bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boundary controllability for a 1D degenerate parabolic equation with drift, a singular potential, and a Neumann boundary condition
Authors: Galo-Mendoza Leandro , López-García Marcos 
Published: June 2024

AbstractWe prove the null controllability of a one-dimensional degenerate parabolic equation with drift and a singular potential. Here, we consider a weighted Neumann boundary control at the left endpoint, where the potential arises. We use a spectral decomposition of a suitable operator, defined in a weighted Sobolev space, and the moment method by Fattorini and Russell to obtain an upper estimate of the cost of controllability. We also obtain a lower estimate of the cost of controllability using a representation theorem for analytic functions of exponential type.
May and Bay: Online Child Sexual Exploitation and Abuse in Southeast Asia — Using Digital Games in Preventative Education
Authors: Reeves Emerita Jane , Jones Stephanie E. , Kosaraju Aravinda , Shemmings David , Rigby Paul , Scharf Kristen , Soutar Emma 
Published: June 2024

AbstractThis article follows the journey of creating a digital preventative education programme for combating online child sexual exploitation and abuse (OCSEA) and child sex trafficking in Thailand and Cambodia. Created and rolled out over 2 years as part of the End Violence Against Children (EVAC) grant during the COVID-19 global pandemic, this article sets out how the programme was designed, with direct input from children and professionals, and underpinned by human rights and contextual safeguarding principles. It outlines how collaborative approaches between children, academia, expert NGO’s, and professionals have resulted in a thought-provoking digital programme (May and Bay) that sensitively tackles sexual grooming and promotes child safeguarding. The article highlights how the game focuses on the interplay between children’s choices online and the environmental constraints they face, with the lead characters May (aged 11) and Bay (aged 13) making ‘risky’ and ‘safe’ choices against interacting aspects of their social and digital environments. The game supports the development of digital competence among children and professionals by promoting awareness of online harms emanating from the interplay of technology with children’s micro, meso, and macro environments against a range of people whose interaction with them may be ‘safe’ or ‘unsafe’. It recognises children, peers, parents, carers, professionals responsible for safeguarding, media, legislators, and local non-governmental and international aid organisations as potential ‘attractors’ or ‘agents within the system’ whose combined efforts can change how child safeguarding systems respond.
Empathisches Textverstehen und Transportation von Grundschulkindern in Abhängigkeit von ihren Eingangsvoraussetzungen, motivationalen Merkmalen und Formen der Textpräsentation
Authors: Heyne Nora , Hermann Hanna 
Published: June 2024

ZusammenfassungLesekompetenz zu vermitteln, einschließlich der Fähigkeiten zum empathischen Textverstehen, denen für die Förderung von Lesemotivation, Lesegewohnheiten und somit von Lesefähigkeiten eine große Bedeutung zugeschrieben wird, zählt zu den zentralen Bildungszielen der Grundschule. Zu dem Stand der Fähigkeiten im empathischen Textverstehen von Grundschulkindern, ihrer Verknüpfung mit motivationalen Merkmalen und Möglichkeiten ihrer Förderung ist bislang wenig bekannt. Daher stehen in der Studie Fragen zum empathischen Textverstehen und der Transportation von Grundschulkindern sowie zu ihren Zusammenhängen mit den motivationalen Merkmalen der Kinder (Lesemotivation, Lesegewohnheiten, Leseumfang zum Vergnügen) im Mittelpunkt. Zudem wird untersucht, inwiefern sich diese Fähigkeiten in Abhängigkeit von den Eingangsvoraussetzungen der Kinder (Klassenstufe, Geschlecht, Sprachhintergrund) sowie Formen der Textpräsentation (mit versus ohne Illustrationen) unterscheiden. Dazu wurden Grundschulkinder (N = 105; Klassenstufe 3 und 4) in einer quasi-experimentellen Studie zu ihren demographischen und motivationalen Merkmalen sowie zu einer Geschichte befragt, die zuvor mit oder ohne Illustrationen in einer Lesung präsentiert wurde. Die Ergebnisse liefern einen Einblick zu den Fähigkeiten in der Transportation und im empathischen Textverstehen von Grundschulkindern. Sie zeigen, dass diese überwiegend mit den motivationalen Schülermerkmalen positiv korrelieren und in Abhängigkeit von der Klassenstufe der Kinder unterschiedlich ausfallen. Zudem werfen die Befunde Fragen nach möglichen Einflussfaktoren, wie dem emotionsbezogenen Vorwissen, und zugrundeliegenden Prozessen der untersuchten Fähigkeiten auf. Diese in zukünftigen Studien näher zu untersuchen, lässt tiefere Erkenntnisse über die Fähigkeiten beim Verstehen literarischer Texte und ihre Bedeutung für die Entwicklung von Lesemotivation und Lesekompetenz erwarten, die schließlich weitere Ansatzpunkte für die Leseförderung im Grundschulalter bieten können.
Measuring the Institutional Capacity of Older Volunteer Organizations in Japan: Comparative Study with the United States
Authors: Chen Li-Mei , Boulos Olivia 
Published: June 2024

