bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deformed Shape Prediction of Knitted Fabrics at the Stitch Level Based on Deep Learning
Authors: Wakamatsu Hidefumi , Nara Hikaru , Iwata Yoshiharu 
Published: August 2024

Abstract
Due to the global focus on sustainability in recent years, reducing the mass waste of clothing has become one of the important issues. A wearing simulator is thought one solution to such an issue because there is no need to stock large quantities of clothing in stores for trying on. However, conventional wearing simulators cannot accurately reproduce knitted products because prediction of their behavior at the stitch level is very time-consuming. Therefore, in this study, a method is proposed to predict the knitted fabric shape at the stitch level based on deep learning. To use deep learning, it is necessary to prepare large and diverse datasets for training. So, a procedure to efficiently generate such datasets is proposed considering the characteristics of stitches in deformed fabrics at first. Next, a shape predictor of each stitch is constructed with neural networks and learned. Then, the predictor can derive the stitch shape immediately when the boundary conditions of the stitch are given. Finally, by optimizing the boundary conditions of all stitches in a knitted fabric, the deformed shape of the fabric at the stitch level can be predicted.
Designing a Mobile Manipulator and Motion Planning for Autonomous Navigation With A* and Q-Learning Algorithms
Authors: Kaimujjaman Md. , Nishi Tatsushi , Fujiwara Tomofumi , Liu Ziang 
Published: August 2024

Abstract
Mobile manipulators have a crucial role in large manufacturing industries, production houses and retailer shops. Although fixed manipulator arms are very familiar in industries and production houses, a manipulator arm mounted on a movable robot equipped with the feature of autonomous navigation is still unfamiliar in this age. In this research, we propose an autonomous navigation method with A* and Q learning algorithm for a 6-DOF manipulator robot arm that is mounted on a movable 2-wheeled robot and the robot can find its path autonomously in a dynamic environment where knowledge of the environment was not known to the robot previously. The robot scans its surroundings with laser scanners and generates a map of its environment in ROS. The robot’s ability to move from its current location to a desired destination while avoiding obstacles and optimizing its trajectory depends heavily on its motion planning. For motion planning of the manipulator robot graph based and reinforcement learning based algorithms can be integrated. Incorporation of these algorithms helps the manipulator robot to find its path to a known or unknown environment. The result demonstrates the environment map generation using laser scans in RViz and applying A* and Q-Learning algorithms the robot finds its path to move from its initial state to its goal state on a generated map.
Investigation of Localization and Posture Accuracy of AMR During Indoor Mapping Using SLAM With LiDAR and Camera Technology
Authors: Omi Yasuaki , Sasa Hibiki , Matsui Tomoya , Kato Daiki , Nakagawa Masao , Hirogaki Toshiki , Aoyama Eiichi 
Published: August 2024

Abstract
To cope with variable types and quantities of production in factories and a wide variety of orders in distribution centers, the demand for autonomous mobile robots (AMRs), which are not restricted by guide rails, is increasing in place of automated guided vehicles (AGVs). Accurate localization is necessary to realize a highly efficient AMR transport system, and accurate posture control is necessary for cooperative operation with a manipulator on AMR. To realize this, it is important to investigate how AMR changes its localization and posture accuracy while operating, and to correct its position and posture. In this study, we tracked the actual position of an AMR using an overhead camera while the AMR was operating, and examined the accuracy of the AMR’s localization and posture sequentially when the course geometry was changed. It was found that the reflected light was weak in the areas where the incident angle of infrared rays was large, and the areas were lost on the map, which affected the accuracy of localization. A linear relationship was observed between the posture estimation error and angular velocity, and the accuracy could be improved by modifying the posture estimates using this relationship. The accuracy of posture estimation decreased when the AMR turned, which affected the accuracy of localization.
Bearing Remaining Useful Life Prediction Using Personalized Soft Aggregation in Federated Learning
Authors: Chen Xi , Wang Hui , Lu Siliang , Yan Ruqiang 
Published: August 2024

