bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Reinforcement Learning for Dial-A-Ride Problem
Authors: YILDIZ Özge ASLAN , SARIÇİÇEK İnci , YAZICI Ahmet 
Published: October 2024

Abstract

Intelligent transportation systems are an essential issue within the scope of smart mobility. The Dial-a-Ride problem provides a solution integrated with intelligent transportation technologies to enable individuals to use public transportation systems effectively and efficiently. This problem involves determining the most effective and efficient routes using limited vehicles and resources to meet the demands of individuals in a specific region who need to travel to various destinations. Logistics service providers require systems that can deliver optimal solutions to these combinatorial problems within a reasonable time. Recently, there has been a significant increase in the use of artificial intelligence optimization algorithms such as meta-heuristics to solve such problems. However, to the best of our knowledge, no studies have explored the use of reinforcement learning for solving the DARP. In this study, the transformer-based deep reinforcement learning method is proposed to solve the Dial and Ride problem for a single service vehicle. The proposed method is compared against four different metaheuristic methods and demonstrates superior performance over them. Additionally, the proposed method is tested on a real-world scenario generated in the Buyukdere neighborhood of Eskisehir. The results demonstrate that the proposed method make it possible to solve the problem within a reasonable time. This study confirms that reinforcement learning can effectively address Dial-a-Ride Problems.
Levels of circulatory branched-chain amino acids are associated with dietary regimen. A cross- sectional analysis
Authors: Liu Keyuan , Borreggine Rebecca , Gallart-Ayala Hector , Ivanisevic Julijana , Marques-Vidal Pedro 
Published: October 2024

Abstract

Background & aims:
Higher levels of circulatory branched chain amino acids (BCAA, isoleucine, leucine, and valine) are associated with a higher risk of diabetes and cardiovascular diseases. Diet is the main source of BCAA, but previous studies have shown conflicting results on the influence of diet on circulatory BCAA concentration. We evaluated the association between BCAA concentration and diet in a large population-based sample.
Methods
Data from 2159 participants (58.2% women, mean age 53.4 ± 8.6years) was included. Dietary intake was assessed by questionnaire and included 91 individual foods and 15 different nutrients. BCAA concentrations were measured by stable isotope dilution liquid chromatography-mass spectrometry (LC-MS) assay.
Results
The circulatory BCAA levels were higher in men than in women (250.2 ± 45.2 vs. 207.9 ± 36.1, 136.0 ± 24.4 vs 106.3 ± 17.4, 63.6 ± 13.0 vs 48.1 ± 9.2 µmol/L, p < 0.001). BCAA levels were negatively associated with vegetal protein intake (multivariable-adjusted beta: -0.051 and − 0.063 for Isoleucine and Valine, respectively, p < 0.05) and dairy product (-0.037, -0.063 and − 0.038, respectively, p < 0.05) consumption. The opposite trend was observed for consumption of meat and meat-derived products, but the associations did not reach statistical significance. Of the 15 different nutrients, 13 showed a significant correlation with BCAA. Specifically, total protein, total carbohydrates, polysaccharides, saturated fat (SFA), and total fat all showed significant positive association with BCAA, while total fibre, monosaccharides, and calcium showed significant negative correlations with BCAA.
Conclusions
Levels of circulatory in humans are negatively associated with plant protein and positively associated with polysaccharides, total fat, and animal protein. The associations are gender specific.
Replication Capacity and Susceptibility of Nirmatrelvir-Resistant Mutants to Next-Generation Mpro Inhibitors in a SARS-CoV-2 Replicon System
Authors: Lo Chieh-Wen , Kariv Omri , Hao Chenzhou , Gammeltoft Karen Anbro , Bukh Jens , Gottwein Judith , Westberg Michael , Lin Michael Z , Einav Shirit 
Published: October 2024

