Zero-Knowledge Proofs ZKP provide a reliable option to verify that a claim is true without giving detailed information other than the answer. A classical example is provided by the ZKP based in the Graph Isomorphism problem (GI), where a prover must convince the verifier that he knows an isomorphism between two isomorphic graphs without publishing the bijection. We design a novel ZKP exploiting the NP-hard problem of finding the algebraic ideal of a multivariate polynomial set, and consequently resistant to quantum computer attacks. Since this polynomial set is obtained considering instances of GI, we guarantee that the protocol is at least as secure as the GI based protocol.

With the emergence of blockchain and smart contracts, traditional digital applications 1 such as identity management, supply chain management, banking and finance etc. are expected 2 to be transformed into Decentralized Applications (DApps). Blockchain interoperability is a new 3 and exciting aspect of blockchain technology that is quickly gaining popularity in many industries. 4 However, the widespread use of blockchains has not yet been achieved because DApps running on the 5 blockchain using smart contracts require access to authentic off-chain data. Users are more conscious 6 of their personal data privacy and consequently are more reluctant to share their data, posing a 7 challenge in the adoption of DApps. To solve this challenge, we present a novel quantum-resistant, 8 data authentication and zero-knowledge proof scheme named zk-DASTARK. Based on our proposed 9 scheme, we present a novel framework which can be used to feed authenticated off-chain data to 10 DApps without compromising user data privacy. Our proposed framework is quite efficient against 11 well-known off-chain data authentication frameworks. The proposed framework is implemented on 12 state-of-the-art quantum-resistant IOTA Blockchain and is highly efficient as it takes approximately 13 60 ms to generate a proof and approximately 10 ms to verify a proof.

Internet of Things includes all connected objects from small embedded systems with low computational power and storage capacities to efficient ones, as well as moving objects like drones and autonomous vehicles. The concept of Internet of Everything expands upon this idea by adding people, data and processing. The adoption of such systems is exploding and becoming ever more significant, bringing with it questions related to the security and the privacy of these objects. A natural solution to data integrity, confidentiality and single point of failure vulnerability is the use of blockchains. Blockchains can be used as an immutable data layer for storing information, avoiding single point of failure vulnerability via decentralization and providing strong security and cryptographic tools for IoE. However, the adoption of blockchain technology in such heterogeneous systems, containing light devices, presents several challenges and practical issues that need to be overcome. Indeed, most of the solutions proposed to adapt blockchains to devices with low resources confront difficulty in maintaining decentralization or security. The most interesting are probably the Layer 2 solutions which build offchain systems strongly connected to the blockchain. Among these, zk-rollup is a promising new generation of Layer 2/off-chain schemes which can remove the last obstacles to blockchain adoption in IoT, or more generally, in IoE. Despite their promises illustrated by recent systems proposed by startups and private companies, very few scientific publications explaining or applying this barely-known technology have been published, especially for non-financial systems. In this context, the objective of our paper is to fill this gap for IoE systems in two steps. We first propose a synthetic review of recent proposals to improve scalability including onchain (consensus, blockchain organization, ...) and offchain (sidechain, rollups) solutions and we demonstrate that zk-rollups are the most promising ones. In a second step, we focus on IoE by describing several interesting features (scalability, dynamicity, data management, ...) that are illustrated with various general IoE use cases.

In this paper I take the book by Michel Serres “Thumbelina” as the occasion for a reflection on the conceptual basis of knowledge management, as it was built by Ikujiro Noanka and co-workers. The direct access to knowledge that Thumbelina practices together with her peers is, in fact, for me, a god observation point to bring the reflection of Nonaka further, towards the discovery of a new understanding of knowledge and knowing processes. If the digital revolution is third step after writing and printing, in the soft changes in the relations between human beings and knowledge, then it poses in an urgent manner the problem to deepen our understanding of what knowledge and intelligence are and to change our practice at the education level and to design new digital tools to support our knowledge management processes.

As Cybercrimes continue to rise, researchers and industry players have continued to work hard to come up with solutions that could reduce and possibly eradicate these criminalities. This research has been able to discover the major factor that usually causes people to fall prey to these cyber criminals. This was why a school of thought came up with the Zero Trust Access model to strengthen the network framework. While previous network assets relied on the "trust but verify" philosophy, this technology's primary tenet is "never trust, always verify," which applies to every user and device connected to the network. This study interrogated the existing network models of the Integrative Trust Model (ITM) and Zero Trust Access (ZTA) in addition to the trust model (TA) to understand their concepts, implementation needs, strengths, and shortcomings. This made it possible for the study to establish the position of the ZTA model in repositioning the network security architectures vis-a-vis protecting the users

This paper presents how social media platforms and their components could be integrated into the KMS for the purpose of managing and sustaining Somali Indigenous knowledge (IK). The discovery of knowledge and its utilization is now fuelled by the advancement of technology, which connects users to external sources through using different platforms. The rapidly increasing use of SM and mobile technologies create opportunities to form knowledge networks that can facilitate the process of creating, preserving, and sharing knowledge and skills that are unique to communities in the Somali context. Somali society being an oral society with rich IK and other cultural practices lacked a framework in place to organize the existing knowledge in various methods. The paper refers to existing methodology E-learning and KM functions. This method first identifies functional similarities between SM, E-Learning, and KM systems and their interactions if they are properly integrated. The proposed framework consists of two functional parts; KM and SM. The KM part involves knowledge capturing, validation, formatting, storing, and distribution. SM part of the framework involves knowledge presentation, sharing, and application. Since the Somalis are said to be an oral society, this framework helps to capture and disseminate IK residing in knowledge holders.

While the knowledge about the development of understanding positive integers is rapidly growing, the development of understanding zero is not well-known. Here we tested several components of preschoolers’ understanding zero: whether they can use empty sets in numerical tasks, whether they can use empty sets soon after they understand the cardinality principle, whether they know what the word “zero” refers to, and whether they categorize zero as a number. The results show that preschoolers can handle empty sets in numerical tasks as soon as they understand the cardinality principle or even earlier, and some of them know that these sets are labeled as “zero.” However, they are unsure whether zero is a number. These results identify three components of knowledge about zero: operational knowledge, linguistic knowledge, and meta knowledge. To account for these results we propose that preschoolers might understand numbers as the properties of items or objects in a set. In this view, zero cannot be a number, because an empty set does not include any items, and the missing items cannot have any property, excluding also the number property. This model might explain why zero is handled correctly in numerical tasks, while it is not regarded to be a number.

Zero-shot learning ability robotics enables robots to generalize their knowledge and perform tasks for which they have not been explicitly trained. This ability is extremely helpful because in classic learning approaches, robots are trained on specific tasks and require extensive data and labeled examples to perform accurately. However, in real-world scenarios, robots often encounter new or unseen tasks that were not part of their training data. We briefly survey works in this area to give the reader a perspective about progresses in this area.

While there is a coordinated effort around reaching zero dose children and closing existing equity gaps in immunization delivery, it’s important that there is agreement and clarity around how ‘zero dose status’ is defined and what is gained and lost by using different indicators for zero dose status. There are two popular approaches used in research, program design, and advocacy to define zero dose status: one uses a single vaccine to serve as a proxy for zero dose status, while another uses a subset of vaccines to identify children who have missed all routine vaccines. We provide a global analysis utilizing the most recent publicly available DHS and MICS data to compare the number, proportion, and profile of children 12 to 23 months who are ‘penta-zero dose’ (have not received the pentavalent vaccine), ‘truly’ zero dose (have not received the BCG, polio, pentavalent, and measles vaccines), and ‘misclassified’ zero dose children (those who are penta-zero dose but have received at least one other vaccine). Our analysis includes 194,829 observations from 82 low- and middle-income countries. Globally, 14.2% of children are penta-zero dose and 7.5% are truly zero dose, suggesting that 46.5% of penta-zero dose children have had at least one contact with the immunization system. While there are similarities in the profile of children that are penta-zero dose and truly zero dose, there are key differences between the proportion of key characteristics among truly zero dose and misclassified zero dose children, including access to maternal and child health services. By understanding the extent of connection zero dose children may have with the health and immunization system and contrasting it with how much the use of a more feasible definition of zero dose may underestimate the level of vulnerability in the zero dose population, we provide insights that can help immunization programs design strategies that better target the most disadvantaged populations. If the vulnerability profiles of the truly zero dose children are qualitatively different from that of the penta zero dose children, then failing to distinguish the truly zero dose populations, and how to optimally reach them, may lead to the development of misguided or inefficient strategies for vaccinating the most disadvantaged population of children.

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.

The zero-catch problem is a key issue in CPUE(Catch Per Unit Effort) standardization, and previous studies have treated all zero-catch data uniformly, but this actually loses some correctly-labeled samples. On the other hand, for the main catches with few zero-catch samples, the problem of low performance of fisheries forecasting remains unsolved even though the forecasting model structure is updating constantly, since we cannot know whether the samples are correctly recorded. In this paper, we propose a method based on confident learning theory to detect anomalous samples in the datasets and unify zero-catch and non-zero samples as noise through an overarching framework of learning with noisy labels, which reveals the heterogeneity among zero-catch samples (as well as among non-zero samples) and the homogeneity between zero-catch samples and non-zero samples. Using three species of tuna in the tropical Atlantic Ocean with the spatial resolution of 0.5 ◦ × 0.5 ◦ and time resolution of days from 2016 to 2019 as experimental material, performance on all three classical machine learning models(Random forest, Support Vector Machine and XGBoost) is significantly improved compared to each baseline.This confirms that we propose a self-adaptive, effective method for detecting and repairing anomalous samples in the fishery dataset.

Zero-dose children, or children who have not received any routine vaccination, are a priority population for global health policy makers as these children are at high risk of mortality from vaccine-preventable illnesses. We conducted a narrative review to identify potential interventions, both within and outside of the health sector, to reach zero-dose children. We reviewed peer-reviewed and grey literature and identified 59 relevant resources. Additionally, we interviewed six key informants to enhance synthesis of our findings. Data were organized into three priority settings: (1) urban slums, (2) remote or rural communities, and (3) conflict settings. We found that zero-dose children in the three-priority settings face differing barriers to vaccina-tion and, therefore, require context-specific interventions, such as leveraging slum health commit-tees for urban slums or integrating with existing humanitarian response services for conflict set-tings. Three predominant themes emerged for grouping the various interventions: (1) community engagement, (2) health systems strengthening and integration, and (3) technological innovations. The barriers to reaching zero-dose children are multifaceted and nuanced to each setting, there-fore, no one intervention is enough. Technological interventions especially must be coupled with community engagement and health systems strengthening efforts. Evaluations of the suggested interventions are needed to guide scale up, as the evidence-base around these interventions is rel-atively small.

