bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protocol for the economic evaluation of paraprofessional-led case management and two brief culture-informed suicide prevention interventions for American Indian youth
Authors: Kemp Christopher G. , Goklish Novalene , Suttle Rosemarie , Minjarez Tina , Kaytoggy Cindy , Garcia Mitchell , Tessay Robin , Rock Heather , Haroz Emily E. , Stifter Meredith , Aldridge Luke A. , Barlow Allison , Cwik Mary 
Published: December 2024

Abstract

Background: Suicide is a leading cause of death among American Indian youth, reflecting the intergenerational consequences of colonization, historical trauma, racism, and the chronic underfunding of critical health and social services in Native communities. American Indian values, spiritualities, and cultural practices promote the physical, social, and emotional health of Native people, and there is a need for community-based case management approaches and culture-informed behavioral interventions that build from this strength. Cost and cost-effectiveness estimates are critical for policymakers in Tribal communities considering investing in such services.
Objectives: Our objective will be to estimate the cost and cost-effectiveness for community-based paraprofessionals to deliver three preventive services to American Indian youth (aged 10-29): case management, New Hope (a brief intervention to reduce immediate suicide risk) and Elders’ Resilience (a brief intervention incorporating Elders to increase connectedness, self-esteem, and cultural identity).
Methods: We will conduct an economic evaluation as part of a Sequential Multiple Assignment Randomized Trial in a rural, reservation-based American Indian community in the Southwest. A five-year time horizon, societal perspective, and 3% discount rate will be used. An ingredients-based approach will estimate fixed program costs (e.g., intervention development, shared overhead) and variable program costs (e.g., labor and intervention delivery). Additional costs to the participants and healthcare payer will be estimated. Data collection methods will include key informant interviews, activity logs, expenditure reports and records review, direct observation, and medical chart review. Total cost estimates for each service will be divided by the respective numbers of participants reached to estimate relative cost-efficiency. Primary and secondary outcomes will be quality-adjusted life years and suicidal ideation, respectively. Incremental cost effectiveness ratios will be estimated.
Discussion: We will develop much-needed estimates of the cost and cost-effectiveness of delivering community-based, paraprofessional-delivered case management and culture-informed suicide prevention interventions in a rural, reservation-based American Indian community in the Southwest. These estimates will fill a key gap for Tribal policymakers considering comparable services for their communities.
Trial Registration: Clinical Trials NCT03543865, June 1, 2018.
Rel2Graph: Automated Mapping From Relational Databases to a Unified Property Knowledge Graph
Authors: Zhao Ziyu , Liu Wei , French Tim ,   Michael Stewart1
Published: December 2024

Abstract

Although a few approaches are proposed to convert relational databases to graphs, there is a genuine lack of systematic evaluation across a wider spectrum of databases. Recognising the important issue of query mapping, this paper proposes an approach called Rel2Graph, an automatic knowledge graph construction (KGC) approach from an arbitrary number of relational databases. Our approach also supports the mapping of conjunctive SQL queries into pattern-based NoSQL queries. We evaluate our proposed approach on two widely used relational database-oriented datasets: Spider and KaggleDBQA benchmarks for semantic parsing. We employ the execution accuracy (EA) metric to quantify the proportion of results by executing the NoSQL queries on the property knowledge graph we construct, which aligns with the results of SQL queries performed on relational databases. Consequently, the counterpart property knowledge graph of benchmarks can be ensured to have high accuracy and integrity. The code and data will be publicly available. The code and data are available at github∗.
∗https://github.com/nlp-tlp/Rel2Graph
A Deep Learning Approach for Healthcare Insurance Fraud Detection
Authors: Shungube Precious Sihle , Bokaba Tebogo , Ndayizigamiye Patrick , Mhlongo Siyabonga , Dogo Eustice 
Published: December 2024

