bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geospatial insights into open defecation vulnerability in Gulumbe, Nigeria
Authors: Muktar Abdullahi , Ibrahim Sa’ad , Yelwa Sadiq A. 
Published: September 2024

AbstractOpen defecation (OD) poses a serious public health risk by exposing communities to diseases and compromising the well-being of people. One potential approach to mitigating its impact is the application of spatial planning techniques. However, spatial data paucity is one of the major problems in addressing open defecation issues in Nigeria. This study employed spatial analysis to identify areas particularly susceptible to OD using Geographical Information System (GIS) including Merginmap applications on Android and QGIS software, which were used with field observations to georeferenced residential areas, public toilets, and instances of open defecation. Proximity analysis and local indicators of spatial autocorrelation, based on Moran’s I, were employed to assess vulnerability. Buffer analysis was conducted to identify residential areas within 100 m of an OD site, and the findings indicated residential areas at high risk of experiencing negative impacts from OD. The LISA analysis revealed a high-to-high clustering pattern (p < 0.05) in the southern region of the study area, which aligns with the results of the buffer analysis and further suggests consistent spatial patterning. Furthermore, OD was more prevalent near water bodies and inner residential areas, increasing the risk of water and air pollution. This pollution could facilitate the spread of harmful bacteria, such as E. coli and Salmonella, from OD sites to nearby households, increasing the risk of disease. This study stresses the potential of GIS in evaluating areas vulnerable to OD and highlights the need to expand awareness campaigns regarding proper hygiene and sanitation practices in rural communities.
RvXmBlendNet: A Multi-architecture Hybrid Model for Improved Skin Cancer Detection
Authors: Prity Farida Siddiqi , Hasan Ahmed Jabid , Anik Md Mehedi Hassan , Hossain Rakib , Hossain Md. Maruf , Bhuiyan Sazzad Hossain , Islam Md. Ariful , Lavlu Md Tousif Hasan 
Published: September 2024

AbstractSkin cancer, one of the most dangerous cancers, poses a significant global threat. While early detection can substantially improve survival rates, traditional dermatologists often face challenges in accurate diagnosis, leading to delays in treatment and avoidable fatalities. Deep learning models like CNN and transfer learning have enhanced diagnosis from dermoscopic images, providing precise and timely detection. However, despite the progress made with hybrid models, many existing approaches still face challenges, such as limited generalization across diverse datasets, vulnerability to overfitting, and difficulty in capturing complex patterns. As a result, there is a growing need for more robust and effective hybrid models that integrate multiple architectures and advanced mechanisms to address these challenges. Therefore, this study aims to introduce a novel multi-architecture hybrid deep learning model called "RvXmBlendNet," which combines the strengths of four individual models: ResNet50 (R), VGG19 (v), Xception (X), and MobileNet (m), followed by "BlendNet" to signify their fusion into a unified architecture. The integration of these models is achieved through a synergistic combination of architectures, incorporating self-attention mechanisms using attention layers and adaptive content blocks. This study used the HAM10000 dataset to refine dermoscopic image preprocessing and enhance deep learning model accuracy. Techniques like OpenCV-based hair removal, min–max scaling, and adaptive histogram equalization were employed to improve image quality and feature extraction. A comparative study between the proposed hybrid "RvXmBlendNet" and individual models (CNN, ResNet50, VGG19, Xception, and MobileNet) demonstrated that "RvXmBlendNet" achieved the highest accuracy of 98.26%, surpassing other models. These results suggest that the system can facilitate earlier interventions, improve patient outcomes, and potentially lower healthcare costs by reducing the need for invasive diagnostic procedures.
Super-resolution reconstruction of hydrate-bearing CT images for microscopic detection of pore
Authors: Ye Wangquan , Chen Yu , Chen Liang , Li Chengfeng , Liu Shuo , Hou Guohua , Chen Qiang , Hu Gaowei , Sun Jianye , Zheng Ronger 
Published: September 2024