Abstract

There is an ongoing need to expand the anti-SARS-CoV-2 armamentarium to include agents capable of suppressing replication of drug-resistant mutants emerging during monotherapy with approved direct-acting antivirals. Using a subgenomic SARS-CoV-2 replicon system, we studied the RNA replication capacity of nirmatrelvir (NTV)-resistant mutants and their susceptibility to next-generation Mpro inhibitors, including ibuzatrelvir (ITV), ensitrelvir (ETV), and ML2006a4. Our findings revealed that E166V Mpro mutants reduced viral RNA replication, whereas other Mpro mutations retained or increased the replication capacity, suggesting the potential of the latter to dominate under NTV selective pressure. Except for having an advantage against E166A mutants, ITV largely showed the same mutational sensitivity as NTV. ETV was more effective than NTV against E166V mutants but less effective against S144A, E166A, and L167F mutants. ML2006a4 demonstrated the most effective suppression across most mutants (S144A, E166V, S144A+L50F, E166A/V+L50F, L167F+L50F, and E166A+L167F+L50F). Thus, ML2006a4 represents an attractive investigational candidate against clinically relevant NTV-resistant SARS-CoV-2 mutants.
Enhanced anomaly detection and normal behaviour power curve modelling in wind farm SCADA data: A hybrid approach
Authors: Mehmood Zahid , Wang Zhenyu 
Published: October 2024

Abstract

To achieve optimal performance and reduce the maintenance cost of wind turbines, anomaly detection and power curve modelling are crucial. The supervisory control and data acquisition (SCADA) system provides continuous and real-time data insights by collecting different wind-turbine operational parameters. This study introduces a novel strategy combining the strengths of Isolation Forest (iForest) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to identify and isolate anomalous data. The hybrid iForest-DBSCAN model processes enormous amounts of SCADA data to detect outliers and anomalies of wind turbines under different operating conditions. By utilizing normal data with minimum anomalies, normal behavious power curves (NBPC) were modelled using a robust Locally Estimated Scattered Smoothing (LOESS) technique. Robust power curves allow us to compare the performances of wind turbines and ensure an optimized function with minimum maintenance. Different datasets validated the proposed method with higher accuracy and fewer computational resource requirements than traditional methods. From the two wind farms, the iForest-DBSCAN model identified the datasets effectively while successfully generating NBPC with a 95% confidence interval. This study demonstrated the effectiveness of cutting-edge data-driven models and techniques for optimizing the efficiency and performance of wind farms.
The Health Effects of Being Unhoused and its Association with Congestive Heart Failure
Authors: Novin Niloufar , Jones Stephen Scott , Chiuzan Codruta , Zhang David , Yu Pey-Jen , Coleman Kristie , Leon Luis David Olivera , Parikh Nisha , Cohn Elizabeth 
Published: October 2024

Abstract

Unstable housing is a critical social determinant of health (SDOH). Prior studies of homelessness and congestive heart failure (CHF) have looked primarily at the association between socioeconomic status and hospitalization. The association between unstable housing and the development of CHF has not been fully investigated.
We examined data from 4,408 participants with annual household income below $50,000 in the All of Us Research Program, a national cohort study enriched for individuals underrepresented in biomedical research. Within the inceptive survey, participants were asked if they were worried or concerned about not having a place to live in the past 6 months. We assessed the association between this self-reported housing concern and CHF occurrence, finding that individuals with low income and unstable housing had a 44% higher risk of CHF diagnosis than those with stable housing (HR 1.44; 95%CI 1.03-2.01). The increased risk remained significant after adjusting for cardiovascular risk factors as potential confounders (HR 1.73; 95%CI 1.19-2.51) such as cholesterol, history of diabetes, and older age categories aged 55-64 years, 65-74 years, 75 years and older.
Compared with men, women in the study were estimated to be at lower risk of CHF diagnosis (HR 0.52; 95%CI 0.38-0.70) with incidence at 5.3% for men and 2.9% for women. We found that participants with unstable housing had a higher risk of developing CHF compared to those with stable housing, highlighting the potential health impact of this healthcare disparity.
Capturing the attenuating influence of the Three Gorges Dam on downstream sediment loads using artificial neural networks
Authors: Zhang Lei , Song Xiaolong , Wang Dayu , Huang Hai , Guan Jianzhao 
Published: October 2024