During the creation and integration of a health care system based on medical knowledge graphs, it is necessary to review and select the vocabularies and definitions that best fit the information requirements of the system being developed. This implies the reuse of medical knowledge graphs; however, full importation of knowledge graphs is not a tractable solution in terms of memory requirements. In this paper we present a modularization-based method for knowledge graph reuse. A case study of graph reuse is presented by transforming the original model into a lighter one.

This paper is motivated by three main assumptions: (1) The currently dominant forms of knowledge representation (natural language text, formulas, graphics) are suboptimal to facilitate knowledge transfer between control engineering sub-fields and into potential application domains. (2) Formal knowledge representation (in general) is a promising supplementary approach, but (3) the established technologies so far have failed to be significantly adopted for formal representation of control engineering knowledge. Thus, after briefly reviewing existing representation methods, we introduce our own approach: The Python based imperative representation of knowledge (PyIRK) and its application to formulate the Ontology of Control Systems Engineering (OCSE). One of its main features is the possibility to represent the actual content of definitions and theorems as nodes and edges of a knowledge graph, which is demonstrated by selected elements from Lyapunov theory. While the approach is still experimental, the formalization already allows to apply methods of automated quality assurance and a semantic search mechanism. The current feature set of the framework is demonstrated on various examples before directions for further developments are discussed.

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.

The realization of the third-generation artificial intelligence (AI) requires the evolution from perceptual intelligence to cognitive intelligence, where knowledge graphs may not meet the practical needs anymore. Based on the dual channel theory, cognitive graphs are established and developed through coordinating the implicit extraction module and the explicit reasoning module as well as integrating knowledge graphs, cognitive reasoning and logical expressions, which have achieved successes in multi-hop question answering. It is desired for cognitive graphs to be widely used in advanced AI applications such as large-scale knowledge representations and intelligent responses, promoting the development of Al dramatically. This review discusses cognitive graphs systematically and elaborately, including basic concepts, generations, theories and technologies. Moreover, we try to predict the development of cognitive intelligence in the short-term future and further enlighten more researches and studies.

Whilst prior works have characterised the affordances of prototyping methods in terms of generating knowledge about a product or process, the types, or ‘dimensions’ of knowledge towards which they contribute are not fully understood. In this paper we adapt the concept of ‘design domains’ as a method to interpret, and better understand the contributions of different prototyping methods to design knowledge in new product development. We first synthesise a set of ten dimensions for design knowledge from a review of literature in design-related fields. A study was then conducted in which participants from engineering backgrounds completed a Likert-type questionnaire to quantify the perceived contributions to design knowledge of 90 common prototyping methods against each dimension. We statistically analyse results to identify patterns in the knowledge contributions of different methods. Results reveal that methods exhibit significantly different contribution profiles, suggesting different methods to be suited to different knowledge generation. Thus, this paper indicates potential for new methods, methodology and processes to leverage such characterisations for better selection and sequencing of methods in the prototyping process.

An exposition of entropy applications to highlight some potential entropic applications to artificial intelligence and knowledge transfer. Entropy is a basic idea in artificial intelligence that is applied to many different tasks, such as reinforcement learning, data compression, and decision-making. By quantifying uncertainty and information content, it helps artificial intelligence models provide predictions and decisions that are well-informed. Therefore, this paper shines on spotlighting the significance of entropy to attract the attention of artificial intelligence research community to entropy as a powerful tool to advance artificial intelligence.The significance of knowledge transfer (KT), particularly intergenerational knowledge transfer (IGT), in knowledge management is also covered in this paper. To quantify the complexity of knowledge distribution inside an organisation and assess the efficacy of knowledge transfer (KT) initiatives, the notion of knowledge entropy (KE) is presented. Additionally, the KT model—which is based on the conceptions of tacitness and information content—is introduced. It combines personalisation and codification methodologies. Future research directions are offered alongside a few difficult open problems.

Energy market price volatility and an upward trajectory of prices per unit of electricity have sent all industrial sectors and many economies to the brink of recession. Alongside the urgent need for decarbonisation of all industries, achieving a higher level of energy independence across all sectors seems imperative. A multi-disciplinary approach with a proposed system of CO₂ emissions reduction and capture technologies has the potential for short-term emissions reduction to near-zero in absolute terms. The findings of this research showed CO₂ emissions reduction of ~30% from 977t of CO_2e to 684t in one single blast furnace production cycle, by switching the energy provider generating energy exclusively from renewable sources. Replacing coal with biomass (BECCS), resulted in an additional reduction of ~30%, to CO_2e to 479t CO_2e. Installing solar PV panels for energy generation on site resulted in a further ~30% reduction, to 335 tonnes CO_2e. Finally, the installation of CO₂ filters reduced the CO₂ emissions to near-zero. Simultaneously, energy-saving and process improvement measures implementation (up to 60% efficiency increase), excess heat recovery (<30% of energy savings), and retrofitting renewable energy technology resulted in an energy independence of 88%. Short-term engineering solutions, partly subsidised in the UK, are readily available.

Recently, the focus of entity linking research has centered on the zero-shot scenario, where the entity mention to be labeled at the time of testing was never observed during the training phase or may belong to a different domain than the source domain. Current studies have used BERT as the base encoder as it effectively establishes distributional links between source and target domains. The currently available negative sampling methods all use an extractive approach, which makes it difficult for the models to learn diverse and more challenging negative samples. To address this problem, we propose a generative negative sampling method, Adaptive_mixup_hard, which generates more difficult negative entities by fusing the features of both positive and negative samples on top of hard negative sampling and introduces a transformable adaptive parameter W to increase the diversity of negative samples. Next, we fuse our method with the Biencoder architecture and evaluate its performance under three different score functions. Ultimately, experimental results on the standard benchmark dataset Zeshel demonstrate the effectiveness of our method.

The global agricultural sector is increasingly pressured to adopt sustainable practices and reduce its environmental impact. In this context, greenhouses play a crucial role in enabling year-round crop production, ensuring food security, and minimizing reliance on traditional open-field farming. However, the energy consumption associated with greenhouse operations poses a significant challenge to achieving sustainability goals. As a result, there is a growing emphasis on transitioning greenhouses towards near-zero energy consumption. Near-zero energy consumption in greenhouses refers to the ambitious objective of minimizing energy usage to the greatest extent possible while maintaining optimal growing conditions for crops. This goal encompasses reducing energy consumption for heating, cooling, lighting, and other operational needs, as well as exploring renewable energy sources to power greenhouse operations. This review article offers a comprehensive overview of greenhouse energy consumption, with the main goal of analyzing the present situation, identifying key challenges, exploring potential opportunities, and proposing future perspectives for decreasing energy usage in greenhouse environments. As the focus on sustainable agricultural practices grows, the need to reduce energy consumption in greenhouses becomes increasingly important. The review critically examines current technological models and strategies applied in smart greenhouse applications, as well as the monitoring of microclimatic conditions inside the greenhouse, encompassing factors such as temperature, humidity, CO2 levels, soil quality, and crop cultivation. Moreover, it aims to present existing literature that investigates the advancement of greenhouses toward achieving significant reductions in energy consumption.

Epsilon-near-zero nanoantennas can be used to tune the far-field radiation pattern due to their exceptionally large intensity-dependent refractive index. Here, we propose hybrid optical antenna based on indium tin oxide (ITO) to optically tune the deflection of radiation. In particular, a hybrid structure antenna of ITO and dielectric material, which makes the deflection angle changes 17 ∘ as incident intensities increases. Finally, the array of ITO or hybrid nanodisks can enhance the unidirectionality to be needle-like, with the angular beam width α< 8∘ of main lobe. The deflection angle of radiation pattern response with needle-like lobe pave the way for further studies and applications in beam steering and optical modulation where dynamic control of the nanoantennas is highly desirable.

Through history, particular attention has been paid of the study of the relationship between the energy use and the city structure. Improving energy efficiency in modern agglomerations is the most promising means to mitigate climate change and its impacts. In this current context of globalisation, European Union proposes initiatives and policy targets to rethink the urban development strategies towards the ‘zero energy objectives’. Providing a methodological approach with a simulation district analysis, the present article summarizes how the ‘zero energy’ challenge is analyzed in an existing district (Epinlieu) to articulate the users’ requirements in energy. This study contributes to the scientific discussion of the districts’ urban structure and energy planning by establishing a linkage among the beneficial influence of the KPIs of the districts’ form to increase their energy efficiency and its application in a real case study in Belgium.

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.

Scientific social networking sites like Researchgate or Academia.edu have become part of the work practice of academic researchers. These digital platforms have been designed precisely to encourage the exchange of knowledge between scholars and to help the expansion of collaborative networks among them. Even if studies on this topic have multiplied in recent years, there is a dearth of research on the actual impact of these platforms on scientific production. The goal of this study is to investigate the relation between the attitude of researchers towards scientific social networks and the use of knowledge in their scientific work. Data from users of the scientific social networking site Researchgate were collected. A total of 143 valid responses were received and structural equation modeling was applied for data analysis. Findings of this study confirmed that researchers use knowledge obtained from scientific social networking sites both incorporating it within their research products and to acquire new competences. In particular approaching the platform as a scientific community with a shared language and a shared vision was found to have a positive impact on knowledge use. To the best knowledge of the authors this is the first study investigating the actual use of knowledge from scientific social networking sites by academic researchers. Results help to understand the impact of these platforms on the work practice of a strategic sector like scientific research.

Leveraging the open-world understanding capacity of large-scale visual-language pre-trained models has become a hot-spot in point cloud classification. Recent approaches rely on transferable visual-language pre-trained models, classifying point clouds by projecting them into 2D images and evaluating consistency with textual prompts. These methods benefit from the robust open-world understanding capabilities of visual-language pre-trained models and require no additional training. However, they face several challenges summarized as prompt ambiguity, image domain gap, view weights confusion, and feature deviation. In response to these challenges, we propose PointBLIP, a zero-training point cloud classification network based on the recently introduced BLIP-2 visual-language model. PointBLIP is adept at processing similarities between multi-images and multi-prompts. We separately introduce a novel method for point cloud zero-shot and few-shot classification, which involves comparing multiple features to achieve effective classification. Simultaneously, we enhance the input data quality for both the image and text sides of PointBLIP. In point cloud zero-shot classification tasks, we outperform state-of-the-art methods on three benchmark datasets. For few-shot classification tasks, to the best of our knowledge, we present the first zero-training few-shot point cloud method, surpassing previous works under the same conditions and showcasing comparable performance to full-training methods.