Abstract

Healthcare fraud is a global financial challenge affecting economic stability and trust in services, with traditional machine learning models struggling to accurately capture its complexity and adaptive nature. This study investigates the application of three deep learning (DL) models, which are artificial neural networks (ANN), convolutional neural networks (CNN) and long-short-term memory networks (LSTM) for healthcare fraud detection. This study used healthcare claim data, including patient demographics, claim amounts, diagnostic codes, and procedure types, to analyse healthcare service usage and identify fraudulent activity. To enhance the interpretability of these models, locally interpretable model-agnostic explanations (LIME) were used. The evaluation results demonstrated that the ANN was the best performer with an accuracy of 0.94, precision of 0.78, recall of 0.45, and F1-score of 0.57. While CNN excelled in accuracy, the LSTM was more effective in reducing false negatives. The LIME for ANN shows the prediction of a claim to be non-fraudulent with a high probability of 0.96, as opposed to a 0.03 probability of being fraudulent with ‘PotentialFraud', as a driving feature, the evaluation metrics show that it is good at correctly identifying fraudulent cases. This study highlights the efficacy of integrating deep learning models with explainable AI (XAI), contributing to the growing research body in healthcare insurance fraud detection.
CurrI2P: Inter- and Intra-Modality Similarity Curriculum Learning for Image-to-Point Cloud Registration
Authors: Lin Liwei , Lin Chunyu , Nie Lang , Huang Shujuan , Zhao Yao 
Published: December 2024

Abstract

Image-to-point cloud (I2P) registration aims to align 2D images and 3D point clouds within the same scene. However, existing methods neglect the differences in learning difficulties among different samples, failing to bridge the image-to-point cloud modality gap adequately. Moreover, the features of images or point clouds within the same modality are easily affected by various geometric transformations, which further increases the complexity of the registration task. To address these issues, we propose a similarity curriculum learning framework for I2P registration, termed CurrI2P, which not only effectively captures similarities between different data pairs but also gradually adapts the model to more complex data transformations. Specifically, we first present inter-modality similarity curriculum learning to progressively enhance cross-modality similarity to reduce inaccurate matches caused by coarse registration at the early training stage. In addition, we design intra-modality similarity curriculum learning, particularly targeting to learn invariant features of images or point clouds within the same modality under the geometric disturbance of increasing magnitude. In experiments, we incorporate CurrI2P into different baselines to validate the feasibility and achieve state-of-the-art (SoTA) performance on both KITTI and nuScenes datasets. The code is available at https://github.com/lin-liwei/CurrI2P.
Knowledge Fusion Guided Pre-training Non-intrusive Load Sparse Sample Recognition
Authors: Jiang Yanmei , Liu Lin , Liu Mingsheng 
Published: December 2024

Abstract

The deep learning technology can realize the rapid recognition of the non-intrusive load, but this technology relies on huge amount of the offline labeled sample for the model training, which increases the cost of the modeling. Due to the randomness of the daily electricity consumption in the users and the sparsity of the unknown load sampled data, the new unknown load sample models exist the low accuracy and the poor reliability. These problems seriously affects the promotion and application of the non-intrusive load identification (NILI) in the electric power industry. In the paper, we present a sparse sample recognition framework, namely KFG-DBiLSTM, to enhances the fusion feature representation ability while improves the knowledge transfer reliability. KFG-DBiLSTM uses the Ad-HW algorithm to detecting and denoising of the raw load data for improving the data availability. To learn more key features information and to enhance the representation interpretability, we propose a dual-layer Transformer network, which improve the fusion features extraction ability in the pre-training stage. By fusion the load knowledge features to train a DBiLSTM network as the load type recognizer for reducing the error rate of the model recognition effectively, which overcomes the bidirectional dependence of the load time series sampled data. To ensure the reliability of the model parameters fine-tuning and transfer, we present a weighted cosine similarity (WCS) measurement method, WCS can eliminate the difference of the load feature fusion and parameters transfer in the fine-tuning stage. A large number of the experiments on the REDD, UK-DALE, and RDSA datasets reveal that our method has a higher unknown load identification accuracy and the good stability. In the case of meeting certain accuracy, a small sample set is used to complete the fine-grained load identification, and this method has strong technical applicability in the smart grid.
Phase-Transition-Driven Reconfigurable Thermoelectric Logic in Correlated Electron Systems
Authors: Zhang Libo , Sun Xin , Xiao Kening , Wei Yingdong , Han Li , Zhang Kaixuan , Yang Yage , Wang Fang , Chen Xiaoshuang , Wang Lin , Hu Weida 
Published: December 2024