AbstractVolunteerism as a civic engagement activity for older adults has grown considerably around the world as countries face population aging and prolonged longevity. The ability to recruit older adults from diverse backgrounds and sustain their activities are some of the challenges facing a super-aging society like Japan. Whether Japanese volunteer organizations have the institutional capacity for the recruitment and retention of their older adults is not known. This study tests the measures of institutional capacity of older volunteer organizations developed in the United States and contextualizes the findings from Japan by drawing a comparative perspective with a study conducted in the United States. The findings show a nuanced development of the institutional capacity of older volunteer organizations in Japan by history, culture, and policies, and provide valuable insights and lessons that transcend borders.
Characterization of urinary metabolites associated with malaria infection using infra-red spectroscopy and liquid chromatography–mass spectrometry in South Western Uganda
Authors: Birungi Grace , Achar Joan Beryl , Byamugisha Denis 
Published: June 2024

AbstractEarly malaria diagnosis improves outcomes during malaria treatment; routine diagnostic techniques rely on blood samples obtained invasively. Therefore, this study used infra-red (IR) spectroscopy coupled with Principle Component Analysis (PCA) to study the urinary profile of malaria patients and that of controls aimed at understanding metabolite perturbation during malaria infection so as to contribute towards development of non-invasive malaria diagnosis methods. Freeze dried human urine samples form malaria infected individuals (cases) and controls were screened in the IR region of 4000 cm−1 to 600 cm−1 and overall spectral differences were observed at wave numbers 1618 cm−1, 1679 cm−1 (amino acids). Peaks at 3030 cm−1 (NH4+) and 940 cm−1 (O–H of carboxylic acids) showed high absorbance in patients compared to controls. Liquid-chromatography–mass spectrometry (LC–MS/MS) was used to quantify amino acids in the urine samples and the results indicated a significant increase of amino acid cystine (P = 0.012). Lysine and tyrosine also increased in patients compared to controls. The use of IR-PCA differentiated clusters of urine samples from patients with malaria from control and the demonstrated amino acid perturbation is consistent with malaria infection. This data provides baseline information for application in development of a non-invasive diagnostic tests for malaria.
Understanding How British Pakistani Women Speak About Resilience Through the Lens of the Resilience Portfolio Model
Authors: Ajayi Chinyere Elsie 
Published: June 2024