Biodiversity plays an important role in maintaining the ecological balance of the earth. The study of traditional knowledge related to biological resources is a hot issue in the field of international biodiversity conservation. Xishuangbanna is a key area of biodiversity and a cultural hotspot of international significance. According to the Technical Regulation for Classification, Investigation, and Inventory of Traditional Knowledge Relating to Biological Diversity issued by the Ministry of Ecology and Environment, we investigated and catalogued the traditional knowledge related to biodiversity of the Jino people who have lived in Xishuangbanna for generations, and collected 490 entries of traditional knowledge related to biodiversity of the Jino people. Drawing on the traditional knowledge diversity index calculation method proposed by Wang Guoping, the overall traditional knowledge α-diversity index of the Jino people is 0.63, indicating that the richness of the traditional knowledge of the Jinuo people is relatively high. The traditional culture related to biodiversity, the traditional knowledge related to agricultural genetic resources, and the traditional technology related to the sustainable utilization of biological resources are relatively rich and diverse. The diversity index is 0.86, 0.82 and 0.79 respectively. In addition, Xishuangbanna has invested a lot of energy in biodiversity protection, including the establishment of nature reserves, botanical gardens, zoos, ecological tea gardens and other species reserves, the promulgation of laws and policies related to biodiversity protection, and has achieved remarkable results in in-situ protection and ex-situ protection. On the basis of analyzing the progress and achievements of biodiversity conservation in Xishuangbanna, this study points out that Xishuangbanna faces challenges such as the loss of traditional knowledge, insufficient conservation efforts, and great changes in land use, and puts forward corresponding suggestions.

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.

In an innovation driven business environment, cross-border access to resources is important for companies to improve innovation capabilities and development performance. Based on the previous research, it shows that there are barriers to cross domain communication among alliance firms because of the restriction of multidimensional ties and dyads. Simmelian ties, as a form of alliance network with ternary connections, it effectively restrained opportunism and self-interest in the cooperation process and take a crucial role to evaluate innovation related performance in corporation. Based on the theory of Simmelian, this paper builds a theoretical framework and proposes corresponding research hypotheses between Simmelian ties and enterprise innovation performance. After designing questionnaires, collecting data and conducting empirical analysis to test theoretical models and hypotheses. Results have shown that: (1) Simmelian ties generally have a positive impact on enterprise innovation performance. (2) Knowledge capturing and knowledge integration play a partial intermediary role between Simmelian ties and enterprise innovation performance, and the mediating chain formed by the two variables plays a serial mediating role in the effect. (3) Network routines significantly positively moderates the relationship between Simmelian ties and knowledge capturing. And also, the positive relationship between Simmelian ties and enterprise innovation performance is also actively moderated by network routines. The conclusion of this study is meaningful for companies to establish of Simmelian ties, improve knowledge management capabilities and further promote enterprise innovation performance.

In this digital world, organisations are facing global competition as well as manpower pressures leading towards knowledge economy, which heavily impacts on their local and international businesses. The trend is to foster collaboration and knowledge sharing to cope with these problems. With the advancement of technologies and social engineering that can connect people in virtual world across time and distance, several organisations are embarking on knowledge management (KM) systems, implementing community of practice (CoP) approach. However, virtual communities are relatively new paradigms, and there are several challenges to their successful implementation from an organisation’s point of interest. There is lack of CoP implementation framework that can cater to today’s dynamic business and sustainability requirements. To fill the gap in literature, this paper develops a practical framework for a CoP implementation with a view to align KM strategy with business strategy of an organization. It explores the different steps of building, sharing and using tacit and explicit knowledge in CoPs by applying Wiig KM cycle. It proposes a practical CoP implementation framework that adopts the Benefits-Tools-Organisation-People-Process (BTOPP) model in addressing the key questions surrounding each of the BTOPP elements with a structured approach. Finally, it identifies key challenges such as organizational culture and performance measurements, and provides practical recommendations to overcome them for a successful CoP implementation.

Background: Manoka Health District (MHD), an enclaved archipelago district in Cameroon, is home to about 1,732 under-2 children. Over 90% of these children have not received a single dose of any vaccine. In this paper, we explored the reasons for the high proportion of zero-dose children in this district so as to generate information that policymakers can use to develop context-specific interventions to boast coverage for routine immunization (RI) in this remote fishing island Methodology: We collected qualitative data via key informant interviews (KII) and focused group discussions (FGD) and analyzed it using thematic analysis. Participants for KII were selected using purposive sampling, and a snowballing approach helped to recruit an intermixed population of locals and immigrants for FGDs. Results: MHD is a hard-to-reach zone with a lone health facility that lack a functional cold chain equipment to cover the 47 islets of the district. Diurnal floods, long distance, sea turbulence, infrastructural and resource constraints, and immigrant population without residence permits hinders optimal childhood vaccination. Insufficient community health workers and lack of proper community engagement with feedback loops hamper effective communication and vaccine uptake during campaigns and outreaches. The reasons for vaccination hesitancy included hospital-based vaccination preference over home-based vaccination, fear of post-vaccination fever, rumors, repeated postponement of the vaccination schedules, and refusal by some ethnic group leaders. Conclusion: This study revealed context-specific reasons for zero-dose childhood vaccination status in MHD. These findings should be leveraged to design tailored interventions to raise RI in MHD and similar under-vaccinated communities. Keywords: zero-dose, childhood vaccination, missed communities, Cameroon

New setting is introduced to study failed zero-forcing number and failed zero-forcing neutrosophic-number. Leaf-like is a key term to have these notions. Forcing a vertex to change its color is a type of approach to force that vertex to be zero-like. Forcing a vertex which is only neighbor for zero-like vertex to be zero-like vertex but now reverse approach is on demand which is finding biggest set which doesn’t force. LetNTG : (V,E,σ,μ) be a neutrosophic graph. Then failed zero-forcing number Z(NTG) for a neutrosophic graph NTG : (V,E,σ,μ) is maximal cardinality of a set S of black vertices (whereas vertices in V (G) \ S are colored white) such that V (G) isn’t turned black after finitely many applications of “the color-change rule”: a white vertex is converted to a black vertex if it is the only white neighbor of a black vertex. Failed zero-forcing neutrosophic-number Zn(NTG) for a neutrosophic graphNTG : (V,E,σ,μ) is maximal neutrosophic cardinality of a set S of black vertices (whereas vertices in V (G) \ S are colored white) such that V (G) isn’t turned black afterfinitely many applications of “the color-change rule”: a white vertex is converted to a black vertex if it is the only white neighbor of a black vertex. Failed zero-forcing number and failed zero-forcing neutrosophic-number are about a set of vertices which are applied into the setting of neutrosophic graphs. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs namely path-neutrosophic graphs, cycle-neutrosophic graphs, complete-neutrosophic graphs, star-neutrosophic graphs, bipartite-neutrosophic graphs, and t-partite-neutrosophic graphs are investigated in the terms of maximal set which forms both of failed zero-forcing number and failed zero-forcing neutrosophic-number. Neutrosophic number is reused in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number to compare with other vertices. Summation of three values of vertex makes one number and applying it to a comparison. This approach facilitates identifying vertices which form failed zero-forcing number and failed zero-forcing neutrosophic-number. In path-neutrosophic graphs, the set of vertices such that every given two vertices in the set, have distance at least two, forms maximal set but with slightly differences, in cycle-neutrosophic graphs, the set of vertices such that every given two vertices in the set, have distance at least two, forms maximal set. Other classes have same approaches. In complete-neutrosophic graphs, a set of vertices excluding two vertices leads us to failed zero-forcing number and failed zero-forcing neutrosophic-number. In star-neutrosophic graphs, a set of vertices excluding only two vertices and containing center, makes maximal set. In complete-bipartite-neutrosophic graphs, a set of vertices excluding two vertices from same parts makes intended set but with slightly differences, in complete-t-partite-neutrosophic graphs, a set of vertices excluding two vertices from same parts makes intended set. In both settings, some classes of well-known neutrosophic graphs are studied. Some clarifications for each result and each definition are provided. Using basic set not to extend this set to set of all vertices has key role to have these notions in the form of failed zero-forcing number and failed zero-forcing neutrosophic-number. The cardinality of a set has eligibility to form failed zero-forcing number but the neutrosophic cardinality of a set has eligibility to call failed zero-forcing neutrosophic-number. Some results get more frameworks and perspective about these definitions. The way in that, two vertices don’t have unique connection together, opens the way to do some approaches. A vertex could affect on other vertex but there’s no usage of edges. These notions are applied into neutrosophic graphs as individuals but not family of them as drawbacks for these notions. Finding special neutrosophic graphs which are well-known, is an open way to pursue this study. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Theoretical analysis into the energetics of a novel putative electromagnetic field propulsion device by the author, found that it was able to impart momenergy to the ground state of the electromagnetic field; some rest-energy of the craft was converted to kinetic energy of the craft. Electrical analysis showed that the propulsor was always a net electrical load – if the device accelerated from one frame, then deaccelerated to the original frame, both processes would consume electrical work. The aim of this paper is to look further into this sinking of high-grade electrical energy into the field ground state and to show that an even more pernicious form of 2^nd Law of Thermodynamics exists.

Clinical trials, by contributing to the development of diagnostics and to the search for modern, more effective, and safer therapies, have become one of the most important elements of the healthcare system. The aim of this study was to assess Poles' knowledge and beliefs about clinical trials. Methods: The survey was conducted among Poles aged 18 and over with the help of external company, Ariadna, which is an independent research panel. The questionnaire contained 22 questions, of which 13 questions concerned beliefs and attitudes towards clinical trials. Results: One thousand and seventy-nine participants took part in the study (N = 1079). The mean age of respondents was 44.96 years (SD = 16.30). Slightly more women (N = 568, 52.6%) than men (N = 511, 47.4%) took part in the study. Among the respondents, 86.5% (N = 933) were aware of clinical trials. The main sources of information about clinical trials were the media (53.8%) including the Internet (N= 355, 32.9%), TV (N = 175, 16.2%), press (N = 30, 2.8%) and radio (N = 21, 1.9%). 43.2% (N = 466) of respondents reported little knowledge of clinical trials, while more than three quarters (N = 805, 75.2%) said they would like to learn more about clinical trials. Most respondents (N = 879, 81.4%) agreed with the statement that participation in a clinical trial is completely voluntary, and more than half (N = 580, 53.7%) agreed with the statement that hospitals participating in clinical trials provide better healthcare. The statement that the results of clinical trials are made available to the public was disagreed with by 37.2% (N = 402) of participants. Only 30.3% (N = 327) of participants agreed that clinical trials should be conducted with children. Conclusions: Poles rate their knowledge of clinical trials as low and would like to learn more. To reach the largest possible group of Polish patients, parallel educational activities on multiple levels may have the best effect. Poles' knowledge of clinical trials is mainly based on commercial sources. Further studies in different groups, i.e., clinical trial patients and investigators, are needed.