Abstract
Data-driven bearing prognostic methods have achieved significant success, but existing methods often rely on a single data resource, which overlooks the practical scenario in industrial settings where condition monitoring data is usually distributed across multiple locations and generated under diverse operating conditions. To address this issue, this paper proposes a bearing remaining useful life (RUL) prediction method using personalized soft aggregation in federated learning, called PSA-FL. The proposed method involves a central server and multiple clients, where each client possesses monitoring data collected under a specific working condition. Specifically, clients conduct local training of their models and upload them to the central server. The server then uses the personalized soft aggregation algorithm to create an ensemble model for each client, taking advantage of the aggregated degradation features contained in heterogeneous data scenarios. Subsequently, the ensemble model is returned to each client for further rounds of local training. By iteratively repeating the process of local training and personalized soft aggregation, each client obtains its personalized prognostic model. Experiments with bearing data show that the PSA-FL method is effective in RUL prediction tasks. Additionally, the PSA-FL method demonstrates inherent robustness by successfully limiting client drift in real-world settings.
Two new species of the mite family Parholaspididae Evans (Acari: Mesostigmata) from China
Authors: Zhang Shuo , Shen Wei Xing , Wang Yi Zhuo , Jia ChunYan , Wang Hao Ran , Xie Li Xia , Yan Yi 
Published: August 2024

Two new species of mites belonging to the family Parholaspididae are described based on female specimens from China, Gamasholaspis transaduncus Zhang, Xie & Yan sp. nov. from Guangdong Province, and Neparholaspis taishanensis Zhang, Xie & Yan sp. nov. from Shandong Province. A key to world species of the genus Gamasholaspis is provided.
Sugar-Sweetened Beverages and Adverse Human Health Outcomes: An Umbrella Review of Meta-Analyses of Observational Studies
Authors: Lane Melissa M. , Travica Nikolaj , Gamage Elizabeth , Marshall Skye , Trakman Gina L. , Young Claire , Teasdale Scott B. , Dissanayaka Thusharika , Dawson Samantha L. , Orr Rebecca , Jacka Felice N. , O'Neil Adrienne , Lawrence Mark , Baker Phillip , Rebholz Casey M. , Du Shutong , Marx Wolfgang 
Published: August 2024

Our aim was to conduct an umbrella review of evidence from meta-analyses of observational studies investigating the link between sugar-sweetened beverage consumption and human health outcomes. Using predefined evidence classification criteria, we evaluated evidence from 47 meta-analyses encompassing 22,055,269 individuals. Overall, 79% of these analyses indicated direct associations between greater sugar-sweetened beverage consumption and higher risks of adverse health outcomes. Convincing evidence (class I) supported direct associations between sugar-sweetened beverage consumption and risks of depression, cardiovascular disease, nephrolithiasis, type 2 diabetes mellitus, and higher uric acid concentrations. Highly suggestive evidence (class II) supported associations with risks of nonalcoholic fatty liver disease and dental caries. Out of the remaining 40 meta-analyses, 29 were graded as suggestive or weak in the strength of evidence (classes III and IV), and 11 showed no evidence (class V). These findings inform and provide support for population-based and public health strategies aimed at reducing sugary drink consumption for improved health.
No Compulsion in Religion: Jawdat Saʿīd (d. 2022) and the Jihād of the Prophets
Authors: Pizzi Paola 
Published: August 2024

Abstract
Freedom of belief and of conscience is well attested in the Qurʾan by the many verses that exhort to tolerance towards “others”, among which Q. 2:256: ‘There is no compulsion in religion’. In contemporary Islam, some intellectuals have endeavoured to reaffirm this principle as an essential goal: among them, the Sunni Syrian thinker Jawdat Saʿīd (d. 2022). In his works, Q. 2:256 is at the core of an anthropocentric and social hermeneutics which emphasises the centrality of non-compulsion, considered as the true jihad that Muslims should undertake. His position is in open polemic with a tendency within Islamic societies not to recognise the legitimacy of those opinions – religious or political – that deviate from the “official” discourse on the one hand, and to combat this discourse with violence on the other. This entails a renegotiation of other key doctrinal concepts, the case of nasḫ, “abrogation”, being a key example.
On Andreas Malm’s How to Blow Up a Pipeline
Authors: Martin Brian , Christoyannopoulos Alexandre , Svensson Isak , Gallagher Cunningham Kathleen , Anisin Alexei , Durance Antoine , Cervera-Marzal Manuel 
Published: August 2024

