The healthcare situation in Africa is characterized by limited resources and a high burden of disease, presenting significant challenges to the healthcare systems in the region. The integration of Artificial Intelligence (AI) technologies in African healthcare holds immense potential for addressing these challenges and improving health outcomes. This paper aims to provide a comprehensive understanding of the current healthcare landscape in Africa and the urgent need for AI-driven solutions.In addition to discussing the potential applications of AI in African healthcare, such as disease diagnosis, treatment planning, and medical imaging analysis, this manuscript seeks to shed light on the specific challenges hindering the implementation of AI in the region. By providing detailed examples and case studies, we aim to offer insights into the obstacles that need to be overcome and potential solutions that can be pursued.By leveraging AI technologies, Africa has the opportunity to revolutionize its health systems, bridging the gap in access to quality healthcare across the continent. The objective of this review article is to not only highlight the potential benefits that AI can bring to African healthcare but also to emphasize the urgent need for action and collaboration in implementing and scaling up AI innovations in the region. By doing so, African countries can pave the way for improved health outcomes and ensure that their populations receive the healthcare services they deserve.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

The review addresses a critical research gap in ethnobotanical knowledge within Kerala's tribal communities. A scarcity of studies hampers our understanding of their traditional practices, risking cultural erosion and knowledge loss. Synthesizing existing documentation, it aims to provide a comprehensive overview, emphasizing the urgent need for further research to impact sustainable resource management, biodiversity conservation, and tribal empowerment.

Over the last two decades, knowledge production, research and reconfiguration of universities have been understood as ways of giving new meanings to the university-society binomial. In this regard, humanities are the subject of multiple debates in the face of ideas about their impact in relation to the "other sciences". Based on these premises, this article sets out to explore possible meanings attributed by researchers to the concepts of commitment, mobilization and transfer of research in humanities in view of the debates on the university-society interaction and the third mission of the university (Alonso, Cuschnir and Napoli, 2021). The methodology used will address bibliographical analysis, theoretical background and statements from different institutions, as well as the analysis of material from four interviews. As a first instance, the preliminary results show that strengthening critical thinking as forms of commitment emerge as central senses, focusing on hungarian characteristics and productions in order to unravel the ways of understanding and imagining Eastern European reality. In this respect, the discussion of certain western knowledge is seen as a task associated with social commitment with public universities as a focus of resistance.

The rise of macrolide-resistant Mycoplasma pneumoniae (MRMP), marked bypoint mutations in the 23S rRNA gene, poses a growing global concern since its initial detection in 2001. The prominence of the A2063G mutation during this emergence remains unexplained. This study aimed to clarify the possibility of detecting MRMP from recent clinical macrolide-susceptible M. pneumoniae by exposure to azithromycin (AZM), which has a long half-life and was launched immediately before the first MRMP detection. Six strains isolated from Japanese children in 2019 and reference strain (FH), all belonging to the recent dominant P1 genotype, two or two subtype, were cultivated in a medium containing slightly higher concentrations than the originated minimum inhibitory concentration (MIC) of AZM and underwent sequencing if they grew. Four out of the seven strains grew after exposure to AZM, and C2617G, C2617A were detected, with no mutation in two strains. After another cultivation and sequencing, two of four strains grew and one was changed from C2617G to A2063G, and the other remained C2617A. The MIC of AZM in A2063G strains was 128 mg/mL; for C2617A, it was 0.0156 mg/mL. This is the first study to detect the strains with A2063G mutation from recent macrolide-susceptible M. pneumoniae using AZM exposure.

Background: Injury is an important cause of mortality and morbidity.(1). FA is the immediate assistance provided to a suddenly injured or sick person until professional help arrives or that person has recovered.(2), could be a potential factor differentiating between life and death in RTA . Many lives would be saved if proper first aid is provided early. (3) In the middle east, there are limited studies that explore knowledge and practices towards first aid needed during RTA. Objective: The main aim of this study is to investigate the knowledge and attitude towards first aid among drivers in Sharjah. Methodology: A cross-sectional study was conducted through a self-administered questionnaire written in Arabic and English languages. Participants were 18 years or older holding a driving license in the city of Sharjah. Paramedics and certified participants with a certification from authorized organizations were excluded . A non-proportional convenient sampling method was used. A total of 343 participants have completed the questionnaires. Data was entered and analysed using SPSS. Results: Majority of the study participants were less than 40 years old and (56.76%) were males. Most participants(94.2%) indicated that they know the term ‘First Aid’. However, (49.73%) of the participants knew the ambulance number and (52.43%) of the participants indicated that the victim should be moved to the hospital without the ambulance. With regards to attitude, 34.86% were not willing to provide first aid in the case of RTA. The main reason was lack of knowledge followed by fear of legal consequences. Most participants (83,78%) were willing to participate in first aid classes to improve their knowledge and attitude. Conclusion: Most participants are aware of the basic term of first aid; however, they are not willing to provide first aid in cases of RTA due to lack of knowledge and fear of legal consequences. Based on these findings we recommend providing first aid classes for new drivers and to obtain certification. References: 1 and 3. Midani, O., Tillawi, T., Saqer, A., Hammami, M., Taifour, H. and Mohammad, H., 2020. Knowledge And Attitude Toward First Aid: A Cross-Sectional Study In The United Arab Emirates. 2.Van de Velde S, Heselmans A, Roex A, Vandekerckhove P, Ramaekers D, Aertgeerts B. Effectiveness of nonresuscitative first aid training in laypersons:A systematic review. Ann Emerg Med 2009;54:447-57, 457e1-5.

This paper applies conceptualization from Paulo Freire, Tracey Nicholls, and bell hooks to develop a framework to understand art- and media-based communication of knowledge. Increasing use of art and digital media in research and formal educational settings emphasize knowledge-communication intent, and the theory attempts to rationalize why individuals potentially devalue, discard, or misconstrue messaging. Drawing upon two case studies: children’s literature, and existing scholarship on true crime as a media genre, the framework proposes art and media consumption based on perceived task-applicability of art and media. Stemming from the complex nature of socially-imposed, self-determined, and art- & media-instated tasks that an individual may face throughout their lifetime, an individual may be drawn to Freirean power and privilege - even fictional depictions - as societal structures can grant power and privilege with universal task-applicability. Potential usage of this framework towards participatory, qualitative inquiries conclude the paper, in attempt to support future art and media designed with knowledge-communication intent.

The unsupervised domain-adaptive vehicle reidentification approach aims to transfer knowledge from a labeled source domain to an unlabeled target domain, however there are knowledge differences between the target domain and the source domain. To reduce domain differences, existing unsupervised domain-adaptive rerecognition methods generally require access to the source domain data to assist in re-training the target domain model. But for security reasons, in many cases, data between different domains cannot communicate. To this end, this paper proposes an unsupervised domain-adaptive vehicle re-identification method based on source-free knowledge transfer. First, by constructing a passive domain knowledge migration module, the target domain is consistent with the source domain model output to train a generator to generate the "source-like samples". Then, it can effectively reduce the model knowledge difference and improve the model generalization performance. According to the experiment and testing of VeRi776 and VehicleID, two mainstream public data sets in this field, the rank-k and mAP indexes obtained are both improved, and are suitable for object re-recognition tasks without source data.

Many parameters and complex boundaries are involved in the spatial arrangement of an under-ground powerhouse for a hydropower station, which requires reference to many relevant cases and specifications. However, in practical applications, retrieving relevant cases or specifications is difficult, and there is a lack of knowledge of cascading logic among design parameters. For this question, a targeted knowledge graph based on knowledge graph management technology is established to support subsequent applications. This paper proposes a new concept of con-structing a knowledge graph for building information modeling (BIM) underground power-houses of hydropower stations. Firstly, the ontology skeleton of hydropower station spatial ar-rangement design, which represents the knowledge organization structure of the knowledge graph, is reconstructed by carefully analyzing the requirements for intelligent modeling of un-derground powerhouses. A large amount of unstructured data is identified based on optical character recognition (OCR) technology and is divided into words to extract correlation knowledge based on THULAC. In the next step, the knowledge triad of the spatial arrangement of the underground powerhouse is extracted based on ChatGPT and stored in a Neo4j knowledge base to build a knowledge graph. Finally, the knowledge graph is serviced to realize the query of knowledge and parameter recommendation to assist the digital intelligent design of spatial arrangement of an underground powerhouse of pumped storage hydropower stations.

Earth Observation (EO) techniques have significantly evolved over time, covering a wide range of applications in different domains. The scope of this study is to review the research conducted on EO in the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region and to identify the main knowledge gaps. We searched through the Web of Science database for papers published between 2018 and 2022 for EO studies in the EMMENA. We categorized the papers in the following thematic areas: Atmosphere, Water, Agriculture, Land, Disaster Risk Reduction (DRR), Cultural Heritage, Energy, Marine Safety and Security (MSS) and Big Earth Data (BED); 6647 papers were found with the highest number of publications in the thematic areas of BED (27%) and Land (22%). Most of the EMMENA countries are surrounded by sea, yet there was a very small number of studies on MSS (0.9% of total number of papers). This study detected a gap in fundamental research in the BED thematic area. Other future needs identified by this study are the limited availability of very high resolution and near real time remote sensing data, the lack of harmonized methodologies and the need for further development of models, algorithms, early warning systems and services.

Madagascar is a biodiversity hotspot with a long history of trading in its wildlife, especially its hyper diverse Amphibian taxa. Due to globally raised concerns over the conservation for harvested amphibian species on Madagascar, CITES was introduced as a global mechanism to monitor and regulate the trade. Utilising data collated from the CITES Trade database, this study sought to investigate the trade and CITES effectiveness in managing the trade. Over the 28 year period investigated, 20 known amphibian species were exported from Madagascar with a total of nearly 271,000 individuals. Formal descriptions of Malagasy amphibian species has and continues to increase greatly over time, there has not been a concomitant, longitudinal relationship in the numbers of individuals traded. Overall, the numbers of individuals traded has declined over time but, where assessments were provided by the IUCN Redlist, population declines were reported in all but one species of Malagasy amphibian. Mantella (97.5%) continue to dominate the trade with certain, high conservation concern species continuing in the trade. Despite early concerns over the effectiveness of CITES actions, after concerted efforts it appears that CITES actions were having an impact in regulating the trade. However, going forward, concerns remain over the appropriateness of the quotas set and the robustness of their underpinning NDFs. Furthermore, with the increase in recognised species raises the potential for incorrect species labelling on CITES permits that needs attention.

Background: The outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in the global COVID-19 pandemic. The urgency for an effective SARS-CoV-2 vaccine has led to the development of a first series of vaccines at unprecedented speed. The discovery of SARS-CoV-2 spike-glycoprotein mutants, however, and consequentially the potential to escape vaccine-induced protection and increased infectivity, demonstrates the persisting importance of monitoring SARS-CoV-2 mutations to enable early detection and tracking of genomic variants of concern. Results: We developed the CoVigator tool with three components: 1) a knowledge base that collects new SARS-CoV-2 genomic data, processes it and stores its results; 2) a comprehensive variant calling pipeline; 3) an interactive dashboard highlighting the most relevant findings. The knowledge base routinely downloads and processes virus genome assemblies or raw sequenc-ing data from the COVID-19 Data Portal (C19DP) and the European Nucleotide Archive (ENA), respectively. The results of the variant calling pipeline are visualized through the dashboard in the form of tables and customizable graphs, making it a versatile tool for tracking SARS-CoV-2 variants. We put a special emphasis on the identification of intrahost mutations and make available to the community what is, to the best of our knowledge, the largest dataset on SARS-CoV-2 intrahost mutations. In the spirit of open data, all CoVigator results are available for download. The CoVigator dashboard is accessible via covigator.tron-mainz.de. Conclusion: With increasing demand worldwide in genome surveillance for tracking the spread of SARS-CoV-2, CoVigator will be a valuable resource of up-to-date list of mutations, which can be incorporated into global efforts to sustainably prevent or treat infections.

The metabolic syndrome, first introduced by Hermann Haller in 1975, was sometimes also known as insulin resistance syndrome, syndrome X, and plurimetabolic syndrome. In 1989 it was rechristened by Kaplan as "Deadly Quartet" based on a consolidation of central obesity, impaired glucose tolerance, dyslipidemia, and systemic hypertension. Metabolic syndrome is positively associated with a pro-inflammatory and pro-thrombotic state, attributed to increased pro-thrombotic and inflammatory markers activity. Moreover, Metabolic syndrome is frequently associated with increased atherosclerotic cardiovascular disease, impaired glucose tolerance, hyperuricemia, obstructive sleep apnea, and chronic kidney disease. Despite concerted endeavors worldwide, the complexity of the pathophysiology of metabolic syndrome is still not clearly understood. Currently, therapeutic possibilities are confined to individual therapy of hyperglycemia, hypertension, hypertriglyceridemia, hyperuricemia, regular physical exercise, and a restricted diet.