This article aims to highlight the intricate interplay between psychological knowledge and local wisdom. Ethiopia is a diverse and multicultural country, with a rich diversity of languages, cultures, and traditions. Ethiopian local stories, proverbs, and poems have long served as vessels of wisdom, offering valuable life lessons and insights into human behavior. This article seeks to uncover the local wisdom through psychological lenses by demonstrating the psychological richness embedded within Ethiopian local stories, proverbs, and poems. Thus, valuable insights can be found by drawing connections between these traditional forms of wisdom and contemporary psychological theories. Moreover, researchers can foster a more inclusive and culturally sensitive approach to understanding and addressing psychological issues by bridging the gap between academic knowledge and local wisdom. This symbiotic relationship has the potential to expand the boundaries of psychological knowledge and encourage innovative ideas and principles, ultimately enriching both domains.

Artificial insemination (AI) is considered as the most efficient feasible tool to improve the dairy cows’ profitability and productivity. In bovines, AI helps to promote genetic improvement and can positively impact the rural economy. The achievement of education in rural populations was one of the Millennium Development Goals (MDGs), made by the United Nations. During the last World Summit on Sustainable Development (WSSD), it was concluded that most of the world’s poor, illiterate and undernourished population lives in rural areas; therefore, access to education is considered one of the greatest challenges for governments in countries with developing economies. To determine the effects of a theoretical-practical training program related to rural management and leadership, AI, and bovine genetic improvement, on the perception and level of knowledge in a rural Colombian population that has been affected by the armed conflict. Phase 1. Included the practical and theoretical training of undergraduate animal sciences students in three dimensions rural management; leadership (D-ML), AI in bovines (D-AI), and genetic improvement (D-GI) after training students were evaluated and selected according to their skills, characteristics, solidarity skills, and their social sensitivity was identified. Phase 2. Included the socioeconomic characterization and training of rural residents by students and field experts in three dimensions D-ML, D-AI, and D-GI. After training we evaluated the perception and level of knowledge before and after training in 63 rural residents using an evaluative instrument. The data before and after (post-test) of the theoretical-practical training, were analyzed to obtain a statistical significance. The perception of knowledge in rural residents was low for general knowledge (2.48±0.76, p ˂ 0.05), D-ML (2.89±1.18, p ˂ 0.05) and D-AI and D-GI (2.17±0.83, p ˂ 0.05). On the other hand, before the theorical-practical training the level of general knowledge was 45.9%, however, after the training increased at 77.6% (p<0.01), while the level of knowledge for the D-AI was increased from 38.5 % to 80.6 % (p ˂ 0.05) after training. Regarding the level of knowledge for the D-GI pre-training was 50.8 and increased to 73.0% (p<0.01) then after. Finally, the level of knowledge for the D-ML was increased (p<0.01) from 54.8 before training to 75% after training. Altogether, the rural extension programs contribute to the closing of knowledge gaps in relation to the use of reproductive biotechnologies and bovine management in rural areas affected by armed conflict.

Objectives: to assess the knowledge level of parents from the central region of Saudi Arabia about oral health and care of preschool children and its relation with sociodemographic variables, parents‟ self-perception toward their dental health, importance of teeth and frequency of dental visits. Methods: a random sample of 754 parents participated in this cross-sectional study and completed an internationally accepted questionnaire. Chi square test and logistic regression analysis were used to analyze the data (p<0.05). Results: mean knowledge score of the parents was 4.8 (out of 11). Less than 20% of the parents were knowledgeable about the best position for tooth brushing, the concentration of fluoride in a child‟s toothpaste, timing of first dental check-up, and best time to give a sugary snack. Mothers, parents with high educational level and family income, parents with positive attitude towards teeth and excellent self-perception of their dental health were significantly more likely to score higher (p<0.05). Conclusions: knowledge of parents about oral health and care of preschool children in the central region of Saudi Arabia was deficient. Gender, education level of parents, family income, attitude about teeth and self-perception of parents‟ own dental health were factors which influenced their knowledge. To improve parents‟ knowledge, role of health professionals should be improved and TV commercials directed toward the areas which had gaps in knowledge.

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.

This study explores the implementation of an interdisciplinary curriculum in product and media design education and its impact on knowledge innovation and competency development. The curriculum is based on scaffolding theory, incorporating design proposals, workshops, digital design, marketing tests, and marketing activities guided by teachers and mentors from a branded ceramic workshop. The research findings demonstrate that the interdisciplinary curriculum facilitates knowledge innovation and fosters the development of students' professional skills, creativity, and problem-solving skills. The study also highlights the importance of stable scaffolding, including artefact, peer, and teacher support, which significantly contributes to cultivating transformational competencies, as outlined in the 2030 OECD Learning Compass. Additionally, the collaboration with Shanshing Four Seasons Celadon Studio on a patented ceramic product, "Funny Monkey," is a tangible example of the journey towards a triple-helix knowledge economy. This research underscores the importance of interdisciplinary curricula in promoting knowledge innovation and integrating transformational competencies in education. Scaffolding theory provides practical guidance for student learning and teaching strategies, presenting a sustainable roadmap for developing interdisciplinary curricula and offering a concrete and transferable pedagogical prototype for educational innovation.

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.

When an aircraft malfunctions, quickly and accurately identifying the faulty unit is essential for ensuring normal operation. Unfortunately, maintenance engineers often struggle to acquire the necessary fault-related knowledge due to poor management and utilization of aircraft fault documents. To address this issue, we introduce knowledge graph technology into the field of aircraft fault diagnosis, exploring its construction and application for effective knowledge management. Our work starts by analyzing the critical knowledge elements required for aircraft fault diagnosis and designing a schema layer for fault knowledge graphs. We then we then combine deep learning and heuristic rules to extract fault knowledge from both structured and unstructured data, enabling the construction of aircraft fault knowledge graphs. Finally, we develop a fault question-answering system based on fault knowledge graphs that can accurately give solutions to questions posed by maintenance engineers. Our practice demonstrates that knowledge graphs provide an effective means of managing aircraft fault knowledge, assisting engineers in locating fault reasons accurately and quickly.

The photodegradation of azithromycin present was carried out in water using H2O2 under UV irradiation. The reaction variables considered in this study were the amount of H2O2 solution and the initial concentration of azithromycin to evaluate the performance of the photodegradation process. The azithromycin degradation was not observed in the dark during stirring for 20 minutes. The study showed efficient photodegradation of azithromycin using H2O2 as an oxidant in the presence of UV irradiation. The azithromycin degradation was affected significantly by the pH of the irradiated solution. The degradation was low at an acidic pH and showed an increasing trend as the pH changed to basic. The azithromycin degradation was increased with a higher amount (higher concentration) of H2O2. The degradation of azithromycin decreased with a higher concentration of azithromycin in the reacting solution. The highest degradation of AZT was achieved in 1 hour using a 1.0 ppm AZT solution containing 3 ml of H2O2. The experimental data obtained was well-fitted to zero-order reaction kinetics. The results of this study were found to be superior when compared with those reported in the literature, with photocatalysis using nanomaterials and photolysis using irradiation and H2O2. The UV/H2O2 system was found to be quite efficient for the photodegradation of azithromycin, and this system can be applied to degrade other organic pollutants present in industrial wastewater. To this point, such a study has not been reported specifically for AZT photodegradation.

This paper explores the potential of using the SAM segmentator to enhance the segmentation capability of known methods. SAM is a promptable segmentation system that offers zero-shot generalization to unfamiliar objects and images, eliminating the need for additional training. The open-source nature of SAM on GitHub allows for easy access and implementation. In our experiments, we aim to improve the segmentation performance by providing SAM with checkpoints extracted from the masks produced by DeepLabv3+, then merging the segmentation masks provided by these two networks. Additionally, we examine the \enquote{oracle} method (as upper bound baseline performance), where segmentation masks are inferred only by SAM with checkpoints extracted from ground truth. In addition, we tested in the CAMO datasets an ensemble of PVTv2 transformers; combining the ensemble and SAM yields state-of-the-art performance in that dataset. The results of our study provide valuable insights into the potential of incorporating the SAM segmentator into existing segmentation techniques. We release with this paper the open-source implementation of our method.

Valorization of food and fruit wastes has the potential for the production of sustainable energy and biochemicals. Approximately 70% of the weight of the original jackfruit (Artocarpus heterophyllus L.) fruit is lost during processing as waste in the form of peeled skin and core, both of which have not been utilized and, thus contribute to disposal as well as pollution issues. The major components, cellulose, and hemicellulose, can be biologically transformed easily into bioenergy sources like ethanol, methanol, and butanol; valuable phenolics and biotechnological products like pectin, citric acid, bromelain, ferulic acid, and vanillin; and many other products. These residues can also be utilized as essential sources for the biological transformation process leading to the production of numerous products with added value, such as phenolic antioxidants, phenolic flavor compounds, and organic acids. Thus, the value addition of jackfruit waste can support the sustainable solution towards food and nutritional security. In this way, zero waste can be achieved through novel biorefineries which are critically highlighted in this paper. Furthermore, novel technologies for the conversion of jackfruit wastes are summarized with recent findings.

Current State-of-the-Art (SotA) chatbots are able to produce high quality sentences, handling different conversation topics, and larger interaction times. Unfortunately, the generated responses highly depend on the data on which they have been trained, the specific dialogue history and current turn used for guiding the response, the internal decoding mechanisms, ranking strategies, among others. Therefore, it may happen that for semantically similar questions asked by users, the chatbot may provide a different answer, which can be considered as a form of hallucination or produce confusion in long-term interactions. In this research paper, we propose a novel methodology consisting of two main phases: a) hierarchical automatic detection of topics and subtopics in dialogue interactions using a Zero-Shot learning approach, and b) detecting inconsistent answers using K-Means and the Silhouette coefficient. To evaluate the efficacy of topic and subtopic detection, we used a subset of the DailyDialog dataset and real dialogue interactions gathered during the Alexa Socialbot Grand Challenge 5 (SGC5). The proposed approach enables detecting up to 18 different topics and 102 subtopics. For the purpose of detecting inconsistencies, we manually generate multiple paraphrased questions and employ several pre-trained SotA chatbot models to generate responses. Our experimental results demonstrate a weighted F-1 value of 0.34 for topic detection, a weighted F-1 value of 0.78 for subtopic detection in DailyDialog, then 81% and 62% accuracy for topic and subtopic classification in SGC5; finally, to predict the number of different responses, we obtained a mean squared error (MSE) of 3.4 when testing smaller generative models and 4.9 in recent large language models.

