bluuebunny/crossref_metadata_2025_split huggingface dataset:
Room‐Temperature Single‐Phase Synthesis of Semiconducting Metal‐Covalent Organic Frameworks With Microenvironment‐Tuned Photocatalytic Efficiency
Authors: Wu Dongchuang , Zhang Qiongshan , Yin Shiyu , Song Congying , Gu Ning , Wang Dong , Cai Tao , Zhang Bin 
Published: October 2024

AbstractIn order to improve the solubility of metallated monomers and product crystallinity, metal–covalent organic frameworks (MCOFs) are commonly prepared via high‐temperature sol‐vothermal synthesis. However, it hampers the direct extraction of crystallization evolution information. Exploring facile room‐temperature strategies for both synthesizing MCOFs and exploiting the crystallinity mechanism is extremely desired. Herein, by a novel single‐phase synthetic strategy, three MCOFs with different microstructure is rapidly prepared based on the Schiff base reaction between planarity‐tunable C3v monomers and metallated monomers at room temperature. Based on detailed time‐dependent experiments and theoretical calculations, it is found that there is a planarity‐tuned and competitive growth relationship between disordered structures and crystal nucleus for the first time. The high planarity of monomers boosts the formation of crystal nucleus and rapid growth, suppressing the forming of amorphous structures. In addition, the microenvironment effect on selective photocatalytic coupling of benzylamine (BA) is investigated. The strong donor‐acceptor (D‐A) MCOF exhibits efficient photocatalytic activity with a high conversion rate of 99% and high selectivity of 99% in 5 h under the 520 nm light irradiation. This work opens a new pathway to scalable and efficient synthesis of highly crystalline MCOFs.
Effect of toughening agent and flame‐retardant additives on the recycled polypropylene/oil palm empty fruit bunch laminated composites
Authors: Abd Wahab Nur Ain Adila , Jaafar Mariatti , Che Hassan Nor Hasima , Sanz Raúl García 
Published: October 2024

AbstractThe increasing awareness of the environmental problems caused by the use of plastics has led to a demand for sustainable materials. The concept of turning waste into wealth has been considered in the study where the waste materials are value‐added into new composite materials that are recyclable, durable, and fire‐resistant. This effort aims to meet global environmental goals and the demand for high‐performance and sustainable building materials. The purpose of this current study is to develop laminated composites based on the combination of recycled plastic and oil palm empty fruit bunch (OPEFB). The addition of various loading of ammonium polyphosphate (APP) and 6 wt% of ethylene vinyl acetate (EVA) in the formulation was considered to enhance the performance of the composite laminates. The rPP and additives were compounded using a two‐roll mill. Then the rPP sheet and OPEFB were laminated using compression molding techniques. Results showed that rPP with addition of 30 wt% APP and 6 wt% EVA exhibited the highest thermal stability and the lowest melt flow index (MFI) value compared to other samples. Composites with 20 wt% APP and 6 wt% EVA showed 56% increase in flexural properties and 33% increase in impact strength compared to that of rPP/OPEFB composite sample without EVA. Addition of 30 wt% in recycled PP and OPEFB demonstrated self‐extinguished properties when exposed to fire compared to other samples. These findings indicated that rPP/OPEFB laminated composites with the addition of APP and EVA have a potential to be used in applications that require good strength and fire performance. The use of rPP/OPEFB composites with addition of APP and EVA has a potential to reduce virgin plastic consumption and agriculture material waste and establishing an environmentally friendly material for construction sector.Highlights
Additives included in recycled PP enhance its thermal stability and reduce MFI.
Recycled PP with OPEFB composite self‐extinguished at 30 wt% APP.
The highest flexural strength is shown by composite laminates with 20 wt% APP and 6 wt% EVA.
rPP/OPEFB laminates are ideal for building materials.
Sterile pyogranuloma/granuloma syndrome in two dogs presenting with extensive ulceration and systemic illness
Authors: Ludwig Courtney B. , Vogelnest Linda J. 
Published: October 2024

