation to seek and use the drug. Understanding the neurobiology of nicotine dependence is crucial for developing effective treatment strategies. Pharmacological interventions, such as nicotine replacement therapy and medications like bupropion and varenicline, can help individuals manage cravings and withdrawal symptoms. Additionally, behavioral therapies and counseling play a vital role in enhancing self-efficacy and providing support for smoking cessation efforts. By reviewing the existing literature, this article sheds light on the intricate neural pathways and processes involved in nicotine addiction. It emphasizes the importance of a multidimensional approach that combines pharmacological treatments and behavioral interventions to address the physiological and psychological aspects of nicotine dependence. This knowledge can inform the development of more targeted and personalized treatment approaches to help individuals overcome tobacco addiction and improve their chances of successful smoking cessation.

In this inclusive review article, the focus is on navigating the dynamic landscape of literature education, particularly the profound pedagogical shifts observed in the aftermath of the pandemic. The article synthesizes global insights, delving into how educators have adapted to hybrid models and embraced digital tools, fundamentally transforming the reading, analysis, and engagement with literary works. Exploring the integration of digital tools in literature education, the review uncovers the transformative impact of technology on traditional pedagogies. It analyzes the challenges and opportunities inherent in adapting literature education to the digital era, emphasizing the need for inclusive practices and adaptability. The article concludes by suggesting future research directions, encompassing AI integration, inclusive practices, cultural variations, long-term effects of hybrid models, and effective pedagogical strategies for technology integration. With a comprehensive approach, this review not only summarizes the current state of literature education but also discusses its implications, offering a holistic understanding of the contemporary educational landscape and setting the stage for future research endeavors.

This research aims to enhance scholarly understanding Analysis of potential Value Creation research on managing transit oriented that may arise from Mass Rapid Transit resources through an extensive literature review, analyzing 235 papers from the Scopus database spanning 2011-2024, with a specific focus on value creation managing transit-oriented area. Data collection was conducted on January 1, 2024, using Harzing's Publish or Perish tool. The selected studies are associated with keywords such as 'managing transit orientation (154 papers), Value creation MRT (45 papers), Innovation MRT (36 papers)/ In the filtering process, 235 papers were assessed, excluding those unrelated to the research focus on the cash flow statement. The inclusion of 31 carefully selected articles reflects a targeted approach, ensuring alignment with the research focus on value creation in managing transit orientation a relevant dataset for analysis. This article was created by accessing several scientific articles regarding the application of identification in managing transit orientation using Vos viewer. Value creation research in managing transit oriented is needed to explore the following areas: Long-term sustainability of identified core competencies, Competitive Imitation, Organizational Adaptability, Industry Specific Applications, Performance Measurement, Dynamic Capability Development, Cross-Cultural Perspective. Potential areas for further research include Incorporate additional contingent factors into the model, such as environmental dynamism and competitiveness, to test the validity of the Resource-Based View (RBV) model. Extend the analysis to small and medium-sized businesses to examine how organizational structure and competitive strategy impact performance in this context.

The state of community lock-down due to COVID-19 pandemic caused restricted movements of people. There are existing evidence of the negative impact of quarantine and isolation to the mental health of a person in different contexts. A scoping review of literature using Google Scholar was conducted to discover records about the public mental health while in a community quarantine due to COVID-19 pandemic. A methodological approach suggested by Arksey and O’Malley was utilized. It comprised (a) identifying the research questions, (b) identifying relevant literatures, (c) selecting literature, (d) charting the extracted data, and (e) summarizing, analyzing, and reporting the results. As of April 17, 2020, there were only 4 original articles found that discuss psychosocial aspect of the COVID-19 crisis. After an online survey, they present evidence that (1) there is an outward change in the people’s behavior toward self-care during the pandemic and (2) trusting the community governing bodies can minimize the level of anxiety and stress. Other literatures found are original articles in preprint (n=8), letters, commentaries, editorial (n=6), review paper (n=4), and WHO guideline (n=1). It is evident that the psychosocial aspect of COVID-19 crisis needs more attention from the scholars and a large research gap can be lessened trough expansion of online platforms.

The artificial intelligence chatbot ChatGPT can answer questions and solve tasks posed by the user within seconds. Using an exemplary task, this study investigates the reliability and con-sistency of the answers given by ChatGPT. For this purpose, it was analyzed whether the an-swers differ when a question is asked repeatedly and whether selected content categories and associated word combinations coincide with those from scientific literature. ChatGPT was asked 400 times, how the connectedness between humans and nature can be increased. The responses were classified into a categorization system and the most frequently occurring word combina-tions for each category were extracted. These word combinations were used for a search of re-lated scientific literature. In addition, the Normalized Mutual Information (NMI) between the 400 individual responses was calculated. The results show that the phrases used by ChatGPT within the categories are also found in the scientific literature, however, the number of mentions between scientific literature and ChatGPT differs. In addition, the NMI suggested that there are large differences between the categories mentioned in the individual answers. These results in-dicate that ChatGPT currently still has difficulties in answering complex questions and cannot yet replace scientific literature research or academic writing.

This manuscript aims to provide a nuanced study of the idea of rights and duties prevalent in ancient Vedic society through Vedic literature and Dharmaśāstras . This manuscript delves into the exegesis of the Védas and Dharmaśāstras to accomplish this. The archaic Vedic literature and Dharmaśāstra texts are the origin and backbone of Sanskrit literature. They have a plethora of ideas that, if accepted, could be quite useful for the protection of any person's human rights. In Védas and Dharmaśāstras, rights and duties complement each other, and rights are integrated by duties. According to these texts, rights and duties are correlated and the relationship between rights and duties leads to the core concept of dharma (constitutional laws). Dharma is a systematic Sanskrit concept that includes traditions, obligation, morals, laws, order, and justice. It was a unique concept of dharma that kept checks and balances on sovereign officials and prevented them from becoming autocratic and anarchist. It also provided the common man with a protective shield against the dictatorship of sovereign officials. Ordinary citizens had more privileges and fewer responsibilities relative to the state's highest officials. The greater the authority, the less his privileges were, and the more extensive his responsibilities became. This research is an exegetical analysis of ancient Indian Vedic and later Vedic literature and is primarily aimed at deciphering some of the essential ideas of the rights found in these texts, which are akin to contemporary human rights. It endeavours to discern and explain the tenets of human rights obnubilated in the pristine mantras of Antediluvian Vedic and Smṛti texts of India. The essay further attempts to add a much needed non-western perspective to the historiography of human rights.

In today's complex and rapidly changing world, integrating values, critical thinking, and moral reasoning in language and literature education is crucial for equipping students with the skills to navigate multifaceted ethical dilemmas and become responsible global citizens. This article highlights the connection between language, literature, critical thinking, moral reasoning, and values integration in education. Through language and literature, teachers can incorporate values education in their classroom, which can benefit not only individual students but also society as a whole. Theoretical frameworks such as character education, moral education, and values education provide the basis for this approach. The researcher recommends strategies for incorporating values integration in language and literature curricula, including the use of literary texts that promote critical thinking and moral reasoning skills. The limitations of this approach, including the challenges in assessing the effectiveness of values integration and potential resistance from some stakeholders, are also discussed. Ultimately, this article aims to call on educators to take a proactive role in promoting values integration in language and literature education, guided by the principles of Jesus Christ and the belief that education is not only about acquiring knowledge but developing character as well. Moreover, this concept has a significant and lasting impact on students' overall development that highlights the importance of values and moral reasoning needed to live a better life.