Despite the increase in popularity of Zero Waste (ZW) concept, the successful implementation of this concept in waste management is still facing many challenges. The plastic recycling rate in Australia is currently only about 9.4%, which could leave up to 90.6% of plastic consumption being sent to landfills. The state of Victoria (in Australia) has proposed an ambitious plan to upgrade its waste and recycling system and to divert about 80% of waste from landfills by 2030. The aim of this research is to study Victoria’s current waste management plan and to develop a simulation model to assess the feasibility of it achieving zero plastic waste by 2035. In this direction, a fundamental knowledge of global ZW implementation needs to be acquired in order to understand the challenges, obstacles, and uncertainties in achieving ZW target. A simulation model is established using a method called double baselines. This method was developed as an improvisation to address the limitation of data availability for the model development. The model will run on 4 scenarios including one from Victoria’s current plan. Outcomes from the model are produced in comparative charts covering 6 key considerations including the rates of plastic consumption, waste to landfill, diversion, recycling, relative accumulative cost and effort. The findings of this study pointed out that Victoria’s current plan are feasible for its goal and presented with opportunities for improvement especially towards zero plastic waste. Besides, study results also reveal that the Victoria’s current plan to achieve 80% diversion rate by 2030 is possible but the zero plastic waste target by 2035 is less likely to happen.

The zero velocity update(ZUPT) algorithm is the core of a foot-mounted pedestrian navigation system. The zero velocity detection method is the premise and guarantee of the effective application of the ZUPT algorithm. To make ZUPT work properly, it is necessary to detect zero velocity intervals correctly. The detection accuracy of the existing zero velocity detection methods is easy to be affected by users and environment. A novel zero velocity detection method based on the plantar pressure is proposed in this paper, which has higher detection accuracy and better environmental adaptability. First, the paper analyzes the motion characteristics of foot during walking. Second, the inherent relationship between the plantar pressure and the gait change during walking is studied based on the pressure sensor. Then, the model of the zero velocity detection method using the plantar pressure is established. Finally, the indoor and outdoor multi-scene experiments show that this method not only has a high detection accuracy, but also has good adaptability to users and walking environment.

Keywords: Knowledge; Attitudes; Practices; Salt intake.

Inconsistent results published in previous studies make it difficult to determine the precise effect of consumer knowledge on their acceptance of functional foods, which were developed to improve consumers’ health status by providing adequate nutrition. We conducted a systematic review and meta-analysis by identifying and collecting relevant literature from three databases. Of the 1050 studies we reviewed, we included 40 in the systematic review and 18 in meta-analysis. Based on the focus of each included study, we operationally defined knowledge as knowledge of the functional food concept, nutritional-related knowledge, and knowledge of specific functional products. Results from the systematic review indicate that most participants from the included studies had a low level of knowledge, especially nutrition-related knowledge associated with consuming functional foods, and they were generally not familiar with the concept of functional foods. It is possible that participants’ level of knowledge was influenced by their demographic characteristics (e.g., age, gender, educational level, marital status, nationality). Results from the meta-analysis generated a summary effect size (r = 0.14, 95% CI [0.05; 0.23]), measured by the correlation coefficient r, which indicates that a small positive relationship exists between consumers’ level of functional foods knowledge and their acceptance of functional foods.

Water literacy is the ability to feel familiar with and get actively involved in water to face issues about it. This study aims to analyze the water literacy of students who come from areas that have indigenous knowledge related to water conservation and do not have indigenous knowledge but have come from the same province with a similar abundance of water. The samples of this study were 439 people consisting of 184 boys and 255 girls aged 11-18 years from junior and senior high school students in Palembang Municipality and three sub-districts in Muara Enim Regency, namely Semende Darat Laut, Semende Darat Tengah, and Darat Ulu and both are indonesian. There were 39 questions for measuring water literacy in the form of a Likert scale (1-5) to measure practical and living literacy with Cronbach alpha values of 0.692 and 0.773, respectively, and were analyzed with SPSS version 21 through the Mann-Whitney (u) and Cronbach alpha statistical tests. The total alpha was 0.838. Social literacy was measured in the open-ended question instrument and analyzed descriptively. The results showed that practical water literacy in Palembang was significantly different from Semende's but not with living water literacy. Students' social water literacy in the Semende had two different answer patterns, while, in Palembang, it was more diverse with six different response patterns. Meanwhile, when asked to describe a diagram of the flow of water in nature in Semende, no students think that it is the neglect of customs that results in reduced water in Semende as understood by some students in Palembang who are not involved with these customs.

The aims of the study to analyze the influence of knowledge, attitude, education and gender of the head of the family for household preparedness against flood from Bengawan Solo River in Kedungdowo Village, Balen District of Bojonegoro Regency. The method used in this study is survey method. This study is explanatory observational research. Population studied is 85 head of families from Kedungdowo Village, Balen District, Bojonegoro Regency. The sampling method for collecting the data from the families is stratified random sampling. Data analysis methods used in this study are descriptive statistical analysis and logistic regression analysis with a 95% confidence level to identify the level of preparedness and the relationship between factors that affect preparedness. The findings shows that knowledge, attitude, education and gender significantly influence household preparedness against Bengawan Solo flood. Attitude is the most dominant variable that influenced household preparedness

Saudi Arabia is an oil-reliant nation as a large percentage of its GDP comes from oil resources. Oil dependency leaves a county at the mercy of the international crude market, and a decrease in the price of crude can seriously destabilize the economy of such nations. An example is the case of Venezuela whose dependence on oil caused a national disaster (McCarthy, 2017). As such, the nation’s exports, GDP, and government revenue are primarily dependent on oil revenue, and the recent decrease in the oil prices has decreased Venezuela’s national revenue resulting in economic collapse as well as inflation. A shift from a resource based economy to a knowledge based economy will help Saudi Arabia become less reliant on its oil revenues for its economic stability and growth (Nurunnabi, 2017).

Aiming to reveal the kinetic characteristics of ceramic ball grinding of fine magnetite comprehensively, two types of ceramic balls ground with the same filling rate and total weight as steel balls were researched. The results show that the breakage rate of ceramic ball grinding is only half of that of steel ball grinding with the same media filling rate. With the same total media weight and the feed size less than 0.212 mm, the breakage rate of the ceramic ball grinding approaches the steel ball grinding and is 21.43% higher than that of the steel ball grinding. The main crushing form of magnetite changed from impact to abrasion in ceramic ball grinding compared with steel ball grinding, which significantly affected the value of the zero-order output constant a. Consequently, there is a noticeable difference in the variation of the parameter β related to the fines generation rate of the ceramic ball grinding compared with the steel ball grinding.

Mill scale is the by-product of iron and steel industry. It can be recycled via sinter plant or solid as sinter feed materials. 85 to 90% of the constituent particles are more than 0.008 inches. The iron content is near around 70 %, with a very small amount of alkaline compounds and non-ferrous metals. Mill scale is polluted and contaminated with lubricants, oils and greases from the equipment. In this experiment for recovering of oil from mill scale, it is treated with three different methods. Then all methods were compared according to the ability of oil elimination and iron recovered. After washing and boiling with surfactants, large amount of polluted waste water becomes a problem for environment so this wastewater was utilized for making of Microbial Fuel Cells (MFCs), production of electricity in MFC depends on the biodegradation of organic materials, so different waste were added in wastewater for making MFC. The remaining of MFC was converted in bioethanol, biodiesel and biofertilizer. So this research is economical and environmentally friendly and fulfilled the important aspect of green environment with zero waste. It will be a mile stone in the research of metallurgy, environmental engineering, recycling technology and zero waste management.

Exploiting the linguistic knowledge of the source language for neural machine translation (NMT) has recently achieved impressive performance on many large-scale language pairs. However, since the Turkish→English machine translation task is low-resource and the source-side Turkish is morphologically-rich, there are limited resources of bilingual corpora and linguistic information available to further improve the NMT performance. Focusing on the above issues, we propose a multi-source NMT approach that models the word feature in parallel to external linguistic features by using two separate encoders to explicitly incorporate linguistic knowledge into the NMT model. We extend the word embedding layer of the knowledge-based encoder to accommodate for each word’s linguistic annotations in the context. Moreover, we share all parameters across encoders to enhance the representation ability of the NMT model on the source language. Experimental results show that our proposed approach achieves substantial improvements of up to 2.4 and 1.1 BLEU scores in Turkish→English and English→Turkish machine translation tasks, respectively, which points to a promising way to utilize the source-side linguistic knowledge for the low-resource NMT.

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.

The purpose of this paper is to propose a novel transfer learning regularization method based on knowledge distillation. Recently, transfer learning methods have been used in various fields. However, the problems such as knowledge loss still occur during the process of transfer learning to a new target dataset. To solve these problems, there are various regularization methods based on knowledge distillation techniques. In this paper, we propose a transfer learning regularization method based on feature map alignment used in the field of knowledge distillation. The proposed method is composed of two attention based submodules: self-pixel attention (SPA) and global channel attention (GCA). The self-pixel attention submodule utilizes both the feature maps of the source and target models, so that it provides an opportunity to jointly consider the features of the target and the knowledge of the source. The global channel attention submodule determines the importance of channels through all layers, unlike the existing methods that calculate these only within a single layer. Accordingly, transfer learning regularization is performed by considering both the internal of each single layer and the depth of the entire layer. Consequently, the proposed method using both of these submodules showed overall improved classification accuracy than the existing methods in classification experiments on commonly used dataset.

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.

This study aimed to investigate the knowledge of patients with hypertension about their condition, adherence to antihypertensive medication, and the factors influencing it. A cross-sectional study was conducted in two cardiology outpatient clinics of two tertiary hospitals, in Greece. The study included 188 patients diagnosed with hypertension. The patient’s knowledge about their disease and adherence to medication were assessed by using the HK-LS and A-14 scales, respectively. Patients had sufficient knowledge levels about their disease, but significantly low levels of adherence to medication. Patients with higher knowledge levels were more adherent to medications [r(188) = 0.885, p &lt; 0.001]. By using multivariate analysis, higher age (p = 0.018), residence in a more populous area (p = 0.041), more years with the disease (p = 0.012), and a lower number of medications (p = 0.03) were associated with higher levels of knowledge. Conversely, younger age (p = 0.036), lower educational levels (p = 0.048), fewer years with the disease (p = 0.001), and a higher number of medications (p = 0.003) were associated with lower adherence to medication. The Greek patients' hypertension knowledge was sufficient, however, adherence to medication was significantly low. Healthcare managers could utilize our findings to design targeted interventions for improving adherence to medication for these patients.