Abstract
Andreas Malm says sabotage is needed to save the world from climate catastrophe. In this Forum, scholars of pacifism and nonviolence caution against such a course of action by pointing to several important factors at play in determining the success or otherwise of activist campaigns, including barriers to participation, organisational dynamics, loyalty shifts, the backfire effect, and the role of framing and public opinion. Ongoing research into pacifism and nonviolence presents a nuanced picture of the current strategic landscape of climate activism, revealing lessons that the climate movement must consider as it reflects on what repertoire of action to embrace to enhance its effectiveness and mitigate the unfolding climate emergency.
Primary biliary cholangitis has causal effects on systemic rheumatic diseases: a Mendelian randomization study
Authors: Zhang Hai-Ping , Zhou Zhe , Chen Ke , Xiong Li-Fen , Wu Jun , Jin Lei 
Published: August 2024

Abstract
Background
An association has been observed between primary biliary cholangitis (PBC) and systemic rheumatic diseases (SRDs) in observational studies, however the exact causal link remains unclear. We aimed to evaluate the causal effects of PBC on SRDs through Mendelian randomization (MR) analysis.

Methods
The genome-wide association study (GWAS) summary data were obtained from MRC IEU OpenGWAS and FinnGen databases. Independent genetic variants for PBC were selected as instrumental variables. Inverse variance weighted was used as the main approach to evaluate the causal effects of PBC on Sjögren syndrome (SS), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), mixed connective tissue disease (MCTD) and polymyositis (PM). Horizontal pleiotropy and heterogeneity were measured by MR‒Egger intercept test and Cochran’s Q value, respectively.

Results
PBC had causal effects on SS (OR = 1.177, P = 8.02e-09), RA (OR = 1.071, P = 9.80e-04), SLE (OR = 1.447, P = 1.04e-09), SSc (OR = 1.399, P = 2.52e-04), MCTD (OR = 1.306, P = 4.92e-14), and PM (OR = 1.416, P = 1.16e-04). Based on the MR‒Egger intercept tests, horizontal pleiotropy was absent (all P values > 0.05). The robustness of our results was further enhanced by the leave-one-out method.

Conclusions
Our research has provided new insights into PBC and SRDs, indicating casual effects on various SRDs.
Perspectives of older adults with chronic illness on person-centered practice at an inpatient hospital department: a descriptive study
Authors: Vareta Diana , Ventura Filipa , Família Carlos , Oliveira Célia 
Published: August 2024

Abstract
Background
The growing aging trend associated with a higher prevalence of chronic illnesses is increasing the demand for the development of person-centered practice in specific care settings. Knowing the person’s perception of the care and the care experience is essential to improving inpatient care toward person-centeredness. This study aims to characterize the perceptions of person-centered practice of hospitalized older adults with chronic illness at a Portuguese inpatient hospital department.

Methods
A quantitative, descriptive, cross-sectional approach was followed. Data were collected using a sociodemographic and health history questionnaire and the Person-Centered Practice Inventory - Care (PCPI-C). The effect of the different variables on each PCPI-C construct was determined using analysis of variance (ANOVA).

Results
The results show that person-centered practice was positively perceived in the five constructs of the person-centered processes domain (M = 3.92; SD = 0.47). The highest-scored construct was working with the person’s beliefs and values (M = 4.12; SD = 0.51), and the lowest was working holistically (M = 3.68; SD = 0.70). No significant effect of the independent variables was found to influence the perceptions of any of the constructs in the person-centered processes domain.