This study investigates how digital alchemy can enhance literature and language teaching through a combination of online and face-to-face learning. It uses constructivist learning theory and the SAMR model to examine how digital tools and resources can transform learner engagement, critical thinking, and creativity. The study gathered data from interviews, focus groups, and document analysis with 30 participants from private HEI schools. The results show that digital alchemy through blended learning allows learners to personalize and collaborate in their exploration of various literary texts. However, the study also identifies some challenges related to resource availability and educator training. The study emphasizes the importance of using digital alchemy in literature and language teaching and suggests some ways for educators, administrators, and policymakers to effectively use digital tools and resources for student-centered teaching methods in the digital era.

Amidst the dynamic landscape of education, this paper embarks on a transformative journey that explores the integration of Artificial Intelligence (AI) in literature and language education. Through a qualitative exploratory approach, purposeful and maximum variation sampling method, the researcher delves into the experiences of educators and learners, unraveling the multifaceted dimensions of AI-driven pedagogy in SMC. Drawing upon a theoretical framework encompassing Constructivism, Connectivism, and Socio-Cultural Theory, the study examines AI's role in reshaping pedagogical landscapes, fostering critical thinking, and expanding access to education. The results resonate with participants' narratives, unveiling AI's potential in fostering personalized learning pathways, enhancing collaborative engagement, and bridging digital divides. Ethical considerations in AI education are explored, leading to the proposition of responsible guidelines. These findings underline the transformative power of AI in education, aligned with the institution's commitment to quality education and innovation. Overall, the study calls for ongoing exploration, emphasizing the qualitative research method's depth and richness, as well as the theoretical framework's guidance in realizing the study's objectives. As AI continues to shape education's frontiers, this research underscores the significance of adaptability, ethical awareness, and holistic engagement for school administrators, educators, learners, and researchers alike.

As the increase threat of flood risk and environmental safety due to the urbanization, Sponge city research has been attracting extensive attention both in practical and theoretical research field. To date, there are only scattered studies about Sponge city. Moreover, vary names of Sponge city prevalent in different countries, which leads to disconnection of literature in the same field of Sponge city. In this paper, a thorough systematic literature mining of Sponge city is presented. A literature analysis system is created, which includes literature export from Web of Sciences and systematic analysis via NoteExpress and CiteSpace. Some literature statistical results are derived. Challenges and opportunities for future research are anticipated. Our goals are to promote this promising thought, summarize past research, and identify issues for future research to create impacts on the practice of Sponge city.

(1) In an era where sustainable behavior is increasingly crucial, understanding the discrepancy between individuals' sustainability-oriented values and their actual behaviors, known as the inner-outer gap, is vital. This study explores the potential of the Tripartite Structure of Sustainability (TSS) framework to address this gap within the context of sustainable education. By reviewing literature from the databases APA, ERIC, and Web of Science, we systematically examined factors influencing sustainable actions. (2) Employing a qualitative content analysis approach, we analyzed 56 articles over a 15-year period, identifying 83 factors that either bridge or reinforce the inner-outer gap. These factors were categorized within the TSS framework, which segments sustainability-oriented actions into individual, social, and self-transcendent domains, alongside their activation points: stable, situational, or automated. (3) Our analysis revealed that self-focused factors often reinforce the gap, suggesting a hindrance to sustainable behavior. Conversely, self-transcendent factors consistently bridged the gap, promoting sustainability. Social factors showed variable impacts based on the ethical and sustainable context they were placed in, suggesting that the social environment's orientation significantly influences sustainable behavior. (4) The study concludes that the TSS framework offers a promising approach to advancing sustainability in education by facilitating a paradigm shift towards holistic and interconnected perspectives. This shift is critical for fostering sustainable behaviors, thereby contributing to the field of educational psychology and offering practical implications for educators aiming to nurture a sustainable future.

This qualitative study unveils the intricate interplay between blended learning, language and literature learning, internationalization, and the development of 21st century skills within the realm of higher education. Set against the backdrop of the environment of St. Michael's College in Iligan City, this exploration seeks to unravel the profound significance and transformative implications of these educational dimensions. By delving into the rich perspectives and experiences of 30 college students, this study addresses critical gaps in the literature and sheds light on the potential of these integrated elements. Guided by a robust theoretical framework that amalgamates renowned scholars' insights on blended learning, language acquisition, internationalization, and 21st century skills, the study employs a qualitative research design, employing interviews, observations, and document analysis. The findings illuminate the dynamic nature of blended learning, empowering students with enhanced engagement, flexibility, and accessibility in language and literature education. The incorporation of diverse literary texts and cultural perspectives fosters intercultural competence and global awareness. Moreover, the study underscores the cultivation of critical 21st century skills through immersive learning experiences. Drawing upon the insights gained, the study provides practical recommendations for educators and curriculum designers to harness the potential of blended learning, foster diversity in literary texts, and facilitate the application of 21st century skills. Recognizing the inherent limitations, including the specific context of St. Michael's College and the modest sample size, this study encourages future research to explore broader contexts and diverse participant cohorts. Overall, this illuminating study contributes to the scholarly discourse on integrating blended learning, language and literature learning, internationalization, and 21st century skills in college education. It beckons educators and policymakers to embark on a transformative journey, nurturing an enlightened future where students are equipped with the competencies to navigate the complexities of the 21st century.

In the wake of globalization and the revolutionary impact of Artificial Intelligence (AI), literature and language education play a pivotal role in preparing the next generation to navigate an ever-changing world. This reflective concept paper explores the profound insights shared by educators, focusing on literature and language education amidst globalization and AI. Drawing on interviews and observations, teachers' reflections reveal the enduring value of literature in shaping young minds, fostering critical thinking, and promoting empathy. Additionally, they emphasize the importance of embracing multilingualism and cultural diversity to equip students for an interconnected world. In the face of challenges, educators showcase their resilience and adaptability, harnessing technology, particularly AI-driven tools, to foster future-ready learners. Identifying gaps and implications in literature and language education, this paper sets the stage for collective efforts among stakeholders to shape the future of education. Ultimately, teachers hold the key to nurturing a generation capable of embracing the complexities of the AI-driven global landscape with confidence and compassion, empowering students as transformative agents in a rapidly changing world.

In an era of global connectivity, language and literature education faces the challenge of navigating multilingualism, cultural diversity, and technological advancements. This paper explores the challenges and opportunities in language and literature education in the era of global connectivity. Through a qualitative research approach, interviews, focus group discussions, and classroom observations were conducted with 30 Arts and Sciences students and teachers. The findings reveal significant themes related to cultural diversity, multilingualism, and the integration of technology in language learning. The study emphasizes the importance of inclusive pedagogies, critical thinking development, and the incorporation of authentic and diverse literary works. Recommendations are provided for educators and policymakers to promote intercultural understanding and enhance language and literature education. The limitations of the study suggest areas for future research, including long-term language proficiency and diverse contextual considerations. Overall, this paper calls for ongoing innovation and collaboration to meet the evolving needs of language and literature education in an interconnected world.