AbstractThis report describes two cases of canine sterile pyogranuloma/granuloma syndrome presenting with fulminant extensive ulcerations, pyrexia and systemic malaise; one case with concurrent unilateral uveitis. This presentation contrasts to typically reported cases, and due to the severity of signs, urgent distinction from aggressive infectious causes was required. Both cases required extended immunosuppressive treatments for resolution.
Reforestation effects on low flows: Review of public perceptions and scientific evidence
Authors: van Meerveld Ilja , Seibert Jan 
Published: October 2024

AbstractThis review article focuses on the complex relationships between forests and water, particularly the effects of forests on streamflow during meteorological droughts. The impact of forests on water resources is a long‐standing research topic, but there are also many common beliefs that are not based on scientific evidence or only selective evidence. We critically examine the origin of some of the common public misconceptions and review the wealth of studies on how forests impact precipitation, soil water dynamics, evapotranspiration, and streamflow. Generally, reforestation increases evapotranspiration and decreases groundwater recharge and streamflow. However, some of the evaporated water will return as precipitation, potentially offsetting some of the increased evapotranspiration losses. Where reforestation leads to more extensive infiltration and recharge due to the effects of forests on the soil's hydraulic properties, it might increase streamflow during dry periods. Although these individual processes have been studied, predicting the impacts of forests on streamflow remains challenging as the effects are site‐specific and depend on many factors, such as the climate, the forest‐ and soil‐characteristics before and after reforestation, and the hydrogeological setting. However, a more accurate and nuanced understanding of the role of forests on hydrology and a better ability to predict where and when the net effects of reforestation are positive or negative is crucial for sustainable forest and water management.This article is categorized under:
Science of Water > Science of Water
Science of Water > Water and Environmental Change
Science of Water > Hydrological Processes
Engineering Water > Sustainable Engineering of Water
Wess-Zumino-Witten terms of Sp QCD by bordism theory
Authors: Saito Shota 
Published: October 2024

Abstract
We investigate the four-dimensional Wess-Zumino-Witten (WZW) terms within the framework of Sp quantum chromodynamics (QCD) using invertible field theory through bordism theory. We present a novel approach aimed at circumventing both perturbative and non-perturbative gauge anomalies on spacetime manifolds endowed with spin structures. We study both ungauged and gauged WZW terms including the problems of the topological consistency of gauged WZW terms.
Periodically modulated solitary waves of the CH–KP-I equation
Authors: Nilsson Dag , Svensson Seth Douglas , Wang Yuexun 
Published: October 2024

AbstractWe consider the CH–KP-I equation. For this equation, we prove the existence of steady solutions, which are solitary in one horizontal direction and periodic in the other. We show that such waves bifurcate from the line solitary wave solutions, i.e. solitary wave solutions to the Camassa–Holm equation, in a dimension-breaking bifurcation. This is achieved through reformulating the problem as a dynamical system for a perturbation of the line solitary wave solutions, where the periodic direction takes the role of time, then applying the Lyapunov–Iooss theorem.
Geospatial Mapping and Meteorological Flood Risk Assessment: A Global Research Trend Analysis
Authors: Sibandze Phila , Kalumba Ahmed Mukalazi , H. Aljaddani Amal , Zhou Leocadia , Afuye Gbenga Abayomi 
Published: October 2024