Abstract

Charge density waves (CDWs), as a hallmark of strongly correlated electronic systems in low-dimensional materials, exhibit collective quantum phenomena that enable phase-coherent electronic manipulation. In this work, we demonstrate a reconfigurable logic system based on CDW-driven phase transitions, tailored for terahertz optoelectronic applications. By precisely modulating metastable macroscopic quantum states through cooperative thermal, electrical, and optical stimuli, the device achieves deterministic switching between resistive and dissipationless states. Experimental results reveal exceptional performance, including a high current responsivity of 6.79 A/W, a noise equivalent power of 2.64 nW/Hz1/2, and an ultra-fast response time of 2.5 μs at 0.3 THz. The thermally mediated CDW transitions allow fine-tuning of device functionalities, integrating sensing, logic, and memory within a single architecture. This approach offers a paradigm shift by breaking away from conventional von Neumann architectures, addressing energy efficiency and latency bottlenecks through localized, in-sensor computation. Furthermore, our findings provide deep insights into the interplay of symmetry-breaking mechanisms, quantum coherence, and non-equilibrium dynamics in CDW systems, elucidating the underlying physical principles driving the device performance. The long-term retention of resistance states and robust phase stability under multi-field control demonstrate the feasibility of CDW-based devices for secure communication, cryptographic processing, and programmable optoelectronic logic. These results underscore the transformative potential of CDW-driven thermoelectric logic systems in advancing terahertz optoelectronic networks, while simultaneously broadening the understanding of correlated quantum phenomena in condensed matter physics.
Routine Electronic Mother-Infant Data (REMInD): a proof-of-concept Data to Care study to support retention in maternal HIV treatment and infant HIV testing in Cape Town, South Africa
Authors: Phillips Tamsin K. , Gomba Yolanda , Mogoba Pheposadi , Phelanyane Florence , Anderson Kim , Chi Benjamin H. , Clouse Kate , Davies Mary-Ann , Euvrard Jonathan , Knight Lucia , Myer Landon , Abrams Elaine J. 
Published: December 2024

Abstract

Data to Care (D2C) strategies – using routine data to facilitate identification and linkage back to care of people living with HIV who are not in care – have shown promise in high-income settings but received little attention in lower resourced or vertical HIV transmission prevention (VTP) contexts. In this proof-of-concept study, we monitored existing linked electronic medical records in near real-time to identify key gaps in postpartum VTP steps among 336 mothers living with HIV and their infants in Cape Town, South Africa (recruited March 2021 – April 2022). We attempted to confirm observed gaps through source data systems and telephonic tracing, and facilitated re-engagement in care where needed. There were 302 gaps observed in the routine data; 123 (41%) were false gaps and 179 (59%) were considered probable gaps (133 mother-infant pairs). Overall, 54 mothers (16%) did not link to HIV care within 12 weeks of delivery, 43 mothers (13%) linked to care but had a gap in ART dispensing by nine months postpartum, 25 infants (10%) did not have an HIV test around 10 weeks and 57 (17%) had no HIV test around 6 months of age. Only 100 of the probable gaps (56%) could be confirmed through telephonic tracing and, of those, only 47 were successfully re-linked to care. Mobility and clinic transfer, fear of stigma and employment-related challenges were commonly reported reasons for gaps in VTP steps. This study highlights that linked routine data sources linking mother-infant pairs across health facilities has the potential to streamline tracing efforts; however, implementation is challenging and, even when gaps are identified, re-engagement in care may be difficult. Further research is needed to combine D2C strategies with interventions addressing broader social and structural determinants of health, and to tailor D2C strategies to fit available resources and data sources in low-resource settings.
A Comparative Environmental and Economic Analysis of CFRP Recycling Processes Using Life Cycle Assessment and Life Cycle Costing
Authors: Vogiantzi Christina , Tserpes Konstantinos 
Published: December 2024

