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In the context of global economic integration and Industry 4.0, digital manufacturing has become crucial. As one of the economic cores of China, the digitization process of the manufacturing industry in the Yangtze River Delta is particularly critical to the overall economic growth. Based on the theory of Industry 4.0 and digital manufacturing, this study deeply analyzes the current digital development of the manufacturing industry in the Yangtze River Delta. More importantly, this paper successfully constructs a fuzzy control model to quantitatively evaluate and guide the process of digital transformation of manufacturing industry in this region. The empirical results of the model reveal how key factors such as capital, talent, technology and data security affect the digitization process, and provide concrete and operational transformation strategies for the Yangtze River Delta region. In addition, combined with industrial advantages, policy support, technological progress and market demand, this paper predicts the digital development prospects of the manufacturing industry in the Yangtze River Delta. Overall, the study not only provides in-depth insights on the digitization of manufacturing in the Yangtze River Delta, but also provides practical guidance for actual operation, which has high theoretical and practical value. [ABSTRACT FROM AUTHOR]

This document discusses the societal impact of applying artificial intelligence (AI) to traffic and transportation. Sustainable transport is considered crucial for sustainable cities and communities, and AI has the potential to significantly influence daily life in urban areas. The document highlights the interdisciplinary challenges of understanding and coordinating transportation systems, which involve various players with conflicting goals and constraints. It also presents a selection of innovative solutions related to traffic management, including machine learning, reinforcement learning, and optimization approaches. The document concludes by expressing gratitude to the authors, reviewers, and committee members involved in the creation of the special issue. [Extracted from the article]

BACKGROUND: Data about performance measures (PM) in patients with ST segment Elevation Myocardial Infarction (STEMI) in low- and middle-income countries is really scarce. One of the reasons is the lack of appropriate measures for these scenarios where coronary intervention is not the standard treatment. OBJECTIVE: This study aimed to develop a set of PM and quality markers for patients with STEMI in these countries. METHODS: Two investigators systematically reviewed existing guidelines and scientific literature to identify potential PM by referring to documents searched through PubMed from 2010 through 2019, using terms "Myocardial Infarction", "STEMI", "quality indicator", and "performance measure". A modified Delphi technique, involving multidisciplinary panel interview, was used. A 15-member multidisciplinary expert panel individually rated each potential indicator on a scale of 1 (lowest) to 5 (highest) during three rounds. All indicators that received a median score ≥4.5, in final round without significant disagreement were included as PM. RESULTS: Through the consensus-building process, 84 potential indicators were found, of which 10 were proposed as performance measures and 2 as quality metrics, as follows: Pre-Hospital Electrocardiogram; Patients with reperfusion therapy; Pre-hospital Reperfusion; Ischemic time less than 120 minutes; System delay time less than 90 minutes; In-hospital Mortality; Complete in-hospital Treatment; Complete in-hospital Treatment in patients with Heart Failure; 30 day-Re-admissions; 30 day-mortality; Patients with in-hospital stress test performed; and, Patients included in rehabilitation programs. CONCLUSION: This document provides the official set of PM of attention in ST segment Elevation Myocardial Infarction of the Cuban Society of Cardiology and Cuban National Group of Cardiology. [ABSTRACT FROM AUTHOR]

Background: Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach. Objective: To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials. Methods: As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory. Results: An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages. Conclusion: We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges. [ABSTRACT FROM AUTHOR]

BACKGROUND: Workplace inspections are applied to facilitate the adherence to the occupational health and safety regulations. The Iranian Ministry of Health introduced a new software system for tablets to inspect workplaces. OBJECTIVES: The aim of this study was to take measurements of the usability, mental workload, and mood of inspectors. METHODS: Inspectors used both pen-and-paper and tablet methods to inspect the automotive industry in a mixed-method procedure. The NASA-TLX score, QUIS score, I-PANAS (SF) situation, inspection time, and number of errors were collected throughout the procedure. The differences were investigated using a paired sample and the Wilcoxon signed ranks test. RESULTS: In terms of efficacy, using the tablet resulted in lower error rates, but it took longer to complete the inspection task (P < 0.001). Participants perceived a lower workload when inspecting with a tablet rather than the traditional method. (Mental Demand: p < 0.002, Performance: p < 0.009, Effort: p < 0.012, TLX: p < 0.002 based on various subcomponents of NASA-TLX). The newly introduced system's usability was insufficient. CONCLUSION: Although the use of tablets has improved safety inspections, ergonomic redesign of the system and consideration of a user-centered approach, as well as inspector training, can make the system more likely to succeed. [ABSTRACT FROM AUTHOR]

Background: There is no molecular test for Alzheimer's disease (AD) using self-collected samples, nor is there a definitive molecular test for AD. We demonstrate an accurate and potentially definitive TempO-Seq® gene expression test for AD using fingerstick blood spotted and dried on filter paper, a sample that can be collected in any doctor's office or can be self-collected. Objective: Demonstrate the feasibility of developing an accurate test for the classification of persons with AD from a minimally invasive sample of fingerstick blood spotted on filter paper which can be obtained in any doctor's office or self-collected to address health disparities. Methods: Fingerstick blood samples from patients clinically diagnosed with AD, Parkinson's disease (PD), or asymptomatic controls were spotted onto filter paper in the doctor's office, dried, and shipped to BioSpyder for testing. Three independent patient cohorts were used for training/retraining and testing/retesting AD and PD classification algorithms. Results: After initially identifying a 770 gene classification signature, a minimum set of 68 genes was identified providing classification test areas under the ROC curve of 0.9 for classifying patients as having AD, and 0.94 for classifying patients as having PD. Conclusions: These data demonstrate the potential to develop a screening and/or definitive, minimally invasive, molecular diagnostic test for AD and PD using dried fingerstick blood spot samples that are collected in a doctor's office or clinic, or self-collected, and thus, can address health disparities. Whether the test can classify patients with AD earlier then possible with cognitive testing remains to be determined. [ABSTRACT FROM AUTHOR]