Abstract
Flooding is a global threat causing significant economic and environmental damage, necessitating a policy response and collaborative strategy. This study assessed global research trends and advances in geospatial and meteorological flood risk assessment (G_MFRA), considering the ongoing debate on flood risk management and adaptation strategies. A total of 1872 original articles were downloaded in BibTex format using the Web of Science (WOS) and Scopus databases to retrieve G_MFRA studies published from 1985 to 2023. The annual growth rate of 15.48% implies that the field of G_MFRA has been increasing over time during the study period. The analysis of global trends in flood risk research and practice highlights the key themes, methodologies, and emerging directions. There exists a notable gap in data and methodologies for flood risk assessment studies between developed and developing countries, particularly in Africa and South America, highlighting the urgency of coordinated research efforts and cohesive policy actions. The challenges identified in the body of extant literature include technical expertise, complex communication networks, and resource constraints associated with the application gaps of the study methodologies. This study advocates for a holistic research approach to flood disaster management through ecosystem-based adaptation that underpins the Sustainable Development Goals to develop innovative flood techniques and models with the potential to influence global decision-making in the G_MFRA domain. Addressing these global challenges requires a networked partnership between the research community, institutions, and countries.
Development of Asymmetric Convection in a Tropical Cyclone under Environmental Uniform Flow and Vertical Wind Shear
Authors: Li Yubin , Jiang Yuncong , Chan Johnny C. L. , Cheung Kevin K. W. 
Published: October 2024

AbstractIdealized numerical simulations have been carried out to reveal the complexity in the development of asymmetric convection in a tropical cyclone (TC) under the influence of an environment with either uniform flow, vertical wind shear (VWS), or both. Results show that rainwater is enhanced to the right of the motion in the outer rainband, but such enhancement occurs in the upshear-left area of the inner-core region. Additionally, due to the asymmetries introduced by environmental flow, wavenumber-1 temperature and height anomalies develop at a radius of ~1000 km in the upper levels. A sub-vortex aside from the TC center encompassing the wavenumber-1 warm center appears, and asymmetric horizontal winds emerge, which, in turn, changes the storm-scale (within 400 km) VWS. Deep convection in the inner core closely follows the changing storm-scale VWS when its magnitude is larger than 2 m s–1 and is located downshear of the storm-scale VWS in all the experiments with environmental flow. In the outer rainbands, the maximum boundary layer convergence is mainly controlled by the direction of motion and is located in the rear-right quadrant. These results extend upon the findings of previous studies in three aspects: (1) The discovery of the roughly linear combination effect from the uniform flow and large-scale VWS; (2) The development of upper-level asymmetric winds on a 1000-km scale through the interaction between the TC vortex and environmental flow, resulting in changes in the storm-scale VWS pattern within the TC area; (3) The revelation that TC asymmetric convection closely aligns with the direction-varying storm-scale VWS instead of the initially designated VWS.
Resolving social dilemmas with minimal reward transfer
Authors: Willis Richard , Du Yali , Leibo Joel Z. , Luck Michael 
Published: October 2024

AbstractSocial dilemmas present a significant challenge in multi-agent cooperation because individuals are incentivised to behave in ways that undermine socially optimal outcomes. Consequently, self-interested agents often avoid collective behaviour. In response, we formalise social dilemmas and introduce a novel metric, the general self-interest level, to quantify the disparity between individual and group rationality in such scenarios. This metric represents the maximum proportion of their individual rewards that agents can retain while ensuring that a social welfare optimum becomes a dominant strategy. Our approach diverges from traditional concepts of altruism, instead focusing on strategic reward redistribution. By transferring rewards among agents in a manner that aligns individual and group incentives, rational agents will maximise collective welfare while pursuing their own interests. We provide an algorithm to compute efficient transfer structures for an arbitrary number of agents, and introduce novel multi-player social dilemma games to illustrate the effectiveness of our method. This work provides both a descriptive tool for analysing social dilemmas and a prescriptive solution for resolving them via efficient reward transfer contracts. Applications include mechanism design, where we can assess the impact on collaborative behaviour of modifications to models of environments.
HIV Denial in the COVID Era
Authors: Smith Tara C. 
Published: October 2024

