bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computational Study of Rapid Direct Metal Laser Sintering for Compression Mold Manufacturing
Authors: Mirzaei Shokoufeh , Siaumau Ryan 
Published: September 2023

Abstract
Compression mold tooling fabrication has been traditionally conducted via machining processes—for example, computerized numerical control machining, mill, or lathe operations. While subtractive manufacturing operations provide high-precision tooling, they have an extended lead time and generate material waste, which increases manufacturing costs. This paper analyzes Direct Metal Laser Sintering (DMLS) as a viable alternative to traditional compression mold manufacturing. DMLS is an additive manufacturing process that uses high-powered lasers to fuse metal powders in a layered approach to create high-precision metal components. Through layering materials, DMLS can produce complex geometries which can have features impossible to machine from traditional manufacturing methods. Additionally, DMLS uses less material for parts, reducing material costs and lead times. In this paper, DMLS manufactured mold was computationally studied against a traditional compression mold's thermal and pressure requirements. The DMLS mold was designed with a honeycomb structure to reduce material usage while maintaining structural integrity. Computational Analysis showed that the production requirement, “maximum deflection of 0.001 inches”, was achieved with the DMLS when pressures and temperatures were similar to those required for the tooling. In addition, DMLS-produced mold utilized 74% less material than a traditionally manufactured mold.
Rivaroxaban Plus Aspirin vs Dual Antiplatelet Therapy in Endovascular Treatment in Peripheral Artery Disease and Analysis of Medication Utilization of different Lesioned vascular regions
Authors: H SiYan , Che Jun 
Published: September 2023

Abstract
Background
Peripheral arterial disease (PAD) necessitates administration of anticoagulant or antiplatelet medications. Dual antiplatelet therapy(DAPT) and rivaroxaban show promise in reducing adverse outcomes. Heterogeneity in lower limb artery pathology may calls for personalized treatment strategies.
METHODS
In a single-center retrospective study, pharmacotherapy in peripheral artery disease involved aspirin plus rivaroxaban（5 mg twice daily） or aspirin plus clopidogrel（75 mg once daily). The primary efficacy outcome was a composite of Rutherford classification increase, acute limb ischemia, amputation for vascular reasons, target lesion revascularization, myocardial infarction, ischemic stroke, and cardiovascular death.The primary safety outcome was major bleeding, defined according to the Thrombolysis in Myocardial Infarction (TIMI) classification; major bleeding as defined by the International Society on Thrombosis and Haemostasis (ISTH) was a secondary safety outcome.Two subgroups analyzed: suprapatellar and infrapatellar arterial lesion-only patients.
Results
From January 2016 to December 2021, 455 patients received clopidogrel plus aspirin or rivaroxaban plus aspirin after endovascular treatment(EVT). Rivaroxaban group (n=220) had lower primary efficacy outcome incidence (49.1% vs 60.4%, hazard ratio(HR) 0.77, P=0.006), but more TIMI major bleeding events (5.9% vs 2.1%, HR 2.6, P=0.04). ISTH major bleeding events did not significantly differ, though more rivaroxaban patients discontinued medication due to bleeding(10% vs 4.7%, HR 2.2,P=0.03). In suprapatellar subgroup, rivaroxaban group had lower primary efficacy outcome incidence (28.2% vs 45.2%，HR 0.55, P=0.02). In infrapatellar subgroup, No significant difference was found in the occurrence of primary efficacy events between the two groups (58.7% vs 64.8%，HR 0.76, P=0.14).
Conclusion
Rivaroxaban plus aspirin improved outcomes compared to DAPT in lower extremity artery disease. Similar findings were seen in the suprapatellar artery lesion-only group. In the infrapatellar artery lesion-only group, rivaroxaban plus aspirin did not outperform DAPT. Safety-wise, Rivaroxaban plus aspirin had higher bleeding risks and treatment discontinuation compared to aspirin plus clopidogrel.
A Comparative Analysis Of Machine Learning Algorithms To Predict Backorder In Supply Chain Management
Authors: Banik Semonti , Islam Md. Rifatul , Rahman Kazi Naimur , Rahman Md. Abdur 
Published: September 2023