The text is an introduction to the selected papers from the HES-2023 conference, which focuses on the application of electromagnetic fields for materials processing. The conference was postponed by a year due to the pandemic and the war in Ukraine. The main developments in electroheat involve a multi-physics approach to modeling and simulation, with a focus on coupling different physical domains. The use of AI-based methods, such as digital twins and machine learning, in electrothermal systems is a current topic of research. The conference also covered topics such as induction heating, induction hardening, and inverse problems in induction heating. Overall, 52 papers were presented at the conference, and the 10 selected papers cover the main topics discussed. [Extracted from the article]

The 2023 edition of the AIxIA Conference, held in Rome, brought together a large number of researchers and practitioners to discuss the most recent and important advancements in Artificial Intelligence (AI). The conference featured 19 workshops, organized by 77 experts, attracting 248 submissions and resulting in 16 proceedings. This special issue presents extended versions of selected papers initially showcased at these workshops. Each paper underwent rigorous review and represents a diverse array of topics, reflecting the multifaceted nature of the Italian AI community. The topics covered include ethical foundations to symbiotic AI, symbolic knowledge extraction from black-box models, creative influence prediction using graph theory, AI approaches to multidimensional poverty prediction, an assessment of AI-based supports for informal caregivers, deep learning-based EEG denoising, AI-assisted board-game-based learning, large language models for assessment and feedback in higher education, geometric reasoning in the Traveling Salesperson Problem, defeasible reasoning in weighted knowledge bases, and conditional computation in neural networks. These contributions demonstrate the innovative and interdisciplinary research within the AI community, offering valuable insights and advancing the field. [ABSTRACT FROM AUTHOR]

The number of scientific papers has been increasing ever more rapidly. Researchers have to spend a lot of time classifying papers relevant to their study, especially into fine-grained subfields. However, almost all existing paper classification models are coarse-grained, which can not meet the needs of researchers. Observing this, we propose a lightweight fine-grained classification model for scientific paper. Dynamic weighting coefficients on feature words are incorporated into the model to improve the classification accuracy. The feature word weight is optimized by the Mean Decrease Accuracy (MDA) algorithm. Considering applicability, the lightweight processing is conducted through algorithm pruning and training sample pruning. Comparison with mainstream models shows simultaneous improvement in accuracy and time efficiency by our model. [ABSTRACT FROM AUTHOR]

BACKGROUND: External focus isometric exercises using a paper balloon can change trunk muscle activation in the chest squeeze; however, it is unknown whether this method affects muscle activities in conventional exercises. OBJECTIVE: To check variations of trunk muscle activity during front plank (static task) and shoulder press (dynamic task) both with and without instruction to avoid crushing an object. METHODS: Twenty-six healthy adult males aged 19–49 were recruited. Ten trunk muscle activities were measured using surface electromyography during a front plank and dynamic shoulder press exercises, both with and without external-focus instruction. RESULTS: Adding the external-focus using the paper balloon to the front plank significantly activated 8 out of the 10 muscles. In the downward shoulder press, 5 out of 10 muscles with 50% 1 RM, 2 out of 10 muscles with 100% 1 RM were significantly activated. CONCLUSIONS: Adding external-focus instruction using paper balloon increases trunk muscles in front plank and shoulder press while possibly improving trunk stability. Novel exercises using paper balloon may efficiently activate specific muscles without external loading thus possibly reducing the stress on the involved joints during exercise. [ABSTRACT FROM AUTHOR]

The purpose of this research is to address the challenges faced by visually impaired individuals, particularly in handling household appliances independently. With approximately 285 million visually impaired individuals worldwide, technological solutions are crucial to enhancing their accessibility and independence. This paper introduces a Smart Assistance System designed to empower visually impaired individuals to interact with household appliances in real-time without assistance. In this study, three Convolutional Neural Network (CNN) algorithms are compared to develop the system. The evaluation metrics include accuracy, precision, recall, F1 score, and hamming loss on validation images. The performance comparison reveals that the custom architecture CNN, MobileNetv2, and YOLO models achieve F1 scores of 0.43, 0.63, and 0.24, respectively. To enhance object detection and classification, the paper suggests implementing bounding box buttons categorization using YOLOv8, which demonstrates superior performance with a 95% classification accuracy on testing images of home appliance buttons. They face similar difficult while in public and accessing public property. Expanding upon the proposed system's capabilities, the paper introduces the concept of panic button detection and activation in a bus environment tailored for blind individuals. This system relies on various factors such as the number of people onboard, heart rate monitoring, and the detection of distress signals or SOS sounds emitted by the user. By integrating advanced sensing technologies and intelligent algorithms, this panic button detection system aims to provide prompt assistance and ensure the safety of visually impaired passengers in public transportation settings. [ABSTRACT FROM AUTHOR]

BACKGROUND: In todays' society, the rapid development of the wine industry and the improvement of peoples' living standards make people pay more and more attention to wine grape quality. OBJECTIVE: To evaluate the wine grape varieties in Northeast Chinas' grape growing regions for better wine grape quality, we evaluated the quality of different varieties of wine grapes. METHODS: The grape varieties 'Hassan' 'Zuoshaner' 'Beibinghong' 'Zuoyouhong' 'Beta' 'Shuanghong' 'Zijingganlu' 'Cabernet Sauvignon' and 'Syrah' were planted in the grape growing area of Jilin, Northeast China, were used as the subjects of this study. The grape berries were analyzed and tested for morphological indicators, basic physicochemical indicators, color, and phenolic and aromatic composition. RESULTS: According to lab results, 'Hassan' contained the highest amount of total phenolics; 'Zuoyouhong' had the highest solids and total sugar content; 'Shuanghong' had the most elevated total acid and anthocyanin content; 'Zijngganlu' had the highest tannin content and acid fixation ratio; Seventy-one volatile compounds were detected in nine grape varieties. CONCLUSIONS: Each of the nine grape varieties has a distinctive flavor, and because of this, grape processing products with regional flavors can be created. The same offer valuable data for future scientific grape resource collection, conservation, and exploitation. [ABSTRACT FROM AUTHOR]

