bluuebunny/crossref_metadata_2025_split huggingface dataset:
Poverty and Temporary Employment in Italy
Authors: Mussida Chiara , Sciulli Dario 
Published: October 2024

AbstractThis paper explores the relationship between temporary employment and poverty in Italy by using 2016–2019 longitudinal EU-SILC data. We model both poverty and labour market outcomes and account for possible endogeneity of temporary employment in the poverty equation. We find that temporary employment reduces the risk of poverty whether compared with inactivity and unemployment. Temporary workers are more likely to stay in poverty with respect to their permanent counterpart. The different effect of permanent/temporary employment on the risk of poverty is more pronounced for householders than for partners, thereby stressing the leading role of the former in income formation. There is evidence of feedback effects from past poverty to current temporary employment. We also find significant genuine state dependence in both the processes of poverty and temporary employment. For the latter, we note the prevalence of a trapping effect into unstable jobs relationships, especially for householders. Finally, we stress the relatively weak role of social transfers in integrating labour income from temporary employment and therefore in breaking the detrimental effect of temporary work on poverty.
A Flexible Smart Healthcare Platform Conjugated with Artificial Epidermis Assembled by Three-Dimensionally Conductive MOF Network for Gas and Pressure Sensing
Authors: Zhou Qingqing , Ding Qihang , Geng Zixun , Hu Chencheng , Yang Long , Kan Zitong , Dong Biao , Won Miae , Song Hongwei , Xu Lin , Kim Jong Seung 
Published: October 2024

AbstractThe rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare. Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli. However, realistic mimesis, both in the skin’s three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities, remains a challenging yet vital need for simplifying the design of flexible logic circuits. Herein, we construct an artificial epidermal device by in situ growing Cu3(HHTP)2 particles onto the hollow spherical Ti3C2Tx surface, aiming to concurrently emulate the spinous and granular layers of the skin’s epidermis. The bionic Ti3C2Tx@Cu3(HHTP)2 exhibits independent NO2 and pressure response, as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication. Ultimately, a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits. This system can assess risk factors related with asthmatic, such as stimulation of external NO2 gas, abnormal expiratory behavior and exertion degrees of fingers, achieving a recognition accuracy of 97.6% as assisted by a machine learning algorithm. Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis.
Application of nano-TiO2 and micro-ZnO on cementitious surfaces for self-cleaning façades by spray coating and dip coating: A comparative study
Authors: Pereira Lessa Fabíula , Lima Jr Orlando , Margalho Élida , Pinheiro Claver , Rocha Segundo Iran , Oliveira Carneiro Joaquim 
Published: October 2024

AbstractBuilding façades are constantly exposed to atmospheric pollution and various external agents that can degrade their aesthetic qualities and introduce degradation patterns that affect the durability and performance of the materials. Façades with self-cleaning properties are important in the modern construction industry and the conservation of historic buildings, as they reduce costs and allow the preservation of original surfaces without the need for invasive interventions that could compromise cultural heritage. This study does a comparative analysis of the application of photocatalytic coatings composed of aqueous dispersions of titanium dioxide nanoparticles (TiO₂) and zinc oxide microparticles (ZnO) on cementitious substrates for use on façades by two functionalisation methods: spray coating and dip coating. A comprehensive characterisation was carried out using techniques such as scanning electron microscopy (SEM), X-ray diffraction (XRD), and diffuse reflectance spectroscopy (DRS) to assess the morphology, crystal structure and light absorption properties of the photocatalyst particles while Energy Dispersive Spectroscopy (EDS) and scanning electron microscopy (SEM) were employed to evaluate the substrate. The self-cleaning performance was evaluated by monitoring the degradation of Rhodamine B (RhB) dye under simulated sunlight. Spectrophotometric analysis was used to assess the colour coordinates using a standard colour system (CIELAB colour space). The results showed that the photocatalytic coatings improved the surfaces' self-cleaning properties while maintaining the substrate's original aesthetics. Spray-applied micro-ZnO-based coatings showed the most significant effectiveness in terms of self-cleaning.
Society in charge: the connection of artificial intelligence, responsibility, and ethics in German media discourse
Authors: Winkel Marek 
Published: October 2024