Abstract
In supply chain inventory management, the backorder of products is a common occurrence. A backorder can only be successful if the supplier can be relied upon to provide the out-of-stock product when required or if the consumer is prepared to wait for the product without becoming impatient. So, to avoid uncertain circumstances and lessen the loss, it is important to know which goods are more likely to be back-ordered ahead of time so that appropriate measures can be taken. This work presents a backorder predictive model based on an imbalanced historical dataset obtained from an online source. The data has undergone sampling techniques, various Machine Learning algorithms, and evaluation metrics. After Random Undersampling (RUS), Random Forest (RF) achieved the highest accuracy of 99.328% while an accuracy of 98.917% was obtained from Extreme Gradient Boosting (XGBoost) model, which was highest after applying Synthetic Minority Oversampling Technique (SMOTE). XGBoost has outperformed other models with highest ROC-AUC score of 94.55% and 95.93% for oversampled and undersampled data respectively. In this paper, we made a visualization of the attributes of the dataset, then applied and analyzed Machine Learning algorithms to predict the backorder.
Test and numerical simulation of vibratory pile sinking in expansive soil layer
Authors: Zhang Tao , Cai Min , Shan Cancan , Shu Dongqing , Chen Jun 
Published: September 2023

Abstract
In order to study the pile sinking characteristics of steel sheet piles (H-shape) under vibratory loading in expansive soil layer, the test results of pile sinking depth and pile sinking rate in expansive soil layer were obtained through field tests under two different conditions, i.e. without auxiliary measures and with the auxiliary measures of "hydrodynamic method". Using finite element numerical analysis method, a three-dimensional numerical calculation model was established under the two different conditions to simulate and analyse the pile sinking process, and the ultimate depth of pile sinking in expansive soil layer was obtained, which reveals the variation rules and characteristics of the pile side friction resistance and the total pile side resistance. The results can be used to assess the reliability of pile sinking in expansive soil layer and provide quantitative reference for the design and construction of vibratory loaded pile sinking in expansive soil layer.
Unignorable Influence of Chest Pain on Mood Symptoms and Prognostic Values in Coronary Artery Disease: A Cross-sectional Study
Authors: Tan Hanxuan , Xu Mingyu , Li Weiya , Liu Quanjun , Yin Han , Geng Qingshan 
Published: September 2023

Abstract
Background
Prior studies examining depression and anxiety among individuals with coronary artery disease (CAD) have predominantly concentrated on their connection with clinical and laboratory markers, disregarding the profound effect of the cardinal symptom—chest pain. The potential influence of chest pain on the prognostic significance of depression and anxiety, encompassing cardiovascular outcomes, has yet to be fully investigated.
Methods
Secondary analyses based on a cross-sectional research for investigating prevalence of mood symptoms/disorder in CAD patients. Five-hundred and sixty-one consecutive inpatients were enrolled. The prognostic data was consistently monitored over a median follow-up period of 26 months. The aims of this study were to determine the influence of chest pain on depression and anxiety symptoms and their prognostic effects in CAD. Logistic regression models were used for selecting the most relevant predictors for mood symptoms. Cox regression model were applied for analyzing the prognostic values.
Results
The prevalence of having depression and anxiety symptoms in CAD reached 37.6% and 27.3%, respectively. Comprehensive analyses revealed that the primary correlated factors for depression were chest pain frequency, age, history of diabetes, and exercise time, and for anxiety were chest pain frequency, chest pain course, and education level. As the common and strongest predictor, chest pain frequency demonstrated a dose-dependent relationship with the risk for mood symptoms. Chest pain frequency and course were not directly associated with prognosis, however impact the prognostic effect of mood symptoms. The association between major adverse cardiovascular events (MACEs) and depression symptoms was primarily observed in patients with a high chest pain frequency, whereas with anxiety was mainly presented in patients with a short chest pain course. For noncardiac rehospitalization, anxiety presented higher predictive value in participants with low chest pain frequencies, while depression was right the opposite.
Conclusions
These findings underscore the significance of considering chest pain as a crucial factor when investigating the influence of mood symptoms in CAD patients. Particularly, individuals with mood symptoms who experience frequent chest pain episodes despite a short course warrant special attention. Enhancing their emotional well-being and addressing chest pain symptoms might potentially yield valuable clinical benefits.
Drivers of unprofessional behaviour between staff in acute care hospitals: A realist review
Authors: Aunger Justin Avery , Maben Jill , Abrams Ruth , Wright Judy M , Mannion Russell , Pearson Mark , Jones Aled , Westbrook Johanna I 
Published: September 2023