In this paper, the mechanical properties of nano-silica modified insulating paper under the combined action of mechanical vibration and temperature conditions are studied. Unmodified and nano-silica modified cellulose insulating paper with 2 wt% and 4 wt% were prepared, respectively, and a series of mechanical-thermal synergy experiments were carried out. With the same mechanical stress and temperature, and with the same aging duration of 144 h (6d), the tensile strength of modified insulating paper with 4 wt% nano-silica, increased 0.99 kN/m and 0.55 kN/m, respectively, compared with those of the unmodified and the 2 wt% nano-silica modified insulating paper. The experiments indicate that the nano-silica modification can effectively improve the mechanical properties of insulating paper. In this work, the modified mechanism of nano-silica is analyzed from the interface effect of modified polymer and the quantum effect of the modified polymer interface two aspects. It is shown that the interface formed in the modified insulating paper can transfer the mechanical stress acted on the insulating paper and prevent the cracks formed in the aging process of the test sample from further expansion, while the quantum effect discretizes the electron energy level, which can restrict the motion of the molecular chain segment to some extent. The conclusion can be used for reference to improve the performance of insulating paper. [ABSTRACT FROM AUTHOR]

BACKGROUND: Toe function is characterised by the strength and dexterity of toe motion. However, previous studies have mostly focused on the importance of toe strength. OBJECTIVE: This study aimed to investigate the relationships between flexion strength and dexterity of the toes and physical performance. METHODS: Twenty healthy participants were included in this study. The flexion force of each toe was measured using a digital force gauge, and the toe dexterity was evaluated using the marble pick-up and rock-paper-scissors tests. These parameters were statistically analysed in relation to physical performance, including repeated side step and balance ability, which was evaluated using centre of pressure (COP) data during single-leg standing, tiptoe standing, and single-leg drop-jumping. RESULTS: A significant correlation was found between the first toe flexion force and the total trajectory length of the COP during one-leg standing and between the time required for marble pick-up and the rock-paper-scissors score and the COP during single-leg drop-jumping. CONCLUSION: The results underscore the importance of flexion strength and dexterity of the toes in human physical performance and the necessity for the evaluation and improvement of both functions. [ABSTRACT FROM AUTHOR]

For many, Covid-19 is a short-term, mildly debilitating disease. But some people are still struggling with monthly symptoms with persistent inflammation, chronic pain and shortness of breath. The situation of "long-term cowardice" has become so debilitating that it is now common for some to say that they are tired even if they walk a short distance. So far, the focus has been on saving lives from the plague. But now there are growing concerns about people facing the long-term consequences of the COVID epidemic. The fundamental question, with the uncertainty of whether those with chronic goiter, or all those affected, will fully recover is raised. In this paper a smart monitoring model was proposed to keep monitoring the COVID patient's health conditions. The smart method keep on watching the different changes reflected in the body conditions and ensure the changes in the database. In case any emergency is raised, then these smart monitoring tools inform the information to the doctors. This can very much helpful for the patients to communicate with the doctors. [ABSTRACT FROM AUTHOR]

BACKGROUND: Physical therapy modalities are often applied in treatment of neurological conditions in children and adolescents. OBJECTIVE: Evaluation of the methodological quality of research focusing on the application of physical therapy modalities in children and adolescents with neurological conditions. METHODS: Papers published between 2007 and 2018 were included in the review. 149 papers were analyzed and finally 26 studies investigating the use of physical therapy modalities in children and adolescents with neurological conditions were included in the review. Jadad scale (0–5) was used to assess the methodological value of the studies. RESULTS: The mean Jadad score was 1.46 (researcher 1) and 1.38 (researcher 2). A score of 0 was awarded to nine (r1) and eight papers (r2). A score of 5 points was awarded to three (r1) and two papers (r2). CONCLUSION: 1. The evidence showing the effectiveness of the use of physical therapy modalities is mainly of low quality. 2. The Jadad scale is a valuable tool to assess the quality of research, although it does not always reflect the real value in the case children participate in studies. 3. The analyzed studies show that physical therapy modalities are effective in the treatment of children and adolescents with neurological disorders. [ABSTRACT FROM AUTHOR]

As more people express their thoughts on products on various online shopping platforms, the feelings expressed in these opinions are becoming a significant source of information for marketers and buyers. These opinions have a big impact on consumers' decision to buy the best quality product. When there are too many features or a small number of records to analyze, the decision-making process gets difficult. A recent stream of study has used the conventional quantitative star score ratings and textual content reviews in this context. In this research, a decision-making framework is proposed that relies on feature-based opinions to analyze the textual content of reviews and classify buyer's opinions, thereby assisting consumers in making long-term purchases. The framework is proposed in this paper for product purchase decision making based on feature-based opinions and deep learning. Framework consists of four components: i) Pre-processing, ii) Feature extraction, iii) Feature-based opinion classification, and iv) Decision-making. Web scraping is used to obtain the dataset of Smartphone reviews, which is subsequently clean and pre-processed using tokenization and POS tagging. From the tagged dataset, noun labeled words are retrieved, and then the probable product's features are extracted. These feature-based sentences or reviews are processed using a word embedding to generate review vectors that identify contextual information. These word vectors are used to construct hidden vectors at the word and sentence levels using a hierarchical attention method. With respect to each feature, reviews are divided into five classes: extremely positive, positive, extremely negative, negative, and neutral. The proposed method may readily detect a customer's opinion on the quality of a product based on a certain attribute, which is beneficial in making a purchase choice. [ABSTRACT FROM AUTHOR]