Many educational institutions are using technology-enhanced learning. However, studies have shown that increased access to technological tools/gadgets is a precursor to incidents of cyberbullying. Using Bronfenbrenner’s Ecological Theory, we explored educators’ knowledge and intervention strategies regarding cyberbullying in schools. The design used in this study was qualitative and descriptive in nature. Purposive sampling technique was used to recruit a sample of eight educators working at secondary school in Johannesburg, South Africa. Data were collected using one-on-one interviews. Thematic analysis method was used to analyse the data. The findings revealed educators had sufficient knowledge of cyberbullying and how it affects learners in schools. However, interventions the teachers had put in place to prevent and manage incidences of cyberbullying were found to be ineffective due to parental disengagement and learners not reporting cases of cyberbullying. Recommendations for enhancing management of cyberbullying cases are provided.

Deep neural networks (DNN) have successfully delivered a cutting-edge performance in several fields. With the broader deployment of DNN models on critical applications, the security of DNNs becomes an active and yet nascent area. Attacks against DNNs can have catastrophic results, according to recent studies. Poisoning attacks, including backdoor and Trojan attacks, are one of the growing threats against DNNs. Having a wide-angle view of these evolving threats is essential to better understand the security issues. In this regard, creating a semantic model and a knowledge graph for poisoning attacks can reveal the relationships between attacks across intricate data to enhance the security knowledge landscape. In this paper, we propose a DNN Poisoning Attacks Ontology (DNNPAO) that would enhance knowledge sharing and enable further advancements in the field. To do so, we have performed a systematic review of the relevant literature to identify the current state. We collected 28,469 papers from IEEE, ScienceDirect, Web of Science, and Scopus databases, and from these papers, 712 research papers were screened in a rigorous process, and 55 poisoning attacks in DNNs were identified and classified. We extracted a taxonomy of the poisoning attacks as a scheme to develop DNNPAO. Subsequently, we used DNNPAO as a framework to create a knowledge base. Our findings open new lines of research within the field of AI security.

Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graph-based data model has seen ever-broadening adoption, particularly on the Web. This adoption has prompted the standardization of the SPARQL query language for RDF, as well as the development of a variety of local and distributed engines for processing queries over RDF graphs. These engines implement a diverse range of specialized techniques for storage, indexing, and query processing. A number of benchmarks, based on both synthetic and real-world data, have also emerged to allow for contrasting the performance of different query engines, often at large scale. This survey paper draws together these developments, providing a comprehensive review of the techniques, engines and benchmarks for querying RDF knowledge graphs.

Sherubtse College under Royal University of Bhutan has a total of 1582 students, where 787 0f them are female. They suffer from menstrual and menstrual cramps every month and they use napkins to stay clean and healthy. As all the college girls are educated on the norms and use of sanitary napkins, the proper management of the waste generated is lacking. The disposal of used sanitary napkins and management is a challenge to the college management. This small research aims to investigate on how girls in college campus manage the menstural waste and the amount of sanitary napkins used. The lack of proper dumping areas leads to the improper sanitary waste management and sometimes the waste generated from the sanitary napkins are toxic and unhealthy. It is very important to initate some ways to dump the pads and its related problem should be seriously addressed by the college management. It is also important to come up with different soultion and management of these wastes for sustainable environment. Therefore, this research will be mainly mentioning about the suggestions and how the sanitary waste is being managed in Sherubtse College campus and the amount of sanitary pads used in a month or an year.

The e-commerce platform in the digital economy era has evolved into a data platform ecosystem built around data resources and data mining technology systems. The most typical applications of big data are also concentrated in the field of e-commerce. E-commerce companies should first grasp the interactive relationship among the three major factors of data, technology and innovation, e-commerce platform operation is a multidisciplinary research field. It is not easy for researchers to obtain a panoramic view of the knowledge structure in this field. Knowledge graph is a kind of graph that shows the development process and structure relationship of knowledge with the field of knowledge as the object. It is not only a visual knowledge mapping, but also a serialized knowledge pedigree, which provides researchers with a quantitative research method for the development trend of statistics and academic status. The purpose of this research is to help researchers understand the key knowledge, evolutionary trends and research frontiers of current research. This study uses Citespace bibliometric analysis to analyze the data of the Science Net database and finds that: 1) The development of the research field has gone through three stages, and some representative key scholars and key documents have been recognized; 2) the common knowledge mapping of literature The co-occurrence of citations and keywords shows research hotspots; 3) The results of burst detection and central node analysis reveal research frontiers and development trends. Today, the visualization of big data brings different challenges. The abstraction between the world and today's data visualization occurs when the data is captured. Every user sees his own visualization data generated by standardized calculations. At the same time, there are still many controversies in the theoretical model, structure and structural dimensions. This is the direction that future researchers need to further study.

Knowledge and attitude towards mental illness play major role in the recognition, management, sociocultural factors and health seeking behavior among those with mental disorders. The study aim was to determine the knowledge and attitude among Nyamagana community members towards mental illness, Tanzania; A descriptive cross-sectional quantitative study involving 384 participants from sample population aged 18 years and above who were mentally health and semi-structured questionnaires was used to collect data. The results 110 (28.8%) respondents have good knowledge toward mental illness, about 292(76%) have negative attitude towards mentally ill people, 92(24%) respondents have positive attitude toward people who are mentally ill. More over about 318 (82.9%) respondents agreed that care and support of family and friends, could help people with mental illness to get rehabilitation while 66(17.1%) respondents disagreed on the care and support of the family and friends could help mentally ill people to get rehabilitation; The findings show most have poor knowledge and negative attitudes towards people with mental illness and may impair their social reintegration in the community. There’s need to develop strategies to enlighten the public regarding nature of mental illness so as to foster acceptance of people with mental illness by the community members.

(1) Background: Travel medicine practice has not been a part of practice in the community pharmacies in Japan. However, it’s getting more common for pharmacists to run travel clinic in North America. With ongoing globalization, Japanese pharmacists might be practicing travel medicine in future. This descriptive study is to examine the current knowledge, attitudes, and practices among Japanese community pharmacists. (2) Methods: Invitation to the study was sent to all pharmacies or corporates listed on Nippon Pharmacist Association member list plus one another large size pharmacy chain that was not member of NPhA. Community pharmacists working under those companies received a weblink to the survey. The survey was conducted from June to July 2017 by online questionnaire. (3) Results: The self-declared knowledge level of infectious diseases as well as travel vaccinations was generally low. The frequency of correct answer of the antibiotic resistance in South East Asia was 48.5%. Knowledge level of qunine resistance to Plasmodium falciparum malaria in Ghana and Nicaragua was very low. (4) Conclusions: Japanese community pharmacists are not familiar with travel related infectious diseases and vaccines used in travel medicine. The knowledge on the antibiotic resistance in traveler’s diarrhea and malaria prophylaxis was all low that is consistent with low degree of exposure to travel health questions from patients in daily practice and low percentage of intention to earn travel health certificates.

The challenges to sustainability governance across multiple geographical/cultural contexts lead us to the “piecemeal engineering” idea advocated by the philosopher Karl Popper, which explicitly considers context. We argue for adopting the piecemeal engineering approach, augmented by adaptive policies and modern (online) collaboration platforms to maximize the prospects of sustainable practices worldwide. This recommended course is not intended to be a theory in itself. Rather, it is a well-grounded, practical and practicable stop-gap measure in times when complexity and change outpace theories and strategies. We present a philosophical foundation for this “Augmented Popperian Experimentation.” Focusing on The Water Network (the largest collaborative platform for water researchers and professionals), we show that sustainability-oriented organizations in the water realm and others are inching toward the practice we advocate. We discuss implications.

The extensive use of rare earth elements (REEs) in a number of technologies is expected to impact on human health, including occupational REE exposures. A body of experimental evidence on REE-associated toxicity has been accumulated in recent decades. Unlike experimental studies, the consequences of REE exposures to human health have been subjected to relatively fewer investigations. Geographical studies have been conducted on residents in the Chinese REE mining districts, reporting on REE bioaccumulation, and associations between REE residential exposures and adverse health effects. A more limited series of studies has been focused on occupational REE exposures, such as movie operator (with occurrence of cerium aerosol) with the observation of pneumoconiosis and lung fibrosis. Similar effects have been reported in case reports for other workers, such as a lens grinder and a printer exposed to carbon-arc lamp emission. As for the occupations related to REE mining and processing, REE bioaccumulation in scalp hair and excess REE urine levels were reported. A study was devoted to workers employed in e-waste separation, showing alterations of several plasma markers. As for other REE occupational exposures, mention should be made of: a) mechanical workshops, with exposures to diesel exhaust microparticulate (containing nanoCeO₂ as a catalytic additive) and, b) production and manufacture of REE supermagnets for hybrid engines and wind turbines. Diesel exhaust microparticulate has been studied in animal models, leading to evidence of several pathological effects in animals exposed by respiratory or systemic routes. As for supermagnet production and manufacture, a body of literature is reviewed of experimental studies, and of human exposure studies showing several pathological effects of static magnetic fields, warranting further investigations.

In this paper we show that the Schwarzschild radius can be extracted easily from any gravitationally-linked phenomena without having knowledge of the Newton gravitational constant or the mass size of the gravitational object. Further, the Schwarzschild radius can be used to predict any gravity phenomena accurately, again without knowledge of the Newton gravitational constant and also without knowledge of the size of the mass, although this may seem surprising at first. Hidden within the Schwarzschild radius are the mass of the gravitational object, the Planck mass (their relative mass), and the Planck length. We do not claim to have all the answers, but this seems to indicate that gravity is quantized, even at a cosmological scale, and this quantization is directly linked to the Planck units. This also supports our view that the Newton gravitational constant is a universal composite constant of the form $G=\frac{l_p^2{c}^3}{\hslash }$ , rather than relying on the Planck units as a function of G. This does not mean that Newton’s gravitational constant is not a universal constant, but that it is instead a composite universal constant that depends on the Planck length, the speed of light, and the Planck constant. Further, $\frac{G\times 1\hspace{0.17em}\mathrm{weight}\hspace{0.17em}\mathrm{unit}}{c^2}=\frac{G}{c^2}$ is the Schwarzschild radius off one weight unit. So G is only needed when we want to use gravity to find the weight of an object, such as weighing the Earth. This is, to our knowledge, the first paper that shows how a long series of major gravity predictions and measurements can be completed without any knowledge of the mass size of the object, or Newton’s gravitational constant. As a minimum we think it provides an interesting new angle for evaluating existing gravity theories, and it may even give us a small hint on how to combine quantum gravity with Newton and Einstein gravity.

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

Artificial intelligence (AI) is increasingly being used to improve the quality control of point-of-care diagnostics. This is caused by a number of factors, including the following: 1. AI can accelerate and improve testing accuracy. In comparison to humans, AI technology can review data more quickly and precisely, reducing errors and improving overall quality assurance. 2. When it comes to improving POC test findings on healthcare issues such as infectious diseases or medical crises such as heart attacks, AI can be used for sophisticated predictive analytics and modeling that aid in better decision-making. 3. Artificial intelligence facilitates process automation, increasing productivity and lowering labor costs in labor-intensive tasks such as testing and analyzing samples collected at point-of-care facilities. 4. The use of AI enables organizations implementing these solutions to gain insights from large volumes of raw diagnostic data generated faster and more accurately, allowing them to build solid frameworks around preventive care initiatives and significantly influence public health outcomes.5. Artificial intelligence (AI) has been demonstrated to be a useful tool for real-time monitoring systems that identify any problems with test results early so that they can be corrected before affected patients receive inaccurate diagnoses or treatment plans based on false information provided by diagnostic tests performed at points of care such as clinics or hospitals.Using these technologies would allow healthcare organizations to spend less on labor while still receiving exact diagnoses and rapid treatment delivery at a fraction of the cost that manual approaches required earlier.