AbstractThe pore structure of marine natural gas-hydrate-bearing sediments is a key factor related to the physical properties of reservoirs. However, the resolution of micro-computed tomography (micro-CT) images is unsuitable for the analysis of pore structures in fine-grained sediments. In this regard, super-resolution (SR) reconstruction technology is expected to improve the spatial resolution of micro-CT images. We present a self-supervised learning method that does not require high-resolution datasets as input images to complete the training and reconstruction processes. This method is an end-to-end network consisting of two subnetworks: an SR network and a downscaling network. We trained on a self-built dataset of hydrate samples from three different particle sizes. Compared with typical methods, the SR results indicate that our method provides high resolution while improving clarity. In addition, it has the highest consistency with the liquid saturation method with the subsequent calculation of porosity parameters. This study contributes to the investigation of seepage and energy transfer in sediments containing natural gas hydrates, which is particularly important for the exploration and development of marine natural gas hydrate resources.
Predicting antibiotic resistance in Enterobacterales to support optimal empiric treatment of urinary tract infections in outpatient veterans
Authors: Brintz Ben J. , Madaras-Kelly Karl , Nevers McKenna , Echevarria Kelly L. , Goetz Matthew B. , Samore Matthew H. 
Published: September 2024

Abstract

Objective:
Bacterial resistance is known to diminish the effectiveness of antibiotics for treatment of urinary tract infections. Review of recent healthcare and antibiotic exposures, as well as prior culture results is recommended to aid in selection of empirical treatment. However, the optimal approach for assessing these data is unclear. We utilized data from the Veterans Health Administration to evaluate relationships between culture and treatment history and the subsequent probability of antibiotic-resistant bacteria identified in urine cultures to further guide clinicians in understanding these risk factors.

Methods:
Using the XGBoost algorithm, a retrospective cohort of outpatients with urine culture results and antibiotic prescriptions from 2017 to 2022 was used to develop models for predicting antibiotic resistance for three classes of antibiotics: cephalosporins, fluoroquinolones, and trimethoprim/sulfamethoxazole (TMP/SMX) obtained from urine cultures. Model performance was assessed using Area Under the Receiver Operating Characteristic curve (AUC) and Precision-Recall AUC (PRAUC)

Results:
There were 392,647 prior urine cultures identified in 214,656 patients. A history of bacterial resistance to the specific treatment was the most important predictor of subsequent resistance for positive cultures, followed by a history of specific antibiotic exposure. The models performed better than previously established risk factors alone, especially for fluoroquinolone resistance, with an AUC of .84 and PRAUC of .70. Notably, the models’ performance improved markedly (AUC = .90, PRAUC = .87) when applied to cultures from patients with a known history of resistance to any of the antibiotic classes.

Conclusion:
These predictive models demonstrate potential in guiding antibiotic prescription and improving infection management.
A novel approach for safe and automated implementation of far ultraviolet-C light decontamination in clinical areas
Authors: Memic Samir , Cadnum Jennifer L. , Osborne Andrew , Rutala William A. , Donskey Curtis J. 
Published: September 2024

Abstract
A novel wall-mounted far ultraviolet-C (UV-C) light technology providing automated delivery of far UV-C only when people are not present reduced methicillin-resistant Staphylococcus aureus in a patient room and equipment room. The safety feature that discontinues far UV-C output when people are detected was effective in preventing far UV-C exposure.
Predictors of postpandemic preparedness for special pathogens
Authors: Kuhnly Morgan M. , Adams Barker Caitlin M. , Stewart Kathleen O. , Kim Justin J. 
Published: September 2024

Abstract
In this survey of 31 hospitals, large metropolitan facilities had a 9.5-fold odds of reporting preparedness for special pathogens; hospitals with special pathogens teams had a 14.3-fold odds of reporting preparedness for special pathogens. In the postpandemic world, healthcare institutions must invest in special pathogen responses to maximize patient safety.
Local parameters of supercuspidal representations
Authors: Gan Wee Teck , Harris Michael , Sawin Will , Beuzart-Plessis Raphaël 
Published: September 2024