Quantitative methods for determining the quality of scientific publications evolved gradually from popularity methods to prestige methods. However, existing methods have some drawbacks, such as inability to account for important factors and mutual reinforcement between different entities, and limitation of using novel information techniques like artificial intelligence (AI) methods. This study proposes an intelligent time-aware mutual reinforcement ranking (TAMRR) model that accounts for mutual reinforcement, and temporal factors, such as the time of citation, to measure the prestige of scientific papers. The method also considers the distribution of the co-authors' contributions, which indicates the credit allocation of citations. Moreover, mutual reinforcement which indicates interactive impact between different entities by means of the extension of an AI algorithm, i.e., Hyperlink-Induced Topics Search (HITS) algorithm, is adopted to further explore the interactions of papers, journals and authors. Another AI algorithm, i.e., PageRank, is also enhanced to measure the prestige of papers, journals, and authors in citation networks, which are then used as the inputs to the modified HITS. Experiments on temporal factors and heterogeneous networks reveal that these factors are likely to be informative in prestige measurements. Analysis of correlations suggests that our proposed intelligent ranking method is reasonable. This study offers an intelligent method for researchers, authors, and entrepreneurs to quantify the importance of scientific papers and the conclusions are likely to be of importance for researchers in both the academic and enterprise domains. [ABSTRACT FROM AUTHOR]

COVID-19 disease is characterized by serious clinical manifestations which could require urgent hospitalization. Prolonged hospitalization, with catabolism and immobilization, induces a decrease in weight and muscle mass which can result in sarcopenia, a condition that impairs respiratory and cardiac function, worsening the prognosis. In this scenario there is an urgent need of nutritional indications aimed to prevent or contrast hospital malnutrition by improving the patient's response to therapy and to facilitate healthcare professionals in managing nutritional interventions on patients, reducing their already high workload due to the state of emergency. [ABSTRACT FROM AUTHOR]

The Clinical Hemorheology & Microcirculation journal has established the A.L. Copley Best Paper Prize to recognize the best article published each year. The prize is named after Alfred Lewin Copley, the journal's founding editor. The winning paper for 2022 is titled "COVID-19 hemodynamic and thrombotic effect on the eye microcirculation after hospitalization: A quantitative case-control study" by Aristotle Koutsiaris and colleagues. The study investigates the impact of COVID-19 on the eye microcirculation of patients who received thromboprophylaxis after hospital discharge. The findings suggest that COVID-19 significantly reduces blood velocity and increases microthrombosis in the eye, potentially contributing to long COVID and indicating the presence of an unknown coagulation factor. [Extracted from the article]

The voltage on the valve side windings of the converter transformer is non-sinusoidal, which contains many high-order harmonic components. To calculate the nonlinear electric field distribution under the non-sinusoidal voltage, the harmonic-balanced decomposition finite element method (HBDFEM) is proposed in this paper. By using the fixed-point method, the finite element stiffness matrix of each iteration is decomposed according to the harmonic order, by which the memory consumption can be remarkably reduced. To verify the effectiveness of the proposed algorithm, a typical model of the oil-paper insulation structure is taken for instance, and the results obtained by the HBDFEM is compared with two algorithms, the traditional HBFEM and the time step method. The calculation results show that the HBDFEM can effectively reduce the computation cost for the nonlinear electric field problems with the non-sinusoidal periodic voltage. And it can be applied to analyze the compound electric field problems of the actual converter transformer. The electric field distribution of a ±500 kV converter transformer is calculated and analyzed considering the nonlinear relationship between the electric field and the medium conductivity. [ABSTRACT FROM AUTHOR]

Background: Enhancing the interactions between study participants, clinicians, and investigators is imperative for advancing Parkinson's disease (PD) research. The Canadian Open Parkinson Network (C-OPN) stands as a nationwide endeavor, connecting the PD community with ten accredited universities and movement disorders research centers spanning, at the time of this analysis, British Columbia, Alberta, Ontario, and Quebec. Objective: Our aim is to showcase C-OPN as a paradigm for bolstering national collaboration to accelerate PD research and to provide an initial overview of already collected data sets. Methods: The C-OPN database comprises de-identified data concerning demographics, symptoms and signs, treatment approaches, and standardized assessments. Additionally, it collects venous blood-derived biomaterials, such as for analyses of DNA, peripheral blood mononuclear cells (PBMC), and serum. Accessible to researchers, C-OPN resources are available through web-based data management systems for multi-center studies, including REDCap. Results: As of November 2023, the C-OPN had enrolled 1,505 PD participants. The male-to-female ratio was 1.77:1, with 83% (n = 1098) residing in urban areas and 82% (n = 1084) having pursued post-secondary education. The average age at diagnosis was 60.2±10.3 years. Herein, our analysis of the C-OPN PD cohort encompasses environmental factors, motor and non-motor symptoms, disease management, and regional differences among provinces. As of April 2024, 32 research projects have utilized C-OPN resources. Conclusions: C-OPN represents a national platform promoting multidisciplinary and multisite research that focuses on PD to promote innovation, exploration of care models, and collaboration among Canadian scientists. Plain Language Summary: Teamwork and communication between people living with Parkinson's disease (PD), physicians, health professionals, and research scientists is important for improving the lives of those living with this condition. The Canadian Open Parkinson Network (C-OPN) is a Canada-wide initiative, connecting the PD community with ten accredited universities and movement disorders research centers located in – at the time of this analysis–British Columbia, Alberta, Ontario, and Quebec. The aim of this paper is to showcase C-OPN as a useful resource for physician and research scientists studying PD in Canada and around the world, and to provide snapshot of already collected data. The C-OPN database comprises de-identified (meaning removal of any identifying information, such as name or date of birth) data concerning lifestyle, disease symptoms, treatments, and results from standardized tests. It also collects blood samples for further analysis. As of November 2023, C-OPN had enrolled 1,505 PD participants across Canada. Most of the participants were male (64%), living in urban areas (83%), and completed post-secondary education (82%). The average age at diagnosis was 60.2±10.3 years. In this paper, we look at environmental factors, motor and non-motor symptoms, different disease management strategies, and regional differences between provinces. In conclusion, C-OPN represents a national platform that encourages multidisciplinary and multisite research focusing on PD to promote innovation and collaboration among Canadian scientists. [ABSTRACT FROM AUTHOR]