In Nigeria, Cervical cancer (CC) and lack of Human Papillomavirus (HPV) awareness poses significant HPV infection risk among women. This study was conducted at Ibrahim Badamasi Babangida (IBB) University in Nigeria; focused on assessing HPV awareness and knowledge, particularly concerning its association with CC and oral contraceptive (OC) pills among students and staff. We adapted and validated a 20-item HPV knowledge scale and explored factors influencing knowledge, vaccination rates, awareness, and the impact of ethnicity on HPV knowledge. Also, due to the non-normality of the knowledge score, non-parametric tests were done. Data were summarized using median and interquartile range (IQR), while categorical data were presented in frequency and percentage distribution. We established the reliability of the 20-item knowledge scale with a strong Cronbach's alpha coefficient of 0.913, indicating internal consistency. However, it revealed a concerning lack of awareness and knowledge about HPV, only 34.8% of participants were aware of HPV infection, and only 25.0% knew about HPV vaccine. Additionally, ethnicity was identified as a significant factor affecting HPV knowledge. Considering these findings, this study emphasizes the need for targeted interventions to enhance HPV awareness and knowledge, particularly among specific ethnic groups. Despite the development and validation of a reliable knowledge scale, the study underscores the importance of educational initiatives to address this knowledge gap, ultimately reducing the risk of HPV infection and CC in Nigeria.

This paper presents two control design strategies for voltage regulation in a single inductor dual output (SIDO) DC-DC Buck converter system. Based on a nominal multiple input multiple output (MIMO) plant model and performance requirements, both an LQR and a decoupled PI control laws are designed to control the power converter system, under parametric uncertainties such as voltage source variation, CPL power variation, and load resistance variation. Therefore, the SIDO converter can cascade operating, which may cause the undesired effects of voltage oscillation and reduce the system's stability margin. The control performance was assessed under both uncertainties resistive loading and power variation of a constant power load (CPL). A SIDO DC-DC Buck converter board has been developed for experimental tests. The experimental results show that the LQR strategy, compared to the PI strategy, presented a robust performance in the presence of parametric uncertainties in the resistive loads being, however, sensitive to uncertainties due to the presence of CPL loads.

Intellecta dataset emerges as an innovative synthetic dataset, engineered to enhance the cognitive processing capabilities of contemporary language models. With a composition of 11.53 billion tokens, integrating 8.01 billion tokens of synthetic data with 3.52 billion tokens of rich textbook data, Intellecta is crafted to foster advanced reasoning and comprehensive educational narrative generation. Leveraging the Mixtral-8x7B-Instruct-v0.1 model, the dataset facilitates the generation of complex thought processes and detailed, textbook-style explanations, thus enabling language models to engage in both critical thinking and profound educational discourse. This hybrid dataset stands as a testament to the potential of synthetic data in pushing the boundaries of AI, offering a repository that is not only vast and varied but also refined to align with ethical standards and intellectual rigor.

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

The transition to sustainability requires major behavioural changes. This requires a complete rethinking of ecosystems and their interconnections, reassessing environmental issues, and a behavior change manifesting. Thus, understanding how sustainability Knowledge, Attitudes, and Practices (KAP) change is essential to sustainability as they shape human behaviour. The main aim of this study was to investigate the constructs of sustainability KAP among university and non-university populations. Data were collected using a structured questionnaire of items measured on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The questionnaire was distributed to diverse participants, ensuring a broad representation of views on sustainability. There are ten sociodemographic variables, 344 respondents in UAE where the female (28.5%) and male (13.7%), (58.1%) participants did not belong to the UAE university and their age fall into the 18-24 years old. The mean scores indicate a positive orientation towards sustainability, with Knowledge (M = 4.2272), Attitudes (M = 4.2650), and Practices (M = 3.8198) all above the midpoint and the UAE university students showed more knowledge, attitude and practices scores ‎than others population. Associations between KAP were significant at a significant level of p < 0.05. This indicates that the next generation will have more environmentally KAP.

European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills skills gap and/or enables acquisition of new ones related to the planning and implementation of such solutions can empower local/ regional authorities to identify them, adopt them and eventually deliver them properly. The aim of this paper is to present the Key Performance Indicator (KPI) framework that has been used for the assessment of the effectiveness of the Learning and Exchange Programme applied in an EU-funded project. It presents the methodological steps for the adoption of the KPIs, as well as the tools used for the selection of the KPI data and the KPI monitoring at project level. It also presents the results from the application of the framework for assessing the knowledge performance towards the deployment of sustainable mobility solutions. It finally reflects on recommendations for applying the KPI framework to other cases and thematic contents.

Geospatial knowledge in massive academic papers can provide knowledge services such as location-based research hotspot analysis, spatio-temporal data aggregation, research results recommendation, etc. However, geospatial knowledge often exists implicitly in literature resources in unstructured form, which is difficult to be directly accessed and mined and utilized for rapid production of massive thematic maps. In this paper, we take the geospatial knowledge of the area studied as an example and introduce its extraction method in detail. An integrated feature template matching and random forest classification algorithm is proposed for accurately identifying research areas from the abstract texts of academic papers and producing thematic maps. Firstly, the precise recognition of geographical names is achieved step by step based on BiLSTM-CRF algorithm and improved heuristic disambiguation method; then, the area studied is extracted by the designed integrated feature recognition template of area studied using random forest classification algorithm, and a fast thematic map is designed for the knowledge of area studied, topic and literature. The experimental results show that the area studied recognition accuracy can reach 97%, the F-value is 96%, and the recall rate reaches 96%, achieving high accuracy and high efficiency of area studied extraction in text. Based on the geospatial knowledge, the thematic map can achieve the effect of fast map formation and accurate expression.

Keywords: iron deficiency anemia; IDA; anemia; knowledge; awareness.

Digital Twin Cities (DTCs) play a fundamental role in city planning and management. They allow three-dimensional modeling and simulation of cities. 3D semantic segmentation is the foundation for automatically creating enriched DTCs, as well as their updates. Past studies indicate that prior level fusion approaches demonstrate more promising precisions in 3D semantic segmentation compared to point level fusion, features level fusion, and decision level fusion families. In order to improve point cloud enriched semantic segmentation outcomes, this article proposes a new approach for 3D point cloud semantic segmentation through developing and benchmarking three prior level fusion scenarios. A reference approach based on point clouds and aerial images was proposed to compare it with the different developed scenarios. In each scenario, we inject a specific prior knowledge (geometric features,classified images ,etc) and aerial images as attributes of point clouds into the neural network’s learning pipeline. The objective is to find the one that integrates the most significant prior knowledge and enhances neural network knowledge more profoundly, which we have named the "smart fusion approach". The advanced Deep Learning algorithm "RandLaNet" was adopted to implement the different proposed scenarios and the reference approach, due to its excellent performance demonstrated in the literature. The introduction of some significant features associated with the label classes facilitated the learning process and improved the semantic segmentation results that can be achievable with the same neural network alone. Overall, our contribution provides a promising solution for addressing some challenges, in particular more accurate extraction of semantically rich objects from the urban fabric. An assessment of the semantic segmentation results obtained by the different scenarios is performed based on metrics computation and visual investigations. Finally,the smart fusion approach was derived based on the obtained qualitative and quantitative results.

this article presents the results of implementing existing software tools in the accounting field. The teaching processes regarding the use of Learning and Knowledge Technologies (TAC) in the university environment, and very specifically, in what has to do with the pedagogical integration of the same in the curriculum is deficient and disjointed with the current technological development. Thus, in the different curricula of professional programs of Public Accounting and related, the courses related to computer automation processes are oriented only towards the management of computer science and accounting software and the great diversity of existing applications that would undoubtedly directly benefit the student to know the potential of these in their future accounting practice is not taken into account. Strengthen the various skills of a Public Accountant in training through Learning and Knowledge Technologies (TAC), under the hypothesis of developing skills in the accounting field through TACs. The research was developed using a quantitative approach, an empirical-analytical method, with a type of descriptive research under an experimental design based on G1 x O1 and G2–O2, three phases were defined. In the first phase, the characterization of the existing software tools in the accounting field was carried out. In the second phase, their relevance was determined. In the third phase, performance was evaluated and then classified in a repository. The data obtained were analyzed with parametric analysis techniques through which it was found that the difference in quantitative results in the academic process between the experimental and control groups was statistically significant, which concluded the success of the experimental treatment. The use of CT scans in the classroom by the experimental group resulted in an improvement in their academic performance compared to the control group, strengthening their self-learning processes and facilitating the development of cognitive functions and skills necessary in the exercise of their accounting profession. This research supports and strengthens the work skills developed in the classroom for public accounting students. The tools TAC is developed from the request made by the radiometry laboratory as a first phase and a second phase is necessary for validation with experts.

Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modelling capability as well as a high-level of customisation and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad-hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such a complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as it suitable within a number of applications contexts - i.e. as a research/educational tool, communication framework, gamification and participatory modelling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.

In this paper we try to demonstrate that the classical model of certainty factos for dealing with innacurate knowledge can be efficiently implemented in a quantum environment. For this, we assume that certainty factors are strongly correlated with the quantum probability. We first explore the certainty factors approach for inexact reasoning from a classical point of view. Next, we introduce some basic aspects of quantum computing, and we pay special attention to quantum rule-based systems. We then build a use case: an inferential network to be implemented in both, the classical approach and the corresponding quantum circuit. Both implementations have been used to compare the behavior of the classical and the quantum approaches when confronted with the same hypothetical case. We analyze three different situations: (1) Only Imprecision (which refers to inaccuracy in declarative knowledge or facts) is present in the use case, (2) Only Uncertainty (which refers to inaccuracy in procedural knowledge or rules) is present in the use case, and (3) Both Imprecision and Uncertainty are present in the use case. Finally, we analyze the results to reach a conclusion about the eventually intrinsic probabilistic nature of the certainty factors model and to pave the way for future quantum implementations of this method for handling inaccurate knowledge.

Rich biodiversity is one of the Philippines’ greatest assets. Unfortunately, there is a continuous decline in the diversity of flora and fauna across the world. This calls for the need to educate people, especially younger generations, to value and protect biodiversity and natural resources. The study aimed to assess the students’ extent of knowledge and identify their perspectives towards biodiversity and its protection and conservation. A total of 268 randomly selected students at Aurora State College of Technology Zabali Campus were involved in the study. Survey questionnaires were used to obtain data and information which were subjected to statistical tests. The students had a moderate knowledge level on biodiversity with a mean score of 6.65 out of 10 items (SD = 1.50). Their perspective on biodiversity was leaning toward its protection and conservation, with a mean score of 7.2 out of 10 items (SD = 1.29). Factors affecting the students’ knowledge were gender (p = .003) and academic department (p = 0.003). Females and those associated with the Department of Forestry and Environmental Sciences and Department of Industrial technology were found to have more knowledge than the others. Males, on the other hand, were found to have a more positive perspective towards biodiversity. Knowledge and perspective had a weak correlation with r = 0.39. Students were not well-aware, but were in support of the Philippines’ biodiversity-related laws, which could help shape their mindset and actions towards biodiversity conservation and protection. As an implication, the college administration must revisit the curricula of all degree programs and ensure that students from each degree program are environmentally educated, emphasizing biodiversity conservation.

We report four allelic variants (3 novel) in three genes previously established as causal for hypopituitarism or related disorders. A novel homozygous variant in the growth hormone gene, GH1 c.171delT (p. Phe 57Leufs * 43), was found in a male patient with severe isolated growth hormone deficiency (IGHD) born to consanguineous parents. A SOX3 allelic variant (p.Met304Ile) was found in a male patient with IGHD and hypoplastic anterior pituitary. YASARA, a tool to evaluate protein stability, suggests that p.Met304Ile destabilizes the SOX3 protein (ΔΔG = 2.49 kcal/mol). A rare, heterozygous missense variant in the TALE homeobox protein gene, TGIF1 (c.268C>T:p.Arg90Cys) was found in a patient with combined pituitary hormone deficiency (CPHD), diabetes insipidus, and syndromic features of holoprosencephaly (HPE). A novel heterozygous TGIF1 variant (c.82T>C:p.Ser28Pro) was identified in a patient with CPHD, pituitary aplasia and ectopic posterior lobe. Both TGIF1 variants have an autosomal dominant pattern of inheritance with incomplete penetrance. In conclusion, we have found allelic variants in 3 genes in hypopituitarism patients. We discuss these variants and associated patient phenotypes in relation to previously reported variants in these genes, expanding our knowledge of the phenotypic spectrum in patient populations.