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.

Background:. Knowledge and positive perception of climate change are crucial for public participation in activities that contain climate change. Limited studies, particularly in South Africa have reported on the knowledge and perceptions of climate change by university students. Study Aim: This study aimed to assess the level of knowledge and perceptions of climate change by the science students at the University of South Africa (UNISA). Methods: This was a quantitative cross sectional survey, undertaken among science students using questionnaire emailed to 500 students in the School of Science through Unisa email system. Bivariate logistic regression was used to test the association between socio-demographics, level of knowledge and perceptions of climate change. Results: A total of 420 students participated in the study. They were predominantly male (70.3%), mostly younger than 35 years of age. Most of the respondents were in the 2nd (34.7%) and 3rd (33.8%) year of study. Majority of respondents (97.9%) knew and perceived (93.6%) that climate change was happening. Overall, 93.8% of respondents had an excellent knowledge and basic concepts of climate change. Conclusion: The majority of students were knowledgeable and had positive perceptions about the basic concepts of climate change. However, the year of study was not significantly associated with positive perceptions of climate change. There is need to include climate change modules in South African university curriculum.

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

Background: Exclusive breastfeeding (EBF) for the first 6 months of life improves the growth, health and survival status of newborns. Breastfeeding has been accepted as the most vital intervention for reducing infant mortality and ensuring optimal growth and development of children. Objectives: The general objective was to identify the factors affecting exclusive breastfeeding among working class women in selected wards in Egbedore Local Government in Osun state, Nigeria. Methodology: This was descriptive cross-sectional study. Leslie Kish formula was used for sample size calculation and multistage sampling was used in selecting 316 working class women for the study. A structured, self-administered questionnaire was used for data collection. Data was analyzed using SPSS version 21.0 and level of significance was set at 5%. Results: 58% of the respondents were between the ages of 25-30. 72% demonstrated good understanding of exclusive breastfeeding based on the 6 months WHO recommendation for exclusive breast feeding, 25.9% had a fair knowledge and awareness of exclusive breastfeeding. 63.3% of the working class mother has a good practice of exclusive breast feeding, 19.6% of the women moderately practices exclusive breastfeeding while 17.1% poorly practices exclusive breastfeeding. Less than 3-months maternity leave for mothers, lack of crèche closer to place of work and lack of breastfeeding break were identified as barriers to exclusive breastfeeding practices among the working class women. The findings demonstrated a significant relationship between knowledge and practices of exclusively breastfeeding among working class women (P-value .009). Conclusion: This study demonstrated that working class women had good knowledge of exclusive breastfeeding and this influenced their breastfeeding practices. A good knowledge was associated with favorable attitudes to the practice of exclusive breast feeding. To derive long-term benefits from early childhood nutrition, interventions should focus on health education and community-based sensitization programs on the needs for mothers to engage in exclusive breast needing for global development.

In the last decade several projects have been developed for the digitization and semantization of cultural heritage data. They were developed to preserve and maintain this heritage, but bringing it closer to all types of users and allowing access to this information to other sectors such as tourism, education, etc. In these developments, web technologies are combined, along with the use of knowledge graphs and interactive visualisation tools. Although remarkably interesting projects have been developed, in those projects, the data visualization tools are usually focused on the project context. This makes it difficult to reuse these jobs. Additionally, there are peculiarities of cultural heritage data considered with little depth, such as uncertainty, spatial and temporal granularity, as well as other aspects, such as relationships between data. In this article, these problems are described and based on other works such as VUMO or VISO, the design of an ontology that formalizes how to visualise this information is proposed, considering these problems. In addition, the development of a platform that allows the visualisation of this information through a web application and its evaluation of its use in projects such as SILKNOW, or Arxiu Valencià del Disseny is exposed

Federated Distillation (FD) has recently attracted increasing attention for its efficiency in aggregating multiple diverse local models trained from statistically heterogeneous data of distributed clients. Existing FD methods generally treat these models equally by merely computing the average of their output soft predictions for some given input distillation sample, which does not take the diversity across all local models into account, thus leading to degraded performance of the aggregated model, especially when some local models learn little knowledge about the sample. In this paper, we propose a new perspective that treats the local data in each client as a specific domain and design a novel domain knowledge aware federated distillation method, dubbed DaFKD, that can discern the importance of each model to the distillation sample, and thus is able to optimize the ensemble of soft predictions from diverse models. Specifically, we employ a domain discriminator for each client, which is trained to identify the correlation factor between the sample and the corresponding domain. Then, to facilitate the training of the domain discriminator while saving communication costs, we propose sharing its partial parameters with the classification model. Extensive experiments on various datasets and settings show that the proposed method can improve the model accuracy by up to $6.02\%$ compared to state-of-the-art baselines.

The traditional Agriculture Knowledge is epic information, was created by the forefathers in the past civilizations. The forefathers practiced traditional agriculture information during Harappa civilizations, Vedic and Iron Age civilizations. The present Small and Marginal farmer utilizes traditional information in the crop production & management, crop protection, farm machinery & tools, soil & water management, medicinal & aromatic plants for diseases diagnosis, animal husbandry, stored grain pests’ management, weed management and value added food product and transfers in the youth. The utilizing traditional informations in the agriculture practices are collected from the different geographical states of India. The informations are practiced in the specific activities by the farmers. The farmer utilizes compositions of natural resource in the geographical states for the crop husbandry and farm linked activities. The traditional information is more practiced by the Southern and North-Eastern Geographical zone. The farmer applies specific informations in the crop production & management, crop protection, farm machinery & tools, soil & water management, medicinal & aromatic plants for diseases diagnosis, animal husbandry, stored grain pests’ management, weed management and value added food product. The farmer preserves and transfers the information in the rural community. The farmer transmits information in the present generation for creating mobilization. The traditional agriculture information transforms agriculture resources, maintains biodiversity ethics and enlightens historical and practical approaches to the present generations.

The aims of this study were to assess oral health knowledge, attitudes, and practices among orthodontic patients between the ages of 15 and 17 years old compared to adolescents without orthodontic treatment. This cross-sectional study included 392 adolescents drawn from various French teaching hospitals. A closed-ended questionnaire was used to collect data. Adolescents undergoing orthodontic treatment had a higher knowledge of oral health than adolescents without orthodontic treatment. The majority of adolescents for both groups (69%) claimed to brush their teeth twice a day. Regarding complimentary dental material, 81.9% of adolescents without orthodontic treatment never used an interdental brush and 78.8% never used dental floss. For those undergoing orthodontic treatment, 48.5% never used interdental brush. Only 4% of adolescents without and 3% of adolescents with orthodontic treatment never consumed fizzy drinks, 4.9% and 3% never consumed sweets, 4% and 8.4% never ate fast-food. Adolescents without treatment consumed more sodas (p=0.04) and more fast food (p=0.03). Adolescents had insufficient knowledge of oral health. Health education programmes should be implemented to improve adolescents' knowledge and individual oral prophylaxis with interdental brushes.

The purpose of this study is to explore conceptual approaches in co-production studies and to examine current research trends of the study. The conceptual paper includes research articles related to co-production in public administration field. By thoroughly scrutinizing 32 research works of co-production, this study highlights major loopholes in the field of the study. The contributions of the study are: (1) identifying two common characteristics of co-production, (2) categorising three types of co-producing by end-users, and (3) finding that goals and success of co-production are more beneficial for service providers though its initial approach is citizen-centric approach. We suggest that future studies should be (1) to focus on reasons for co-production failures or success, (2) to discover further hindrances for co-production in service production, (3) to examine influencing factors on service providers as well as institutional impacts on co-production process, and (4) to include practical assessment in co-production study.

We aimed to assess awareness, knowledge, and attitudes of healthy pregnant women towards human papillomavirus (HPV), to estimate factors associated with a positive attitude towards HPV immunization and to assess the uptake of the vaccine among their children. A cross-sectional study was conducted at the University Clinic of Gynecology and Obstetrics, Belgrade, Serbia among pregnant women attending their regular gynecological check-ups at the 12th gestational week. Knowledge about HPV and HPV vaccine was assessed using a specifically designed 12-item and 5-item questionnaires. Out of total 265 included women, 79.3% had heard of HPV, and 37.5% knew that HPV vaccine exists. HPV vaccine knowledge score was associated with higher odds for a positive attitude towards vaccination of both female (OR = 4.10, 95% CI 1.50-11.29) and male (OR = 3.71, 95% CI 1.52-9.01) child. The number of children (OR = 1.32, 95% CI 1.04-1.67) and high vaccine knowledge score (OR = 1.64 95% CI 1.13-2.39) were independent predictors associated with willingness to vaccinate child against HPV. The gynecologist was the preferable point of reference for information seeking about the HPV vaccine. Despite relatively high HPV awareness and knowledge among pregnant women in Serbia, about one-third of them are HPV vaccine aware, and are willing to vaccinate their children against HPV.

Superstition is a belief that is not based on scientific knowledge. Traditional healers usually use superstition in their practices to manage human health problems and diseases; such practices create a conflict with the medical profession and its evidence-based practices. Medical professionals confirm that this kind of practice is not safe to human health as it is done by untrained people (e.g., tradition healers) utilizing unsterilized instruments within unhygienic environments. Most of the cases eventually develop a variety of complications, which are sometimes fatal. Female genital mutilation, uvulectomy, oral mutilation (tooth bud extraction to cure “Ibyinyo”), and eyebrow incisions are examples of the many different types of superstitious practices which occur commonly in different parts of the world. We described how these traditional practices of superstition have been and continue to be performed in various parts of the world, their complications on oral and general health, and the ways such practices hinder modern medical practices. This paper aims to increase the awareness of these superstition-driven traditional and potentially harmful practices by promoting the importance of evidence-based medical practices.