ABSTRACT

River sediment dynamics have been significantly altered by dam constructions, with the Three Gorges Dam (TGD) on the Yangtze River being a prominent example. This study aims to quantitatively assess the attenuating impact of TGD operations on downstream sediment discharge using artificial neural network (ANN) models. Seven ANN models were developed for stations along the middle and lower Yangtze River, trained on measured water and sediment data. The models effectively captured the relationships between upstream inputs and downstream outputs. Results revealed that variations in sediment discharge at each station were predominantly influenced by changes in sediment input from its immediate upstream section, rather than by changes in water discharge. This suggests that the TGD's impact on downstream sediment transport was primarily due to its sediment trapping efficiency, rather than alterations in the hydrological regime. The influence diminished gradually farther downstream, attributed to tributary contributions and sediment transport dynamics. ANNs, adept at handling input uncertainties, underscore the importance of boundary conditions; the integration of data-driven and physics-based models illuminates sediment dynamics in regulated rivers. This approach provides insight into dam management implications and sediment transport processes.
Sanitation ladder in rural and urban India: can subsidy from the Swachh Bharat Mission ensure transition to safely managed toilets?
Authors: Bose Debasree , Dutta Arijita 
Published: October 2024

ABSTRACT

The Swachh Bharat Mission, globally the biggest public programme to support sanitation, has focused on subsidised construction of household toilets in rural areas, while aiming for solid waste disposal and behavioural changes in urban areas. In spite of that, India witnesses a huge gap from the SDGs related to usage of safely managed sanitation associated with more environment- responsive technology and hygiene management. The hierarchical sanitation ladder identifies fivecategories of toilets, namely, safely managed, basic, limited, unimproved, and open defecation. This study attempts to contribute to the existing literature by locating the empirical estimation of the sanitation ladder in India across both rural and urban settings, using nationally representative unit-level National Sample Survey data. Results find that only 38% of urban and 6% of rural households in India use safely managed toilets. Also, using logistic regression, the study posits that receiving subsidy for toilet construction can significantly improve usage of safely managed toilets along the ladder only among the poorest urbanclass and the factor is generally more potent in rural areas. The findings identify that there is hardly any benefit in subsidizing the middle-income class and hence highlight a need to redesign the subsidy-driven sanitation policy.
Guiding Therapeutics: Lipid Labyrinths and Nanostructures for Enhanced Drug Delivery
Authors: Kushwaha Swatantra K.S. , Khare Shruti , Mishra Amit 
Published: October 2024

Abstract:
Nanostructured lipid carriers (NLCs) offer a breakthrough platform for drug therapy,
surpassing traditional limitations and delivering exceptional performance. Among various nanoparticulate
systems, lipid nanoparticles stand out as one of the most promising options for medication
delivery. NLCs stand out due to their solid matrix at ambient temperatures, setting them apart from
conventional lipid-based carriers such as nanoemulsions and solid lipid nanoparticles. This paper
thoroughly explores the makeup, classification, components, and various methods of preparing
NLCs, based on extensive research findings. It emphasizes their numerous advantages, such as improved
stability, minimal toxicity, extended storage capability, increased drug-loading capacity, and
compatibility with biological systems. The review provides insights into the advantages and limitations
of each method. Exploring the intricacies of drug loading and release, the review also addresses
strategies to bolster NLCs’ stability. Moreover, it provides a detailed summary of both laboratory-
based and animal studies demonstrating the efficacy of NLCs carrying cytotoxic drugs, particularly
emphasizing their promise in targeted drug delivery to the brain. As the next-generation lipid
nanocarriers, NLCs are composed of physiological and biocompatible lipids, rendering them novel
pharmaceutical formulations. These colloidal drug delivery systems boast a solid lipid matrix with
nanosized structures, offering superior drug loading capacity, physical stability, and bioavailability
compared to conventional lipid nanoparticles. Several techniques, including high-pressure homogenization,
microemulsion, solvent evaporation, and melt emulsification, add to the flexibility of
nanostructured lipid carriers. Additionally, their exterior can be altered using coatings such as polyethylene
glycol, chitosan, or antibodies to improve targeting ability and stealth characteristics. By
elucidating the promising role of NLCs across diverse drug delivery systems, this review stimulates
interest in their potential applications. It underscores the significance of understanding the structure,
content, multiple formulation procedures, and characterization of NLCs, which are pivotal aspects
for establishing stable drug delivery systems.
Task-Specific Transformer-Based Language Models in Health Care: Scoping Review
Authors: Cho Ha Na , Jun Tae Joon , Kim Young-Hak , Kang Heejun , Ahn Imjin , Gwon Hansle , Kim Yunha , Seo Jiahn , Choi Heejung , Kim Minkyoung , Han Jiye , Kee Gaeun , Park Seohyun , Ko Soyoung 
Published: October 2024