Irrational use or misuse of antibiotics, particularly by outpatients, increases antibiotic resistance. A lack of public knowledge about ‘Responsible use of antibiotics’ and ‘How to obtain antibiotics’ is a major cause of this. This study aimed to assess the effectiveness of an educational video about antibiotics and antibiotics use to increase outpatient's knowledge in two public hospitals in East Java, Indonesia. A quasi-experimental research setting was used with a one-group pretest-posttest design, carried out from November 2018 to January 2019. The study population consisted of outpatients, to whom antibiotics were prescribed, in two public hospitals in East Java, Indonesia. Participants were selected using a purposive sampling technique; 98 outpatients at MZ General Hospital in S regency and 96 at SG General Hospital in L regency were included. A questionnaire was used to measure the respondents’ knowledge and consisted of five domains, i.e. definition of infections and antibiotics, obtaining the antibiotics, directions of use, storage instructions, antibiotic resistance. The knowledge test score was the total score of the Guttman scale (a dichotomy of ‘yes’ or ‘no’ answers). To determine the significance of the difference in knowledge before and after providing the educational video and in the knowledge score between hospitals, the (paired) Student’s t-test was applied. The educational videos significantly improved outpatients' knowledge, which increased with 41% in MZ General Hospital and 42% in SG General Hospital. An educational video is a useful method to improve the knowledge of the outpatients regarding antibiotics.

Knowledge processing is an important feature of intelligence in general and artificial intelligence in particular. To develop computing systems working with knowledge, it is necessary to elaborate means of working with knowledge representations (as opposed to data) because knowledge is an abstract structure. There are different forms of knowledge representations derived from data. One of the basic forms is called a schema. The goal of this paper is the development of theoretical and practical tools for processing schemas. To achieve this goal, we use schema representations elaborated in the mathematical theory of schemas and use structural machine as a powerful theoretical tool for modeling parallel and concurrent computational processes. We describe the schema of autopoietic machines as physical realizations of structural machines. An autopoietic Machine is a technical system capable of regenerating, reproducing and maintaining itself by production, transformation and destruction of its components and the networks of processes downstream contained in them. We present the theory and practice of designing and implementing autopoietic machines as information processing structures integrating both symbolic computing and neural networks. Autopoietic machines use knowledge structures containing the behavioral evolution of the system and its interactions with the environment to maintain stability by counteracting fluctuations.

In the last two decades, there have been massive advancements in high throughput technologies, which resulted in the exponential growth of public repositories of gene expression datasets for various phenotypes. It is possible to unravel biomarkers by comparing the gene expression levels under different conditions, such as disease vs. control, treated vs. not treated, drug A vs. drug B, etc. This problem refers to a well-studied problem in the machine learning domain, i.e., the feature selection problem. In biological data analysis, most of the computational feature selection methodologies were taken from other fields, without considering the nature of the biological data. For gene expression data analysis, most of the existing feature selection methods rely on expression values alone to select the genes; and biological knowledge is integrated at the end of the analysis in order to gain biological insights or to support the initial findings. Thus, integrative approaches that utilize the biological knowledge while performing feature selection are necessary for this kind of data. The main idea behind the integrative gene selection process is to generate a ranked list of genes considering both the statistical metrics that are applied to the gene expression data, and the biological background information which is provided as external datasets. Since the integrative approach attracted attention in the gene expression domain, lately the gene selection process shifted from being purely data-centric to more incorporative analysis with additional biological knowledge.

Climate change and food security are the most relevant issues to be considered in sustainable agricultural development. The FAO’s initiative of climate-smart agriculture has attracted international attention. Since then, the smart agriculture (SA) has been recognized as the most influential trends in contributing to agricultural development. Therefore, encouraging farmers to adopt digital technologies and mobile devices into farming practices becomes a policy priority worldwide. However, there is limited literature available on psychologic factors that drive farmers’ intentions to adopt SA technologies. The purpose of this study is to investigate how farmer’s knowledge and attitude toward SA affects their adoption of smart technologies in Taiwan. A total of 321 farmers participated in the project’s survey in 2017 and 2018, from which the data was used to perform an OLS regression model of SA adoption. This study contributes to a preliminary understanding of relationship between innovation and adoption of SA technologies in a small-scale farming economic context. The findings suggest that the policy makers and R&D institutes need to concentrate on improving market access for well-known and high important SA technologies.

Data science is facing the following major challenges: (1) developing scalable cross-disciplinary capabilities, (2) dealing with the increasing data volumes and their inherent complexity, (3) building tools that help to build trust, (4) creating mechanisms to efficiently operate in the domain of scientific assertions, (5) turning data into actionable knowledge units and (6) promoting data interoperability. As a way to overcome these challenges, we further develop the proposals by early Internet pioneers for Digital Objects as encapsulations of data and metadata made accessible by persistent identifiers. In the past decade, this concept was revisited by various groups within the Research Data Alliance and put in the context of the FAIR Guiding Principles for findable, accessible, interoperable and reusable data. The basic components of a FAIR Digital Object (FDO) as a self-contained, typed, machine-actionable data package are explained. A survey of use cases has indicated the growing interest of research communities in FDO solutions. We conclude that the FDO concept has the potential to act as the interoperable federative core of a hyperinfrastructure initiative such as the European Open Science Cloud (EOSC).

Small bowel carcinomas (SBC) are uncommon neoplasms, whose predisposing conditions include hereditary syndromes and immune-mediated intestinal disorders, including coeliac disease (CD) and Crohn’s disease (CrD). Although both CD-associated SBC (CD-SBC) and CrD-associated SBC (CrD-SBC) arise from an inflammatory background, they differ substantially in tumour cell phenotype, frequency of microsatellite instability and nuclear β-catenin expression, as well as in prognosis. For these patients, high tumor-infiltrating lymphocyte density and glandular/medullary histotype represent independent positive prognostic factors. Dysplasia adjacent to SBC is rare and characterized by intestinal phenotype and nuclear β-catenin in CD, while it is frequent and typified by gastro-pancreatobiliary marker expression and preserved membranous β-catenin in CrD. Recent evidence suggests that Epstein-Barr virus-positive dysplasia and SBC, albeit exceptional, do exist and are associated with CrD. In this review we summarize the novel pathological and molecular insights of clinical and therapeutic interest to guide the care of CD-SBC and CrD-SBC.

Tuberculosis (TB) associated stigma is well-documented phenomenon that may contribute to sub-optimal TB care in Pakistan. The objective of study was to assess TB related knowledge and perceived stigma among community members. This was cross-sectional survey using convenience sample of 183 individuals recruited between October and December 2017. A validated stigma measurement tool developed by Van Rie et al. was adapted. Data was analyzed using SPSS version 20.0. 183 individuals (73% males; n = 134) participated in survey. Eighty-seven percent were aware that TB is curable disease (n = 159) and 91% thought that it could be transmitted by coughing (n = 167). However, respondents also thought that TB was spread through contaminated food (73%; n = 134), sharing meals (55%; n = 100), sharing utensils (53%; n = 96) and by having sexual intercourse with a TB patient (51%; n = 93). Fifty-seven percent (n = 104) associated TB with high levels of stigma. Persons who had less than six years of education (crude OR = 1.2; 95% CI: 0.89, 1.72) and lacked knowledge that TB is curable (crude OR = 3.42; 95% CI: 1.20, 9.70) were more likely to associate TB with stigma. In addition, females (crude OR = 1.33; 95% CI: 0.87, 2.04) and those who were unemployed (crude OR = 1.06; 95% CI: 0.65, 1.74) were also more likely to associate TB with stigma. We found an association between lack of knowledge about TB and perceived stigma. This highlights need for improved education and awareness about TB.

Reusing the tactile knowledge of some previously explored objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample plus the feature observations of prior objects. By incorporating the auxiliary features, the transfer learning improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer).

This study aims to unravel the paradox of perceptions and knowledge of the flood victims towards the causes of the disaster in both internal and external context. Internal context comprises of a comparison of perceptions and knowledge based on individual characteristics (age, gender, education and income). Whereas, the external context includes the factors of the awareness of the victims towards the amount of rainfall, the impact of land use changes as well as the negligence of the responsible parties. The main objective of this study is to determine the differences of perception and knowledge of December 2014 flood victims in Kelantan towards the factors that lead to the flood. This disaster had resulted in huge amount of money loss as well as traumatize the victims in which can be felt to this day. Since that incident, there were various points of view and different perceptions in finding the cause of the disaster occurred. Besides that, the study found that the level of perception and knowledge as to the cause of the disaster is different in the internal context (individual characteristics). This difference has a significant influence on the awareness of the causes of the floods that occurred in the external context. Significant relationships at the level of p <0.05 has existed between perception and knowledge of the causes of the disaster victims affected by environmental changes in the last 10 years. This indicates that although the victim is aware of the physical environment changes happening around them, but all that is seen as not a major contributing factor to the cause of the floods in Kelantan in 2014.

Background: Fertility is a crucial component of population maintenance and growth. A declin-ing fertility trend has been observed over the past two decades, and it continues. Objective: The aim of this research was to examine the level of fertility knowledge, factors in-fluencing fertility knowledge, and the relationship between fertility knowledge and the decision to have a child. Methods: A cross-sectional study was conducted on a sample of mothers in five hospitals on the Adriatic coast of the Republic of Croatia, involving 1541 mothers from September 2021 to De-cember 2023. The Cardiff Fertility Knowledge Scale was used for the research. Results: The participants were divided into two groups based on fertility status in women, spe-cifically the period of declining fertility in women. Group 1 included participants aged 18-31 with sustained fertility, and Group 2 included participants aged 32 and older experiencing de-clining fertility. Fertility knowledge was 58.9%. Women with higher educational status showed better results (62.3%). The most common sources of fertility knowledge were the healthcare sys-tem and the internet. Factors associated with the level of fertility knowledge included higher education, marital status, and higher economic status. Conclusion: The research results reveal a lack of fertility knowledge among participants, as well as an intention to have a child in later stages of life. The lack of formal education on this topic leads to information gathering from unreliable sources.

Some current systematized reviews of macroalgae are concise and descriptive, but it is important to conduct these of a larger number of taxa to facilitate visualizations of the types of primordial research, relevant methods, and areas of opportunity. The aim was to elaborate the state of the art in the taxonomic knowledge of Dictyota based on a systematized review of the generated information since its original description (1809 to 2023). We conducted a search for names and literature in different databases, followed by a temporal analysis (by century and bidecadal). To date, a total of 313 names have been registered for Dictyota; 108 are accepted names. The largest number of registered taxonomic names (207) was found for the 19th century, derived from large expeditions. Our analysis of literature involved 318 publications, 89 of which corresponded to alpha taxonomy, 187 to beta, and 42 to gamma. We determined that the trend in taxonomic works is integrative in nature because they include other disciplines to explain aspects that go beyond taxonomic description. Our analysis suggests that extensive reviews and monographic approaches are still required to achieve a better understanding of the genus. The effort in integrative taxonomy must be intensified, which allow improve the systematic of Dictyota.

Background: Dermatophytosis, commonly known as tinea, poses a significant public health concern worldwide, especially in environments with poor hygiene and overcrowding, such as prisons. Despite its prevalence and impact on quality of life, there is a lack of research on the knowledge and hygiene practices regarding dermatophytosis among prisoners, particularly in Nepal. Objective: The study aimed to assess prisoners' knowledge, hygiene practice and infection status regarding dermatophytosis in Central Prison, Nepal. Methods: A descriptive cross-sectional study with a sample size of 184 respondents was designed to collect data using a validated pre-tested questionnaire from September 2023 to January 2024. The collected data was then analysed using IBM SPSS version 21. Knowledge and hygiene practices were measured on an eight and 11-point scale and rated as poor (≤4) and sound (>4), bad (≤6), and good (>6), respectively. Summary data were presented by descriptive, while Chi-square and logistic regression were used for inferential statistics at P < 0.05. Results: The findings revealed moderate knowledge among prisoners regarding dermatophytosis, with significant gaps in understanding its spread and prevention. While most prisoners recognised the importance of treatment, there were misconceptions about the inevitability of contracting dermatophytosis and the role of personal hygiene. Conclusions: Despite good knowledge levels, adherence to recommended hygiene practices was suboptimal, highlighting the need for targeted interventions. The study underscores the importance of addressing knowledge gaps, changing attitudes, and promoting hygienic practices to mitigate the burden of dermatophytosis among prisoners.

Knowledge of clinical approaches and barriers in managing childhood myopia is limited. This study explores optometrists' knowledge, attitude, and practice towards childhood myopia. A 26-item survey was circulated online among practising optometrists in India. The questionnaire assessed the demographics, knowledge, self-reported clinical practice behaviour, barriers, source of information guiding their management, and extent of adult caregiver engagement for childhood myopia. Of 393 responses, a significant proportion of respondents (32.6%–92.4%) were unaware of the ocular complications associated with high myopia, with less than half (46.5%) routinely measuring axial length in clinical practice. Despite the improved awareness of emerging myopia management options, the uptake remains generally poor, with single-vision distance full correction spectacles (70.3%) being the most common mode of vision correction. Barriers to adopting emerging evidence are medico-legal concerns and the absence of clinical practice guidelines. Original research articles were the primary source of information supporting clinical practice. Most (>70%) respondents considered involving the adult caregiver in their child's clinical decision-making process. While practitioner knowledge, perspective, and practice are improving, childhood myopia management evidence is constantly evolving and remains inconclusive. Evidence-based practice guidelines and continuing education on myopia control might be helpful for practitioners in improving their clinical decision-making skills.