Abstract
The aim of this study was to gain an in-depth understanding of the way British Pakistani women speak about resilience during the COVID-19 adversity. It draws upon in-depth narrative interviews with 13 British Pakistani women, aged between 38 and 69. The analysis is grounded in the Resilience Portfolio Model developed by Grych and colleagues. The Resilience Portfolio Model proposes that each individual has a unique “portfolio” of strengths and protective factors which consists of “assets” (regulatory strengths, interpersonal strengths, and meaning-making strengths) and resources available to individuals. Just like many people across the globe, women were impacted by the pandemic in different ways; nevertheless, they maintained resilience through regulatory behaviours of walking and enjoying nature, engaging in praying, and reading the Quran. Women invested in positive relationships that supported the development of social capital within their community and allowed them to connect with others in meaningful and reciprocal ways. Their religious beliefs and identity not only were key in their ability to make sense of the pandemic but also promoted a sense of belonging which enabled them to engage with their community resources. Findings show that women’s assets worked in tandem with their resources to promote their overall wellbeing during the COVID-19 adversity. This highlights the need for practitioners to combine individual “strengths” and community resources when developing preventative and responsive interventions for ethnic minority women who have experienced adversity and for policy initiatives to consider recreational resources that help to minimise isolation in ethnic minority communities.
Optimizing Crowd Counting in Dense Environments Through Curriculum Learning Training Strategy
Authors: Fotia Lidia , Percannella Gennaro , Saggese Alessia , Vento Mario 
Published: June 2024

AbstractCounting individuals in highly crowded environments, characterized by thousands of people, has garnered significant attention in recent years, due to the high number of vertical markets wherein such algorithms can prove beneficial, ranging from smart city and transportation to retail sectors, among others. Within this context, in this paper we introduce a novel training methodology tailored for estimating the number of people, ensuring precise counting accuracy in both moderately and highly crowded scenarios. The proposed approach exploits a formulation of the problem based on point detection, where each point represents an individual’s head. Our innovative contributions center around the designing of a novel training strategy employing Curriculum Learning (CL), which aims to replicate the gradual learning process observed in human cognition, training on simpler tasks at the beginning and tackling more complex tasks as the training evolves. In order to evaluate the complexity of each sample image, we propose a novel indicator taking into account both the number of people and their distribution within the image. The experimentation phase encompassed 18 publicly available datasets; the obtained results validate the effectiveness of the proposed approach, surpassing the baseline state-of-the-art point detection by 71% and 70% in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE), respectively
Pufferfish gasdermin Ea is a significant player in the defense against bacterial pathogens
Authors: Xu Hang , Qin Kunpeng , Hao Kangwei , Yuan Zihao , Sun Li 
Published: June 2024

AbstractGasdermins (GSDMs) are proteins cleaved by caspase (CASP) to trigger pyroptosis. In teleosts, pyroptosis is mediated by gasdermin E (GSDME). The Pufferfish, Takifugu rubripes, possesses two GSDME orthologs: named TrGSDMEa and TrGSDMEb. TrGSDMEa is cleaved by CASP3/7 to liberate the N-terminal (NT) domain that can trigger pyroptosis in mammalian cells. However, the biological function of TrGSDMEa in pufferfish is unknown, and TrGSDMEb is poorly studied. We found that TrGSDMEb was cleaved by CASP1/3/6/7/8, but the resulting NT domain, despite its similarity to TrGSDMEa-NT domain in sequence and structure, failed to induce pyroptosis. TrGSDMEa and TrGSDMEb exhibited similar expression patterns in pufferfish under normal physiological conditions but were up- and downregulated, respectively, in expression during Vibrio harveyi and Edwardsiella tarda infection. Bacterial infection induced the activation of TrGSDMEa and CASP3/7 in pufferfish cells, resulting in pyroptosis accompanied with IL-1β production and maturation. Inhibition of TrGSDMEa-mediated pyroptosis via TrCASP3/7 reduced the death of pufferfish cells and augmented bacterial dissemination in fish tissues. Structure-oriented mutagenesis identified 16 conserved residues in teleost GSDMEa that were required for the pore formation or auto-inhibition of GSDMEa. This study illustrates the role of GSDMEa-mediated pyroptosis in teleost defense against bacterial pathogens and provides new insights into the structure-based function of vertebrate GSDME.
Interactions between metabotropic glutamate and CB1 receptors: implications for mood, cognition, and synaptic signaling based on data from mGluR and CB1R-targeting drugs
Authors: Stachowicz Katarzyna 
Published: June 2024