Ethnomedicine refers to the use of medicinal plants by a society, ethnic group or tribe for health benefits and for the prevention, treatment, and cure of different ailments. The healthy relationship between plants and humans has been continuing since the start of human civilization. The present study aims to document the medicinal information about plants used by ethnic people in different wards of Suryabinyak Municipality, Bhaktapur district, to conserve and utilize the traditional knowledge. Ethnomedicinal data were collected by a Rapid Rural Appraisal (RRA) method such as door to door surveys, direct observation. Individual interviews, field visits, and a questionnaire survey with the guidance of key informants. The present study has documented 107 medicinal plant species under 60 families which are used for prevention and treatment of 39 different diseases like Jaundice, diarrhea, dysentery, and cancer and 46 distinct health benefits like cough, cold, anti-bleeding, stomachache, diarrhea, fever, blood pressure, fracture, toothache, etc. Suryabinayak Municipality has a rich diversity in culture, ethnic groups, and medicinal plants, along with a wide geographic and climatic condition. However, with modernization, urbanization, deforestation, and increasing residential areas, the occurrence and use of medicinal plants have been diminished. Thus, documentation of this research is vital for further pharmaceutical research and enhancement and preservation of traditional knowledge of local people living in Suryabinayak Municipality and Nepal.

There has been a growing awareness of the need to implement environmentally friendly operations in the hotel industry, but most studies focus on guest behaviors. Only a few studies investigate employees’ willingness to comply with hotels’ green practices. This study seeks to further the investigation from the human resource perspective. Using alumni from a tourism and hospitality programs, this study collected 233 responses. The study hypothesizes that the employees’ green ability consisting of environmental awareness, environmental knowledge, and environmental skill creates a positive impact on hotels’ green ability. The results indicate that employees contribute approximately a fifth of hotels’ ability to implement greener practices.

The pursuit of Artificial Intelligence (AI) that emulates human cognitive processes is a cornerstone of ethical AI development, ensuring that emerging technologies can integrate seamlessly into societal frameworks requiring nuanced understanding and decision-making. Zero-Shot Instance Retrieval (ZSIR) stands at the forefront of this endeavour, potentially providing a robust platform for AI systems, particularly large visual language models, to demonstrate and refine cognition-aligned learning without the need for direct experience. In this paper, we critically evaluate current cognition alignment methodologies within traditional zero-shot learning paradigms, using visual attributes and word embedding generated by large AI models. We propose a unified similarity function that quantifies the cognitive alignment level, bridging the gap between AI processes and human-like understanding. Through extensive experimentation, our findings illustrate that this similarity function can effectively mirror the visual-semantic gap, steering the model towards enhanced performance in zero-shot instance retrieval. This work not only benchmarks the cognition alignment of AI, but also sets a new precedent for the development of visual language models attuned to the complexities of human cognition.}

We study the coupling of two topologcal subsystems in distinct topological states, and show that it leads to a precursor behavior of the topological phase transition in the overall system. This behavior is solely determined by the symmetry classes of the subsystem Hamiltonians and coupling terms, and is marked by the persistent existence of subgap states within the bulk energy gap. By investigating the critical current of Josephson junctions involving topological superconductors, we also illustrate that such subgap states play crucial roles in physical properties of nanoscale devices or materials.

Super-resolution technology is important not only in bio-related fields but also in nanotechnology, particularly in the semiconductor industry, where fine patterning is required and super-resolution is essential. However, observing microstructures beyond the diffraction limit proposed by Abbe and Rayleigh is considered impossible because of diffraction in traditional optical microscopy ob-servation techniques. However, in recent years, it has been possible to observe microstructures beyond the Rayleigh criterion by analysing the phase distribution of light. This study investigated the physical reasons why phase analysis makes this new analysis technique possible using simula-tions. The results confirmed that the phase component of the zero-order diffracted light reflected from the microstructure and able to pass through the lens system contained the phase information related to the shape of the measured object. Analysis of this information demonstrates the possi-bility of realising super-resolution based on speckle interferometry.

We present three reduced integrable hierarchies of nonlocal integrable NLS type equations from a vector integrable hierarchy associated with a matrix Lie algebra, not being A type. Three similarity transformations are taken to keep the invariance of the transformed zero curvature equations. The key step is to formulate a solution to a reduced stationary zero curvature equation so that the zero curvature formulation works for a reduced case.

Thermoregulation is important for maintaining homeostasis of our body. It can be easily broken under anesthesia. An appropriate method to measure the core body temperature is needed, especially for elderly patients because the efficiency of thermoregulation gradually decreases with age. The aim of this study was to examine the accuracy and feasibility of using of SpotOn® sensor in lower extremity orthopedic surgery in elderly patients aged over 80 years by comparing a SpotOn® sensor with two other reliable minimal-invasive methods: a tympanic membrane thermometer and a bladder thermometer. This study enrolled 45 patients aged over 80 years who were scheduled to undergo a lower extremity surgery. Body temperature was measured using a SpotOn® sensor, tympanic membrane thermometer and bladder thermometer. Agreements between the SpotOn® sensor and the other two methods were assessed using Bland and Altman plots for repeated measures adjusted for unequal numbers of measurements per patient. Compared with TempBladder, bias and limits of agreement for TempZHF were 0.07℃ ± 0.58℃. Compared with TempTympanic, bias and limits of agreement for TempZHF were -0.28℃ ± 0.61℃. 3M SpotOn® sensor using ZHF method for patients aged over 80 years undergoing lower extremity surgery shows feasible measurement value and sensitivity.

This study reports an empirical analysis of an all-electric, Net Zero Energy Housing (NZEH) development located in a mixed-humid climate zone (4A, Virginia, USA). Circuit-level energy monitors were used to measure energy consumption and energy production data (solar photovoltaic) at 1-hr intervals in six identical apartments over 24 months. The study employs a multi-step case study methodology to a) empirically evaluate energy consumption and production data, b) identify the temporal variability of energy consumption and production data at different time scales, c) understand the impact(s) of weather and human-building interaction on energy consumption and production, and d) synthesize the study’s “lessons learned” toward data-driven recommendations for future NZEH researchers and practitioners. The study found that the development’s net zero energy goal was achieved in three of six case units and that NZEH housing performance was more influenced by human-building interaction than weather variability. The analysis also found the solar photovoltaic (PV) performance to be reliable across the sampled units over the periods of measurement, suggesting that solar PV could be oversized as an approach to overcome verifiability in HBI and achieve NZEH performance goals.

U-turns and left turns are sometimes forbidden even though it increases travel distances. The greater travel distances are sometimes outweighed by the improved movement through intersections due to there being fewer conflicting lanes of traffic. One can, further, forbid straight-throughs. Restricting a sufficient number of turns can make intersections free from crossing lanes of traffic (``zero traffic conflict,'' ``ZTC"), though there may still be merging lanes of traffic. It's possible to make \begin{it}all\end{it} intersections in a road \begin{it}network\end{it} ZTC. However, keeping all destinations accessible and travel distances moderate requires careful selection of allowed driving directions and turning directions. We demonstrate through numerical microscopic and macroscopic simulations that there are road networks and ranges of traffic loads for which, in comparison with conventional schemes, ZTC road network can carry approximately $50$\% more vehicular traffic without incurring gridlock.

This paper provides an open dataset of measured energy use, solar energy production, and building air leakage data from a 328 m² (3,531 ft²) all-electric, zero energy commercial building in Virginia, USA. Over two years of energy use data were collected at 1-hour intervals using circuit-level energy monitors. Over six years of solar energy production data were measured at 1-hour intervals by 56 microinverters. The building air leakage data was measured post-construction per ASTM-E779 Standard Test Method for Determining Air Leakage Rate by Fan Pressurization and the United States Army Corps (USACE) Building Enclosure Testing procedure; both pressurization and depressurization results are provided. The architectural and engineering (AE) documents are provided to aid researchers and practitioners in reliable modelling of building performance. The paper describes the data collection methods, cleaning, and convergence with weather data. This dataset can be employed to predict, benchmark, and calibrate operational outcomes in zero energy commercial buildings.

Controversial hypotheses to explain consciousness exist in many fields of science, psychology and philosophy. Recent experimental findings in quantum cognition and magnetic resonance imaging have added new controversies to the field, suggesting that the mind may be based on quantum computing. Quantum computers process information in quantum bits (qubits) using quantum gates. At a first glance, it seems unrealistic or impossible that the brain can meet the challenges to provide either of these. Nevertheless, we show here why the brain has the incredible ability to perform quantum computing and how that may be realized.

We present a discussion and analysis regarding the benefits and limitations of open and non-anonymized peer review based on literature results and responses to a survey on the reviewing process of alt.chi, a more or less open-review track within the CHI conference, the predominant conference in the field of human-computer interaction (HCI). This track currently is the only implementation of an open-peer-review process in the field of HCI while, with the recent increase in interest in open science practices, open review is now being considered and used in other fields. We collected 30 responses from alt.chi authors and reviewers and found that, while the benefits are quite clear and the system is generally well liked by alt.chi participants, they are reluctant to see it used in other venues. This concurs with a number of recent studies that suggest a divergence between support for a more open review process and its practical implementation. The data and scripts are available on https://osf.io/vuw7h/, and the figures and follow-up work on http://tiny.cc/OpenReviews.

The world is facing several global issues such as food and energy crisis, climate change and greenhouse gases emissions. To subdue these issues, many entities from academia and industries have innovated alternate techniques of performing regular activities which cause such problems. One of these innovations is the introduction of vertical and zero acreage farming in the field of sustainability. These carry the potential to solve one of the most important affairs of food security in most countries of the world. But, this technology has been in its nascent stage for many years. This paper uses a comprehensive framework proving the feasibility of initiating vertical farming on university campuses to feed the staff and students, which could also set an example to the rest of the world into using this technique on a wider scale. The study chose Huazhong University of science and technology (HUST) in Wuhan city, China for accessing the return on investment and food sufficiency if vertical farming is implemented. Using Central Limit Theorem, a statistical model was developed, and various scenarios were analyzed. The results indicated that if a separate vertical farm is constructed, the breakeven can be achieved in a range of 10-20 depending on parameters such as type of operation, number of floors and amount of vegetation. The study has shown that the use of vertical farming cannot only bring in revenue for the campus but also aid in mitigating climate change.

The spectral properties of a one-dimensional photonic crystal bounded by a resonant absorbing nanocomposite layer with the near-zero permittivity have been studied. The problem of calculating the transmittance, reflectance, and absorptance spectra of such structures at the normal and oblique incidence of light has been solved. It is shown that, depending on the permittivity sign near zero, the nanocomposite is characterized by either metallic or dielectric properties. For the first time, the possibility of simultaneous formation of the Tamm plasmon polariton at the photonic crystal/metallic nanocomposite interface and the localized state similar to the defect mode with the field intensity maximum inside the dielectric nanocomposite layer is demonstrated. Specific features of field localization at the Tamm plasmon polariton and defect mode frequencies are analyzed.