Aging is a major risk factor for the higher incidence and prevalence of chronic conditions, such as cancer, cardiovascular and metabolic diseases, and neurodegenerative diseases. Closely linked with the onset of all these age-related diseases is immunosenescence, a condition defined as progressive reconfiguration of the immune functions leading to an increased susceptibility to infectious diseases, poorer response to vaccination, increased prevalence of cancer, rheumatoid arthritis, and other chronic diseases characterized by a pro-inflammatory state named inflammaging. Given that immunosenescence frames age-related diseases, it is natural to ask how these illnesses are related under the context of innate and adaptative components of the immune system. Knowledge processing by Formal Concept Analysis (FCA) of age-related diseases framed in an immunosenescence multivalued context shows that a hierarchy among these diseases emerges with a subconcept-superconcept nested structure, with two clusters, first made of metabolic diseases, cancer, and cardiovascular diseases. Second metabolic and neurodegenerative diseases and rheumatoid arthritis. Metabolic diseases seem to be a pivot illness and they must be a primary target given their global incidence and prevalence and their cost-effective treatments like regular physical activity, weight loss, healthy diet, stopping smoking, and reducing or managing stress. Another implication of the ontological analysis of age-related diseases is about the nature of immunosenescence, suggesting that initial symptoms of age-related diseases are mainly related to innate immune mechanisms, and developing of severe symptoms of age-related diseases like cancer, cardiovascular or neurodegenerative diseases depends on the activation of acquired immunity processes.

Culture signifies the customs, language, ceremonies, Indigenous Medical Knowledge (IMK) and other material objects of a tribe. These and many other features are a representation of identity for many Zambian communities. IMK practices are skills inherent by certain individuals in a tribal grouping who are chosen by the spirits (gods) or trained by those who practice. This intrinsic skill is in danger of diminishing as a result of modern medication. This article attempts to understand the role of traditional healers (also known as asing’anga in local language) in preservation of IMK in Chibombo District of Zambia. In so doing, the paper examined methods of preservation used by asing’anga and the challenges faced. Using hermeneutic phenomenology and linear snowball sampling, findings revealed that preservation was done through training. The study found unwillingness, expiration, and spirituality as challenges in the process of preserving IMK. The study recommended that the Lenje Cultural Association consider documenting and disseminating information to the local people by showcasing what is available in the Mukuni Culture Village Museum and Library. This was seen as a way through which many youths would be encouraged to appreciate the indigenous values in their culture.

Main pathogens affecting carob (Ceratonia siliqua) tree in the Mediterranean basin are described in this overview. The most widespread diseases periodically occurring on carob orchards are powdery mildew (Pseudoidium ceratoniae) and cercospora leaf spot (Pseudocercospora ceratoniae). The causal agents of so-called “black leaf spots” (e.g. Pestaliotiopsis, Phyllosticta and Septoria spp.) are responsible for similar symptoms to above mentioned foliar diseases but are reported on carob orchards with a negligible frequency. Likewise, canker and branch diebacks caused by fungal species belonging to Botryosphaeriaceae are almost never recorded. Among wood diseases that may compromise old or previously damaged carob specimens, “brown cubical heart rot” caused by Laetiporus sulphureus is the most widespread and recurrent issue; this pathogen is also well-known for edible fruit bodies that are also appreciated for pharmaceutical and industrial purposes. On the other hand, “white decays” caused by Fomes and Ganoderma species are less common and reported for the first time in this review. Like-gall protuberances on twigs at uncertain aetiology or tumours on branches associated to Rhyzobium radiobacter are described although these symptoms are seldom detected as it happens also for necrotic leaf spots caused by Pseudomonas syringae pv. ciccaronei. A list of worldwide pathogens not yet recorded but at high-risk potential of introduction in Italian carob producing area is also provided. Finally, some concerns are addressed to new phytopathogenic fungi vectored by invasive Xylosandrus compactus ambrosia beetle. Comprehensively, all described pathogens could potentially in near future become limiting factors for carob production, because they could be favoured by high-density orchards, increasing global network of trade exchanges and high frequency through which extreme events of climate changes globally occur. Thus, symptoms and signs, causal agents, epidemiology and whenever applicable recommendations for disease prevention and management are provided in this review.

Antimicrobial resistance (AMR) remains a challenge in Kenya, while the extent remains unknown. To assess the knowledge, cultural beliefs, practices, and behavioral patterns among multisectoral stakeholders in Kenya. The cross-sectional survey was conducted in August 2021 among farmers, animal health service providers and AMR researchers. Regional digital data collection tool developed by FAO was shared and responses obtained through mail, phone calls and direct interviews. Descriptive and inferential analysis were conducted. Antimicrobials were mostly sourced from agro-veterinary shops and from veterinary professionals. Farmers, often implement self-treatment and reported overuse, unnecessary use, and sometimes fail to complete the dosage in livestock. More farmers reported to have heard about antibiotics as compared to antimicrobials, mostly from friends and radio program, however only 9.2% could correctly differentiate the two. Animal Health Service Providers (AHSP) were the source of information to farmers regarding AMR. AHSPs mainly relied on suppliers and distributors for information about antibiotics. Both farmers and AHSPs treated viral infections with antibiotics. One Health Partners (OHPs) had higher knowledge and largely favorable attitudes towards AMR. Up to 72.7% of OHPs from training institutions had AMR included in training curriculum however, they were optimistic livestock farmers and government were less concerned about AMR. Gaps in knowledge and practice on Antimicrobial Stewardship (AMS) were observed in all categories of stakeholders. Given the documented knowledge-practice gap, innovative solutions are needed for both AHSPs and farmers to promote good antimicrobial stewardship practices and to mitigate burdens of AMR. Outcomes of this research should deepen the understanding of critical information and trigger behavioral change in usage and stewardship of antimicrobials.

Ascites is a term that describes a pathological accumulation of fluid in a peritoneal cavity. It is generally a rare occurrence in a pediatric population and is most commonly associated with liver failure and cirrhosis. In that case, a diuretic treatment is usually implemented to relieve the ascites as it forms in the mechanism of water retention and water leakage from the portal venous system due to portal hypertension. It is important to note however that many other issues may cause ascites in children. Those require a catered approach suited to the pathomechanism of ascites formation in those underlying conditions. That is why a complex diagnostic process ought to be run in pediatric patients with ascites to correctly identify a condition causing it and provide the patient with adequate and thorough care.

Chatbots have gained widespread popularity for their task automation capabilities and consistent availability in various domains, including education. However, their ability to adapt to the continuously evolving and dynamic nature of knowledge is limited. This research investigates the implementation of an internet wizard to enhance the knowledge base of an open-domain question-answering chatbot. The proposed approach leverages search engines, particularly Google, and its features, including feature snippets, knowledge graph, and organic search, in conjunction with data science and natural language models. This mechanism empowers the chatbot to dynamically access the extensive and up-to-date knowledge available on the web, enabling the provision of real-time and pertinent answers to user queries sourced from web documents. A pilot study in a higher education context evaluated the chatbot's mechanism and features, confirming its proficiency in generating responses across a broad range of educational and non-educational topics. Positive feedback and high user satisfaction validate these findings. Notably, the chatbot's dynamic feature of retrieving related or follow-up questions from search engines significantly enhances student engagement and facilitates exploration of supplementary information beyond the curriculum.

Human papillomavirus (HPV) infection is a widespread sexually transmitted infection linked to various types of cancers. Although vaccination against HPV is available, global HPV vaccination rates remain low. This study aimed to evaluate the awareness and knowledge of the HPV vaccine and to identify predictors associated with vaccine hesitancy among health college students in Saudi Arabia. A cross-sectional survey was distributed to students enrolled in health colleges. The association of vaccine hesitancy with sociodemographic characteristics was examined using logistic regression analysis. The study found that approximately half of the students (49.9%) were aware of the HPV vaccine. Students from the College of Medicine showed the highest level of knowledge. Only a small proportion (5.2%) reported receiving the vaccine. The overall HPV vaccine hesitancy was 59.1% (43.9% for women and 75.9% for men). The most common reasons for vaccine hesitancy was not knowing enough about it. Men were twice as likely as women to believe that they did not need the HPV vaccine. The odds for HPV vaccine hesitancy were greater among men and younger age group compared to women and older age group. In conclusion, the study underscores the importance of awareness campaigns on HPV vaccination, targeting primarily male students.

With the increasing utilization of intelligent mobile devices for online inspection of electrical equipment in smart grids, the limited computing power and storage capacity of these devices pose challenges for deploying large algorithm models and it’s hard to obtain a substantial number of images of electrical equipment in public. In this paper, we propose a novel distillation method that compresses the knowledge of teacher networks into a compact few-shot classification network, employing a global and local knowledge distillation strategy. Central to our method is exploiting the global and local relationship between the features exacted by the backbone of the teacher network and student network. We compare our method with recent state-of-the-art (SOTA) methods on three public datasets and achieve superior performance. Additionally, we contribute a new dataset, namely EEI-100, which is specifically designed for classification of electrical equipment. We validate our method on this dataset and demonstrate its exceptional prediction accuracy of 94.12% when utilizing only 5-shot images.

Introduction Menstrual hygiene is a critical issue encountered by women and girls of the reproductive age, which negatively affects their health and empowerment. It is still deemed a taboo in several parts of the world and girls hesitate to discuss menstruation with their family members, friends, or schoolteachers, which creates hurdles when they attain their menarche. Girls residing in rural areas encounter more problems, since they lack proper resources, and knowledge to manage their menstruation in school as well as at home. Methods The descriptive cross-sectional design was used to assess the study questions. The consecutive sampling techniques was applied to recruit 300 female participants from remote area of Gilgit, Pakistan, who were 13- to 22-year-old. A pre-tested questionnaire was utilized to collect the data, and to analyze the data the SPSS version 21.0 was used. Results The study found that more than half of the participants had poor level of knowledge, practices, and negative attitude towards menstrual hygiene. This could be because of many cultural and social taboos attached to menstrual hygiene. Conclusions The study concluded that the study participants were not knowledgeable about menstrual hygiene. They had poor practices and attitude regarding menstrual hygiene. Hence, it is recommended that frequent sessions should be conducted by health care workers to enhance the knowledge of parents, teachers, and young girls, to increase the positive attitude and practices regarding menstrual hygiene. Keywords menstruation, knowledge, attitude, practices, Adolescents

Background: Using the COM-B model as a framework, an EU-wide survey aimed to ascertain multidisciplinary healthcare workers’ (HCWs) knowledge, attitudes and behaviours on antibiotics, antibiotic use and antibiotic resistance. The UK findings are presented. Methods: A 43-item questionnaire was developed through a two-round modified Delphi consensus process. The UK target quota was 1,315 respondents. Results: 2,404 participants responded. The highest proportion were nursing and midwifery professionals (42%), pharmacists (23%) and medical doctors (18%). HCWs correctly answered that antibiotics are not effective against viruses (97%), they have associated side effects (97%), unnecessary use makes antibiotics ineffective (97%) and healthy people can carry antibiotic resistant bacteria (90%). However, fewer than 80% correctly answered that using antibiotics increases a patient’s risk of antimicrobial resistant infection or that resistant bacteria can spread from person to person. Whilst the majority of HCWs (81%) agreed there is a connection between their antibiotic prescribing behaviour and the spread of antibiotic resistant bacteria, only 64% felt that they have a key role in controlling antibiotic resistance. The top three barriers to providing advice or resources were lack of resources (19%), insufficient time (11%) and the patient being uninterested in the information (7%). Approximately 35% of UK respondents who were prescribers prescribed an antibiotic at least once in the last week due to fear of patient deterioration or complications. Conclusion: These findings highlight that a multifaceted approach to tackling the barriers to prudent antibiotic use in the UK is required and provides evidence for guiding targeted policy, intervention development and future research. Education and training should focus on patient communication, information on spreading resistant bacteria and increased risk for individuals.

