bluuebunny/crossref_metadata_2025_split huggingface dataset:
A stakeholder analysis to prepare for real-world evaluation of integrating artificial intelligent algorithms into breast screening (PREP-AIR study): a qualitative study using the WHO guide
Authors: Newlands Rumana , Bruhn Hanne , Díaz Magdalena Rzewuska , Lip Gerald , Anderson Lesley A. , Ramsay Craig 
Published: February 2024

Abstract

Background
The national breast screening programme in the United Kingdom is under pressure due to workforce shortages and having been paused during the COVID-19 pandemic. Artificial intelligence has the potential to transform how healthcare is delivered by improving care processes and patient outcomes. Research on the clinical and organisational benefits of artificial intelligence is still at an early stage, and numerous concerns have been raised around its implications, including patient safety, acceptance, and accountability for decisions. Reforming the breast screening programme to include artificial intelligence is a complex endeavour because numerous stakeholders influence it. Therefore, a stakeholder analysis was conducted to identify relevant stakeholders, explore their views on the proposed reform (i.e., integrating artificial intelligence algorithms into the Scottish National Breast Screening Service for breast cancer detection) and develop strategies for managing ‘important’ stakeholders.
Methods
A qualitative study (i.e., focus groups and interviews, March-November 2021) was conducted using the stakeholder analysis guide provided by the World Health Organisation and involving three Scottish health boards: NHS Greater Glasgow & Clyde, NHS Grampian and NHS Lothian. The objectives included: A) Identify possible stakeholders B) Explore stakeholders’ perspectives and describe their characteristics C) Prioritise stakeholders in terms of importance and D) Develop strategies to manage ‘important’ stakeholders. Seven stakeholder characteristics were assessed: their knowledge of the targeted reform, position, interest, alliances, resources, power and leadership.
Results
Thirty-two participants took part from 14 (out of 17 identified) sub-groups of stakeholders. While they were generally supportive of using artificial intelligence in breast screening programmes, some concerns were raised. Stakeholder knowledge, influence and interests in the reform varied. Key advantages mentioned include service efficiency, quicker results and reduced work pressure. Disadvantages included overdiagnosis or misdiagnosis of cancer, inequalities in detection and the self-learning capacity of the algorithms. Five strategies (with considerations suggested by stakeholders) were developed to maintain and improve the support of ‘important’ stakeholders.
Conclusions
Health services worldwide face similar challenges of workforce issues to provide patient care. The findings of this study will help others to learn from Scottish experiences and provide guidance to conduct similar studies targeting healthcare reform.
Study registration:
researchregistry6579, date of registration: 16/02/2021
Health-related Quality of Life and the Influencing Factors in Chinese Elderly Patients with Cognitive Impairment
Authors: Ma Wanting , Wang Weijia , Zou Yuanwen 
Published: February 2024

Abstract
With the increasing number of aging individuals in China, it is important to focus on age-related cognitive impairment and its impact on health-related quality of life (HRQoL) among the elderly population. This study aimed to assess the HRQoL of elderly patients with cognitive impairment in China and identify associated factors. Data from the China Health and Retirement Longitudinal Study (CHARLS) in 2018, including 684 patients with cognitive impairment, were analyzed. The diagnosis of cognitive impairment was based on the Minimum Mental State Examination (MMSE), and the EuroQoL Five Dimensions Questionnaire (EQ-5D-3L) was used to measure HRQoL. The results indicated that age, education level, sleep duration, and social activities significantly influenced the HRQoL of these patients. Specifically, patients aged 75 years or older, those with lower education levels, and those with inadequate sleep had lower health utility values, while patients engaged in social activities exhibited higher health utility values. Tobit regression analysis confirmed the substantial impact of age, education level, sleep duration, and activities on health utility values. Overall, the findings revealed a strong association between diminished health-related quality of life and elderly Chinese patients with cognitive impairment. It was concluded that advanced age, lower education level, insufficient sleep, and limited social engagement were influential factors affecting the HRQoL of these patients. Therefore, the study suggested that collaborative efforts among patients, families, hospitals, and social service organizations are essential to enhance the HRQoL and overall physical and mental well-being of elderly patients with cognitive impairment.
Population parameters of Drosophila larval cooperative foraging.
Authors: Liao Amy , Qian Christy , Abdi Sepideh , Yee Peyton , Cursain Sean Michael , Condron Niav , Condron Barry 
Published: February 2024