Abstract
For a connected reductive group G over a nonarchimedean local field F of positive characteristic, Genestier-Lafforgue and Fargues-Scholze have attached a semisimple parameter

${\mathcal {L}}^{ss}(\pi )$

to each irreducible representation

$\pi $

. Our first result shows that the Genestier-Lafforgue parameter of a tempered

$\pi $

can be uniquely refined to a tempered L-parameter

${\mathcal {L}}(\pi )$

, thus giving the unique local Langlands correspondence which is compatible with the Genestier-Lafforgue construction. Our second result establishes ramification properties of

${\mathcal {L}}^{ss}(\pi )$

for unramified G and supercuspidal

$\pi $

constructed by induction from an open compact (modulo center) subgroup. If

${\mathcal {L}}^{ss}(\pi )$

is pure in an appropriate sense, we show that

${\mathcal {L}}^{ss}(\pi )$

is ramified (unless G is a torus). If the inducing subgroup is sufficiently small in a precise sense, we show

$\mathcal {L}^{ss}(\pi )$

is wildly ramified. The proofs are via global arguments, involving the construction of Poincaré series with strict control on ramification when the base curve is

${\mathbb {P}}^1$

and a simple application of Deligne’s Weil II.
Linguistic synesthesia detection: Leveraging culturally enriched linguistic features
Authors: Zhao Qingqing , Long Yunfei , Jiang Xiaotong , Wang Zhongqing , Huang Chu-Ren , Zhou Guodong 
Published: September 2024

Abstract
Linguistic synesthesia as a productive figurative language usage has received little attention in the field of Natural Language Processing (NLP). Although linguistic synesthesia is similar to metaphor concerning involving conceptual mappings and showing great usefulness in the NLP tasks such as sentiment analysis and stance detection, the well-studied methods of metaphor detection cannot be applied to the detection of linguistic synesthesia directly. This study incorporates comprehensive linguistic features (i.e., character and radical information, word segmentation information, and part-of-speech tagging) into a neural model to detect linguistic synesthetic usages in a sentence automatically. In particular, we employ a span-based boundary detection model to extract sensory words. In addition, a joint model is proposed to detect the original and synesthetic modalities of the sensory words collectively. Based on the experiments, our model is shown to achieve state-of-the-art results on the dataset for linguistic synesthesia detection. The results prove that leveraging culturally enriched linguistic features and joint learning are effective in linguistic synesthesia detection. Furthermore, as the proposed model leverages non-language-specific linguistic features, the model would be applied to the detection of linguistic synesthesia in other languages.
Solid bases and functorial constructions for (p-)Banach spaces of analytic functions
Authors: Cheng Guozheng , Fang Xiang , Liu Chao , Lu Yufeng 
Published: September 2024

AbstractMotivated by new examples of functional Banach spaces over the unit disk, arising as the symbol spaces in the study of random analytic functions, for which the monomials $\{z^n\}_{n\geq 0}$ exhibit features of an unconditional basis yet they often don’t even form a Schauder basis, we introduce a notion called solid basis for Banach spaces and p-Banach spaces and study its properties. Besides justifying the rich existence of solid bases, we study their relationship with unconditional bases, the weak-star convergence of Taylor polynomials, the problem of a solid span and the curious roles played by c0. The two features of this work are as follows: (1) during the process, we are led to revisit the axioms satisfied by a typical Banach space of analytic functions over the unit disk, leading to a notion of $\mathcal{X}^\mathrm{max}$ (and $\mathcal{X}^\mathrm{min}$), as well as a number of related functorial constructions, which are of independent interests; (2) the main interests of solid basis lie in the case of non-separable (p-)Banach spaces, such as BMOA and the Bloch space instead of VMOA and the little Bloch space.
Lack of crucial information exacerbates barriers to mitigating human–elephant conflicts in rural Kenya
Authors: Von Hagen Lynn , Schulte Bruce A. , Steury Todd D. , Dunning Kelly , Githiru Mwangi , Zohdy Sarah , Lepczyk Christopher A. 
Published: September 2024