Sustainability is very important in business. The residential high-rise building all firms wanted to successful and sustainability in business. There is need the construction to completed low time, low cost and high quality in construction work. Therefore, real estate developers must find various strategies to use in construction projects to achieve goals and success of the firm. The purpose of this study was to indicate the very importance of knowledge management can lead to sustainability in business. Analyze 14 critical success to sustainability in residential high-rise building projects, collected questions from literature review, and survey in deep interview senior managers of 15 projects real estate development firms listed on the stock market of Thailand. Budget building more than 1000 million baht per project. From conceptual frame work five foundations integrated to knowledge management of critical success (KMITL PROCESS) used made tool survey in deep interview the critical success to sustainability in residential high-rise building project from project managers. Used IBM SPSS evaluated the critical success to sustainability. Found was one very important of critical success to sustainability, which was quality of products x̄ = 4.83. All 14 critical success to sustainability was found can applied made the knowledge management of critical success to sustainability in residential high-rise building project in firm. Especially in the field of construction managements project can used improve of all construction projects.

Accruing evidence on the influence of β-carotene regarding the prevention of several chronic diseases - in addition to its well-acknowledged role in vision has been a strong driver for developing alternative delivery systems. Though oral delivery is accepted as the most fitting, mild and safe path for delivering bioactive agents, β-carotene delivery via food items poses challenges due to its lipophilic nature, poor water-solubility, high chemical/photochemical instability and poor oral bioavailability. Nanotechnology has opened new windows for delivering bioactive agents. Their physiochemical characteristics, i.e. small size, high surface area, unique composition, biocompatibility and biodegradability make these nanomaterials an attractive tool for β-carotene delivery. Delivering β-carotene through nanoparticles does not only improve its bioavailability/bioaccumulation in target tissues, but also lessens its sensitivity against environmental factors during processing. Regardless of these benefits, nanocarriers inherit some limitations, such as variations in sensory quality, modification of the food matrix, increasing costs, as well as limited consumer acceptance and regulatory challenges. This research area has been rapidly evolved, with a plethora of innovative nano-engineered materials, including micelles, nano/microemulsion, liposomes, niosomes, solid-lipid nanoparticles and nanostructured lipid carriers. These nano-delivery systems make conventional delivery systems appear archaic and promise better solubilization, protection during processing, improved shelf-life, higher bioavailability as well as controlled and targeted release. This review provides information on the state of knowledge on β-carotene nano-delivery systems adopted for developing functional foods: depicting their classification, composition, preparation methods, challenges, release-and absorption of β-carotene in the GIT and possible risks and future prospects.

Sustainable Development Goals (SDGs) envisaged under Agenda 2030 are a set of seventeen goals which envisage a holistic approach towards attaining certain targets keeping humankind and the planet at center. There are total 169 targets spread across seventeen goals covering wide ranging issues and challenges the world is facing in the twenty-first century. And they are to be achieved by 2030. Concerted efforts of all the stakeholders ranging from indigenous communities, common citizens, scientists, policy makers, world leaders are needed to achieve all the goals and targets Of the seventeen goals, at least seven goals are of interest to the ethnobotanists and are associated with traditional ethnobotanical knowledge. Therefore to achieve those set of goals, a thorough understanding is required to disentangle the intricacies involving traditional ethnobotanical knowledge, indigenous people as traditional knowledge holders and their future role. Understanding relationships between traditional ethnobotanical knowledge and indigenous communities, seeking cooperation from and establishing partnerships with them would help us design policies to achieve intended outcomes of SDGs. In this paper, particular attention is attracted towards the potential role of traditional ethnobotanical knowledge in achieving select sustainable development goals and targets.

The reinforcement learning problem of complex action control in the Multi-player wargame is a hot research topic in recent years. In this paper , a game system based on turn-based confrontation is designed and implemented with the state-of-the-art deep reinforcement learning models. Specifically, we first design a Q-learning algorithm to achieve intelligent decision-making, which is based the DQN(Deep Q Network) to model the complex game behaviors. Then, a priori- knowledge based algorithm PK-DQN(Prior Knowledge- Deep Q Network) is introduced to improve the DQN algorithm, which accelerates the convergence speed and stability of the algorithm. The experiments demonstrate, the correctness of the PK-DQN algorithm is validated and its performance surpass the conventional DQN algorithm. Furthermore, the PK-DQN algorithm shows effectiveness in defeating the high level of rule-based opponents, which provides promising results for the exploration of the field of smart chess and intelligent game deduction.

A deep review of the existing literature on the culpeo ecology is carried out, using scientific articles, book chapters and web resources. For information published before 1988, the synthesis made by a previous report was used. For subsequent information, bibliographic searches were carried out through the main servers, considering all of the generic names used to define the species so far. From this update, new general patterns on ecology, behavior and conservation concerns about culpeos are described. Gaps in current knowledge have been identified and new lines of research are proposed.Most of the studies focused on diet, conflicts with the species in livestock areas, and on the use of space and habitat. We found an incomplete, poor justification for all of the proposed subspecies and their supposed geographical distribution, as well as a scarcity of studies on genetic issues, population dynamics and conservation concerns. It is remarkable that vast regions in South America holding culpeos lacked basic information on the species.Diet studies describe a marked trend towards resources selection at the local level, which supports the view of the culpeo as a facultative trophic specialist. In addition, it has been confirmed that in the high Andes the culpeo is also a top predator that may regulate carnivorous communities, as well as that in arid environments culpeos can act as important seed dispersers. The assessment of the conservation status of the species differs among regions, although there is no sufficient information to reach clear conclusions in most cases. Even so, in Ecuador and Colombia the species has been listed as ‘Vulnerable’. Direct persecution and habitat alteration are considered to be the most important threats that the species is facing in many countries, although other risk factors such as climate change could also have serious consequences for the canid at the global scale.

This review chronicles the indirect transmission method which seems to be overlooked by most people and makes attempts to clearly document the various transmission ways with a hope that such information may strengthen the knowledge base of researchers towards methods of eradicating the pandemic. Current knowledge of transmission and exposure of SARS-CoV-2 has been explained. Various researchers have put forward different ways of exposure and transmission. Literature does not reveal whether the indirect transmission route is the dominant one. However total lockdown could be a veritable means to reduce both direct and indirect transmission routes. In many countries where the indirect transmission has been reduced, the scourge of the virus is less. The work creates awareness on the need to watch out for those routes of transmissions that may not be popular and suggested key knowledge gaps that needs to filled.

Fire accidents are common accidents amongst residential house occupants in Libya. Some of the factors that can mitigate fire accidents in Libyan residential houses include fire safety awareness and knowledge. This study investigated the level of awareness and knowledge of fire safety amongst residential house occupants in Libya. The possibility and consequences of fire hazards and risk existing in residential houses in Libya were also studied. Experimental data obtained for 1.5 m/s and 3.5 m/s as walking and running evacuation time, respectively amongst residential house occupants in Libya were also compared. The sample consist of 90 respondents with instruments of fire safety awareness and knowledge, fire hazard and consequences, and the involvement of residential house occupants in fire emergency. Statistical analysis was performed at p < 0.05 to determine the levels of residential awareness and knowledge regarding fire safety and the hazard and consequences. The findings illustrated that the items were highly reliable (α > 0.7) and normally distributed. Also, the results illustrated that the majority of residential house occupants in Libya have fair level of fire safety awareness and knowledge with overall percentage of 80% and 90%, respectively. On the other hand, the results further showed that majority of residential house occupants have good level of fire emergency involvement with 90%. This paper proposes a fire safety assessment method which may form the basis of future fire safety practice in Libya.

In the contemporary construction management, poor project performance, cost overrun, and low-quality construction have become a central point of attention for improving project performance including information, interaction and communication management. virtual design and construction and building information modelling play indispensable role in improving the project performance. The aim of this study is to propose a Virtual Information Modeling as a novel information and communication technology method with potential to overcome problems in the construction industry. Using one-sample t test with Kolmogorov-Smirnov approach, we analysed data collected from structured questionnaire survey involving project managers working at architecture, engineering and construction industries in Tehran, Iran. The results suggest that the most important benefits and challenges of using Virtual Information Modeling are related to the area of integration, and implementation of Virtual Information Modeling has the greatest impact on this area of project management knowledge. Thus, integration should be considered a top priority for construction companies implementing Virtual Information Modeling in their projects. Policymakers should understand that careful management of virtual information is essential for improving the performance of projects and enhancing the process efficiency.

For most of its history, archaeology has taken an indulgent attitude toward looting and antiquities trafficking. The primary response to these dangers has been to publish the main findings made outside of academia. As a result of this approach and the prominent role played by police techniques in investigating such crimes, investigations are primarily based on documentary research. This approach makes it harder to determine such essential factors in this field as an object’s collecting history or discovery date. This paper offers an overview of the state of the research on the fight against antiquities trafficking. It then proposes new ways of studying collecting history, drawing on research projects on the use of archaeometry to shed light on cases of looting or trafficking involving police, court, or government intervention; hence, its qualification as “forensic.” Although the current state of knowledge does not enable the presentation of novel research, we believe that researchers and interested institutions should be made aware of the advisability of using archaeometry more directly in the fight against these scourges.

Background: Microscopic examination of acid-fast stained sputum smears for detecting mycobacterial acid-fast bacilli (AFB) remains the most economical and readily available method for laboratory diagnosis of tuberculosis (TB). However, this conventional approach has limitations, including low sensitivity and labor-intensive procedures. Methods: An automated microscopy system incorporating artificial intelligence (AI) and machine learning for AFB identification was evaluated. The study was conducted at an Infectious Disease Hospital in Jiangsu Province, China, utilizing an intelligent microscope system (TB-Scan, Wellgen Medical, Kaohsiung). A total of 1,000 sputum smears were included in the analysis, with the system capturing digital microscopic images and employing an image recognition model to automatically identify and classify AFB. Referee technicians provided the gold standard for discrepant results. Results: The automated system demonstrated an overall accuracy of 95.00% (950/1,000), sensitivity of 91.24% (177/194), and specificity of 95.91% (773/806). Notably, the system identified 21 smears as positive that were previously reported as negative, with referee technicians confirming 17 of these as true positive and retracting the test results accordingly. Recalculating the performance, the accuracy increased to 96.70% (967/1,000), sensitivity to 91.94% (194/211), and specificity to 97.97% (773/789), with a false negative rate of 8.06% (17/211) and a false positive rate of 2.03% (16/789). Conclusions: The incorporation of AI and machine learning into an automated microscopy system demonstrated the potential to enhance the sensitivity and efficiency of AFB detection in sputum smears compared to conventional manual microscopy. This approach holds promise for widespread application in TB diagnostics and potentially other fields requiring labor-intensive microscopic examination.

This scientific paper explores the increasingly widespread use of collaborative robots in the industrial environment, highlighting them as a solution to challenges related to the high costs of human labour and the associated management difficulties. The authors focus on the process of defining requirements for the implementation of collaborative robots, providing strategies based on mathematical management models. This approach translates into significant benefits for companies, such as cost reduction, quality improvement, and increased operational efficiency. Additionally, the paper proposes an innovative mathematical model for assessing total costs, budgeting, profitability, and electric power consumption associated with the operation of collaborative robots. This model allows for a comparison between the costs involved in using human labour and those associated with collaborative robots, providing critical information for technological investment decisions. The efficiency of this mathematical model is demonstrated through a practical application, where collaborative robots were integrated into a production environment, and costs and efficiency were evaluated compared to the use of human labour. This scientific paper provides a systematic and efficient approach to implementing collaborative robots in industrial processes, benefiting from strategies based on mathematical management models and an original mathematical model for evaluating performance and associated costs.

Structured science summaries or research contributions using properties or dimensions beyond traditional keywords enhances science findability. Current methods, such as those used by the Open Research Knowledge Graph (ORKG), involve manually curating properties to describe research papers' contributions in a structured manner, but this is labor-intensive and inconsistent between the domain expert human curators. We propose using Large Language Models (LLMs) to automatically suggest these properties. However, it's essential to assess the readiness of LLMs like GPT-3.5, Llama 2, and Mistral for this task before application. Our study performs a comprehensive comparative analysis between ORKG's manually curated properties and those generated by the aforementioned state-of-the-art LLMs. We evaluate LLM performance through four unique perspectives: semantic alignment and deviation with ORKG properties, fine-grained properties mapping accuracy, SciNCL embeddings-based cosine similarity, and expert surveys comparing manual annotations with LLM outputs. These evaluations occur within a multidisciplinary science setting. Overall, LLMs show potential as recommendation systems for structuring science, but further finetuning is recommended to improve their alignment with scientific tasks and mimicry of human expertise.