Abstract

Background
Unprofessional behaviours (UB) between healthcare staff are rife in global healthcare systems, negatively impacting staff wellbeing, patient safety and care quality. Drivers of UBs include organisational, situational, team, and leadership issues which interact in complex ways. An improved understanding of these factors and their interactions would enable future interventions to better target these drivers of UB.
Methods
A realist review following RAMESES guidelines was undertaken with stakeholder input. Initial theories were formulated drawing on reports known to the study team and scoping searches. A systematic search of databases including Embase, CINAHL, MEDLINE and HMIC was performed to identify literature for theory refinement. Data were extracted from these reports, synthesised, and initial theories tested, to produce refined programme theories.
Results
We included 81 reports (papers) from 2,977 deduplicated records of grey and academic reports and 28 via Google, stakeholders, and team members, yielding a total of 109 reports. Five categories of contributor were formulated: (1) workplace disempowerment; (2) harmful workplace processes and cultures; (3) inhibited social cohesion; (4) reduced ability to speak up; and (5) lack of manager awareness and urgency. These resulted in direct increases to UB, reduced ability of staff to cope, and reduced ability to report, challenge or address UB. Twenty-three theories were developed to explain how these contributors work and interact, and how their outcomes differ across diverse staff groups. Staff most at risk of UB include women, new staff, staff with disabilities, and staff from minoritised groups. UB negatively impacted patient safety by impairing concentration, communication, ability to learn, confidence, and interpersonal trust.
Conclusion
Existing research has focused primarily on individual characteristics, but these are inconsistent, difficult to address, and can be blamed to deflect organisational responsibility. We present a comprehensive programme theory furthering understanding of contributors to UB, how they work and why, how they interact, whom they affect, and how patient safety is impacted. More research is needed to understand how and why minoritised staff are disproportionately affected by UB.
Study registration
This study was registered on the international database of prospectively registered systematic reviews in health and social care (PROSPERO): https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021255490.
EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma
Authors: Gao Xiaqing , Yang Chunting , Li Hailong , Shao Lihua , Wang Meng , Su Rong 
Published: September 2023

Abstract
This study was designed to evaluate the prognosis and pharmacological therapy sensitivity of epithelial mesenchymal transition-related genes (EMTRGs) that obtained from the EMTome database in hepatocellular carcinoma (HCC) using bioinformatical method. The expression status of EMTRGs were also investigated using the clinical information of HCC patients supported by TCGA database and the ICGC database to establish the TCGA cohort as the training set and the ICGC cohort as the validation set. The differentially expressed EMTRGs between HCC tissue and liver tissue in the TCGA cohort were investigated to perform the WGCNA analysis. Subsequently, the data were then analyzed in the order of univariate COX regression, LASSO regression, and multivariate COX regression to construct a risk model for EMTRGs. In addition, enrichment pathways, gene mutation status, immune infiltration, and response to drugs were also analyzed in the high-risk and low-risk groups of the TCGA cohort, and the protein expression status of EMTRGs was verified. The results showed a total of 286 differentially expressed EMTRGs in the TCGA cohort, and EZH2, S100A9, TNFRSF11B, SPINK5, and CCL21 were used for modeling. The TCGA cohort was found to have a worse outcome in the high-risk group of HCC patients, and the ICGC cohort confirmed this finding. In addition, EMTRGs risk score was shown to be an independent prognostic factor in both cohorts by univariate and multivariate Cox regression. The results of GSEA analysis showed that most of the enriched pathways in the high-risk group were associated with tumor, and the pathways enriched in the low-risk group were mainly associated with metabolism. Patients in various risk groups had varying immunological conditions, and the high-risk group might benefit more from targeted treatments. To sum up, the EMTRGs risk model was developed to forecast the prognosis for HCC patients, and the model might be useful in assisting in the choice of treatment drugs for HCC patients.
The characteristics of vaginal microbiome comparing pre- and post-testosterone treatment in transgender men
Authors: Paniachaya Punika , Panyakhamlerd Krasean , Suwan Ammarin , Ariyasriwatana Chai , Visedthorn Suthida , Chanchaem Prangwalai , Klomkliew Pavit , Payungporn Sunchai , Nilgate Sumanee , Chatsuwan Tanittha , Tuntiviriyapun Punkavee , Chavaengkiat Suchanant , Bumphenkiatikul Thanapob , Nimitpanya Panachai 
Published: September 2023