We study two fundamental linguistic channels ‒ the Sentences and the Interpunctions channels ‒ and show they can reveal deeper connections between texts. The theory applied does not follow the actual paradigm of linguistic studies. As study‒case, we consider the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in writing style (mathematically defined) of writers, and in reading skill required to their readers. The analysis is based on deep‒language parameters and communication/information theory. To set the New Testament texts in the larger Greek Classical Literature, we consider texts written by Aesop, Polybius, Flavius Josephus and Plutarch. The results largely confirm what scholars have found about the New Testament texts giving, therefore, credibility to the theory. The gospel according to John is very similar to Fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse, are each other “photocopy” in the two linguistic channels, and not linked to all other texts. These two texts deserve further study by historians of the early Christian Church Literature at the level of meaning, readers and possible Old Testament texts which might have influenced them. The theory can guide scholars to study any literary corpus.

Kininogens are multidomain glycoproteins found in the blood of most vertebrates. They are important in the blood coagulation cascade pathways - in intrinsic pathway activation leading to thrombin generation partially independently from tissue factor dependent extrinsic pathway, connecting blood coagulation with the kallikrein-kinin system. Nothing is known about the shape on atomic level therefore the endeavor to obtain the good-quality spatial structure of kininogens is important for a better understanding of their role in disease and treatment. Application of cryo-EM is important for solving the spatial structure of kininogens, drawing new frontiers in understanding the function and opening new pathways for drug development.

This study employs a qualitative research approach to investigate the intrinsic and extrinsic motivations that influence college students' engagement, learning experiences, and long-term commitment to language and literature studies within the context of blended learning modality. Drawing on the theoretical frameworks of Self-Determination Theory and Achievement Goal Theory, the research explores the complex interplay between intrinsic factors (e.g., passion, self-improvement, personal growth) and extrinsic factors (e.g., external rewards, recognition). The study is conducted at SMC among the 30 participant and utilizes interviews and classroom observations, in conjunction with a comprehensive review of relevant literature, to gain insights into the impact of these motivations on academic performance and learning outcomes, particularly in blended learning environments. The study acknowledges the limitations inherent in its locale-specific scope and the challenges associated with ensuring the validity and reliability of data collected through online surveys and virtual classroom observations. The findings of this study have significant implications for educators and policymakers, highlighting the importance of nurturing intrinsic motivation while leveraging extrinsic factors to establish supportive learning environments that foster student autonomy, incorporate student interests, and provide timely feedback. By comprehending the motivations that drive student engagement and long-term commitment, educators can enhance learning experiences, elevate academic performance, and sustain students' engagement with language and literature studies amidst the evolving educational landscape of blended learning modality.

Carbapenem-resistant Acinetobacter baumannii (CRAB) infections represent the fourth-leading cause of death attributable to antimicrobial resistance globally, but a standardized therapy is still lacking. In this narrative review we focused the antibiotic treatment of CRAB infections in view of newly β-lactam agents (NBLs) like sulbactam/durlobactam and cefiderocol, discussing the main hot points such as the superiority of combination treatment over monotherapy and the best antibiotic partner to use in combination. Sulbactam/durlobactam seems to be the best candi-date to replace current back-bone agents. Cefiderocol, could play a crucial role in combina-tion-regimen. Due to toxicity and the PK/PD limitations, colistin (or polymyxin B) should be used as an alternative agent (when no other options are available). Tigecycline (or minocycline) and fosfomycin could represent suitable partners for both NBLs. Randomized clinical trials (RCTs) are needed to better evaluate the role of NBLs in CRAB infection treatment and to compare the ef-ficacy of tigecycline and fosfomycin as partner antibiotics. Synergism should be tested between NBLs and “old” drugs (rifampicin and trimethoprim/sulfamethoxazole). Huge efforts should be made to accelerate pre-clinical and clinical studies on safer polymyxin candidates with lung im-proved activity, as well as on the i.v. rifabutin formulation.

BACKGROUND: Is pharmacovigilance at a moment of prominence for science and in relation to government responsibilities towards their nations, as the new coronavirus pandemic has surprised everyone in a negative and lethal way. OBJECTIVE: Evaluate pharmacovigilance as a resource for controlling and understanding the adverse effects caused by vaccines in use. DESIGN AND SETTING: Narrative review developed by a research group at Faculty of Medicine of the University of Porto. METHODS: This is a narrative review of the literature available in electronic media, government bulletins and similar bodies. The search was carried out using the descriptors: "Pharmacovigilance AND COVID-19 in Brazil", "Vaccine Development AND COVID-19 in Brazil", "Vaccination Hesitancy AND COVID-19 in Brazil", "Pharmacovigilance AND COVID-19", "Vaccine Development AND COVID-19", "Vaccination Hesitancy AND COVID-19", Pharmacovigilance AND COVID-19, Vaccine Development AND COVID-19, Vaccination Hesitancy AND COVID-19, "Public Health Surveillance AND COVID-19". In the period from May 2021 to June 2022. RESULTS: From the database search, 3 journal articles, 4 government bulletins and 535 scientific articles were identified. Of the total of 542 bibliographic materials, 36 were selected according to the selection criteria and objectives of the study. CONCLUSIONS: The vaccines in use have proven efficacy, despite adverse reactions that cannot be attributed solely and exclusively to their use, since the medical history of each patient should be considered in the investigation of each case, especially when there is death. The Brazilian data for adverse events, although the country is continental in its size, are acceptable given the number of deaths recorded.

Statistics of languages are calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G – the semantic index G_C, proportional to the number of characters per word, and the syntactic index G_F, proportional to the reciprocal of the number of words per sentence −, G_F is dominant because G_C is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y=mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is, in author’s opinion, that between the short−term memory capacity, described by Miller’s “7∓2 law”, and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval is spread in the same of Miller’s law, and the time interval is spread in the same range of short−term memory response times. The connection between the word interval (and time interval) and short−term memory appears, at least empirically, justified and natural, and should further investigated. Technical and scientific writings (papers, essays etc.) ask more to their readers. A preliminary investigation of these texts shows clear differences: words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as Greek or Latin, could bring us a flavor of the short term−memory features of these ancient readers.

In recent years, humanity has faced a growing challenge posed by the rise of antibiotic-resistant bacteria, resulting in an alarming surge in fatalities and the emergence of increasingly hard-to-manage diseases. Among these resilient pathogens is Acinetobacter baumannii, due to its escalating prevalence in hospitals, elevated mortality rates, and resistance to treatment. Despite its clinical significance, our understanding of this pathogen in non-hospital settings and its virulence factors remains limited. Therefore, this review aims to shed light on the latest research regarding its ecological niche, microbiological traits, and antibiotic resistance profiles. Recent investigations have expanded its detection to various environmental niches, including rivers, treatment plants, and soils. Moreover, this bacterium has been discovered in diverse food sources such as meat and vegetables, as well as in farm animals and household pets like dogs and cats. This broader presence of Acinetobacter baumannii outside of hospital environments underscores a significant risk of environmental contamination, necessitating heightened awareness and preventive measures to address potential public health implications.