Abstract
Cooperative foraging behavior can be advantageous when there is a common exploitable resource. By cooperating, members of the group can take advantage of the potential of increased efficiency of working together as well as equitable distribution of the product. An experimental signature of cooperative foraging is an Allee effect where at a certain number of individuals, there is a peak of fitness. What happens when there are intruders especially ones that do not contribute to any work required for foraging? Drosophila larvae secrete digestive enzymes and exodigest food. Under crowded conditions in liquid food these larvae form synchronized feeding clusters which provides a fitness benefit. A key for this synchronized feeding behavior is the visually guided alignment between adjacent larvae in a feeding cluster. Larvae who do not align their movements are excluded from the groups and subsequently lose the benefit. This may be a way of editing the group to include only known members. To test the model, the fitness benefit from cooperative behavior was further investigated to establish an Allee effect for a number of strains including those who cannot exodigest or cluster. In a standard lab vial, about 40 larvae is the optimal number for fitness. Combinations of these larvae were also examined. The expectation was that larvae who do not contribute to exodigestion are obligate cheaters and would be expelled. Indeed, obligate cheaters gain greatly from the hosts but paradoxically, so do the hosts. Clusters that include cheaters are more stable. Therefore, clustering and the benefits from it are dependent on more than just the contribution to exodigestion. This experimental system should provide a rich future model to understand the metrics of cooperative behavior.
Healthcare service access challenges and determinants among persons with Disabilities in Bangladesh
Authors: Rahman Mizanur , Rana Md Shohel , Rahman Md Mostafizur , Khan Md Nuruzzaman 
Published: February 2024

Abstract

Background: Persons with disabilities in LMICs facing numerous challenges in accessing essential healthcare services. However, this understanding is lacking so far in LMICs and Bangladesh. This study aimed to explore the pattern and determinants of healthcare services access among persons with disability in Bangladesh.
Methods: We analysed data from 4,293 persons with disabilities extracted from the 2021 National Survey on Persons with Disabilities. The outcome variable was healthcare service access within three months of the survey, categorized as either "yes" or "no" based on perceived needs. Several individual, household, and community-level factors were considered as explanatory variables. We utilized a multilevel mixed-effect logistic regression model to explore the association of the outcome variable with explanatory variables. The analysis included stratification by age groups: 0-17 years and 18-95 years.
Results: One out of every four persons with disabilities in Bangladesh reported that they could not access healthcare services based on their needs within three months of the survey. The main reasons for not accessing services were healthcare costs (52.10%), followed by lack of family support (27.0%), and absence of healthcare facilities in their areas of residence (10.10%). Among those who did receive healthcare services, the majority reported accessing them from governmental hospitals (26.50%), followed by village practitioner (20.50%), and private healthcare centres (19.78%). There was a higher likelihood of accessing healthcare services among persons with disabilities residing in households with higher wealth quintiles and living in the Chattogram and Sylhet divisions. Unmarried or divorced/widowed/separated persons with disabilities reported lower likelihoods of accessing healthcare services.
Conclusion: The findings of this study emphasize the need for policies and programs to ensure healthcare services for persons with disabilities in Bangladesh. This entails raising awareness about the importance of providing healthcare services for this demographic, as well as considering healthcare services as part of social safety net programs.
Knowledge-based Discovery of Multi-level Co-location Patterns Using Ontology
Authors: Wang Long , Chang Liang , Bao Xuguang , Zhu Chuangying , Gu Tianlong 
Published: February 2024