In the present paper, we study the existence and concentration of multiple normalized solutions to the following nonlinear biharmonic Schrödinger equation: ε 4 Δ 2 u + V ( x ) u = λ u + h ( u ) , x ∈ R N , ∫ R N | u | 2 d x = c 2 ε N , x ∈ R N , where ε > 0 is a positive parameter, λ ∈ R is unknown and appears as a Lagrange multiplier, and V is a positive potential such that inf Λ V < inf ∂ Λ V for some open bounded subset Λ ⊂ R N ( N ⩾ 5 ). Applying the penalization techniques and Ljusternik–Schnirelmann theory, we obtain multiple mormalized solutions u ε . When ε → 0, these solutions concentrates around a local minimum of V.This paper extends the results of Alves and Thin (2023), which considered the nonlinear Schrödinger equations with general nonlinearities, to the biharmonic Schrödinger equations. We develop a truncated skill to obtain the minimum via careful analysis. Moreover, we also obtain orbital stability of the solutions. [ABSTRACT FROM AUTHOR]

This paper details the importance of virtual and non-traditional information sharing mediums to create better information access outcomes for people experiencing multiple forms of oppression simultaneously. Non-mainstream media platforms and formats like Tumblr and zines, are a valuable potential contribution to the discourse on coloniality, decoloniality, and how resistant knowledges manifest according to the needs of the people who create them. The information sciences are limited as a result of the majority white, abled nature of the field, and Tumblr and zines create a forum for out of the box thinking and re-search that creatively and thoughtfully sidesteps censorship. The paper is via a personal lens of lived experience and aims to uplift the recognition and validation of non-standard methods of information sharing used by BIPOC, Queer, and disabled communities. It underscores how these methods serve as vital avenues for community building, education, and the preservation and dissemination of marginalized voices and experiences. The paper emphasizes the necessity of acknowledging and integrating these unconventional sources into the broader landscape of information sciences, arguing for their value and legitimacy alongside traditional information repositories. [ABSTRACT FROM AUTHOR]

BACKGROUND: One of the main illnesses in the globe that causes impairment and death in people is stroke. In the globe today, it ranks as the second leading cause of death and the leading cause of death in China. OBJECTIVE: This paper analyses into the critical role of risk perception in developing individual awareness of stroke risk and encouraging proactive preventive health behaviors, essential for effective primary stroke prevention strategies and reduced stroke incidence. It discusses the concept of risk perception, the content and dimensions of global stroke assessment tools, and their application status, aiming to provide insights for their development and intervention research. METHODS: Risk perception encompasses subjective assessments of stroke likelihood and severity, influenced by personal experiences, knowledge of risk factors, beliefs about prevention effectiveness, and emotional responses. Global stroke assessment tools, like the Framingham Stroke Risk Score and CHA2DS2-VASc Score, evaluate stroke risk based on factors such as age, gender, blood pressure, and cholesterol levels. In order to improve risk perception and proactive health management and lower the burden of strokes, the paper assesses the advantages and disadvantages of these tools and makes recommendations for improving accessibility, customizing interventions, running educational campaigns, promoting multidisciplinary collaboration, and integrating technology. RESULTS: By combining the research tools of stroke risk perception, it is found that the evaluation tools are mostly single-dimensional evaluation tools centered on the two dimensions of onset possibility and susceptibility. CONCLUSION: Some scholars have developed multi-dimensional evaluation tools, but the evaluation population is relatively limited, and the evaluation system lacks comprehensiveness and systematization. [ABSTRACT FROM AUTHOR]

In its regulatory enterprise to improve the conditions of data sharing and reuse, the European Union has enacted new legislation: the Data Governance Act (DGA). The DGA envisages new forms of sharing public sector data (PSD). Based on a legal analysis of the DGA and an in-depth study of data governance literature, this paper highlights what is at stake in the new regulatory framework and argues that more than the mere openness of more PSD will be necessary to ensure that the European Union policy goals are achieved, especially those concerning enhancing innovation for the common good. From this perspective, the paper argues that the public data trust model of data governance and the Responsible Research and Innovation approach offer two powerful tools for public sector data governance. In this context, this paper contributes to the debate about new data governance models and discusses tools and frameworks enabling the use of data for the common good. It also provides insights to public administration practitioners aiming to implement a framework for increased and sustainable PSD sharing. [ABSTRACT FROM AUTHOR]