Abstract
Though scientific consensus regarding HIV causation of AIDS was reached decades ago, denial of this conclusion remains. The popularity of such denial has waxed and waned over the years, ebbing as evidence supporting HIV causation mounted, building again as the internet facilitated connection between denial groups and the general public, and waning following media attention to the death of a prominent denier and her child and data showing the cost of human life in South Africa. Decades removed from these phenomena, HIV denial is experiencing another resurgence, coupled to mounting distrust of public health, pharmaceutical companies, and mainstream medicine. This paper examines the history and current state of HIV denial in the context of the COVID pandemic and its consequences. An understanding of the effect of this phenomenon and evidence-based ways to counter it are lacking. Community-based interventions and motivational interviewing may serve to contain such misinformation in high-risk communities.
Deep models for multi-view 3D object recognition: a review
Authors: Alzahrani Mona , Usman Muhammad , Jarraya Salma Kammoun , Anwar Saeed , Helmy Tarek 
Published: October 2024

AbstractThis review paper focuses on the progress of deep learning-based methods for multi-view 3D object recognition. It covers the state-of-the-art techniques in this field, specifically those that utilize 3D multi-view data as input representation. The paper provides a comprehensive analysis of the pipeline for deep learning-based multi-view 3D object recognition, including the various techniques employed at each stage. It also presents the latest developments in CNN-based and transformer-based models for multi-view 3D object recognition. The review discusses existing models in detail, including the datasets, camera configurations, view selection strategies, pre-trained CNN architectures, fusion strategies, and recognition performance. Additionally, it examines various computer vision applications that use multi-view classification. Finally, it highlights future directions, factors impacting recognition performance, and trends for the development of multi-view 3D object recognition method.
Speech based detection of Alzheimer’s disease: a survey of AI techniques, datasets and challenges
Authors: Ding Kewen , Chetty Madhu , Noori Hoshyar Azadeh , Bhattacharya Tanusri , Klein Britt 
Published: October 2024

AbstractAlzheimer’s disease (AD) is a growing global concern, exacerbated by an aging population and the high costs associated with traditional detection methods. Recent research has identified speech data as valuable clinical information for AD detection, given its association with the progressive degeneration of brain cells and subsequent impacts on memory, cognition, and language abilities. The ongoing demographic shift toward an aging global population underscores the critical need for affordable and easily available methods for early AD detection and intervention. To address this major challenge, substantial research has recently focused on investigating speech data, aiming to develop efficient and affordable diagnostic tools that align with the demands of our aging society. This paper presents an in-depth review of studies from 2018–2023 utilizing speech for AD detection. Following the PRISMA protocol and a two-stage selection process, we identified 85 publications for analysis. In contrast to previous literature reviews, this paper places a strong emphasis on conducting a rigorous comparative analysis of various Artificial Intelligence (AI) based techniques, categorizing them meticulously based on underlying algorithms. We perform an exhaustive evaluation of research papers leveraging common benchmark datasets, specifically ADReSS and ADReSSo, to assess their performance. In contrast to previous literature reviews, this work makes a significant contribution by overcoming the limitations posed by the absence of standardized tasks and commonly accepted benchmark datasets for comparing different studies. The analysis reveals the dominance of deep learning models, particularly those leveraging pre-trained models like BERT, in AD detection. The integration of acoustic and linguistic features often achieves accuracies above 85%. Despite these advancements, challenges persist in data scarcity, standardization, privacy, and model interpretability. Future directions include improving multilingual recognition, exploring emerging multimodal approaches, and enhancing ASR systems for AD patients. By identifying these key challenges and suggesting future research directions, our review serves as a valuable resource for advancing AD detection techniques and their practical implementation.
Digital deception: generative artificial intelligence in social engineering and phishing
Authors: Schmitt Marc , Flechais Ivan 
Published: October 2024