AbstractArtificial intelligence (AI) is playing an increasingly important role in society, and applications like ChatGPT and Dall-E, which can produce texts and pictures on their own, are becoming very popular. This development raises questions regarding ethics, values, and responsibility, as AI-generated documents may promote misinformation and erode democracy, while human actors can scarcely be held accountable. AI technology may also support an efficient, rationalized society, which has its advantages and disadvantages. Two main spheres, which influence society’s perspective on the connection between AI, ethics and responsibility, are public media debates and the legal system. Popular newspapers reach broad audiences, so insight is provided into what perspectives on these issues are helping everyday citizens form their opinions. Legal frameworks potentially regulate citizens’ and companies’ dealing with AI technology—and may get included in media discussions on AI. Acknowledging that, this article presents a two-folded analysis. First, the article presents the results of a discourse analysis of 113 articles from German newspapers, ranging from the center-left to the conservative spectrum. The analysis examined how these media frame the connection of AI, ethics, values, and responsibility. The article discusses the discourse analysis together with theoretical assumptions around the question, which actors in society could be counted as accountable in AI regards. Second, a discussion of the European AI legal system is added, to evaluate its connection with the media discourses. The article presents the results of both parts of the analysis together and finally discusses further research perspectives.
A multi-step regularity assessment and joint prediction system for ordering time series based on entropy and deep learning
Authors: Zhou Yichen , Han Wenhe , Zhou Heng 
Published: October 2024

AbstractCustomer maintenance is of vital importance to the enterprise management. Valuable assessment and efficient prediction for customer ordering behavior can offer better decision-making and reduce business costs significantly. According to existing studies about customer behavior regularity segment and demand prediction most focus on e-commerce and other fields with large amount of data, making them not suitable for small enterprises and data features like sparsity and outliers are not mined when doing regularity quantification. Additionally, more and more complex network structures for demand prediction are proposed, which builds on the assumption that all the samples have predictive value, ignoring the fine-grained analysis of different time series regularity with high cost. To deal with the above issues, a multi-step regularity assessment and joint prediction system for ordering time series is proposed. For extracting features, comprehensive assessment of customer regularity based on entropy weight method with the result of predictability quantification using K-Means clustering algorithm, real entropy, LZW algorithm and anomaly detection adopting Isolation Forest algorithm not only gives an objective result to ‘how high the regularity of customers is’, filling the gap in the field of regularity quantification, but also provides a theoretical basis for demand prediction models selection. Prediction models: Random Forest regression, XGBoost, CNN and LSTM network are experimented with sMAPE and MSLE for performance evaluation to verify the effectiveness of the proposed regularity quantitation method. Moreover, a merged CNN-BiLSTM neural network model is established for predicting those customers with low regularity and difficult to predict by traditional machine leaning algorithms, which performs better on the data set compared to others. Random Forest is still used for prediction of customers with high regularity due to its high training efficiency. Finally, the results of prediction, regularity quantification, and classification are output from the intelligent system, which is capable of providing scientific basis for corporate strategy decision and has highly extendibility in other enterprises and fields for follow-up research.
The secreted protein FonCHRD is essential for vegetative growth, asexual reproduction, and pathogenicity in watermelon Fusarium wilt fungus
Authors: Lou Jiajun , Wang Jiajing , Zeng Shanshan , Xiong Xiaohui , Guo Mengmeng , Li Dayong , Song Fengming 
Published: October 2024

AbstractFungal pathogens often secrete numerous effectors to interfere with and/or suppress plant immunity to promote their infection. Watermelon Fusarium wilt, caused by the soil-borne fungus Fusarium oxysporum f. sp. niveum (Fon), is one of the devastating diseases that severely affect the watermelon industry. Here, we report the function of a candidate effector protein, FonCHRD, in Fon. FonCHRD harbors a chordin (CHRD) domain of unknown function and has a signal peptide with secretion activity. FonCHRD shows a relatively high expression level in Fon marcoconidia and is inducible by watermelon root tissues. Phenotypic analysis of the targeted deletion mutant revealed that FonCHRD plays roles in vegetative growth, asexual reproduction, and conidial morphology of Fon, while it is not involved in spore germination as well as cell wall, oxidative and salt stress responses. Deletion of FonCHRD impaired the ability to colonize and spread within host plants, significantly reducing its virulence on watermelon. FonCHRD is distributed across multiple compartments of plant cells but can target to the apoplast space in plants. FonCHRD inhibits the INF1- and Bcl2-associated X protein-triggered cell death and defense gene expression in transiently expressed Nicotiana benthamiana leaves. These findings suggest that FonCHRD is essential for Fon pathogenicity by modulating invasive growth and spreading abilities as well as by suppressing plant immune responses.
Perceived corruption, economic freedom, and firms in India
Authors: Dutta Nabamita , Stivers Adam , Kar Saibal 
Published: October 2024