Gelatin industry residues are increasingly used as fertilizer and soil conditioner. However, correct residue dosage is critical for grass development and minimizing environmental impacts. This randomized block design study determined adequate dosage of Mixed Gelatin Sludge (MGS) for Marandu grass production in wet/dry seasons in Brazil. Five MGS levels (0%–200% of required nitrogen) were compared to mineral fertilizer. Agronomic/productivity characteristics, bromatological composition, macro/micro-nutrient composition of leaves, and soil chemical attributes were evaluated. Agronomic/productivity characteristics were influenced by MGS dose in both dry/rainy seasons, except for leaf blade pseudostem ratio and percentage of leaves/pseudostem. Bromatological composition was influenced by MGS doses in dry/rainy seasons except for dry/mineral material quantities. Marandu leaf tissue chemical composition was significantly influenced by MGS dose, except for potassium, boron, and iron. Chemical composition of four soil layers between 0–50 cm influenced GMS dose, except for pH, organic matter, magnesium, copper, manganese, and zinc. GMS dose for Marandu production should be 200% of nitrogen (N) requirement. GMS application increased productivity/quality of Marandu grass. Macronutrients (N, phosphorus) and micronutrients (Ca, Mg, S, Cu, and Zn) increased in Marandu grass and in the soil (Ca, S, and Na). Increased sodium (Na) level was not limiting.

This study focuses on examining various approaches for Tensor Decompositions (TDs) and their potential applications in satellite imaging (SI) and deep learning (DL). The research highlights how these decompositions can contribute to the advancement of SI and DL, providing valuable insights for future utilization of TDs in research. It explores how these techniques contribute to the advancement of SI and DL methods, providing insights into their potential applications and suggesting future research directions. The study aims to enhance the use of TDs techniques to further advance research efforts in these fields. More importantly, the current investigation offers a thorough analysis of the potential advantages and reasons for employing TDs techniques in different domains, including satellite imaging and deep learning. The aim is to enhance research outcomes by utilizing TDs. The review also identifies unresolved issues and proposes future directions for further investigation in this field. Fundamentally, these proposed open problems will open new grounds to the research community to articulate, innovate, and provide more real-life applications to improve the current state of the art by delving into a wider vision for a higher-level performance of both satellite imaging (SI) and deep learning (DL). Looking at the bigger scenario, this also suggests that TDs could be potentially employed to revolutionize existing machine learning technologies as well as the current space AI industry.

Background: The bacterium Capnocytophaga spp. is a part of the oral microbiome of dogs, which has zoonotic potential. This study aimed to assess factors that influence the prevalence of Capnocytophaga cynodegmi and Capnocytophaga canimorsus in Wrocaw’s dog population. Methods: Molecular detection (PCR) involved 105 swabs, examining parameters such as oral cavity condition, underlying health issues, recent antibiotics, age, medications, material collection, and dog chews. Results: The study highlighted significant associations between the presence of Capnocytophaga cynodegmi and oral cavity condition, material collection method, and use of dog’s chews. Conclusions: Correlations obtained in this study between the oral health of Wroclaw's dog population and the presence of Capnocytophaga cynodegmi suggest its significance in the oral microbiome of dogs. Limitations, including the small sample size, highlight the need for more research to comprehensively understand additional factors that affect the prevalence of Capnocytophaga spp. in dogs

The purpose of this study is to elucidate the factors influencing the voluntary adoption of IFRS by examining, analyzing, and synthesizing findings from empirical studies conducted worldwide. The research scrutinizes 185 relevant studies on the voluntary adoption of IFRS published before August 2023. Our assessment reveals that, in prior research, the factors influencing the voluntary adoption of IFRS are categorized into seven main factors, including corporate operations, capital structure, ownership structure, internationalization, financial performance, corporate governance, and several other factors. These studies employ various methodologies, including data surveys, and cross-sectional data, to estimate the relationships between these factors and the voluntary adoption of IFRS. In addition to providing an evaluation of the research in this field, this study can serve as a framework for future researchers to link and compare the results of different studies. We anticipate that this research will be beneficial for future scholars interested in the factors influencing the voluntary adoption of IFRS. Furthermore, the study proposes essential guidance for future research considerations.

Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. However, traditional reliability estimation theories may not apply when data is limited or subject to right censoring. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum-likelihood method under the abovementioned conditions. The likelihood equation lacks an explicit analytical solution, necessitating the use of numerical methods for resolution. The proposed approach presented in this article leverages the Expectation-Maximization (EM) algorithm for estimating the Weibull distribution parameters. This method provides more accurate estimates of failure rates and probabilities by accounting for limited and censored data. The findings are demonstrated through a case study, showcasing the practical application of the proposed approach.

Barcoding of DNA is a species identification technique that utilizes a small DNA fragment from a specific gene or genes known as "sequencing." The idea behind DNA barcoding is that a single sequence can be used to specifically identify an organism to species by comparison with a reference library of these DNA sections. Herbal adulteration can be monitored using DNA barcodes that utilize medicinal plants such as Atropa belladonna. Because it is challenging to distinguish between species solely based on morphology, other plants belonging to the same genus are replacing it in trade. Such replacement with plants not utilized for medical purposes could have negative side effects. Also, Atropa belladonna's positive effects can be completely lost. Taxonomists also have trouble distinguishing the genuine Atropa belladonna plant from cultivated items. As a result, DNA barcoding can now be used to overcome this challenge. The development of DNA barcodes may help with trade control, which protects and conserves endangered species from export outside of the country due to their economic and biological significance. In this review, we discuss the DNA barcoding of Atropa belladonna plant in the medicinal plants field.

Considerable research on intergroup relations emphasizes attitudes, motivations, and emotions that lead to reduction of prejudice. While factors that actively promote positive intergroup interactions have been emerging, a central theoretical framework has not been formally proposed. To address this gap, we engage a positive psychology lens to explore how and why people overcome their internalized biases to seek out successful and positive intergroup relations, looking to the positive counterparts of traditional prejudice-reduction models to begin building a framework of understanding. We reviewed the literature on values that guide intergroup behavior. After scanning 16,840 records that emerged in PsycInfo using keywords “egalitarian,” “non-prejudice,” and “intergroup,” we assessed 158 articles for eligibility. Among the relevant articles (N = 54), we analyzed authors’ definitions, methods of measurement, types of processes, and outcomes associated with egalitarian and non-prejudice values as they related to intergroup behavior. Overall, there was notable variability in how researchers conceptualized and observed egalitarianism. We discuss the five broad categories of egalitarianism (prejudice reduction, positive expression, concern for others, low social-dominance orientation, and universal orientation) and how they relate to positive or negative, and approach or avoidant outcomes. We propose a centralized model for studying positive values in intergroup contexts moving forward.

The era of digital technology has brought about a substantial shift in language development, especially for younger generations who have grown up surrounded by it. Language development is impacted by digital media exposure in both positive and bad ways. Positively, users can interact with a variety of linguistic communities across the globe by using digital platforms, which offer a wealth of options for linguistic exposure and practice. This exposure can promote imaginative language use, increase vocabulary, and improve reading comprehension. Since the brevity and informality of digital communication frequently stress speed over correctness, there are worries that digital media could encourage shallow communication, shorter attention spans, and a deterioration in professional writing skills. This paper aims to gather literature about language development in the digital age. In order to make sure that technical breakthroughs support language development, standards for the responsible and balanced use of digital media in educational settings must also be developed. Teachers can better support their students' language development in a constantly changing digital environment by remaining knowledgeable and flexible.