Abstract

The growing adoption of Carbon Fiber Reinforced Polymers (CFRPs) in advanced structural applications has emphasized the need for sustainable recycling methods to address environmental and economic challenges associated with end-of-life (EoL) management. While CFRPs offer exceptional specific mechanical properties, their thermosetting matrix complicates recycling efforts, often resulting in energy-intensive disposal or significant waste accumulation. In recent years, considerable advancements have been made in CFRP recycling, with three primary processes emerging: mechanical, thermal, and chemical recycling. Existing comparisons of these methods have focused on the mechanical performance of recovered fibers, yet their broader sustainability implications warrant further exploration. This study undertakes a comprehensive Life Cycle Assessment (LCA) and Environmental Life Cycle Costing (eLCC) analysis of four key recycling techniques: mechanical recycling, pyrolysis, solvolysis, and high-voltage fragmentation. The analysis encompasses the metrics of cumulative energy demand, global warming potential, damage assessment by the Recipe endpoint method, and cost. In the analysis, available data from the literature, process models, and experimental and manufacturing procedures were used. The study's findings emphasize that CFRP recycling methods significantly reduce energy consumption and carbon footprints compared to the production of virgin fibers. Among the recycling techniques evaluated, mechanical recycling and high-voltage fragmentation demonstrate the lowest environmental impact, contributing positively to human health and the preservation of natural resources. The results enable the informed selection of sustainable and cost-effective CFRP recycling processes, supporting advancements in sustainable manufacturing and end-of-life product management.
Primary Care Services use as a Factor in Glycemic and Cholesterol Management in Type 2 Diabetes: A Retrospective Study
Authors: Ibrahim Eiman , Amoateng Magdelene , Domenicano Ilaria , Mensah Edward , Werner Linda , Thomas Aiswarya 
Published: December 2024

Abstract

Introduction: We aimed to evaluate the association among regular primary care visits, hemoglobin A1C (HbA1C) and low-density lipoprotein (LDL) levels in patients with type 2 diabetes mellitus.
Methods: We randomly sampled data from 200 patients’ electronic medical records. Mann–Whitney and chi-square tests were used to investigate the association between glycemic control lipid profile and the number of patient visits.
Results:The mean age of the participants was 61.78 years and the average body mass index was 34.5 kg/m2. Females constituted 61.79% of participants. The predominant race seen at the clinic was Black (43.8%), followed by White (42.69%). Patient adherence to scheduled visits was not statistically significantly associated with either HbA1C or LDL (chi-square = 1.1, p-value = 0.29 for HbA1c and chi-square = 1.12, p-value = 0.99 for LDL).
Conclusion: In the sample studied, no statistically significant association existed between adherence to primary care visits and either HbA1C or LDL levels. This data can guide physicians to invest on favoring high-quality primary care contact rather than high frequency of visits.
КУЛЬТУРНАЯ ПАМЯТЬ КАК ПРЕДМЕТФИЛОСОФСКОГО ОСМЫСЛЕНИЯ
Authors: Буллер А. , Линченко А.А. 
Published: December 2024

В статье предпринимается попытка философской концептуализации культурной памяти. Показано, что современная критика cultural memory studies связана с развитием конкретных исследований культурной памяти, что способствует как увеличению разнообразия тематик и жанров исследований, так и децентрализации методологии исследований культурной памяти. Используя идеи философской герме-невтики, авторы рассматривают проблему культурной памяти из перспективы философии культуры. Представлен философский анализ общепринятого тезиса о не-соизмеримости различных типов культурной памяти и мемориальных культур.
The article deals with an attempt of philosophical conceptualisation of cultural memory. It is shown that modern criticism of cultural memory studies is associated with the development of the specific studies of cultural memory, which contributes both to increase in the diversity of subjects and genres of research, and to the decentralization of the methodology for the study of cultural memory. On the basis of hermeneutical methodology, the problem of cultural memory is examined from the perspective of the philosophy of culture. The authors attempt to philosophize the generally accepted thesis of the incommensurability of various types of cultural memory and cultures of remembrance.
АНТИЧНЫЕ ТЕКСТЫ IN STATU QUOИСТОКИ ЖАНРА ПЕДАГОГИЧЕСКОЙ АНТОЛОГИИКАК ФОРМЫ ИСТОРИЧЕСКОЙ ПАМЯТИ
Authors: Пичугина В.К. 
Published: December 2024