Background
Transformer-based language models have shown great potential to revolutionize health care by advancing clinical decision support, patient interaction, and disease prediction. However, despite their rapid development, the implementation of transformer-based language models in health care settings remains limited. This is partly due to the lack of a comprehensive review, which hinders a systematic understanding of their applications and limitations. Without clear guidelines and consolidated information, both researchers and physicians face difficulties in using these models effectively, resulting in inefficient research efforts and slow integration into clinical workflows.

Objective
This scoping review addresses this gap by examining studies on medical transformer-based language models and categorizing them into 6 tasks: dialogue generation, question answering, summarization, text classification, sentiment analysis, and named entity recognition.

Methods
We conducted a scoping review following the Cochrane scoping review protocol. A comprehensive literature search was performed across databases, including Google Scholar and PubMed, covering publications from January 2017 to September 2024. Studies involving transformer-derived models in medical tasks were included. Data were categorized into 6 key tasks.

Results
Our key findings revealed both advancements and critical challenges in applying transformer-based models to health care tasks. For example, models like MedPIR involving dialogue generation show promise but face privacy and ethical concerns, while question-answering models like BioBERT improve accuracy but struggle with the complexity of medical terminology. The BioBERTSum summarization model aids clinicians by condensing medical texts but needs better handling of long sequences.

Conclusions
This review attempted to provide a consolidated understanding of the role of transformer-based language models in health care and to guide future research directions. By addressing current challenges and exploring the potential for real-world applications, we envision significant improvements in health care informatics. Addressing the identified challenges and implementing proposed solutions can enable transformer-based language models to significantly improve health care delivery and patient outcomes. Our review provides valuable insights for future research and practical applications, setting the stage for transformative advancements in medical informatics.
Virtual Reality–Based Exposure With 360° Environments for Social Anxiety Disorder: Usability and Feasibility Study
Authors: Ernst Mathias , Bouchard Stéphane , Andersen Tonny , Orskov Per Trads , Tarp Kristine , Lichtenstein Mia Beck 
Published: October 2024

Background
Social anxiety disorder (SAD) is a long-term and overwhelming fear of social situations that can affect work, school, and other daily activities. Although cognitive behavioral therapy is effective, few seek treatment, and many who do start often drop out. This may be due to the component of exposure inherent to cognitive behavioral therapy, where the patient confronts feared stimuli outside the therapist’s office, which they otherwise try to avoid. As an alternative, research has explored the effectiveness of virtual reality (VR)–based exposure therapy with promising results. However, few studies have investigated the feasibility of VR tools using mixed methodologies before assessing their efficacy.

Objective
This study aims to assess the usability, feasibility, and presence of four 360° virtual environments and whether these were able to evoke anxiety in patients with SAD.

Methods
A total of 10 adult participants with SAD and 10 healthy controls were recruited for 1 experimental session (age range 21-32 y; 12/20, 60% male participants). Questionnaire and interview data were collected and analyzed. A mixed methods triangulation design was applied to analyze and compare the data.

Results
Participants with SAD experienced increased anxiety when exposed to VR, and environments were considered relevant and useful as an exposure tool. Participants with SAD reported significantly higher average anxiety levels (P=.01) and peak anxiety levels (P=.01) compared with controls during exposure; however, significant differences in anxiety when accounting for baseline anxiety levels were only found in 2 of 4 environments (P=.01, P=.01, P=.07, and P=.06). While presence scores were acceptable in both groups, participants with SAD scored significantly lower than controls. Qualitative analyses highlight this finding within the SAD group, where some participants experienced presence reduction due to being observed while in VR and in situations with reduced interaction in VR.

Conclusions
VR exposure with 360° videos seems to be useful as a first step of exposure therapy for patients with SAD. Future exploration in the clinical application of VR-based exposure for SAD, as well as means of increasing presence within the virtual environments, may be useful.
Incidence of unexpected condylar displacement following comprehensive orthodontic treatment in adults
Authors: Jang Hosik , Lee Ji-Hyun , Nguyen Tung , Kim Kyung-Ho , Chung Chooryung J. 
Published: October 2024

ABSTRACT

Objectives
To evaluate the incidence and pattern of unexpected/excessive condylar displacement after comprehensive orthodontic treatment in adults.