AbstractResearch has shown that the relationship between economic freedom and corruption is rather complex. While some studies suggest a negative relationship, others show the matter to be more nuanced. While more regulations are known to foster corrupt institutions, a competitive market can also incentivize bribery and corruption. Our study examines the role of economic freedom as it relates to perceived corruption, measured via a survey for India. Using firm-level data, we explore the relationship between perceived corruption in the formal sector and economic freedom across Indian states. In our baseline results for Indian firms, we find a significantly negative relationship between perceived corruption and lagged economic freedom. These results hold when we design matching models and include a number of potentially confounding factors to control for identification issues. Additionally, we show that small and young firms and those with sole ownership perceive greater benefits from higher economic freedom. In contrast, older firms perceive higher corruption when economic freedom is higher. This lends support to the idea that competition facilitated by economic freedom can increase rent seeking behavior. Our study contributes to the literature by emphasizing that the relationship between economic freedom and corruption in India is layered, with firm characteristics playing a crucial role.
Highway digital twin-enabled Autonomous Maintenance Plant: a perspective
Authors: Xu Jie , Anvo N’Zebo R. , Taha-Abdalgadir Hussameldin , d’Avigneau Alix M. , Palin Damian , Wei Ran , Hadjidemetriou Georgios , Schaefer Samuel , de Silva Lavindra , Al-Tabbaa Abir , Iida Fumiya , Brilakis Ioannis 
Published: October 2024

Abstract
The importance of automating pavement maintenance tasks for highway systems has garnered interest from both industry and academia. Despite significant research efforts and promising demonstrations being devoted to reaching a level of semi-automation featuring digital sensing and inspection, site maintenance work still requires manual processes using special vehicles and equipment, reflecting a clear gap to transition to fully autonomous maintenance. This paper reviews the current progress in pavement maintenance automation in terms of inspection and repair operations, followed by a discussion of three key technical challenges related to robotic sensing, control, and actuation. To address these challenges, we propose a conceptual solution we term Autonomous Maintenance Plant (AMP), mainly consisting of five modules for sensing, actuation, control, power supply, and mobility. This AMP concept is part of the “Digital Roads” project’s cyber-physical platform where a road digital twin (DT) is created based on its physical counterpart to enable real-time condition monitoring, sensory data processing, maintenance decision making, and repair operation execution. In this platform, the AMP conducts high-resolution survey and autonomous repair operations enabled (instructed) by the road DT. This process is unmanned and completely autonomous with an expectation to create a fully robotized highway pavement maintenance system.
Interdisciplinary methods for researching climate-mental health links through the Methane Early Warning Network (ME-NET): improving ‘visibility’ and integrating complex multi-datasets
Authors: Moore Harriet Elizabeth , Atanbori John , Amankwaa Ebenezer Forkuo , Gussy Mark , Siriwardena Aloysius Niroshan , Hanna Edward 
Published: October 2024

Abstract
Climatic and atmospheric conditions impact mental health, including increased incidents of depression associated with air pollution. A growing body of research considers time-bound ‘snap-shots’ of climatic drivers and mental health outcomes. Less is known about the likely effects of future climate change on mental health. Research is often inhibited by data scarcity, the challenge of synthesising data across multiple geospatial and temporal scales, and the under-representation of hard-to-reach groups. Thus, research methods are needed to integrate and analyse complex environmental and mental health multi-datasets while improving the visibility of under-represented groups. In this methods paper we present a novel approach for investigating the impact of climate change on mental health and addressing some challenges with, a) invisibility of vulnerable groups, and b) integrating complex environmental and mental health multi-datasets. The research aim is to pilot a web-based and smartphone application (Methane Early Warning Network (ME-NET)) for investigating the role of methane as a precursor of on-ground ozone, and the impact of ozone on mental health outcomes to improve civic knowledge and health-protection behaviour in the United Kingdom and Ghana. The methods include exploring the feasibility of using machine learning to develop an ozone early warning system and application co-design.
The Path of Telemedicine in Disaster Response
Authors: Boyle Tehnaz 
Published: October 2024

Abstract

Telehealth, or the use of digital health technology to support clinical care, education, and health administration over a distance, has increased dramatically in the 21st century. The frequency and severity of disasters that cause damage, disruption, loss of life, and health service deterioration have also increased over the same period. Advances in telecommunication networks and mobile technology have made telehealth systems more accessible and affordable, and rising acceptance has engaged hesitant users. Yet, telehealth remains underutilized particularly for cross-jurisdictional disaster response in the United States. In this presentation, we will discuss progress in the development and implementation of new regional disaster telehealth systems funded by the U.S. Administration for Strategic Preparedness and Response. We will review administrative and legal barriers to implementation in the context of real-world examples to understand how they impact domestic disaster response capabilities. We will also discuss innovative new global partnerships that have successfully leveraged digital tools to provide access to health resources for international humanitarian disaster response. Finally, we will consider next steps in the path to fully actualizing the potential for telehealth to transform disaster response.