Abstract

Spatial co-location pattern discovery (SCPD), a kind of knowledge discovery process, aims at discovering potentially unknown co-location patterns (co-locations). Co-locations have been widely used in many aspects, including life services, ecological environment, business research, etc. Many methods have been proposed to discover co-locations. However, these methods only discovered co-locations consisting of fine-grain spatial features, since the user knowledge is ignored, many interesting and general patterns are still undiscovered. Meanwhile, co-locations that are discovered by current frameworks are quantity-numerous and independent, thus, their usefulness is strongly limited. To overcome these shortcomings, this paper introduces the user knowledge into the process of SCPD, to discover general and intrinsic co-locations and help users quickly find their interested patterns. First, a framework OCPM (Co-location Pattern Miner using Ontology) is proposed, where an ontology is employed to integrate user knowledge to guide the process of SCPD. Second, a new co-location consisting of ontology concepts is proposed. Under the guidance of the ontology, we propose the prevalent semantic multi-level co-locations (PSMCs) consisting of ontology concepts to represent richer knowledge. Third, we design two different ways, i.e., the Apriori-like and clique-based ways, to meet the requirements of OCPM and propose a novel clique-based algorithm named IDG to discover PSMCs. Meanwhile, a top-down search strategy is proposed to help users quickly find interesting knowledge via the ontology. Finally, we validate OCPM and IDG on both real and synthetic datasets respectively, the experimental results demonstrate their effectiveness.
Please Show Restraint: Excessive Focus on Catastrophic Events Can Lead to Greater Psychological Trauma
Authors: Liu Huaqiang , Lan Zhensong , Zhao Qi , Deng Fafang , Huang Xuefang 
Published: February 2024

Abstract

Background: This study explored the relationship between attention, negative emotions, empathy, mindfulness, and psychological trauma in catastrophic events to reduce the public’s psychological trauma.
Methods: A total of 526 adults in Guangxi Province, China, were investigated using self-rating scales for post-traumatic stress disorder, emotion, and empathy, a five-factor self-rating mindfulness scale, and a catastrophic incident concern questionnaire.
Results: The results reveal the following: (1) Women are vulnerable to psychological trauma in catastrophic events (F [464]=0.681, p<0.05). (2) Emotion has a significant mediating effect between attention and psychological trauma. (3) Empathy has a significant mediating effect between attention and psychological trauma. (4) Mindfulness is conducive to buffering an individual’s negative emotions and also regulates the degree of psychological trauma in the public’s attention to catastrophic events. Therefore, people should be rational and restrained in the face of such events.
Conclusions: When people pay attention to catastrophic events, they should remain rational and restrained, and avoid excessive emotional involvement, to reduce the excessive psychological trauma caused by the event.
Anthracophyllum sontraense (Omphalotaceae, Agaricales), a new species from Danang, Vietnam
Authors: Tran Phu Thi , Do Hanh Hong , Nguyen Toan Sy , Huynh Uyen Thi-Diem , Nguyen Hai Thi-Lam , Phan Thi Thanh Tam , Nguyen Thi Thu Hoai , Nguyen Trung Thanh 
Published: February 2024

Abstract
During the collection of macrofungi resources in Son Tra Nature Reserve, Danang, Vietnam, a novel species of the genus Anthracophyllum living saprophytically on small shrubs and rotten wood of Mussaenda frondosa Linn in the forest at an elevation 368 m above the sea level was recorded. The phylogenetic analyses based on the combined ITS and LSU molecular markers placed the specimens within Anthracophyllum genus. Together with specific morphological characteristics, we introduced A. sontraense sp. nov. as a new species. A. sontraense was characterized by the pileus with the skewed bell shape when young, dark blue to midnight blue, 1.0−1.5 cm diam, stipeless, light pink lamellae, sparse, occasionally branching. Basidiospores broadly ovoid to subglobose, 6–7 × 5.5–6 µm. Molecular phylogeny analyses revealed that the new species formed a clade with A. archeri with strong support. In addition, A. sontraense formed a separate lineage which was closer related to A. archeri and A. sinense than A. lateritium. To our knowledge, this is the first record of Anthracophyllum fungus in Vietnam.
Multiomic analysis of human kidney disease identifies a tractable inflammatory, pro-fibrotic tubular cell phenotype
Authors: Conway Bryan , Reck Maximilian , Baird David , Sutherland Callum , Bell Rachel , Hur Heeyoun , Cairns Carolynn , Campbell Ross , Nam Andy , Yang Wei , Schurman Nathan , Williams Claire , Veizades Stefan , O'Sullivan Eoin , Corsinotti Andrea , Bellamy Christopher , Hughes Jeremy , Laird Alexander , Denby Laura , Chandra Tamir , Ferenbach David 
Published: February 2024