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

We assume that the current mathematical knowledge K is a finite set of statements from both formal and constructive mathematics, which is time-dependent and publicly available. Any theorem of any mathematician from past or present belongs to K. The set K exists only theoretically. Ignoring K and its subsets, sets exist formally in ZFC theory although their properties can be time-dependent (when they depend on K) or informal. In every branch of mathematics, the set of all knowable truths is the set of all theorems. This set exists independently of K. Algorithms always terminate. We explain the distinction between algorithms whose existence is provable in ZFC and constructively defined algorithms which are currently known. By using this distinction, we obtain non-trivial statements on decidable sets X⊆N that belong to constructive and informal mathematics and refer to the current mathematical knowledge on X. This and the next sentence justify the article title. For any empirical science, we can identify the current knowledge with that science because truths from the empirical sciences are not necessary truths but working models of truth about particular real phenomena.

This conceptual, interdisciplinary paper will start by introducing the commencement of a new era in which human society faces continuously accelerating technological revolutions, named for short ‘Padkos’. In this context, a conceptual model of sustainable development with a focus on knowledge sharing and management will be proposed. The construct of knowledge management will be unpacked into a three-layer model with a focus on the knowledge-human and data-machine spheres. Then, each sphere will be discussed with concentrating on the learning and decision- making processes, the digital supporting systems and the human actors’ aspects. Moreover, the recombination of new knowledge development and contemporary knowledge management into one amalgamated construct will be proposed. The holistic conceptual model of knowledge sharing for sustainable development is comprised by time, cybersecurity and two alternative humanistic paradigms (Homo Technologicus and Homo Sustainabiliticus). Two additional particular models are discussed in depth. First, a recently proposed model of quantum organizational decision-making is elaborated. Next, a boundary management and learning process is particularized. The paper ends with several implications for the future based on the deliberations in the paper and the models discussed.

With the progression of AI, embedding advanced AI technologies into small robotics and mobile devices has become essential, driving research towards lightweighting AI models. Our study enhances the EPINET depth estimation model for light field images, aiming for compactness and faster inference while preserving accuracy. We conducted two-step experiments aimed at enhancing inference efficiency: Initially, by adjusting input streams and convolution layers, we simplified the CNN model, achieving faster inference times at the cost of reduced accuracy. To address this reduction in accuracy, we then applied knowledge distillation, allowing the simplified model to learn from the original model’s more complex patterns. In our quantitative experiments using two error metrics, MSE (Mean Squared Error) and BadPix, we identified optimal knowledge positions and evaluated the required complexity for the student model. As a result, our method improved MSE by 21% and BadPix by 14% compared to training without it. Furthermore, the student model achieved an inference speed 13% faster than the teacher model and surpassed its accuracy by 10% in MSE. Additionally, we demonstrated that repeatedly applying our approach could further enhance both model compactness and accuracy.

Knowledge is not merely the characteristic of certain pieces of information being deemed true and justifiable, but rather a process. Within an axiomatic system, the set of information that reaches the status of knowledge forms a universe that provides an interpretation of the reality one aims to describe. Language exchanges information through communication and the process of justification (exchange of information), if it consistently justifies a particular piece of information, it elevates it to knowledge. In this paper, we provide a framework for knowledge within an axiomatic model where we define the fundamental elements of communication and grammar. As a result, the structure dictates that knowledge, to be considered as such, must be investigateable by anyone who utilizes it in its entirety, both in form and content. Ultimately, the development of knowledge processing, referred to as \emph{knowmatics}, represents a clear evolution of the computer science that processes information (subset of knowledge).

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.

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).

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.

Background: Children's environmental health encompasses a wide range of factors that impact the well-being of children, including physical, chemical, biological, and social elements in their immediate environment. Safeguarding children from harmful substances is the crucial role of nursing students. Nursing students play a vital role as valuable resources for individuals, families, communities, and policymakers. This study aims to assess the knowledge and skills of nursing students concerning children's environmental health at academic institutions delivering nursing program in Nekemte town, Ethiopia. Methods: An institutional-based cross-sectional study design was carried out from August 1–30, 2023, among nursing students in Nekemte Town, and 634 study participants were selected through simple random sampling. Data was entered into Epinfo version 6.4 and exported to STATA version 14 for analysis, and multicollinearity was checked. Finally, from the bivariate analysis, variables of < 0.2 were included in the multivariate analysis; an adjusted odd ratio with a 95% CI was computed; and variables with a P-value <0.05 in the multivariable analysis were taken as significant associated factors. Results: The overall nursing students' level of knowledge about children's environmental health was insufficient (56%). More than one-third (34%) demonstrate their skill towards children's environmental health insufficiently, and one-fourth (25%) and 27% of the learners conduct their craft to prevent children from ecological hazards to a good and better level, respectively. While gender of the participant, age of the participant, year of the study, training history of the participants, and field of study of the students were significantly associated variables with their knowledge of children's environmental health. Conclusion: The study reveals that nursing students' knowledge of children's environmental health is limited, with factors such as gender, age, training history, and field of study significantly influencing their understanding. Therefore, female students should be considered for more tutorials to be effectively knowledgeable regarding children’s environmental health.

With global climate change and resource constraints looming large, sustainable design has become a focus of attention for all industries. The purpose of this study was to investigate the attitudes and behavioural intentions of undergraduate fashion design students towards sustainable fashion practices. Undergraduate fashion design students (n = 441) from three universities in Guangdong Province, China, participated in this survey. By constructing different scales of environmental knowledge, attitude towards sustainable fashion practice and behavioural intention towards sustainable fashion practice, and by using structural equation modelling to analyse the relationship between environmental knowledge and sustainable fashion practice, the following conclusions were drawn: (1) environmental knowledge has a positive effect on attitude towards sustainable fashion practice (p＜0.05); (2) environmental knowledge has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05); (3) Subjective norms has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05). (4) Attitudes towards sustainable fashion practice play a mediating role in the relationship between environmental knowledge and intentions towards sustainable fashion practice behaviour (p＜0.05). The findings of this study have implications for environmental education for undergraduate fashion design students and for sustainable production in companies.

Background: Maternal mortality remains dire in Nigeria, claiming 40,000 lives yearly due to pregnancy complications. Factors like limited healthcare access, poverty, and early marriage worsen the crisis. Despite efforts to improve skilled birth attendance, Nigeria struggles to meet MDG targets, underscoring the urgent need for more effective interventions. Objectives: The objective of the study is to assess and understand the knowledge of community members regarding the risk factors influencing maternal mortality in the Ede South Local Government Area of Osun State, Nigeria. Methodology: A descriptive cross-sectional study was conducted. The study methodology involves employing the Leslie Kish formula to select 185 participants from the Ede South Local Government Area in Osun State, Nigeria. The selection process involved the use of a systematic sampling technique to ensure a representative sample based on population demographics and characteristics, ensuring a balanced and accurate selection process. Quantitative data was collected through a self-administered questionnaire and analysed using SPSS version 21. Results: The study encompassed 185 participants. 64.9% females with a mean age of 27.3 + 8.3 years. Among them, 60.5% were single, 46.6% being students, 55.7% held a BSc degree, 64.9% were Yoruba and 61.1% identified as Christian. 91.4% were aware about maternal mortality, 74.6% recognized maternal deaths in reproductive-aged women. Participants identified that maternal deaths mostly occur during labour (91.4%). Direct causes, such as bleeding (88.1%), unsafe abortion (88.6%), infection (49.2%), and hypertension (64.9%), were recognized. Results indicated substantial awareness concerning specific risk factors: lack of education (98.9%), poverty (91.6%), poor health care services in facilities (94.0%), alcohol consumption (87.6%) and poor transportation (78.4%). Conclusion: Findings revealed good awareness of maternal deaths and critical factors such as ANC impact and direct causes of maternal mortality like bleeding and unsafe abortion. However, gaps persisted in SDG awareness, suggesting the need for targeted interventions to enhance overall understanding and address identified knowledge gaps.

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.

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

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.

HIV/AIDS infection increases vulnerability to ill-health states and has a major impact on the general health status. This study aims to describe Angolan adolescents and adults’ comprehensive knowledge of HIV/AIDS and its associated factors based on the 2016 demographic and health survey (DHS). Data from 19,785 individuals between the ages of 15 and 49 years old, who re-sponded to all the DHS questions between October 2015 and March 2016 were included in this study. Multivariable analysis using logistic regression was used to compute the adjusted odds ratio and respective 95% confidence intervals. In Angola, 47.7% of the respondents had general com-prehensive knowledge of HIV/AIDS. The odds of having comprehensive knowledge about HIV/AIDS were higher among individuals who watch television (aOR: 2.40; 95% CI: 2.11, 2.72) or read journals and magazines (aOR: 1.99; 95% CI: 1.72, 2.30) more than once a week and, people with primary or higher-level education (aOR: 1.83; 95% CI: 1.67, 2.00). Similarly, for people living in urban areas (aOR: 1.51; 95% CI: 1.34, 1.71). These results may reflect important inequities and can assist decision-makers in advocating to continue to invest in health literacy for HIV but also in the development of tailored interventions in this area.

Influenza in pregnancy is associated with elevated morbidity and mortality. Influenza vaccines are safe and effective in pregnancy. There are no Mexican surveys in physicians on knowledge, beliefs, and practices towards influenza and influenza immunization during pregnancy. A 32 questions cross-sectional and descriptive survey was conducted addressing general knowledge of influenza, as well as beliefs and practices regarding influenza vaccination during pregnancy among Mexican physicians responsible for prenatal care, traditionally Obstetricians (OBGYNs), and Family Physicians (FPs). A total of 206 surveys were available, 98 (47.6%) from OBGYNs, and 108 (52.4%) from FPs representing an estimated 2,472 daily pregnancy consultations. 54 from 206 (26.2%) weren´t aware that influenza is more severe during pregnancy, 106 from 206 (51.5%) ignored the potential side effects of influenza infection on the fetus, and 56.8% did not know when to vaccinate pregnant women. Pregnancy as a risk factor for developing influenza complications was known only by 99 from 206(48.1%), and 6.1 % believed that vaccination does not confer protection to the fetus. Current beliefs of Mexican OBGYNs and FPs for both influenza morbidity and mortality, and the importance of influenza vaccination during pregnancy, is suboptimal. Understanding drivers for beliefs should be assessed to improve influenza vaccination recommendations, as knowledge alone is not sufficient.