In order to solve the problem of large-scale power grid, complex connection relationship, and large demand for electricity carbon factor calculation resources, this paper proposes an algorithm that is easy to model the power grid topology and has high computational efficiency to implement the application of "One Electricity Carbon Chart". In this paper, the graph computing component is used to realize the graph modelling, distributed storage, and high-performance calculation of the electric carbon factor for the data representing the topology of the power grid, such as the power grid table, AC line segment table, and AC line end table. This paper realizes the rapid grid topology graph modelling of EMS dispatching system data, so that the grid structure and active power flow can be intuitively displayed and dynamically studied. This paper also realizes the distributed parallel calculation of electric carbon factor in the case of a ring network, which solves the problem of difficult analysis and calculation of large-scale power grid topology. We conduct experiments on real datasets, and the experimental results demonstrate the effectiveness of the proposed method. In addition, the research on the "One Electricity Carbon Chart" makes the carbon emission of power plants depend on the power flow of the power grid and transfers the accounting method, realizing the calculation of the carbon emission factor of the power grid at the plant level, and provides a new perspective for the sharing of carbon emission responsibilities in the power system. [ABSTRACT FROM AUTHOR]

In order to solve these problems, this paper introduced the grey system theory (GST) method in the real-time application of intelligent traffic signal optimization (ITSO). In this paper, the deep Q-network (DQN) algorithm was used to realize the dynamic signal light setting of real-time traffic conditions, which can improve the overall operating efficiency of the traffic system, and the PPO (Proximal Policy Optimization) algorithm was used to solve the problem of the lack of real-time performance of the traditional traffic signal optimization methods. By comparing the traffic congestion index of S city before and after the application of the GST method, the paper found that the average one week before the application was 60.1%, but it dropped to 26.6% after the application. In the experimental test of average speed comparison, the speed after applying the GST method was generally higher than the value before application, and the overall speed increase was about 20 km/h. This paper emphasizes the importance of evaluating the robustness of the GST method, particularly in its ability to manage unexpected scenarios. The research concentrates on assessing four critical indicators: outlier handling, noise tolerance, handling missing data, and nonlinear coping ability. [ABSTRACT FROM AUTHOR]

Under the background of globalization, cultural and creative tourism has gradually become a new trend of tourism, providing tourists with rich and diverse travel experience. This paper discusses the development status, characteristics and integration strategies of cultural and creative tourism under the new normal. Through the analysis of the existing literature, it is found that cultural creative tourism not only brings economic benefits to the region, but also promotes the protection and inheritance of local culture. At the same time, technological advances and data convergence provide new opportunities for the promotion and management of cultural and creative tourism. But it also brings challenges, such as how to ensure sustainable development and how to meet the growing demand of tourists. Finally, based on the method of multiple linear regression analysis, the paper analyzes the factors that affect the development of cultural creative tourism. [ABSTRACT FROM AUTHOR]

With the development of technology, fuzzy control algorithm is applied more and more widely in various fields. In the field of music culture dissemination and teaching management, this advanced algorithm opens up new possibilities for the creation, analysis and promotion of music. This study first discusses the basic theory and characteristics of fuzzy control algorithm, and then analyzes its specific application and potential value in music culture communication and teaching management. Through experimental verification, this paper reveals how fuzzy control algorithm plays a key role in music teaching evaluation, curriculum design and student interaction. In addition, the application of this algorithm in the intelligent classification, recommendation and analysis of music content is also studied. After comprehensive analysis, this paper summarizes the advantages and limitations of fuzzy control algorithm in the field of music, and puts forward suggestions for its future research and application. [ABSTRACT FROM AUTHOR]

In the mechanics of materials, the integral method is often used to calculate the bending deformation of the beam. It is relatively simple to use this method under a single load. However, in real life, the load conditions of most beams are complex and diverse, resulting in more segmentation of the bending equation, too many integral constants, complicated equations involved, cumbersome calculation process, and heavy calculation. In order to solve this problem, the concept of singular function is introduced in this paper. By using a bending equation to express the bending moment internal force of the whole beam, and there are only two integral constants after integration, which greatly simplifies the calculation process and reduces the calculation amount. This paper mainly introduces the properties of the singular function and how to use the singular function to express the bending equation of the beam, and solves the bending deformation of the beam with the boundary conditions, and discusses the application of the singular function in the calculation of the statically indeterminate beam. [ABSTRACT FROM AUTHOR]

BACKGROUND: Electronic cognitive assessment tools present potential benefits for clinical practice; however, they warrant examination before use with clinical populations such as people with traumatic brain injury (TBI). OBJECTIVE: The primary study purpose was to compare results from a tablet-based, electronic cognitive assessment to two paper cognitive assessments when administered to adults with TBI. We also explored the effect of iPad comfort on performance. METHODS: We employed a quasi-experimental, correlational study design. Forty adults between 18 to 615 months post TBI completed the Standardized Touchscreen Assessment of Cognition (STAC), the Montreal Cognitive Assessment (MoCA), and the Cognitive Linguistic Quick Test (CLQT) in a systematically, counterbalanced order. We compared participants' performance on these tools and examined the effect of iPad comfort. RESULTS: Three STAC subtests had a good relationship with CLQT subtests: orientation, generative naming category, and generative naming first letter. A good relationship was also identified between two STAC and two MoCA subtests: orientation and generative naming first letter. People who were very comfortable using the iPad performed statistically better on the STAC first letter fluency item than participants who were not comfortable. CONCLUSIONS: Moderate correlations suggest validity for some STAC items; however, modifications and further testing are needed. [ABSTRACT FROM AUTHOR]