AbstractCrop foraging by African savannah elephantsLoxodonta africananegatively affects farmer livelihoods and support for conservation, yet affordable, sustainable and practical solutions remain elusive. To inform conservation priorities, our goal was to assess the hitherto little explored relationships between farmers’ views on agricultural damage and the socio-economic factors limiting their use of elephant deterrents. We tested our hypotheses associated with the demographic categories of age, education level, years spent farming, gender, exposure to information on deterrent methods, farm size, village and relevant combinations of these factors by surveying 206 respondents across six villages in rural Kenya and analysing the resulting data using an information theoretic approach. Respondents were almost four times more likely to use deterrents if exposed to the relevant information, and almost five times more likely to do so if they had secondary education as opposed to none. Farmers with a higher level of education were five times more likely to have received information on deterrents compared to those with no formal education. Participants who had not received information on deterrents were almost three times more likely to believe that they could implement deterrent methods. Respondents who stated that they could not implement deterrents overwhelmingly cited a lack of financial resources as the reason. Overall, we found that crucial information on reducing elephant crop foraging is not reaching the relevant stakeholders, and socio-economic factors such as education and exposure to information appear to limit uptake of protective measures. These insights are important for developing mitigation strategies and supporting the livelihoods of people affected by negative human–elephant interactions, and thus for effective elephant conservation. Our findings also have broader applications for practitioners seeking to understand barriers stakeholders face in their efforts to mitigate negative interactions with wildlife.
Examining contemporaneous and temporal associations of real-time suicidal ideation using network analysis
Authors: Kivelä Liia M. M. , Fried Eiko I. , van der Does Willem , Antypa Niki 
Published: September 2024

AbstractBackgroundSuicidal ideation arises from a complex interplay of multiple interacting risk factors over time. Recently, ecological momentary assessment (EMA) has increased our understanding of factors associated with real-time suicidal ideation, as well as those predicting ideation at the level of hours and days. Here we used statistical network methods to investigate which cognitive-affective risk and protective factors are associated with the temporal dynamics of suicidal ideation.MethodsThe SAFE study is a longitudinal cohort study of 82 participants with current suicidal ideation who completed 4×/day EMA over 21 days. We modeled contemporaneous (t) and temporal (t + 1) associations of three suicidal ideation components (passive ideation, active ideation, and acquired capability) and their predictors (positive and negative affect, anxiety, hopelessness, loneliness, burdensomeness, and optimism) using multilevel vector auto-regression models.ResultsContemporaneously, passive suicidal ideation was positively associated with sadness, hopelessness, loneliness, and burdensomeness, and negatively with happiness, calmness, and optimism; active suicidal ideation was positively associated with passive suicidal ideation, sadness, and shame; and acquired capability only with passive and active suicidal ideation. Acquired capability and hopelessness positively predicted passive ideation at t + 1, which in turn predicted active ideation; acquired capability was positively predicted at t + 1 by shame, and negatively by burdensomeness.ConclusionsOur findings show that systematic real-time associations exist between suicidal ideation and its predictors, and that different factors may uniquely influence distinct components of ideation. These factors may represent important targets for safety planning and risk detection.
Cognitive behavioral self-help interventions for individuals experiencing psychosis: a systematic review
Authors: Kruger Emily , Hall Laura , Martinez Anton P. , Bentall Richard P. 
Published: September 2024