Abstract
Maladaptive proximal tubular cells have been implicated in failure of repair following renal injury in rodent models, however whether this translates to human kidney disease is unknown. Hence, we integrated snRNA-ATAC-seq with single-cell molecular imaging to generate a multiomic atlas of human kidney disease. In injured kidneys, a subset of tubular epithelial cells acquired an inflammatory phenotype, enriched with pro-fibrotic and senescence markers, analogous to maladaptive cells in mice. Cell neighborhood analysis positioned the inflammatory phenotype adjacent to leucocytes and myofibroblasts and ligand-receptor analysis highlighted paracrine signaling from inflammatory tubular cells to mediate leucocyte recruitment and myofibroblast activation. Loss of an HNF4α-driven gene regulatory network and activation of NF-κβ and AP-1 transcription factors epigenetically imprinted the inflammatory phenotype. Targeting these inflammatory tubular cells by administration of an AP-1 inhibitor or a senolytic agent ameliorated inflammation, expression of senescence-associated transcripts and fibrosis in murine models of kidney injury suggesting these as therapies for human kidney disease.
scRNA-seq and scATAC-seq analyses highlight the role of TNF signaling in chronic obstructive pulmonary disease progression
Authors: Zhang Qiang , Zhou Li , Yuan Lindong , Zhang Ruihua , Pan Shanshan , Wang Xizi , Yi Lili , Yuan Fengjiao , Gu Mingliang , Wang Yan , Jia Xiaodong 
Published: February 2024

Abstract

Chronic obstructive pulmonary disease (COPD) is a prevalent and progressive form of respiratory disease in which patients exhibit persistent respiratory damage affecting the alveoli and/or airway due to exposure to toxic gases or particulate matter. The best-studied risk factor associated with COPD incidence is cigarette smoke. C57BL/6 mice were exposed to cigarette smoke and lipopolysaccharide to establish a COPD model, followed by scATAC sequencing and scRNA sequencing of lung tissue samples. The resultant data revealed consistent findings between scATAC-seq and scRNA-seq regarding cell types, differentially expressed genes, and signaling pathways. Tumor necrosis factor (TNF) signaling pathway enrichment was evident in the scRNA-seq and scATAC-seq datasets, with similar trends in monocytes/macrophages, dendritic cells, and B cells. Significant TNFR1 upregulation and high levels of activity related to cellular communication were observed, and significant increases in IL1B, CSF1, and BCL3 site accessibility were evident in cells from COPD model mice. Overall, these findings suggested that the TNF signaling pathway plays roles in the differentiation of monocytes and macrophages, the promotion of T cell proliferation, and the induction of airway inflammation that ultimately drives COPD progression.
DeepVasNet: Retinal Vasculature and FAZ Segmentation in OCTA with EfficientNet-Enhanced U-Net
Authors: Raja Nisan Pranavah , Gopi Varun P. , Francis Bibin , Devi Chelli N. 
Published: February 2024

Abstract
The study and analysis of retinal blood vessels and foveal avascular zone (FAZ) are clinically significant as they help in the early diagnosis of several diseases like diabetic retinopathy, glaucoma, neovasculariza-tion, artery or vein occlusion, and age-related macular degeneration. Recently, optical coherence tomography angiography (OCTA) imaging has been used to visualize the retina due to its non-invasive nature and fast imaging. However, manual retinal vasculature and FAZ segmentation are tedious and time-consuming. In this context, we propose an automated deep-learning-based segmentation method. The traditional U-Net is modified with a pre-trained EfficientNet-B0 in the encoder and a combined spatial, channel attention, squeeze, and excitation mechanism in the decoder. The proposed algorithm is validated on the publicly available OCTA-500 database. Mean Dice coefficients of 88.38, 88.40, 88.48, and 94.55 are obtained for capillary, artery, vein, and FAZ segmenta-tion in the OCTA 6 mm dataset. Whereas mean Dice scores of 90.48, 90.70, 89.59, and 97.98 are reported in the OCTA 3 mm subset for capillary , artery, vein, and FAZ segmentation, respectively. This segmentation performance is superior to other recent methods in the state-of-the-art literature. Overall, the contributions of our work are summarized as DRL-ASOCT follows. The proposed architecture is simple, easy to implement, and requires less memory and time than other networks. Further, we separately segment the retinal vessels (arteries, veins, and capillaries) and achieve improved segmentation accuracy relative to other approaches.
SAutoIDS: A Semantic Autonomous Intrusion Detection System Based on Cellular Deep Learning and Ontology for Malware Detection in cloud computing
Authors: Nazoksara AliReza Gerami , Etminan NaznooshSadat , Hosseinzadeh Reza , heidari behnam 
Published: February 2024