AbstractMetabotropic glutamate receptors (mGluRs) are part of the G protein-coupled receptors (GPCRs) family. They are coupled to Gαq (group I) or Gi/o (groups II and III) proteins, which result in the generation of diacylglycerol (DAG) and inositol 1,4,5-triphosphate (IP3) or the inhibition of adenylyl cyclase, respectively. mGluRs have been implicated in anxiety, depression, learning, and synaptic plasticity. Similarly, CB1 cannabinoid receptors (CB1Rs), also GPCRs, play roles in cognitive function and mood regulation through Gαi/o–mediated inhibition of adenylyl cyclase. Both mGluRs and CB1Rs exhibit surface labeling and undergo endocytosis. Given the similar cellular distribution and mechanisms of action, this review complies with fundamental data on the potential interactions and mutual regulation of mGluRs and CB1Rs in the context of depression, anxiety, and cognition, providing pioneering insights into their interplay.
Efficient machine learning model for settlement prediction of large diameter helical pile in c—Φ soil
Authors: Shuman Nur Mohammad , Khan Mohammad Sadik , Amini Farshad 
Published: June 2024

AbstractMachine learning is frequently used in various geotechnical applications nowadays. This study presents a statistics and machine learning model for settlement prediction of helical piles that relates compressive service load and soil parameters as a group with the pile parameters. Machine learning algorithms such as Decision Trees, Random Forests, AdaBoost, and Artificial Neural Networks (ANN) were used to develop the predictive models. The models were validated using cross-validation techniques and tested on an independent dataset to assess their accuracy and generalizability. Numerical investigation is used here to supplement the field data by simulating various soil conditions and pile geometries that have not been tested in the field. This study compiled numerical results of 3600 models. As the models are well-calibrated and validated, the data from these models can be reasonably assumed to simulate the ground situation. At the end of this study, a comparative analysis of statistic learning and machine learning (ML) was done using the field axial load tests database and numerical investigation on helical piles. It is observed that ML models like Decision Trees and Random Forests provided the better model with R-squared values of 0.92 and 0.96, respectively, for large diameters. The authors believe this study will permit engineers and state agencies to understand this prediction model's efficacy better, resulting in a more resilient approach to designing large-diameter helical piles for the compressive load.
Circular Economy Matrix Guiding Manufacturing Industry Companies towards Circularity—A Multiple Case Study Perspective
Authors: Saari Leila , Valkokari Katri , Martins Jorge Tiago , Acerbi Federica 
Published: June 2024

AbstractManufacturing companies struggle with overwhelming expectations, disruptions and trends sweeping over their business environment. The evident climate change, together with rising sustainable development goals, is forcing companies to discover their environmental impact, in addition to the more familiar economic one. The transformation from a linear economy to a circular economy (CE) reduces waste and improves resource efficiency through the deployed R-cycles, such as recycle, reuse and repair. This transformation is feasible for multinational enterprises because they can allocate sufficient resources for their strategic development goals. For small and medium-sized enterprises (SME), any additional investment must be carefully assessed and planned. Thus, SMEs need support and tools to select their next development investments. Generally, maturity models help companies find their status (compared to others) and identify the most important development areas and actions. This paper presents the CE maturity matrix, which comprises five maturity levels mapped with seven linear manufacturing value chain phases. The matrix was piloted with nine manufacturing industry companies, four of which were from Finland, one from Italy, one from Germany and three from Ireland. The CE matrix interview results showed that none of the interviewed manufacturing industry companies remained at the linearity level. The most common levels varied between systemic material management and CE thinking. In the interviews, over 40 CE actions were identified as the argument for a company reaching a CE maturity level. The transition towards sustainable manufacturing has already started but will require efforts to accelerate and to engage companies to proceed.
CACA guidelines for holistic integrative management of anticancer treatment - induced cutaneous adverse events
Authors: Zhu Guannan , Shi Qiong , Cai Tao , Gu Dongcheng , Zhou Hang , Wang Lu , Liu Fang , Wang Ping , Xiong Jianxia , Huang Yujing , Li Chunying , Gao Tianwen ,   Committee of Melanoma Society, China Anti-Cancer Association
Published: June 2024

Abstract
Purpose
The skin and mucous membrane of cancer patients can be directly or indirectly impaired during the treatment of cancers, bringing about not physical but also psychological damages to cancer patients. A practical guideline is of great significance to improve the quality of life for patients suffered from cutaneous adverse events.