Sentiment analysis and opinion mining is an area that has experienced considerable growth over the last decade. This area of research attempts to determine the feelings, opinions, emotions, among other things, of people on something or someone. To do this, natural language techniques and machine learning algorithms are used. This article discusses the problem of extracting sentiment and opinions from a collection of reviews on scientific articles conducted under an international conference on computing in northern Chile. The first aim of this analysis is to automatically determine the orientation of a review and contrast this with the assessment made by the reviewer of the article. This would allow scientists to characterize and compare reviews crosswise and more objectively support the overall assessment of a scientific article. A hybrid approach that combines an unsupervised machine learning algorithm with techniques from natural language processing is proposed to analyze reviews. This method uses part-of-speech (POS) tagging to obtain the syntactic structure of a sentence. This syntactic structure, along with the use of dictionaries, allows determining the semantic orientation of the review through a scoring algorithm. A set of experiments were conducted to evaluate the capability and performance of the proposed approaches relative to a baseline, using standard metrics, such as accuracy, precision, recall, and the F 1 -score. The results show improvements in the case of binary, ternary and a 5-point scale classification in relation to classical machine learning algorithms such as SVM and NB, but they also present a challenge to improve the multiclass classification in this domain. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present a hybridized technique for analyzing the behavior of an industrial system stochastically by utilizing vague, imprecise, and uncertain data. In the present study two important tools namely Lambda-Tau methodology and particle swarm optimization are used to formulate the hybridized technique PSOBLT (Particle swarm optimization based Lambda-Tau) for analyzing the behavior of the complex industrial system stochastically up to a desired degree of accuracy. Expressions of reliability indices like failure rate, repair time, mean time between failures (MTBF), expected number of failures (ENOF), reliability and availability for the system are obtained by using Lambda-Tau methodology and particle swarm optimization is used to construct the membership function. Fault tree is used to model the system. The press unit of a paper mill situated in a northern part of India, producing approximately 200 tons of paper per day, has been considered to demonstrate the proposed approach. Sensitivity analysis of a system's behavior has also been done. The behavior analysis results computed by PSOBLT technique have a reduced region of prediction in comparison of existing Lambda-Tau and GABLT (Genetic algorithm based Lambda-Tau) technique region, i.e. uncertainties involved in the analysis are reduced. Thus, it may be a more useful analysis tool to assess the current system conditions and involved uncertainties. Thus the paper suggests an approach to improve the systems' performance. [ABSTRACT FROM AUTHOR]

To automatic detect and characterize paper impurities with computer vision, we present a novel two parts evaluation procedure with feature representations using Alternating Direction Method of Multipliers (ADMM) sparse codes. The method is based on an offline training step to obtain sparse coefficients and codebooks via learning extracted features with ADMM optimization, followed by an online detection step to use linear SVM classifier to assess defective paper samples from no-defective ones. Our approach bridges the gap between paper impurities evaluation and sparse feature representations, taking advantages of existing ADMM algorithms to handle sparse codes problem. We compare different feature descriptors and sparse code methods to implement the procedure and experimentally validate it on a dataset of 11 paper classes. Experiment results show that the proposed method is competitive and effective in terms of evaluation accuracy and speed. [ABSTRACT FROM AUTHOR]

Bhardwaj and Kumar (J. Optim. Theory Appl. 163(2), 685-696 (2014)) pointed out that Khan et al. (J. Optim. Theory Appl. 159(2), 536-546 (2013)) have assumed some mathematical incorrect assumptions in their proposed method for solving fully fuzzy linear programming problems (FFLPPs). However, Khan et al. (J. Optim. Theory Appl. 173(1), 353-356 (2017)) replied that their proposed method is valid and no mathematical incorrect assumptions have been considered. The aim of this commentary is to make the researchers aware that Khan et al. (J. Optim. Theory Appl. 173(1), 353-356 (2017)) are misleading the others. In actual case, Khan et al. (J. Optim. Theory Appl. 159(2), 536-546 (2013)) have considered mathematical incorrect assumptions in their proposed method due to which some of the elements of the optimal simplex table, obtained by Khan et al. (J. Optim. Theory Appl. 159(2), 536-546 (2013)), are not triangular fuzzy numbers. [ABSTRACT FROM AUTHOR]

In a complex financial market, people pay more attention to the portfolio selection model in some fuzzy environment. Some properties and definitions of semivariance and entropy are given and proved in this paper. Then, the fuzzy tri-objective mean-semivariance-entropy portfolio model is proposed based on credibility theory when the return rates are fuzzy numbers. We present a novel layer-by-layer tolerance evaluation method to solve the proposed model in this paper. Finally, a numerical example is given to illustrate the effectiveness of the model and method proposed in this paper. There are two improvements in our proposed method: one is that the evaluation function idea is considered in the process of laying objective functions; the other is that the preference degree and subjective wills are presented by tolerant amounts of objective function values. [ABSTRACT FROM AUTHOR]

The Alternative Uses Test is a measure of divergent thinking in which participants are asked to list non-obvious uses for a common object in a fixed amount of time. The goals of this study were to better understand this creativity test, explore how original ideas emerge, and provide suggestions for improvement to the test. Participants were asked to list alternative uses for a paperclip in three minutes. 293 participants, including engineers, designers and students, were tested and evaluated. Using infrequency of responses as a measure of originality, it was found that participants that produced more responses had more original responses. Later responses were significantly more original than early responses and originality of responses increased with quantity. On average, a participant would list 9 responses before arriving at highly original responses. Participants that did not reach 9 responses in the study were likely to have few if any highly original responses. Participants that were more elaborate in their responses had fewer responses in total and therefore fewer original responses. If this test maps to real world idea generation, it suggests that the first ideas we think of are likely to have been suggested already by others and thus not original. The results of this study can help restructure the format of the Alternative Uses Test and provide a database for a digital version of this test. [ABSTRACT FROM AUTHOR]

Fuzzy posets can be regarded as a generalization of classical posets. Many concepts and results in posets can be generalized to fuzzy posets. In order to further improve the fuzzy poset theory, in this paper, we shall introduce the concept of prime (distributive) fuzzy posets which can be seen as the correspondence of prime (distributive) posets in fuzzy setting. First, we consider the extensions of fuzzy ideals in a fuzzy poset. Then by the extensions of fuzzy ideals, we give a characterization for prime (distributive) fuzzy posets, that is, a fuzzy poset X is prime (distributive) if and only if all extensions of normal fuzzy ideals of X are Frink (strong) fuzzy ideals. This paper generalizes the work of Halas in posets into fuzzy posets. [ABSTRACT FROM AUTHOR]