В статье рассматриваются истоки антологического принципа в античных представлениях о памяти. Античные авторы часто брали на себя роль составителей-комментаторов, маневрируя между желанием сделать чужие тексты доступными и желанием манипулировать ими в рамках конкретной культуры. Антология как форма исторической памяти возникает в пространстве между благоговейностью и бесцеремонностью отношения к текстам. Это пространство оформилось в античном прошлом и продолжает существовать в современном настоящем, где также существуют санкционированные и несанкционированные воспоминания и модели памяти, которые репрезентируются с педагогическим умыслом.
The article considers the origins of anthological principle in the ancient notions of memory. Ancient authors often took on the role of compilers-commentators, maneuvering between the desire to make other people's texts accessible and the desire to manipulate them within a particular culture. If we define anthology as a form of historical memory, then we must admit that it arises in the space between reverence and unceremoniousness of the relation to texts. This space took shape in the ancient past and continues to exist in the modern present, where there are also sanctioned and unauthorized memories and memory models that are represented with pedagogical intent.
РУССКО-ЯПОНСКАЯ ВОЙНА 1904–1905 гг.И СОВЕТСКИЕ ПИСАТЕЛИ: РАБОТА НАД ПРОШЛЫМ
Authors: Антипин Н.А. 
Published: December 2024

Русско-японская война 1904–1905 гг. стала одной из тем для советской художественной литературы. По меньшей мере, шесть крупных произведений было посвящено отдельным эпизодам кампании. Автор исследует мотивы, побудившие писателей обратиться к теме Русско-японской войны, влияние власти и идеологии на литературный процесс, отклики читателей на художественные тексты.
The Russian-Japanese War of 1904-1905 became one of the themes for Soviet fiction. At least six major works were devoted to individual episodes of the campaign. The article explores a range of issues related to the motivations of writers who prompted them to turn to the theme of the Russo-Japanese War, the influence of power and ideology on the literary process, and the readers' responses to artistic texts.
ТРАДИЦИИ ПРОПОВЕДИ В АКТОВЫХ РЕЧАХ ПРОФЕССОРОВУНИВЕРСИТЕТОВ РОССИЙСКОЙ ИМПЕРИИ(ВТОРАЯ ПОЛОВИНА XVIII – ПЕРВАЯ ТРЕТЬ ХІХ ВЕКА)
Authors: Посохов С.И. 
Published: December 2024

Автор рассматривает проповедь как основу, на которой в последующем происходило конструирование других текстов культуры. В данном случае цель исследования – изучение влияния традиций проповеди на речи профессоров на торжественных актах в университетах Российской империи второй половины XVIII – первой трети ХІХ в. Сравнение осуществляется по таким параметрам как целевая аудитория, структура, тематика, риторика, аргументация, авторитетный топос. Констатируется значительное влияние традиций проповеди на актовые университетские речи. Однако в целом можно утверждать, что в актовых речах профессоров устоявшиеся традиции соединились с риторическими и идейными новациями.
The author views sermon as a foundation for other cultural texts. In this case, the study is focused on the influence of the tradition of preaching on professorial addresses delivered at University ceremonial occasions in the late 18th – early 19th cc. the following parameters have been compared: intended audience, structure, topics, rhetoric, arguments, topoi. It has been concluded that sermons influenced university orations considerably. However, it can be argued that in the professorial addresses established traditions co-existed with rhetorical and ideological innovations.