AbstractLittle is known about the effectiveness of cognitive behavioral therapy (CBT) specific self-help for psychosis, given that CBT is a highly recommended treatment for psychosis. Thus, research has grown regarding CBT-specific self-help for psychosis, warranting an overall review of the literature. A systematic literature review was conducted, following a published protocol which can be found at: https://www.crd.york.ac.uk/prospero/export_record_pdf.php. A search was conducted across Scopus, PubMed, PsycInfo, and Web of Science to identify relevant literature, exploring CBT-based self-help interventions for individuals experiencing psychosis. The PICO search strategy tool was used to generate search terms. A narrative synthesis was conducted of all papers, and papers were appraised for quality. Ten studies were included in the review. Seven papers found credible evidence to support the effectiveness of CBT-based self-help in reducing features of psychosis. Across the studies, common secondary outcomes included depression, overall psychological well-being, and daily functioning, all of which were also found to significantly improve following self-help intervention, as well as evidence to support its secondary benefit for depression, anxiety, overall well-being, and functioning. Due to methodological shortcomings, long-term outcomes are unclear.
Challenges and Clinical Impact of Medical Search and Rescue Efforts Following the Kahramanmaraş Earthquake
Authors: Celikmen Mustafa Ferudun , Tatliparmak Ali Cankut , Tunaligil Verda , Yilmaz Sarper 
Published: September 2024

AbstractBackground:This study assesses the operational challenges and clinical outcomes encountered by a university-based Emergency Medical Team (EMT) during the medical search and rescue (mSAR) response to the February 2023 earthquakes in Kahramanmaraş, Turkey.Methods:In this observational study, data were retrospectively collected from 42 individuals who received mSAR services post-earthquake. The challenges were categorized as environmental, logistical, or medical, with detailed documentation of rescue times, patient demographics, injury types, and medical interventions.Results:In this mSAR study, 42 patients from 30 operations were analyzed and divided into environmental (26.2%), logistical (52.4%), and medical (21.4%) challenge groups. Median rescue times were 29 (IQR 28–30), 36.5 (IQR 33.75–77.75), and 30.5 (IQR 29.5–35.5) hours for each group, respectively (P = .002). Age distribution did not significantly differ across groups (P = .067). Hypothermia affected 18.2%, 45.5%, and 66.7% in the respective groups. Extremity injuries were most common in the medical group (88.9%). Intravenous access was highest in the medical group (88.9%), while splinting was more frequent in the medical (55.6%) and logistical (18.2%) groups. Hypothermia was most prevalent in the medical group (66.7%), followed by the logistical group (45.5%). Ambulance transport post-rescue was utilized for a minority in all groups.Conclusion:The study concludes that logistical challenges, more than environmental or medical challenges, significantly prolong the duration of mSAR operations and exacerbate clinical outcomes like hypothermia, informing future enhancements in disaster response planning and execution.
Receiving and adjusting to a diagnosis of ALS: A qualitative study with informal caregivers
Authors: Iseli Luzia M. , Poppe Christopher , Wangmo Tenzin 
Published: September 2024

AbstractObjectivesDiagnosis of amyotrophic lateral sclerosis (ALS) takes more than 1year from detection of first symptoms. The paper seeks to understand the ALS diagnostic process and adjustment from the perspective of informal caregivers.MethodsThe data stems from an interview study with 9 current and 13 bereaved informal caregivers of people with ALS in Switzerland. The interviews were analyzed using thematic analysis.ResultsWe identified 3 key themes pertaining to ALS diagnosis. In the first theme, we present the close involvement of informal caregivers in the “diagnosis journey.” Highlighted within this theme is the important role they play, which ultimately leads to diagnosis of ALS avoiding further delays. Second, we relay their perceptions on “diagnosis communication pitfalls” where they underlined empathy and planning from the part of medical professional, while communicating the terminal diagnosis of ALS. Participants’ reactions and adjustments post-ALS diagnosis are described in “the aftermath of diagnosis.” In this third theme, we highlight participants’ shock and their need to rethink overall life plans and roles in their family.Significance of the resultsDiagnosis communication that is clear, empathetic, and adjusted to the needs of the patients as well as their caregivers is critical. More work is needed to improve diagnosis communication for ALS patients. Receiving the diagnosis of ALS leads to complete changes in life of caregivers. It is therefore necessary that medical professionals provide adequate support that allows them to plan for their future.