Learning Objectives
Discuss current federally funded efforts to develop and implement regional telehealth systems designed to support cross-jurisdictional disaster medical response in the United States.
Examine administrative and legal barriers to adoption and implementation that can impact timely mobilization, deployment, and use of disaster telehealth services.
Review examples of successful and failed implementation to guide future research, development, and implementation efforts for system developers, sponsors, and governmental and non-governmental disaster response entities.
Artificial Intelligence Chatbots in Disaster Medicine: What is ChatGPT, and How Do I Use It?
Authors: Franc Jeffrey Micheal 
Published: October 2024

Abstract

In this interactive session which combines instruction with live-streaming, participants will learn about the use of ChatGPT in disaster medicine.

Learning Objectives
Create an OpenAI account, write an effective prompt, and manage a conversation with ChatGPT.
List errors common to ChatGPT and understand why they occur.
Review how ChatGPT can interface with internet connected devices and other apps.
Discuss the ethical, legal, and social implications of generative AI.
Stakeholder Collaboration in the Education of Australian Students With Autism Spectrum Disorder: A Systematic Review
Authors: Vlcek Samantha , Somerton Michelle , Pedersen Scott 
Published: October 2024

AbstractEffective collaboration between key stakeholders increases the educational opportunities and outcomes of students with autism spectrum disorder (ASD). Although the value of collaboration between the central members of a student’s network has been widely cited, how collaboration occurs between different stakeholder groups in the education of Australian primary and secondary students with ASD is not widely known. The aim of this review was to identify the factors that influence collaborative practices between three primary stakeholder groups supporting the education of Australian students with ASD: family, school, and community. Through this lens, we analysed the intent of the collaborative practices as well as the specific details of the collaborative practices identified across the research literature published since the implementation of the Disability Standards for Education 2005 (Commonwealth of Australia, 2006). Results from this review indicate existing motivations and processes of collaboration, as well as directions for future research and practice.
A right to live without stigma? Examining negative stereotyping, negative messages, and Article 8 of the European Convention on Human Rights
Authors: Herring Jonathan , Robinson Heloise 
Published: October 2024

AbstractThe purpose of this paper is to examine the contours of evolving jurisprudence on offensive expression and negative messages, and to suggest that it can best be understood by reference to the concept of stigma. At the European Court of Human Rights, there appears to have been an increasing willingness to recognise the harm of offensive expression through an interpretation of Article 8 of the European Convention on Human Rights, but the reach of this case law remains uncertain. In particular, while some cases associate negative expression with negative stereotyping, not all of these cases do, and there are potential conflicts with freedom of speech. In the domestic context, these issues recently arose in a significant case from the Court of Appeal, R (Crowter) v Secretary of State for Health and Social Care. In this case, the appellants argued that a legal provision sends a negative ‘message’, through the negative stereotyping of disabled people, but this ‘message’ is implicit, rather than explicitly articulated. While these developments raise important questions about the future evolution of case law, we propose that a focus on stigma can more clearly highlight the harms involved.
God of Promise and Voucher: Alienation, Reconciliation, and Resurrection
Authors: Moser Paul K. 
Published: October 2024

AbstractA Christian approach to suffering, sin, and evil cannot offer now a full theodicy. We now ‘know in part’ only regarding divine purposes in allowing suffering, sin, and evil. We can clarify instead how God interacts in righteousness with people as their God of promise and voucher in the midst of suffering, sin, and evil. To that end, this article illuminates a divine effort toward human reconciliation with God in righteousness and resurrection, despite our gaps in explaining suffering, sin, and evil. It identifies current reconciliation with God and resurrection by God that do not fully explain suffering, sin, and evil, but can be a voucher now in human experience and life for eventual eschatological reparations promised by God. If the Spirit of God can be such a voucher, so also can the reconciliation and resurrection now empowered by that Spirit. This article recognizes a special role for the divine ‘fruit of the Spirit’ identified by Paul. It also explains how this role figures in spiritual resurrection with Christ now, in advance of any resurrection of the body. The article contends that the spiritual resurrection in question emerges through reconciliation with God now in volitional cooperation with God’s unique moral personality traits.