Abstract
Cloud computing (CC) is an online technology that has attracted the attention of many users and organizations today. Users send their requests through mobile to CC to perform a process. User requests are exposed to hacker attacks and malware risks. Penetration of malware in mobile devices causes loss of information or theft of mobile data. Today, various methods have been proposed to malware detection. In this paper, a semantic autonomous intrusion detection system (SAutoIDS) based on the ontology and cellular automata (CLA) and group method of data handling deep neural network (GMDH-DNN) is proposed to malware detection. The Semantic Multi-Level Approach (SMLA) processes of the data and transformed into semantic values based on a semantic level. The ontology method selects optimal features from malware data. Then the semantic data are divided into training (80%) and testing (20%). Training data are implemented to the GMDH-DNN for creating the model and CLA to optimize the GMDH model. Finally, testing data are entered into the optimized GMDH model and malwares are detected. We have used CICMalDroid2020 dataset to evaluate the SAutoIDS. By implementing the SAutoIDS, it was observed that the accuracy, precision, and recall improved by 21.96%, 22.41%, and 22.15%, compared to other methods.
Radon Dosimetry in Nchanga Underground Mine on the Copperbelt Province of Zambia
Authors: Banda Rabbison , Hayumbu Patrick , Mumba Ngandwe , Mubambe Patrick , Shaba Philimon 
Published: February 2024

Abstract
A Gamma Ray Spectrometer was used to quantify 222Rn activity in 27 water samples from Nchanga Under Ground Mine on the Copperbelt Province of Zambia. The content of 222Rn in water ranged from 100 to 3,710 Bq/m3 with an average of 1,077.59 ± 0.73 Bq/m3. The calculated radon concentration was compared to the underground mining industry's 500 Bq/m3 action limit. According to statistics, over 82 percent of tested locations exceeded the action limit, while only 41 percent exceeded the agreed limit of 1,000 Bq/m3. To estimate the radiological radon risk presented to mines, the annual effective dose (AED) due to inhalation were determined from radon concentrations. The AED values ranged from 0.77×10− 4 to 26.71×10− 4 mSvy1 with a mean of 7.76×10− 4±5.4×10− 7 mSvy− 1, much below the recommended limit of 20 mSvy− 1. On the other hand, the gamma dose rate measured using a survey meter varied from 0.26 to 0.66 mSvy− 1, with a mean value of 0.41 mSvy− 1. The results revealed that radon emanating from the NUG mine water was very low. As a consequence, miners may operate safely with little radioactive risk.
Parental discipline and self-regulation in children aged 2 to 5: A meta-analysis of research conducted from 2000 to 2022
Authors: Čepukienė Viktorija , Janulevičė Julija 
Published: February 2024

Abstract
This meta-analysis examined the correlation between parental discipline and self-regulation in children aged 2 to 5 years. The relevant literature was searched using ScienceDirect, PsycINFO, the Web of Science, Medline, and Scopus. Only correlational, cross-sectional, or longitudinal studies conducted between 2000 and 2022 that utilized survey techniques and focused on parents and children aged 2–5 years without clinical complaints were considered for inclusion. The data were synthesized and extracted in accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. This meta-analysis included 28 studies involving a total of 27,285 children and caregivers. The study samples varied in size, ranging from 55 to 12,474. The results demonstrated a weak but consistent correlation between parental discipline and children's self-regulation. Both positive and negative parental discipline exhibited comparable effect sizes on self-regulation, though with distinct outcomes. There was a negative correlation between the use of negative discipline and self-regulation, indicating that children who have more negative discipline have lower levels of self-regulation. Conversely, positive discipline was positively correlated with self-regulation, suggesting that children who experience more positive discipline also exhibit better levels of self-regulation. The findings of meta-regression research indicate that the impact of negative parental discipline on self-regulation in children is influenced by age. As children age, the impact of negative parental discipline on self-regulation diminishes.