Artificial intelligence (AI) has witnessed an exponential increase in its use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software engineering problems. However, a comprehensive and holistic understanding of the current status is missing. To close the above gap, synthetic knowledge synthesis was used to induce a research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and five themes, namely natural language processing in software engineering, use of artificial intelligence in the management of software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n=2042), followed by the United States (n=1193), India (n=934), Germany (n=445), and Canada (n=381). A high percentage (n=47.4%) of papers were funded, showing a strong interest in this research topic. The convergence of AI and software engineering can significantly reduce needed resources, improve quality, increase user experience, and improve the well-being of software developers.

We bring a strength-based and socially-oriented lens to behaviors observed in profound autism. Social deficits are a defining characteristic of autism. Yet humans’ biological drive for social connection is sufficiently strong that is should be observable, in some form at least, in individuals with autism. We describe a case that validates this view. Mahad is a 20-year-old Pakistani-American male, with intellectual disability, and minimal verbal abilities. Mahad has an intense interest in food and the steps involved in food preparation. He employs and capitalizes on his family’s meal routines to ensure continual social attention from his mother. When not immersed in food, Mahad uses his limited capacities to pursue the additional biological needs of exploring his environment, seeking information, and developing his cognitive abilities.

This paper will discuss Data, Information, Knowledge, and Wisdom, which is commonly referred to as DIKW. The DIKW Pyramid Model that is often referenced in both academics and practitioner circles will be discussed and shown to be faulty on several levels, including. a lack of definitional agreement. A new DIKW framework will be proposed that focuses on what the DIKW elements do in the way humans think, not what they are by definition. Information as a replacement for wasted physical resources in goal-oriented tasks will be a central organizing point. The paper will move the DIKW discussion to the computer-based concept of Digital Twins (DTs) and its augmentation of how we can use DIKW to be more effective and efficient. This will especially be the case as we move to Intelligent Digital Twins (IDT) with Artificial Intelligence (AI).

We develop new theory from a broad case-study approach to explore a better understanding of what constitutes knowledge and its value as identifiable to human-machine teams. From past research, this trail of exploration will lead to these initial questions: What is the value of debate in the furtherance of knowledge? Will machines with AI be able to contribute to a debate if we humans cannot define it or determine its value sufficiently for a machine’s understanding, contribution, exploration and identification? Like humans, as teammates, machines must be able to determine with AI what constitutes the usable knowledge that contributes to a team’s success in the field (e.g., testing "knowledge" in the field, identifying new knowledge, using knowledge to develop innovation) or its failure (viz., trouble shooting; identifying weaknesses; discovering vulnerabilities, hiding by deception). It matters not whether a debate is public, private or unexpressed by an individual human or machine agent alone; we speculate in this exploration that the process advances the science of autonomous human-machine teams and assists in interpretable machine learning. We conclude with questions and a speculation: How does a human become aware or express its awareness of knowledge? Can a machine be as expressive as its human teammates? And how does a human-machine teammate become aware that its teammates possess sufficient knowledge to perform a task? We speculate that the structure of “knowledge," once found, is resistant to alternatives (i.e., it is ordered); that its functional utility is generalizable; and that its applications are multifaceted (akin to maximum entropy production). The complexity of the team is taken into consideration in our search for knowledge, which can also be used as an information metric.

Enterococcus faecalis is a bacterial pathogen that can cause opportunistic infections. Studies indicate that initial biofilm formation plays a crucial regulatory role in these infections, as well as in colonising and maintaining the gastrointestinal tract as a commensal member of the microbiome of most land animals. It has long been thought that vegetation of endocarditis resulting from bacterial attachment to the endocardial endothelium requires some pre-existing tissue damage, and in animal models of experimental endocarditis, mechanical valve damage is typically induced by cardiac catheterisation preceding infection. This section reviews historical and contemporary animal model studies that demonstrate E. faecalis ability to colonise the undamaged endovascular endothelial surface directly and produce robust microcolony biofilms encapsulated within a bacterially derived extracellular matrix. This report reviews both previous and current animal model studies demonstrating the resilient capacity of E. faecalis to colonise the undamaged endovascular endothelial surface directly and produce robust microcolony biofilms encapsulated in a bacterially derived extracellular matrix. The article also considers the morphological similarities when these biofilms develop on different host sites, for example when E. faecalis colonises the gastrointestinal epithelium as a commensal member of the common vertebrate microbiome, lurking in plain sight and transmitting systemic infection. These phenotypes may enable the organism to survive as an unrecognised infection in asymptomatic subjects, providing an infectious resource for subsequent clinical process of endocarditis.

There is a noticeable absence of health education among college students. This study aimed to evaluate the extent of general nutrition knowledge among Chinese university students and explore its association with eating attitudes. Data were collected from a group of 273 students in Spring of 2023, using a valid and reliable research instrument consisting of three sections: demographic variables, the General Nutrition Knowledge Questionnaire (GNKQ), and the Eating Attitudes Test (EAT-26). The results were analyzed using SPSS, with correlations and t-tests to examine the relationships between nutritional knowledge and dietary attitudes. Furthermore, the present study employed the Random Forest (RF) algorithm, a machine learning technique, utilizing the Mean Decrease Impurity (MDI) method to investigate the influence of various features on participants' eating attitudes. The findings revealed that Chinese university students had an average accuracy of over 60% in their nutritional knowledge, but their understanding of the relationship between diet and disease still needs improvement. Moreover, male students had significantly lower nutritional knowledge than female students, and there was a positive correlation between nutritional knowledge and parents’ income. The study also found a significant correlation between the level of nutritional knowledge and eating attitudes. RF results indicated that family income level exhibited the most substantial impact on the eating attitudes of the participants. The study highlights the need for nutrition education curriculum developers to focus more on improving students' nutritional knowledge, with particular attention given to male students, low-income individuals, and those with an abnormal BMI.

The phenomenon of missing data can be seen everywhere in reality. Most typical attribute reduction models are only suitable for complete systems. But for incomplete systems, we can’t obtain the effective reduction rules. Even if there are a few reduction approaches, the classification accuracy of their reduction sets still needs to be improved. In order to overcome these shortcomings, this paper firstly defines the similarities of intra-cluster objects and inter-cluster objects based on the tolerance principle and the mechanism of knowledge granularity. Secondly, attributes are selected on the principle that the similarity of inter-cluster objects is small and the similarity of intra-cluster objects is large, and then the knowledge granularity attribute model is proposed under the background of clustering; Then, the IKAR algorithm program is designed. Finally, a series of comparative experiments about reduction size, running time and classification accuracy are conducted with twelve UCI data sets to evaluate the performance of IKAR algorithms, then the stability of Friedman test and Bonferroni-Dunn test are conducted. The experimental results indicate that the proposed algorithms are efficient and feasible.

The pandemic was an enormous experience all over the world. The type of living, working and study were changed irreversibly. Facing the opportunity to establish old frames of education in universities is impossible. The adoption of new ways of teaching and assessments reveal their convenience and in the same way their weak points. In response to that stage, on 14 December 2022, the EU parliament accepted the "Digital Decade Policy Programme 2030", for the establishment of a digital transformation community (EU 2022). Trakia University had an online assessment system, quizzes for self-training, and final exams, developed in 2008 on Moodle virtual learning environment. During the pandemic, online exams and lectures were conducted using platforms like BigBlueButton in Moodle or Google Meets. The article gives the results of online exams before, during, and after the pandemic. The outcome, without doubt, displays the lowering knowledge level or performance during the social isolation due to COVID-19, and after, and the reasons are discussed. During the second year of the pandemic was mentioned also a high dropout of students. Now the situation is returning to the previous levels, before the pandemic, but the quality of education is not yet reached. The article values the grades results of session exams and has the intention to clarify the influence of the pandemic period on the excellence of high institution education.

HIV incidence remains alarmingly high among female sex workers (FSWs) in low- and middle-income countries, with Uganda being no exception. The elevated risk of HIV transmission among this vulnerable population can be attributed to a complex interplay of factors, including engaging in sexual activities with multiple partners, inconsistent condom usage, substance use, and structural barriers, such as legal criminalization and pervasive stigmatization by healthcare providers. To combat this epidemic, various HIV prevention interventions have been devised, targeting these multi-faceted challenges. This study involved conducting focus groups among FSWs and healthcare providers in Uganda, with the overarching objective of informing the development of a tailored HIV prevention intervention aimed squarely at FSWs. Through these discussions, valuable insights were gained into FSWs’ perceptions of their HIV risk, their attitudes regarding HIV prevention strategies, and their recommendations regarding the content and delivery of future interventions.

Background. The purpose of the study was to evaluate the intensity and frequency of low back pain (LBP) in people with multiple sclerosis (PwMS) and the patient's knowledge of physiotherapeutic methods of combating. Methods. In this study, patients with confirmed multiple sclerosis were selected. The study was carried out using an original survey questionnaire and a numerical pain intensity scale (Visual Analogue Scale). PwMS were divided into 3 age groups: 18-30 years, 31-50 years, and over 50 years. Results. Ninety PwMS (68 women and 22 men) aged 18 to 60 years were included in the study. The mean duration of the disease was 9.5±4.9 years, and the mean EDSS was 3.5±1.6. Most of the patients had a relapse-remitting form. 68.9% of PwMS felt lower back pain (n = 62). The relationship tested was statistically significant (p=0.0000012), and the strength of the relationship was high (rc=0.695). The average level of low back pain among PwMS was 4.7 out of 10 on the VAS scale. The prevalence of LBP was higher in female patients (p<0.001), with a secondary progressive form (p<0.001) and with a longer duration of the disease (p=0.023). The most widely used methods of LBP therapy were kinesitherapy and manual therapy. Conclusions. LBP is common in multiple sclerosis. A female sex, a secondary progressive form of MS, and a longer duration of the disease increased the risk of LBP. It is important to implement properly planned physiotherapy activities and educate patients on how to combat LBP.

IIt is important that Master’s Degree students in psychology, regardless of their future specialisa-tion, know about Attention Deficit Hyperactivity Disorder (ADHD). The aim is evaluate and an-alyse the ADHD-related knowledge held by students of Early Childhood Education and Primary Education. The findings that were obtained in this study (on the chronicity of the disorder, changes in manifestations throughout the life cycle, and the importance of early and multidisci-plinary intervention) have clear implications in relation to the specific training in ADHD for fu-ture teachers. It is essential to broaden the specific training in relation to ADHD in studies for the Master’s Degrees in Early Childhood Education and Primary Education and through contin-uous training.

Based on the teaching material of "Robotics" course, this paper studied the automatic knowledge graph construction, including knowledge points extraction and knowledge point relation extraction. We proposed a new method of extracting the first-level, second-level, and third-level knowledge points as well as their prerequisite relations of knowledge points in the textbook. For the problem of insufficient knowledge of the pre-trained language model in the specific field, methods such as incremental pre-training and optimization of cost functions are employed to integrate subject knowledge into the pre-trained language model, thus improving its effectiveness. To overcome the problem that the traditional method of relationship extraction can not be applied directly to the extraction of teaching materials, a new scheme for knowledge point relationship extraction based on keyword relationship is proposed. The experimental data from textbooks shows that the F1 score of knowledge point extraction reaches 93%, considerably improved compared to the traditional model. Consequently, the knowledge point entity extraction and relationship extraction methods based on the pre-trained model can effectively extract structured information and facilitate the automatic construction of knowledge graphs.

The article addresses the issue of reducing the carbon footprint in the formula of the European Union’s New Green Deal using nuclear energy introduced in place of coal. It contains an analysis of the possibilities offered by currently developed concepts of using nuclear energy in the context of existing energy infrastructure in Poland. It indicates the compatibility of coal and nuclear technologies for generating electricity and heat, considering only those with the highest level of technological readiness. The aim of the article is to identify the energy transformation in Poland using nuclear technologies and acquiring, creating and developing knowledge on the subject. It is assumed that the future of coal-nuclear transformation depends on determining where investment processes could take place in Poland, demonstrating the power that can be replaced through transformation, and indicating appropriate coal CPP (Carbon Power Plant) and nuclear NPP (Nuclear Power Plant) technologies with which a roadmap for the development of Polish nuclear energy can be created. The direction of potential actions is shown, whose coordination and implementation requires cooperation between many entities with appropriate knowledge and experience. For the purposes of this article, preliminary research was conducted on the possibilities offered by currently developed concepts in the context of existing energy infrastructure in Poland, its transformation, and the necessary social capital and its sources. The considerations did not take into account power plants and combined heat and power plants that have been liquidated or the use of their remaining infrastructure.