Materials and Methods
Adult patients (age ≥18 years) who underwent comprehensive orthodontic treatment with pre-(T1) and post-treatment (T2) cone beam computed tomography scans were consecutively collected within an orthodontic cohort (N = 291). T1 and T2 CBCTs were superimposed three-dimensionally (3D) and condylar displacement was estimated by the 3D changes of condylar neck point (CdN) between T1 and T2 (ΔCdN). Participants with excessive condylar displacement (ΔCdN &gt;1 mm) were classified as condylar displacement (+) and otherwise as displacement (−). The incidence and pattern of condylar displacement, association with factors such as sex, age, skeletal relationship, extraction pattern, treatment duration, history of temporomandibular joint disorder, and presence of condylar resorption with the final occlusal outcome were investigated.

Results
The incidence of unexpected condylar displacement &gt;1 mm in the adult orthodontic cohort was 6.2%. Females (vs males; OR: 9.07; [95% CI: 1.19–69.23]) and Skeletal Class II (vs Classes I and III; OR: 4.57 [95% CI: 1.58–13.20]) demonstrated significantly higher odds of unexpected condylar displacement (P &lt; .05). Condylar resorption was not evident in participants with condylar displacement and did not interfere with the final orthodontic outcome.

Conclusions
Unexpected 3D condylar displacement exceeding 1 mm was noted in approximately 6% of the adult orthodontic patient cohort. However, the condylar displacement per se was not associated with condylar resorption and did not cause clinical concerns.
Maternal Diabetes and Cardiac Left Ventricular Structure and Function in the Infant: A Copenhagen Baby Heart Study
Authors: Ghouse Jonas , Hansson Magdalena , Vøgg Ruth Ottilia B. , Sillesen Anne-Sophie , Pærregaard Sofie , Raja Anna Axelsson , Vejlstrup Niels , Frikke-Schmidt Ruth , Øyen Nina , Kulkarni Aparna , Jensen Magnus T. , Jørgensen Finn Stener , Sundberg Karin , Petersen Olav B. , Wohlfahrt Jan , Damm Peter , Olesen Morten Salling , Mathiesen Elisabeth R. , Iversen Kasper , Bundgaard Henning , Boyd Heather A. 
Published: October 2024

OBJECTIVE
Prenatal exposure to maternal diabetes is associated with an increased risk of offspring heart defects. We evaluated associations with subtle infant cardiac changes.

RESEARCH DESIGN AND METHODS
In a cohort of 25,486 infants with transthoracic echocardiography within 60 days of birth, we investigated associations between maternal preexisting diabetes and gestational diabetes mellitus (GDM) and infant left ventricular (LV) structural and functional parameters, using linear regression to estimate adjusted mean differences (aMDs) between groups.

RESULTS
Infants exposed to maternal preexisting diabetes (n = 198) had thicker LV posterior walls (aMD 0.19 mm; 95% CI 0.11, 0.27), smaller LV internal diameters in systole (aMD −0.27 mm; 95% CI −0.45, −0.18) and diastole (aMD −0.37 mm; 95% CI −0.59, −0.09), reduced stroke volumes (aMD −0.36 mL; 95% CI −0.61, −0.11), and increased heart rates (aMD 3.14 bpm; 95% CI 1.10, 6.18) and mitral valve early peak velocities (aMD 2.17 cm/s; 95% CI 0.31, 4.04) than unexposed infants (n = 24,639). Infants born to mothers with GDM (n = 649) had significantly smaller LV internal diameters in systole (aMD −0.13 mm; 95% CI −0.22, −0.03) and similar structural and functional changes as children exposed to preexisting diabetes, albeit with smaller nonsignificant aMDs. Higher third-trimester HbA1c levels were associated with smaller LV internal diameters and stroke volumes in infants exposed to preexisting diabetes and with lower heart rates in infants exposed to GDM.

CONCLUSIONS
Maternal preexisting diabetes and, to a lesser extent, GDM were associated with changes in infant LV structure and function.