Background: Helicobacter pylori (H. pylori) is a prevalent bacterial pathogen implicated in various gastroduodenal diseases, including chronic gastritis, peptic ulcer disease, and gastric cancer. The COVID-19 pandemic has significantly influenced antibiotic prescription practices, potentially exacerbating antibiotic resistance in H. pylori. Objective: This study aims to investigate antibiotic prescription during COVID-19 pandemic in Croatia and its possible impact on H. pylori antibiotic resistance, with a focus on Croatia. Methods: A comprehensive literature search was conducted to identify relevant studies from March 2020 to June 2024. The search strategy included terms related to COVID-19, antibiotic prescription, and Croatia. Studies were selected based on predefined eligibility criteria, focusing on observational research addressing antibiotic use during the pandemic. Results: The COVID-19 pandemic leads to significant fluctuations in community antibiotic consumption within the European Union/European Economic Area. In Croatia, antibiotic use in 2022 surpassed 2019 levels, driven by increased consumption of macrolides and other antibiotics. This surge, influenced by early pandemic treatment claims and penicillin shortages, contributed to rising antibiotic resistance in H. pylori. Resistance rates to clarithromycin and levofloxacin were notably high, driven by mutations in the 23S rRNA, gyrA, and gyrB genes. Discussion: The increased antibiotic use during the COVID-19 pandemic has highly likely complicated H. pylori eradication efforts, highlighting the necessity of judicious antibiotic use and robust antimicrobial stewardship. The pandemic underscored the need for new therapeutic strategies, optimized eradication regimens, and advanced diagnostic methods to manage bacterial infections effectively. Conclusions: The COVID-19 pandemic has significantly impacted antibiotic use and resistance patterns, posing new challenges for H. pylori eradication. Addressing these challenges requires a multifaceted approach, including the development of new drugs and advanced diagnostics, coupled with sustained efforts in antimicrobial stewardship to combat emerging resistance threats.

Lecanicillium lecanii KMZW-1, is recognized for its potential as a bio-control agent against agricultural and forestry pests, particularly due to its compatibility with integrated pest management (IPM) strategies. This study aimed to investigate the complete genome of L. lecanii KMZW-1 and assess its pathogenicity against Bactrocera dorsalis. Whole genome sequencing revealed a genome size of 47,239,278 bp, comprising 27 contigs, with a GC content of 51.16%. The genome completeness was assessed as 97.93% using BUSCO analysis, AntiSMASH analysis identified 29 gene clusters associated with secondary metabolite biosynthesis providing insights into the genetic basis of its pathogenic mechanisms and biocontrol potential. The pathogenicity of L. lecanii KMZW-1 was assessed using concentrations ranging from 1×10^4 to 1×10^11 spores/mL. Higher-concentrations (1×10^10 to 1×10^11 spores/mL), resulted in significantly increased cumulative mortality rates of B. dorsalis adults compared to the control group. Notably, the pathogenicity was higher in male adults than in females. Probit regression analysis yielded LogLC50 values as 5.662 for female and 4.486 for male B. dorsalis adults. In summary, L. lecanii KMZW-1 exhibits strong insecticidal activity against B. dorsalis and shows potential as a biocontrol agent with IPM strategies. These findings provide robust genomic evidence supporting the use of L. lecanii KMZW-1in managing against B. dorsalis populations.

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analysed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioural and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

Urban agriculture is an early practice, especially for cities in the Global South that are expanding at an unprecedented rate, and in African cities, it can be a way to attend to essential social and health needs. However, it is unclear whether architects and urban planners have expressed interest or already incorporated urban farming within their designs of African cities. This literature review was conducted to understand to what extent architects and urban planners have researched urban agriculture and health. Comprehensive searches based on urban agriculture, health, and Africa were conducted in Scopus, PubMed, and Web of Science from 2000 to December 2020. Zotero, Mozilla Firefox search engine, and Google Chrome were used to collect paper metadata. The duplicate articles were excluded, and all the n = 240 publications remaining were included in the analysis. Food security and the immediate health impact of urban agriculture on health were the most addressed topics. These studies reported the harmful effects of urban agriculture on malaria and the wastewater irrigation of plants. The evidence on urban agriculture is increasing from public health researchers, but not in the field of urban planning or architecture. Future research on urban agriculture's impacts on urban health should be increasingly done by architects and planners to help shape urban planning practices and regulations that could help create urban agriculture that benefits urban health.

Antibiotic resistance is a global health problem. The human gut microbiome is implicated in the dynamics of antibiotic resistance acquisition and transmission, with the gut microbiota thought to play a crucial role. This study aimed to determine the potential influence of human gut bacteria microbiota on the gut resistome and the relationship between gut background microbiota and Escherichia coli resistome. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was used to systematically review studies that characterised gut microbiota and resistome using metagenomic analysis and/or those that reported gut E. coli resistome in healthy individuals. Changes in the diversity and abundance of bacterial gut microbiota and the resistome across different groups and the microbiota composition of the gut harbouring antibiotic-resistant E. coli were summarised. Findings suggest that lower bacterial microbiota diversity is likely associated with an increased abundance of the overall gut resistome. Age-related differences were observed, with younger infants exhibiting lower microbiota diversity and higher ARG abundance compared to older infants and adults. Studies that reported correlation revealed positive correlations between the compositional relative abundance of Proteobacteria and ARGs abundance, mainly driven by members within the Enterobacteriaceae family, particularly E. coli. This study also revealed that human gut microbiome studies that investigate gut resistome using metagenomic sequencing approaches in apparently healthy individuals are at least uncommon.

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to constrain the depositional ages of lake sediments and examine their physical, chemical, and biological characteristics, aiming to construct historical vegetation, environment and climate patterns in Chinese lake watersheds. In this study, we obtained relevant literature on lake sediment records by searching the key word 'age-depth' from the databases – Web of Science and China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in the watershed to lake ecology, and provides a solid foundation for better understanding regional climate change and the preservation of lake environments and ecosystems. In the future, resulting data from environmental reconstruction with lake sediments will be needed to integrate with emerging information processing technologies (e.g., artificial intelligence and meta-analysis), to disentangle the complex interplay between Earth surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change.

: This Systematic Review focused on the use of Bifidobacterium infantis and Bifidobacterium breve in neurodegenerative diseases. The study of metabolomics has demonstrated the relationship between dysbiosis and neuronal death. The modulation of the gut microbiota in the intervention of these pathologies has become a promising area of study, showing beneficial results such as the improvement of synaptic function, the reduction of neuroinflammation, as well as the improvement of associated neuropsychiatric symptoms. Several studies have addressed the administration of Bifidobacterium infantis and Bifidobacterium breve, alone, in conjunction or in combination with other strains, in the intervention of neurodegenerative diseases. This Systematic Review includes the results of 17 research articles (n=5 in humans and n=12 in animal models) and the main result was that the use of these Bifidobacterium strains, alone, in conjunction or in combination with other strains, produced improvements in neurodegenerative disease-related symptomatology and degenerative cellular processes. However, some studies shown neutral results in certain variables. These data suggest that the use of these probiotics has a neuroprotective effect that may delay the progression of the disease. This research provides relevant and updated information on the use of these Bifidobacterium strains in neurodegenerative pathologies such as Alzheimer's disease and Parkinson's disease.