Methods
This guideline was generated based on up-to-date evidence and the consensus of experts specialized in dermatology.

Results
The current guideline include the baseline screening of skin and mucosal membranes, the manifestations of injuries on skin, mucosa and appendages, along with the treatment of them. The causal anti-tumor management include chemotherapy, radiotherapy, immune therapy and surgery.

Conclusion
This guideline can be helpful to reduce the risk of cutaneous adverse events during anti-cancer treatment and improve the quality of life of patients suffered from these adverse events.
Performance evaluation and multivariate analysis of maize accessions against drought stress in Lamjung district, Nepal
Authors: Poudel Rashmi , Kandel Bishnu Prasad , Poudel Ankur , Tripathi Anubhav , Gurung Reema , Ghimire Unisha 
Published: June 2024

AbstractThe selection of drought-tolerant genotypes from the existing gene pool is a preliminary step for breeding for drought tolerance. Research efforts aimed at exploring the ability of crops to withstand drought stress have not yet touched the realm of reproductive drought performance of local genotypes. To examine how local crop accessions demonstrate varying reproductive performance under drought conditions, twenty accessions of maize (Zea mays L.) were evaluated for six quantitative traits in a two-factor factorial completely randomized design with two replications between February to June of 2023. All the traits under study showed significant differences among the genotypes (p < 0.05). Owing to their grain yield, ear weight, and hundred grain weight, accessions NGRC05592, NGRC05582, NGRC05564, NGRC05565, NGRC05571, and NGRC05569 performed better under drought condition than other tested accessions. Accession NGRC05592 showed the highest yield under drought condition, whereas, NGRC05573 and NGRC05576 showed poor performance. GGE Biplot analysis for grain yield revealed that NGRC05571 and NGRC05592 had the highest mean yield, with the accession NGRC05592 standing out as the stable variety under changing soil moisture levels and performing best among all the tested accessions under drought condition. The possibility of accession NGRC05592 being used as a potential genetic resource for drought breeding programs has been observed, but further studies aiming at its stability under field conditions in diverse agro-climatic regions across different years are encouraged to assure its prospect for developing cultivars suited to drought-affected regions.
A travel demand modeling framework based on OpenStreetMap
Authors: Notelaers Lotte , Verstraete Jeroen , Vansteenwegen Pieter , Tampère Chris M. J. 
Published: June 2024

AbstractDemand modeling is an important part of the setup of a traffic model for a city. All travel demand models rely on land use data as the demand for traveling fundamentally stems from activities occurring at different locations; however, many cities lack these data, or experience in estimating travel demand in their region. In response, this study develops a methodology for generating highly detailed land use data in the form of points of interest (POIs) specifically aimed at travel demand estimation purposes. The framework includes a procedure to extract, clean, enhance, and categorize freely available land use data from OpenStreetMap (OSM) into different POI categories, such as residences, schools, and shops. These residential and activity POIs, which are typical origins and/or destinations of trips, serve as the starting point for estimating travel demand. This paper demonstrates the framework’s utility through three case studies across different cities in Belgium. It validates the effectiveness of OSM-derived POIs for travel demand estimation by replicating Antwerp’s existing demand model, examines the POIs classification’s suitability for various travel demand purposes in Leuven, and assesses the transferability of correlations between OSM data and travel demand from Antwerp to Ghent. Beyond the applications illustrated in this paper, the framework provides opportunities for future research on the consistent disaggregation of existing zonal demand estimates and design-based research in which future demand is estimated given the development of POIs. The framework is openly available as a Python tool called Poidpy.