Any Hospital’s primary goal is to restore human health and save lives through health services provided to patients, but at the same time, hazardous wastes are produced. Inconsistent management of unsafe wastes might cause adverse effects and other issues to workers, the environment and public health. Segregation is considered the critical stage for a successful Healthcare Waste Management. Mixing hazardous waste with non-hazardous waste will be avoided by correctly applying practices at the segregation stage. This study aimed to assess personnel’s knowledge about Infectious Medical Waste and segregation practices used at six wards in Nicosia General Hospital. An analytical cross-sectional study was conducted, and data were collected through a structured self-administered questionnaire. The Statistical Package of Social Science (SPPS) version 25 was used with a minimum statistical significance α=0.05. The study population was nurses, nurse assistants, ward assistants and cleaners working at the study wards. Out of 191 questionnaires, 82 were received, with a response rate of 42.93%. Most participants were female (72%) and nurses (85,4%). Participants had medium to good knowledge about Infectious Medical Waste management and good knowledge regarding segregation practices applied in their ward. Segregation was not carried out as it should have since most participants stated that Infectious Medical Wastes were mixed with non-hazardous waste. Correct answers given by the participants regarding color-coding of different Healthcare Waste categories was 67.5%, and only four answered correctly to all questions. Although participants knew segregation practices and the colour-coding process applied for Healthcare Waste, they didn’t use them satisfactorily. They applied methods regarding segregation without specific training, knowledge and guidance. Due to the issue's importance, training programs must be implemented and performed.

To address the deficiency of existing relation extraction models in effectively extracting relational triplets pertaining to railway traffic knowledge in Tibet, this paper constructs a Tibet Railway Traffic text dataset and provides an enhanced relation extraction model. The proposed model incorporates subject feature enhancement and relational attention mechanisms. It leverages a pre-trained model as the embedding layer to obtain vector representations of text. Subsequently, the subject is extracted and its semantic information is augmented using an LSTM neural network. Furthermore, during object extraction, the multi-head attention mechanism enables the model to prioritize relations associated with the aforementioned features. Finally, objects are extracted based on the subjects and relations. The proposed method has been comprehensively evaluated on multiple datasets, including the Tibet Railway Traffic text dataset and two public datasets. The results on the Tibet dataset achieves an F1-score of 93.3\%, surpassing the baseline model CasRel by 0.8\%, indicating a superior applicability of the proposed model. On the other hand, the model achieves F1-scores of 91.1\% and 92.6\% on two public datasets, NYT and WebNLG, respectively, outperforming the baseline CasRel by 1.5\% and 0.8\%, which highlights the good generalization ability of the proposed model.

Aortic dissection is a clinicopathological entity caused by rupture of the intima leading to a high mortality if not treated. Over time, diagnostic and investigative methods, antihypertensive therapy, and early referrals have resulted in improving outcomes according to registry data. Some data has also emerged from recent studies suggesting a link between Human Cytomegalovirus (HCMV) infection and aortic dissection. Furthermore, the use of microRNAs have also become increasingly widespread in the literature. These have been noted to play a role in aortic dissections with elevated levels noted in studies as early as 2017. This review aims to provide a broad and holistic overview of the role of miRNAs, while studying the role of HCMV infection in the context of aortic dissections. The role of long non-coding RNAs, circular RNAs and microRNAs are explored to identify changes in expression during aortic dissections. The use of such biomarkers may one day be translated into clinical practice to allow early detection and prognostication of outcomes and drive preventative and therapeutic options in the future.

Strandings are one of the most worrying issues in relation to the conservation of cetacean species, and in the case of Chile, due to its geography and large extension of the coastline, monitoring and access to these events is difficult, making their study more complex. Chile has a shortage of specialized scientific forensic research facilities for cetacean; however, for this study it was able to collect data recorded from official institutions and sporadic scientific biological sampling oriented to investigate the causes of death or stranding. According to the Chilean government official database, we described that the main causes of unusual mortality events (UME) and mass strandings from year 2015 and 2016 were acute poisoning by biotoxin and trauma to the auditory complex, respectively, while individual strandings would have their causes in anthropogenic activities such as entanglements in fishing an aquaculture gear and collisions with vessels. The predominant species in mass strandings was the sei whale (Balaenoptera borealis). The geographical area of greatest prominence in mass strandings was the Aysén Region in the Central Patagonia of Chile, while the species mostly involved in individual strandings along the south-central, central, and northern coast of Chile was the small porpoise (Phocoena spinipinnis). The most common gross pathological findings were advance decay of the carcasses and nonspecific wounds of different nature, difficult to associate with possible causes of death without further histopathological studies.

The aim of this review was to summarize the available literature regarding resident and medical student education utilizing the spaced repetition program Anki. This review enables current residents and medical students to recognize and utilize evidence-proven study techniques to increase learning efficacy. A systemic review of papers across all medical journals available on Pubmed was conducted to identify studies published without time constraints. The search was for (Anki) and (spaced repetition residency). Available outcome data was collected and discussed independently for students and residents. Many studies showed a statistically significant increase in exam performance associated with Anki use and high levels of satisfaction among residents and medical students. Further research is warranted to provide high-quality evidence of Anki’s applications and there is a need for exploration in additional residency specialties. Anki use has steadily increased with both medical students and residents. The application demonstrated consistent improvement on exam-based performance and was regarded highly by users. As burnout and time constrictions threaten educational workflow, Anki may serve as a powerful tool to improve the quality of learning. Further data needs to be collected and analyzed in specialties where Anki use may already exist.

Using a variety of theoretical foundations, this paper examines the association between corporate social responsibility (CSR) and employees’ knowledge-sharing behavior, investigating the sequential mediation role of perceived organizational support and organizational commitment as well as the moderating role of ethical climate. Hypotheses were formulated to address both the sequential mediation effect of perceived organizational support and organizational commitment on the link between CSR and knowledge-sharing and the moderation effect of ethical climate on the relationship between CSR and perceived organizational support. In order to mitigate the problems of potential common method bias, data were gathered from a sample of 204 South Korean employees at three distinct time points. The results of the study offer compelling evidence that CSR activities exert a positive influence on employees’ knowledge-sharing behavior, an effect that is sequentially mediated by both perceived organizational support and organizational commitment. Furthermore, the research uncovers the positive moderating role played by ethical climate in the relationship between CSR and perceived organizational support. By integrating multiple theoretical frameworks, this study not only advances the extant literature but also offers invaluable insights for organizations striving to bolster knowledge-sharing through the strategic implementation of CSR initiatives.

Poor hygiene in the food services industry is a critical public health concern in the Maldives, with an average of 35 public complaints per month regarding the poor hygienic conditions of the restaurants in Male’, the capital of Maldives. Thus, this study aimed to identify the level of knowledge, attitude, and the gap of self-reported with the observed practice (KAP) of food handlers as well as the potential association between KAP. 290 food handlers from restaurants were surveyed, demonstrating moderate knowledge (55.5%), moderate attitude (3.62±0.51) and good practice (4.18±0.54). However, it is critical the result shows the food handlers in Male’ have poor practice on the time and temperature control where especially on thawing and storage resulting from a lack of training in the temperature danger zone. The work experience impacting the level of knowledge, education impacts the level of attitude and age, and education and work experience impacting practice. Male’ restaurants mostly employed the foreigners mostly from Bangladesh and the food handlers were identified to have low level of education. Association analysis identified significant relationships between knowledge, attitude, and practice, while the principle component analysis shows categories that are related to each of KAP. This study is fundamental for policymakers to review and improve law enforcement to address the current food safety situation in the Maldives.

The Infectious and Tropical Diseases Department of University of Brescia organized free rapid screening tests for HIV and HCV as part of the Fast Track City commitment. A cross-sectional study was conducted, consisting of an anonymous, multiple-choice questionnaire that was administered to individuals who underwent the screening or consultation. The study aimed to compare knowledge and attitudes towards HIV and HCV between age groups (18-40 vs. >40) and sexual orientations (heterosexual vs. LGBTQ+). Overall, 333 questionnaires were completed. Individuals over the age of 40 and those who identified as heterosexual had the lowest level of knowledge about HIV transmission (7.9% and 30% respectively), undetectable=untransmittable (19.7% and 39.4% respectively) and PrEP (9.2% and 18.2% respectively). They were also less willing to cohabit with people with HIV (PLHIV). Only 9.6% of the population demonstrated high levels of knowledge for both HIV and HCV. People over the age of 40 had the largest gaps in knowledge and would benefit the most from educational and prevention interventions.

Background Several vaccines have been approved for prevention of the coronavirus disease discovered on 31st December in Wuhan, China. Pakistan procured vaccines from various countries. However, the lack of knowledge and reluctance of the general population to embrace the use of the vaccines are considered to be the major determinants of the slow vaccination rate. Hence, it is necessary to evaluate the willingness of the general population about their perception of the COVID-19 vaccination. Methods A cross sectional survey based on a self-structured questionnaire comprising 18 questions was conducted (from April 21-June 21) on 400 Pakistani participants to evaluate their knowledge, attitude and perception towards the COVID-19 vaccination. Chi-square independent t-test and one-way Anova including a multiple step wise linear regression were used to draw conclusions about the results. P< 0.05 was considered significant. Results A total of 400 participants responded in the KAP survey of which 46.5% were female and 53.5% were male. The mean age of participants was 36.08 years. This survey showed a poor knowledge (50.5%), a fair attitude (75.1%) and a poor perception (58.1%) towards the COVID-19 vaccination. Higher mean knowledge and attitude scores was reported in the age group 21-40, females and unmarried urban citizens. Regression analysis showed that age, education, residence and employment status influenced the knowledge and perception score to a considerable extent. Conclusions The findings reflect an inadequate knowledge and perception on the one hand but a better attitude towards the COVID-19 vaccination. This KAP survey will help in better understanding the opinion of the general population towards vaccination and will be useful for policy makers and health care authorities aiming to increase the vaccination rate.

Semantic communication is not obsessed with improving the accuracy of transmitted symbols, but is concerned with expressing the desired meaning that the symbol sequence exactly carried. However, the generation and measurement of semantic messages are still an open problem. Expansion combines simple things into complex systems and even generates intelligence, which is consistent with the evolution of the human language system. We apply this idea to semantic communication system, quantifying and transmitting semantics by symbol sequences, and investigate the semantic information system in a similar way as Shannon did for digital communication systems. This work was the first to propose the concept of semantic expansion and knowledge collision, which may provide a new paradigm for semantic communications. We believe that expansion and collision will be the cornerstone of semantic information theory.

Introduction: Blood transfusion involves the transfer of blood from donors to patients. A blood transfusion is carried out every 2 seconds in the US. It is made up of about 29000 units of red blood cells and is transfused every day in the US. When blood transfusion is done correctly, it can result in the saving of lives and the improvement of healthcare. However, it may also lead to immediate, late, delayed, and chronic complications. No previous studies have been conducted in Qatar to address this issue. Methods: This is a cross-sectional study intended to determine the knowledge, attitude, and practice toward blood transfusion among healthcare providers at Hamad Medical Corporation (HMC), which is the principal healthcare provider in Qatar. Participants between 18 and 25 years of age were selected for the research study. A 10-item online questionnaire that people can fill out on their own will be used to get the data needed for the analysis and meet the study's goals. Results: the analysis has indicated that facing negative reactions after blood transfusion and being worried about getting affected by any infection have a small positive association, with the specific values coming in at r = 0.317, p = 0.000. Fever after blood transfusion and feeling like refusing blood transfusion have a significant and moderate positive correlation, with the specific values coming in at r = 0.630 and p = 0.000. Conclusion: The findings of this study have helped us figure out how healthcare providers feel, what they know, and what they do during a blood transfusion.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

As a 21st century trend, sustainability has encompassed the entire world economy, including industry. Today the concept of "Industry 4.0" is known, resulting from advances in ICT (information and communication technologies). In recent years, companies in the metal materials industry have also implemented strategies and technologies belonging to the Industry 4.0 concept. The main purpose of the manuscript is to identify the key issues in the evolution of the development of the metal materials industry. The transition to a higher level of its evolution is based on two vectors, namely: the ecological paradigm, as a vector of in-depth knowledge, and sustainable material, as a vector that ensures sustainability in the areas of convergence of systems in the spheres of life and social consciousness. The systems that have an impact on the sustainable development of the metallic materials industry, through the interactions between them, are: the technological system, the social system and the natural-ecological system. Global knowledge re-quires the use of all inter and multidisciplinary knowledge, which ultimately contributes to the definition and characterization of new intersystem scientific branches: Ecometallurgy, Metallurgical Economics, Metallurgical Ecosociology and Sustainable Materials Engineering. The paper is considered a research study based on elements such as: literary foundations, using databases such as Web of Science (WoS), Scopus, Google Scholar, sustainable universal principles and legislative parameters.