AbstractThe advancement of Artificial Intelligence (AI) and Machine Learning (ML) has profound implications for both the utility and security of our digital interactions. This paper investigates the transformative role of Generative AI in Social Engineering (SE) attacks. We conduct a systematic review of social engineering and AI capabilities and use a theory of social engineering to identify three pillars where Generative AI amplifies the impact of SE attacks: Realistic Content Creation, Advanced Targeting and Personalization, and Automated Attack Infrastructure. We integrate these elements into a conceptual model designed to investigate the complex nature of AI-driven SE attacks—the Generative AI Social Engineering Framework. We further explore human implications and potential countermeasures to mitigate these risks. Our study aims to foster a deeper understanding of the risks, human implications, and countermeasures associated with this emerging paradigm, thereby contributing to a more secure and trustworthy human-computer interaction.
Projecting the impact of COVID-19 on education and intergenerational mobility in Sub-Saharan Africa
Authors: Neidhöfer Guido , Lustig Nora , Larroulet Patricio 
Published: October 2024

AbstractUsing microsimulations, we project the effect of instructional losses caused by COVID-19 on secondary school completion rates and intergenerational mobility of education in eight countries in Sub-Saharan Africa. On average, secondary school completion rates could decrease by 12 percentage points overall and by 16 points for children with low-educated parents. Interestingly, in most countries the gender gap diminishes because, for men, the projected decrease in secondary school completion is higher. A small additional impact on girls’ education due to the potential rise in teenage pregnancy is observed in some countries. Intergenerational mobility of education in the eight Sub-Saharan countries in our sample is expected to decrease, on average, by 10%.
Targeting RAGE-signaling pathways in the repair of rotator-cuff injury
Authors: Rai Vikrant , Deepu Vinitha , Agrawal Devendra K. 
Published: October 2024

AbstractRotator cuff injury (RCI) is a common musculoskeletal problem that can have a significant impact on the quality of life and functional abilities of those affected. Novel therapies, including proteomics-based, stem cells, platelet-rich plasma, and exosomes, are being developed to promote rotator-cuff healing. The receptor for advanced glycation end-products (RAGE) is a multifunctional receptor that is expressed on several cell types and is implicated in several physiologic and pathological processes, such as tissue repair, inflammation, and degeneration. Because of its capacity to bind with a variety of ligands and initiate signaling pathways that lead to inflammatory responses in RCI, RAGE plays a crucial role in inflammation. In this critical review article, we discussed the role of RAGE-mediated persistent inflammation in RCI followed by novel factors including PKCs, TIRAP, DIAPH1, and factors related to muscle injury with their therapeutic potential in RCI. These factors involve various aspects of muscle injury and signaling and the possibility of targeting these factors to improve the clinical outcomes in RCI still needs further investigation.
Open access publications drive few visits from Google Search results to institutional repositories
Authors: Orduña-Malea Enrique , Font-Julián Cristina I. , Serrano-Cobos Jorge 
Published: October 2024

AbstractGiven the importance of Google Search in generating visits to institutional repositories (IR), a lack of visibility in search engine results pages can hinder the possibility of their publications being found, read, downloaded, and, eventually, cited. To address this, institutions need to evaluate the visibility of their repositories to determine what actions might be implemented to enhance them. However, measuring the search engine optimization (SEO) visibility of IRs requires a highly accurate, technically feasible method. This study constitutes the first attempt to design such a method, specifically applied here to measuring the IR visibility of Spain’s national university system in Google Search based on a set of SEO-based metrics derived from the Ubersuggest SEO tool. A comprehensive dataset spanning three months and comprising 217,589 bibliographic records and 316,899 organic keywords is used as a baseline. Our findings show that many records deposited in these repositories are not ranked among the top positions in Google Search results, and that the most visible records are mainly academic works (theses and dissertations) written in Spanish in the Humanities and Social Sciences. However, most visits are generated by a small number of records. All in all, our results call into question the role played by IRs in attracting readers via Google Search to the institutions’ scientific heritage and serve to underscore the prevailing emphasis within IRs on preservation as opposed to online dissemination. Potential improvements might be achieved using enhanced metadata schemes and normalized description practices, as well as by adopting other actionable insights that can strengthen the online visibility of IRs. This study increases understanding of the role played by web indicators in assessing the web-based impact of research outputs deposited in IRs, and should be of particular interest for a range of stakeholders, including open access and open science advocates, research agencies, library practitioners, repository developers, and website administrators.