The practice of telework, remote work, and working from home has grown significantly across the pandemic era (2020+). These practices offer new ways of working but come with a lack of clarity as to the role it plays in supporting the wellbeing of staff. (1) Background: the purpose of this study is to examine the current literature on wellbeing outcomes and effects of telework; (2) Methods: this study adopts a systematic literature review from 2000-2022 using the PRISMA approach and thematic analysis guided by the United Nations Sustainable Development Goals (Wellbeing, Decent Work, Gender Equality, and Inclusive Production); (3) Results: it was evident that there is a lack of clarity on the actual effects of telework on employee wellbeing, but it appeared that it had a generally positive effect on short-term wellbeing of staff, and created more flexible and proactive work design opportunities; (4) Conclusions: there is a need for more targeted research into work designs that support wellbeing and productivity of staff, and consider the environmental sustainability changes from reduced office and onsite work and increased working from home.

Transformative education significantly advances society's growth as an essential doorway to fresh language learning chances. It equips people to succeed in a complicated world by encouraging critical thinking, inclusivity, social responsibility, lifelong learning, and international collaboration. Adopting transformative education can result in a more inventive, sustainable, and equal society where everyone can realize their potential and advance society's interests as educational systems change. This paper aims to gather literature regarding how transformative education becomes a door toward new learning opportunities in societal development especially language. Transformative education may produce a generation of knowledgeable, sympathetic, and proactive students who can bring about constructive social change by prioritizing holistic development. Hence, educators should work to foster a learning atmosphere where all students feel supported and respected. Through integrating social justice ideals into the educational process, transformative education equips students to act as change agents and advocates for equity both within and outside their communities.

Depression is considered by WHO as the main contributor to global disability and it poses dangerous threats to approximately all aspects of human life, in particular public and private health. This mental disorder is usually characterized by considerable changes in feelings, routines, or thoughts. With respect to the fact that early diagnosis of this illness would be of critical importance ineffective treatment, some development has occurred in the purpose of depression detection. EEG signals reflect the working status of the human brain by which are considered the most proper tools for a depression diagnosis. Deep learning algorithms have the capacity of pattern discovery and extracting features from the raw data which is fed into them. Owing to this significant characteristic of deep learning, recently, these methods have intensely utilized in the diverse field of researches, specifically medicine and healthcare. Thereby, in this article, we aimed to review all papers concentrated on using deep learning to detect or predict depressive subjects with the help of EEG signals as input data. Regarding the adopted search method, we finally evaluated 22 articles between 2016 and 2021. This article which is organized according to the systematic literature review (SLR) method, provides complete summaries of all exploited studies and compares the noticeable aspects of them. Moreover, some statistical analysis performs to gain a depth perception of the general ideas of the latest researches in this area. A pattern of a five-step procedure was also established by which almost all reviewed articles fulfilled the goal of depression detection. Finally, open issues and challenges in this way of depression diagnosis or prediction and suggested works as the future directions discussed.

Ipomoea batatas L. (IBL) has gained significant popularity as a complementary therapy or herbal medicine in the treatment of anti-diabetes. The objective of this review is to examine the mechanism of action of flavonoid compounds found in IBL that can activate GLP-1 as an anti-diabetic agent. The review article refers to PRISMA guidelines. The literature search was conducted using electronic databases such as Crossref, Pubmed, Scopus, and Science Direct. The search query was based on specific keywords, including Ipomoea batatas OR sweet potato AND anti-diabetic OR hypoglycemic. A total of 1055 articles were found, but only 32 articles were selected for further review based on inclusion and exclusion criteria. IBL contains various compounds, including phenolic acid, flavonols, flavanols, flavones, and anthocyanins, which exhibit activity against anti-diabetes. Flavonols, flavonols, and flavones belong to a group of flavonoids that possess the ability to form complexes with AlCl3 and Ca2+. Retention of Ca2+ within intracellular L cells, resulting in the release of GLP-1. Flavonols, flavones, and flavone groups have been found to strongly interact with DPP-IV, which inhibits the degradation of GLP-1. This mechanism effectively prolongs the half-life of GLP-1 in the systemic system, thereby contributing to the anti-diabetic activity of IBL

With the rise of serious problems of urbanization and climate change, the call for intelligent and sustainable urban development is increasing nowadays. Therefore, smart cities have become a hot topic in academia, industry, and politics, resulting in the emergency of numerous smart city programs and projects. This study selected 26 evaluation frameworks proposed in recent years or large-scale research projects that have lasted for many years and analyzed and compared them from the 7 aspects of generalizability, comprehensiveness, availability, flexibility, scientific, transparency, and interpretability. The result indicates that the current smart city evaluation framework still needs to be upgraded and updated. These standards can not only guide the development direction and hotspot of the future smart city evaluation model but also serve as a guide for model demanders to test results and an effective tool to verify the framework designed by themselves.

3D human pose estimation has made significant advancements through the integration of deep learning techniques. This survey provides a comprehensive review of recent 3D human pose estimation methods, with a focus on monocular images, videos, and multi-view cameras. Our approach stands out through a systematic literature review methodology, ensuring an up-to-date and meticulous overview. Unlike many existing surveys that categorize approaches based on learning paradigms, our survey offers a fresh perspective, delving deeper into the subject. For image-based approaches, we not only follow existing categorizations but also introduce and compare significant 2D models. Additionally, we provide a comparative analysis of these methods, enhancing the understanding of image-based pose estimation techniques. In the realm of video-based approaches, we categorize them based on the types of models used to capture inter-frame information. Furthermore, in the context of multi-person pose estimation, our survey uniquely differentiates between approaches focusing on relative poses and those addressing absolute poses. Our survey aims to serve as a pivotal resource for researchers, highlighting state-of-the-art deep learning strategies and identifying promising directions for future exploration in 3D human pose estimation.

Geijera Schott is a plant genus of the Rutaceae Juss. (rue and citrus) family, comprising six species which are all native to Oceania. Of the plants belonging to this genus, the most significant species that has a customary use is Geijera parviflora, which was used by Indigenous Australians, primarily as a pain reliever. Herein, a comprehensive review of the literature published on the genus Geijera from 1930-2023 was conducted. This is the first review for this plant genus and it highlights the chemical constituents reported to date, together with the range of pharmacological properties described from the various species and different parts of the plant. These properties include anti-inflammatory, anti-microbial, anti-parasitic, insect repellent, analgesic, neuroactive, and anti-cancer activities. Finally, a reflection on some of the important areas for future focused studies of this plant genus is provided.