Conclusions
These results might indicate that person-centered processes are perceived uniquely by each person through individualized therapeutic relationships rather than a pattern of care shared by hospitalized older adults.
Evaluation of the New York City COVID-19 case investigation and contact tracing program: a cascade of care analysis
Authors: Conderino Sarah , E. Thorpe Lorna , Shilpi Islam Nadia , A. Berry Carolyn , Bendik Stefanie , Massar Rachel , Hong Chuan , Fair Andrew , Bershteyn Anna 
Published: August 2024

Abstract
Background
New York City (NYC) was the first COVID-19 epicenter in the United States and home to one of the country’s largest contact tracing programs, NYC Test & Trace (T2). Understanding points of attrition along the stages of program implementation and follow-up can inform contact tracing efforts for future epidemics or pandemics. The objective of this study was to evaluate the completeness and timeliness of T2 case and contact notification and monitoring using a “cascade of care” approach.

Methods
This cross-sectional study included all SARS-CoV-2 cases and contacts reported to T2 from May 31, 2020 to January 1, 2022. Attrition along the “cascade of care” was defined as: (1) attempted, (2) reached, (3) completed intake (main outcome), (4) eligible for monitoring, and (5) successfully monitored. Timeliness was assessed: (1) by median days from a case’s date of testing until their positive result was reported to T2, (2) from result until the case was notified by T2, and (3) from a case report of a contact until notification of the contact.

Results
A total of 1.45 million cases and 1.38 million contacts were reported to T2 during this period. For cases, attrition occurred evenly across the first three cascade steps (~-12%) and did not change substantially until the Omicron wave in December 2021. During the Omicron wave, the proportion of cases attempted dropped precipitously. For contacts, the largest attrition occurred between attempting and reaching (-27%), and attrition rose with each COVID-19 wave as contact volumes increased. Attempts to reach contacts discontinued entirely during the Omicron wave. Overall, 67% of cases and 49% of contacts completed intake interviews (79% and 57% prior to Omicron). T2 was timely, with a median of 1 day to receive lab results, 2 days to notify cases, and < 1 day to notify contacts.

Conclusions
T2 provided a large volume of NYC residents with timely notification and monitoring. Engagement in the program was lower for contacts than cases, with the largest gap coming from inability to reach individuals during call attempts. To strengthen future test-and-trace efforts, strategies are needed to encourage acceptance of local contact tracer outreach attempts.
B7-1 and PlGF-1 are two possible new biomarkers to identify fracture-associated trauma patients at higher risk of developing complications: a cohort study
Authors: Breinbauer Regina , Mäling Michelle , Ehnert Sabrina , Blumenstock Gunnar , Schwarz Tobias , Jazewitsch Johann , Erne Felix , Reumann Marie K. , Rollmann Mika F. , Braun Benedikt J. , Histing Tina , Nüssler Andreas K. 
Published: August 2024

Abstract
Background
Around 10% of fractures lead to complications. With increasing fracture incidences in recent years, this poses a serious burden on the healthcare system, with increasing costs for treatment. In the present study, we aimed to identify potential ‘new’ blood markers to predict the development of post-surgical complications in trauma patients following a fracture.

Methods
A total of 292 trauma patients with a complete three-month follow-up were included in this cohort study. Blood samples were obtained from 244 of these patients. Two complication groups were distinguished based on the Clavien-Dindo (CD) classification: CD grade I and CD grade III groups were compared to the controls (CD 0). The Mann-Whitney U test was used to compare the complication groups to the control group.

Results
Analysis of the patients’ data revealed that risk factors are dependent on sex. Both, males and females who developed a CD III complication showed elevated blood levels of B7-1 (p = 0.015 and p = 0.018, respectively) and PlGF-1 (p = 0.009 and p = 0.031, respectively), with B7-1 demonstrating greater sensitivity (B7-1: 0.706 (male) and 0.692 (female), PlGF-1: 0.647 (male) and 0.615 (female)). Further analysis of the questionnaires and medical data revealed the importance of additional risk factors. For males (CD 0: 133; CD I: 12; CD III: 18 patients) alcohol consumption was significantly increased for CD I and CD III compared to control with p = 0.009 and p = 0.007, respectively. For females (CD 0: 107; CD I: 10; CD III: 12 patients) a significantly increased average BMI [kg/m2] from 25.5 to 29.7 with CD III was observed, as well as an elevation from one to three comorbidities (p = 0.003).