In the modern medical industry, sensors and other medical electronic equipment such as ECG, thermometers, etc. that measure vitals like blood pressure, body temperature, heartbeat, and blood cells are used to record patient data. The information gathered helps to create a patient profile, which in turn helps doctors treat patients appropriately and helps users gain insights into their health. But, the information collected is regionally specific and not worldwide. Thus, this may create problems in transparency, integrity, and much more. The medical details of patients collected are stored in a simple database which appears to be a centralized application that is prone to be modified or hacked by intruders and also suffers from fault tolerance. This paper aims to solve this problem using Blockchain and Data Possession methodologies. Blockchain helps to store multiple copies of data in a decentralized fashion. Thus, a secured model could be implemented using blockchain in which the patient’s data can be securely sent to any medical professional, thus promoting transparency, security, and integrity. Provable Data Possession helps the users to verify that their information is intact and has not been tampered. It can be achieved using cryptography which encrypts the information of the patients stored. This paper will be beneficial for the medical department and the public such that it will be beneficial in terms of transparency, scalability, and security. [ABSTRACT FROM AUTHOR]

The transition from paper-based information to Electronic-Health-Records (EHRs) has driven various advancements in the modern healthcare industry. In many cases, patients need to share their EHR with healthcare professionals. Given the sensitive and security-critical nature of EHRs, it is essential to consider the security and privacy issues of storing and sharing EHR. However, existing security solutions excessively encrypt the whole database, thus requiring the entire database to be decrypted for each access request, which is time-consuming. On the other hand, the use of EHR for medical research (e.g., development of precision medicine and diagnostics techniques) and optimisation of practices in healthcare organisations require the EHR to be analysed. To achieve that, they should be easily accessible without compromising the patient's privacy. In this paper, we propose an efficient technique called E-Tenon that not only securely keeps all EHR publicly accessible but also provides the desired security features. To the best of our knowledge, this is the first work in which an Open Database is used for protecting EHR. The proposed E-Tenon empowers patients to securely share their EHR under their own multi-level, fine-grained access policies. Analyses show that our system outperforms existing solutions in terms of computational complexity. [ABSTRACT FROM AUTHOR]

As a new type of braking method, the eddy current brake (ECB) is nowadays widely applied in life and military. The ECB can generate the strong resistance by the magnetic field, and obtaining the accurate magnetic induction distribution is essential in the ECB modeling. This paper proposes an analytical model of a cylinder ECB used in the artillery that operates under the intense impact load. This model takes the axial edge effects into consideration in both static and dynamic conditions. Firstly, this paper introduces the structure and working principle of this ECB. Secondly, a multilayer theory with virtual region is proposed to calculate the magnetic induction distribution considering the end effect. Thirdly, Finite Element Method (FEM) model is established to describe the spatial variation of the magnetic field in different conditions. Finally, the analytical model is compared with the FEM model to prove its validity and predict the working characteristic of the ECB under the intense impact load, the max recoil displacement and speed range both meet design and work requirements. [ABSTRACT FROM AUTHOR]

In the context of the development of the new era, computer network technology has become an indispensable and important technological means in people's daily work and life. Through network technology, information resources can be collected, integrated, processed, and applied, thereby improving information analysis and mining capabilities, constructing big data environments for various industries, providing convenient and fast intelligent information services, and promoting social transformation and development. However, in practical development, network security issues seriously affect information security and social stability, and computer viruses and hackers pose a huge threat to computer systems. The computer network security evaluation is the MAGDM problems. Recently, the Logarithmic TODIM (LogTODIM) and TOPSIS technique has been utilized to cope with MAGDM issues. The interval neutrosophic sets (INSs) are utilized as a technique for characterizing uncertain information during the computer network security evaluation. In this paper, the interval neutrosophic number Logarithmic TODIM-TOPSIS (INN-LogTODIM-TOPSIS) technique is conducted to solve the MAGDM under INSs. Finally, a numerical case study for computer network security evaluation is utilized to validate the proposed technique. The prime contributions of this paper are put forward: (1) The entropy technique based on score values and accuracy value are conducted to obtain weight information under INSs; (2) an integrated INN-LogTODIM-TOPSIS technique is conducted to put forward the MAGDM issue; (3) An illustrative example for computer network security evaluation has been accomplished to put forward the INN-LogTODIM-TOPSIS technique. [ABSTRACT FROM AUTHOR]

Textual Question Answering targets answering questions defined in natural language. Question Answering Systems offer an automated approach to procuring answers to queries expressed in natural language. The need for Multilingual Question Answering without performing machine translation is ever existing. Besides that, automating tasks with the help of technology to assist humans, has been the main aim of research in recent years. This paper presents an automated answer evaluation system for reading comprehension-based questions in the Hindi language without requiring translation in any other language. The system accepts text, question, and handwritten answer of a student in the form of an image for answer evaluation. This is accomplished by developing a textual question-answering system for reading comprehension. It is an extractive approach that utilizes RoBERTa transformer model and fine-tunes it for Hindi question-answering. The answer to the question is extracted as a span from the provided text. Further, a handwritten text recognizer model is developed employing a Convolutional Recurrent Neural Network with Connectionist Temporal Classification module along with two layers of Bidirectional LSTM. Experimentation is performed using existing as well as self-created datasets to show the effectiveness of the proposed approach. An accuracy of 98.69% is obtained on the self-created Hindi-QA dataset and the proposed system outperformed the other existing methods. The paper also discusses potential research directions in the field. [ABSTRACT FROM AUTHOR]