Leishmaniasis represents a severe global health problem. In the last decades, there have been significant challenges in controlling this disease due to the unavailability of licensed vaccines, the high toxicity of the available drugs, and an unrestrained surge of drug-resistant parasites, and human immunodeficiency virus (HIV)–Leishmania co-infections. Leishmania spp. preferentially invade macrophage lineage cells of vertebrates for replication after subverting cellular functions of humans and other mammals. These early events in host–parasite interactions are likely to influence the future course of the disease. Thus, there is a continuing need to discover a simple cellular model that reproduces the in vivo pathogenesis. Acanthamoeba spp. are non-mammalian phagocytic amoeba with remarkable similarity to the cellular and functional aspects of macrophages. We aimed to assess whether the similarity reported between macrophages and Acanthamoeba spp. is sufficient to reproduce the infectivity of Leishmania spp. Herein, we analyzed co-cultures of Acanthamoeba castellanii or Acanthamoeba polyphaga with Leishmania infantum, Leishmania amazonensis, Leishmania major, and Leishmania braziliensis. Light and fluorescence microscopy revealed that the flagellated promastigotes attach to the A. castellanii and/or A. polyphaga in a bipolar and or random manner, which initiates their uptake via pseudopods. Once inside the cells, the promastigotes undergo significant changes, which result in the obligatory amastigote-like intracellular form. There was a productive infection with a continuous increase in intracellular parasites. However, we frequently observed intracellular amastigotes in vacuoles, phagolysosomes, and the cytosol of Acanthamoeba spp. Our findings corroborate that Leishmania spp. infects Acanthamoeba spp. and replicates in them but does not cause their rapid degeneration or lysis. Overall, the evidence presented here confirms that Acanthamoeba spp. have all prerequisites and can help elucidate how Leishmania spp. infect mammalian cells. Future work exposing the mechanisms of these interactions should yield novel insights into how these pathogens exploit amoebae.

This paper discusses how mathematical models are used to predict environmental conditions. While these models are successful for larger scale phenomena, it becomes more complex for local weather or wave processes. Several approaches have been proposed to address this problem, including neural networks and statistical and mathematical models. The novelty in this approach is the use of statistical manifolds, which provide a more accurate way to estimate distances and cost functions. This work focuses on advancements in differential and information geometry for creating different types of models that can be used for environmental simulation and forecasting. These fields are vital for many institutes and centres worldwide, as they help solve challenges in areas such as meteorology, renewable energy, and aviation safety. Some potential IG applications to advance energy were given. Closing remarks with new open problems combined with the next research phase are provided.

Consumption is thus fundamentally related to sustainably because every decision pertaining to what to buy, what quantity the buy, how many to consume, or how to dispose of things has a direct influence on the natural world and the generations to come, and the overall impact of every single the customer's purchase is disastrous. A framework-based systematic literature review (SLR) was conducted to better comprehend the body of research on digital innovation and sustainability driving consumer behavior. This was done in order to acquire a deeper understanding of the studies that have already been done in this area. to provide (i) a comprehensive review of the current research landscape and (ii) a rich roadmap for future research. This study evaluated the literature especially in terms of theory, context, traits, and methodology. A total of 107 research articles published between 2013 and 2022 were found using scientific methods in the Scopus database. The findings showed that most research appears to have employed qualitative methodologies and was grounded in the setting of China and Italy. This review could help scholars better grasp the relationship between digital innovation and sustainability, opening the door for additional study and advancement in the field. Additionally, by extending the literature study and emphasizing the elements that can improve digital innovation and sustainability, practitioners will be given a better overall understanding of how to approach the problem.

The opportunistic pathogen Pseudomonas aeruginosa is responsible for numerous chronic infections and has a case fatality rate of 50%. All P. aeruginosa strains express β–lactamase, an enzyme capable of inactivating β–lactam antibiotics, including penicillins. However, β–lactams are still considered desirable therapeutics by physicians due to their low toxicity. The short-term goal of this study was to create an optimal model for ampC expression in P. aeruginosa and determine the selecting antibiotic to be used during mutagenesis. In the long term, this study aims to renew effectiveness of β–lactams by identifying potential allosteric binding sites on β–lactamase for the development of novel β–lactamase inhibitors. To create a system for ampC expression, the chromosomal P. aeruginosa ampC gene encoding for β–lactamase was cloned into Escherichia coli, then conjugated into P. aeruginosa ∆ampC. β– lactamase assays on recombinant E. coli and P. aeruginosa detected much higher production of β–lactamase in pMMB67HE, which was confirmed with antibiotic susceptibility testing (AST) to numerous β-lactams. From AST, carbenicillin was chosen as the antibiotic to select functional β–lactamase production during mutagenesis. Future work includes conducting mutagenesis on ampC to identify allosteric binding sites on the β–lactamase enzyme that may enable the discovery of new β–lactamase inhibitors. This work allows for the development of novel β–lactamase inhibitors that could renew the utility of β–lactams and drastically reduce morbidity and mortality from chronic Pseudomonas infections.

The perceived poor performance of publicly traded companies on their sustainability commitments and the quality of sustainability reporting has prompted stakeholders to consider the economic, environmental, and social impacts of corporate activities. Economic activities have led to various threats in the form of climate change, pollution, greenhouse gas emissions, natural disasters, and other issues that have negatively impacted the environment and stakeholders. Companies are expected to report to stakeholders on their sustainability performance, but reality proves that present reporting falls below stakeholders’ expectations mainly due to its still voluntary nature. The present study aims to provide a literature review of the relationship between sustainability reporting and the role of companies governance, especially observing if climate change requirements and energy-needed changes are being accounted. Results highlight mixed evidence for the influence of board governance attributes, providing interesting insights for research advancement. The study has practical implications for businesses, regulators, governments, and other stakeholders in their policy deliberations and investment decisions. Further empirical studies are recommended to re-examine sustainability reporting using the variables identified as important factors and gaps in this study and other board characteristics to improve the generalizability of the results.

A dataset collected from Central-South Finland is used to investigate the mortality of boreal trees. The mortality rate is found to be the order of three times that predicted by earlier Nordic mortality models, being in the upper range of international literature observations. Small subpopulations of any tree species tend to die out. Mortality of downy birch increases with stand basal area, as well as with stand age. Mortality of Norway spruce and silver birch increases after 100 years, while that of Scots pine is invariant to age. As the relative loss rate of basal area is insensitive to stand basal area, the mortality of trees does not strongly regulate thinning practices.