Conclusions
These two potential new blood markers hold promise for predicting complication development in trauma patients. Nevertheless, further studies are necessary to evaluate the diagnostic utility of B7-1 and PlGF-1 in predicting complications in trauma patients and consider sex differences before their possible use as routine clinical screening tools.
Can minimally invasive transforaminal lumbar interbody fusion achieve a better clinical and radiological outcome than traditional open technique in isthmic spondylolisthesis?
Authors: Ali Elsayed Mohamed Selim , Eladawy Amr Mohamed , ElHewala Tarek 
Published: August 2024

Abstract
Background
Spondylolisthesis is a prevalent condition in the lumbar spine that can cause low back pain, leg pain, neurogenic claudication, and impact health-related quality of life in symptomatic individuals.

Aim
to assess the results of minimally invasive TLIF (MIS-TLIF) versus open-TLIF and the impact of correcting spino-pelvic parameters on the Health-Related Quality of Life (HRQoL) in patients with low-grade isthmic spondylolisthesis. The primary objective was to compare the effectiveness of both methods in correcting spinopelvic parameters. The secondary objectives involved comparing clinical improvement, operating time, blood loss, complications, and postoperative hospital stays between the two procedures.

Patients and methods
Seventy-two patients with low-grade isthmic spondylolisthesis were enrolled in this retrospective cohort-control study, with a minimum follow-up period of 18 months. Disability was assessed using the Oswestry Disability Index (ODI), while back and leg discomfort were rated using the Visual Analogue Scale (VAS) for each patient. The measurements comprised the sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), and Meyerding slip grades. We measured lumbar lordosis (LL), and segmental lordosis.

Results
The seventy-two patients were 60 female and 12 males. There was no statistically significant difference in the duration of operation between the two groups. In the MIS group, there was a notable reduction in blood loss, higher radiation exposure, and a shorter hospital stay (P < 0.001). The back VAS showed more favorable outcomes in the MIS-TLIF, while the leg VAS showed better results in the Open-TLIF in the early outcome. Both procedures significantly reduced leg and back pain VAS scores and ODI, with no notable difference between the two groups at the final follow-up. Post-surgery, the pelvic incidence (PI) and lumbar lordosis (LL) matched properly in all patients, showing a rise in LL and sacral slope along with a decrease in pelvic tilt.

Conclusion
Both open-TLIF and MIS-TLIF are effective methods for correcting spino-pelvic parameters and improving HRQoL in patients with low-grade isthmic spondylolisthesis. The rapid improvement in back pain experienced by these patients favored the use of MIS-TLIF. However, the cost-effectiveness of this approach must be carefully evaluated.
Evaluating the generalizability of graph neural networks for predicting collision cross section
Authors: Engler Hart Chloe , Preto António José , Chanana Shaurya , Healey David , Kind Tobias , Domingo-Fernández Daniel 
Published: August 2024

AbstractIon Mobility coupled with Mass Spectrometry (IM-MS) is a promising analytical technique that enhances molecular characterization by measuring collision cross-section (CCS) values, which are indicative of the molecular size and shape. However, the effective application of CCS values in structural analysis is still constrained by the limited availability of experimental data, necessitating the development of accurate machine learning (ML) models for in silico predictions. In this study, we evaluated state-of-the-art Graph Neural Networks (GNNs), trained to predict CCS values using the largest publicly available dataset to date. Although our results confirm the high accuracy of these models within chemical spaces similar to their training environments, their performance significantly declines when applied to structurally novel regions. This discrepancy raises concerns about the reliability of in silico CCS predictions and underscores the need for releasing further publicly available CCS datasets. To mitigate this, we introduce Mol2CCS which demonstrates how generalization can be partially improved by extending models to account for additional features such as molecular fingerprints, descriptors, and the molecule types. Lastly, we also show how confidence models can support by enhancing the reliability of the CCS estimates.Scientific contributionWe have benchmarked state-of-the-art graph neural networks for predicting collision cross section. Our work highlights the accuracy of these models when trained and predicted in similar chemical spaces, but also how their accuracy drops when evaluated in structurally novel regions. Lastly, we conclude by presenting potential approaches to mitigate this issue.