Green spaces localized in cities create favourable environmental conditions for Ixodes ricinus, the most widespread and important vector of tick-borne pathogens in Central Europe. In this study, we described the prevalence of Borrelia burgdorferi s.l. and Babesia species found in mono- and double infections among I. ricinus ticks occurring in urban areas of the city of Poznań, west-central Poland. Two tick groups were examined: (i) a group of 1,029 host-seeking ticks (460 nymphs, 289 females, and 280 males and (ii) a group of 1,268 engorged female ticks removed from 1,115 tick-infested animals, dogs and cats. The overall prevalence of B. burgdorferi s.l. found in host-seeking ticks was almost two-fold higher in comparison to ticks derived from pets (8.7 vs. 4.7%, respectively, χ2 test, P = 0.001). Borrelia afzelii and B. garinii were the most prevalent species both in ticks from vegetation (3.7% and 3.7%, respectively) and from pets (3.7% and 0.6%, respectively). Babesia infections were slightly more common in feeding ticks compared to those from vegetation (6.0 vs. 4.7%, respectively), however, the difference was not significant. Three Babesia species including Ba. microti, Ba. venatorum and Ba. canis were identified. Babesia canis and Ba. microti were the most prevalent in host-seeking (2.6% and 1.4%, respectively) and feeding ticks (2.8% and 2.2%, respectively), whereas Ba. venatorum was the rarest piroplasm. All Ba microti obtained sequences (n=42) were identical to Ba. microti genotype "Jena/Germany" that is considered as pathogenic to humans. Furthermore, the sequences of Ba. venatorum (n=17) were identical with those isolated from patients in Italy, Austria and Poland. Altogether, out of 121 Babesia-positive ticks, 19.8% were simultaneously infected with B. burgdorferi s.l. spirochetes. We found similar prevalences of co-infections in host-seeking (1.1%) as well as in feeding ticks (1.0%). In the first group, Ba. canis prevailed in coinfections (73%), mostly with B. afzelii and B. garinii, in the second group, Babesia microti dominated with B. afzelii (92.7%). This is the first finding documenting the co-occurrence of both pathogens in ticks from companion animals. The detection of Ba. microti and Ba. venatorum sequences identical to strains pathogenic to humans as well as predominance of LB spirochetes, B. afzelii and B. garinii in I. ricinus from vegetation and animals indicates that there is a potential risk of acquiring human babesiosis and/or Lyme borreliosis in urban areas of the city of Poznań. Although, the overall risk of encountering a Ba. microti and B. burgdorferi s.l. co-infected tick was low (1.0%), the potential for more severe clinical symptoms and complications deserves notice. A relatively high infection rates of Ba. canis in dog-derived ticks (3.2%) and in host-seeking ticks (2.6%), suggests that I. ricinus could potentially be involved in the circulation of this piroplasm in areas, where the competent vector, Dermacentor reticulatus is absent or rare.

The annual demand for fibres continues to rise worldwide. Consequently, more and more fibres must be produced to meet this demand, most of which are melt-spun polymeric man-made fibres. [1] Smooth filaments made of polymers are mainly used for technical applications in industry. For use in clothing or home textiles, for example, a texturing process is used to give the filaments a crimp and thus a feel like that of natural fibres. In this state, they can be processed together with natural fibres and used in textiles. Partially oriented yarns (POY) are of great importance in tex-turing. The yarns are mainly crimped with the help of the so-called false-twist texturing process (FTTP). [2] Since POY accounts for about 60 % of the melt-spun filament yarn produced world-wide, the FTTP is the most important texturing process in the textile industry [3]. In this paper, the main components of false-twist texturing (FTT) machines are explained along with the state of the art and research for each component and its influence on the process. Relevant patents are dis-cussed as well as process optimisation techniques, innovative polymers and yarn types recently used in FTT, followed by a conclusion and an outlook for the process.

Pagiophloeus tsushimanus, a new record of wood-boring pest first reported in China in 2014, has significantly infested Cinnamomum camphora across various administrative districts in Shanghai. And it shows a concerning trend of spread. The larval stage of the insect, being concealed within the trunks of C. camphora, exhibits characteristics such as hidden activity, strong destructiveness, and difficulty in control. This severely affects the normal growth of the host trees. While the primary host plant for P. tsushimanus is the C. camphora, preliminary observations have shown that the pest can also complete its life cycle on Cinnamomum chekiangensis and Phoebe chekiangensis. Both of them are significant species for urban greening. To explore the host selection preference of this beetle, this study investigates the olfactory selection behavior of adult P. tsushimanus towards C. camphora, C. chekiangensis, and P. chekiangensis. Results from choice tests, no-choice tests, and "Y"-shaped olfactometer experiments indicated that both male and female adults exhibited a feeding preference for C. camphora branches, with females showing a preference for laying eggs on C. camphora branches as well. Behavioral responses demonstrated a positive chemotaxis towards volatiles from C. camphora and a negative chemotaxis towards volatiles from C. chekiangensis and P. chekiangensis. Overall, the findings suggest that both male and female adults have a selective preference for volatiles emitted by C. camphora. These provides a theoretical basis for monitoring and controlling host shift occurrences in P. tsushimanus.

The fate of critically sick patients with infections in intensive care units (ICUs) is significantly influenced by antimicrobial resistance, which has become a serious concern in developing nations. This observational study was conducted at the IBN Sina Specialised Hospital in Dhaka, Bangladesh, over a 12-month period from January 2021 to December 2021, in order to track the pattern of antibiotic resistance among the patients admitted to the intensive care unit (ICU). Aspiration pneumonia (29%) and diabetes mellitus (24%), among 200 patients, were the most common main diagnoses. 65 samples (or 26%) of the 250 samples had 85 bacteria identified from them. Urine (14.12%) and tracheal aspirate (64.71%) were the most frequently found sites of infection. In the sample from the tracheal aspirate, Pseudomonas spp. (30.59%), Escherichia coli (24.71%), Acinetobacter spp. (20%), and Klebsiella spp. (14.12) were the most frequently isolated microorganisms. The following antibiotics were shown to have the highest overall patterns of resistance: levofloxacin (68.24), amikacin (64.71), meropenem (49.41), ceftazidime (75.29), ciprofloxacin (78.82), and gentamicin (82.35). The most effective antibiotic against Klebsiella species was meropenem (64.61%), while Acinetobacter species were mostly susceptible to cotrimoxazole (64.67%) and piperacillin + tazobactam (60.50%). Most susceptible to netilmicin (70.48%) and meropenem (49.32%) were Escherichia coli, while Pseudomonas spp. were mostly responsive to colistin (55.14%) and netilmicin (52.25%). Antibiotic resistance is common among intensive care unit (ICU) patients, and most isolated microbes have resistance to traditional medicines.

A three-year survey was conducted to estimate the incidence of grapevine trunk diseases (GTDs) in Greece and identify fungi associated with the disease complex. In total, 310 vineyards in different geographical regions in northern, central, and southern Greece were surveyed, and 533 fungal strains were isolated from diseased vines. Morphological, physiological and molecular (5.8S rRNA gene-ITS sequencing) analyses revealed that isolates belonged to 35 distinct fungal genera, including well-known (e.g. Botryosphaeria sp, Diaporthe spp., Eutypa sp., Diplodia sp., Fomitiporia sp., Phaeoacremonium spp., Phaeomoniella sp.) and lesser-known (e.g. Neosetophoma sp., Seimatosporium sp., Didymosphaeria sp., Kalmusia sp.) grapevine wood inhabitants. GTDs-inducing population structure differed significantly among the discrete geographical zones. Phaeomoniella chlamydospora (26.62%, n=70), Diaporthe spp. (18.25%, n=48) and F. mediterranea (10.27%, n=27) were the most prevalent in Heraklion, whereas D. seriata, Alternaria spp., P. chlamydospora and Fusarium spp. were predominant in Nemea (central Greece). In Amyntaio and Kavala (northern Greece), D. seriata was the most frequently isolated species (>50% frequency). Multi-genes (rDNA-ITS, LSU, tef1-α, tub2, act) sequencing of selected isolates, followed by pathogenicity tests revealed that Neosetophoma italica, Seimatosporium vitis, Didymosphaeria variabile and Kalmusia variispora caused wood infection with the former being the most virulent. To the best of our knowledge, this is the first report of N. italica associated with GTDs worldwide. This is also the first record of K. variispora, S. vitis and D. variabile associated with wood infection of grapevine in Greece. The potential associations of disease indices with vine age, cultivar, GTD-associated population structure and the prevailed meteorological conditions in different viticultural zones in Greece are presented and discussed.