Abstract
Sex hormone levels affect the composition of vaginal flora. Changes in the vaginal microbiome affect individual health. Among transgender men (TM) who receive gender-affirming treatment, there can be a change in the vaginal microbiome causing adverse effects that are neglected by both transgender individuals and healthcare professionals. This study aims to understand the influence of testosterone on the vaginal microbiome. This prospective study was conducted at King Chulalongkorn Memorial Hospital. All TM who had not yet received testosterone were included. High-throughput sequencing was used to evaluate the bacterial community profiles. Testosterone enanthate 150 mg IM every three weeks was given. Vaginal health was reevaluated 12 weeks after treatment. The primary outcome was to compare the vaginal microbiome before and after using testosterone. Twenty-six participants were included in the analysis. Compared to pretestosterone treatment, testosterone-treated TM had a lower likelihood of having Lactobacillus as their dominant bacterial species, considerably higher relative bacterial abundance, and higher alpha diversity (p<0.01). Clinically, after administering testosterone for 12 weeks, participants reported more symptoms (p=0.04), higher vaginal atrophy scores (p<0.01), lower normal flora scores (p<0.01), higher vaginal pH (p<0.01), and worse scores for vaginal maturation values (p<0.01).
Exploring Changes in Facial Microbiota of Maskne Patients and Healthy Individuals Before and After Mask Wearing Using 16S rRNA Analysis
Authors: Deng Kexin , Tong Xiaofei , Chen Shuyue , Wu Guojun , Shi Ke , Chen Hao , Tan YuRong , Liao Junlin , Zhou Jianda , Zhao Junxiang 
Published: September 2023

Abstract
Whether in the field of medical care or in people's daily life and health protection, increased emphasis has been put on the significance of masks. Acne is the most common complication after wearing masks, which is also called as Maskne and has been successfully introduced into the common language,and been a common topic of dermatologist consultations. This study aims to study the microflora changes of Maskne patients and normal people before and after wearing masks. In the summer 2023, we collected a total of 50 samples from 15 Maskne patients and 10 normal people before and after wearing masks for a long time. 16S ribosomal DNA sequencing and identification technology with V3-V4 variable region were adopted to explore the microbiome changes caused by mask-wearing, analyzing the changes in microbial diversity, and making interaction network. LDA effect size analysis and ANOVA t-test were used to find changed microorganisms. After Maskne patients wore masks,the changing degree of their microbiomes was significantly more than those of normal people,with both α diversity and β diversity lower than those of Maskne patients before wearing masks and those of normal people after wearing masks.Co-occurrence network analysis showed that compared with other groups, the network of Maskne patients after wearing masks for a longtime had the lowest connectivity and complexity, but the highest clustering property,while the normal people group was the opposite. Many microbes that are potentially beneficial to the skin decreased significantly after wearing the mask.There was almost no difference in normal people before and after wearing masks.
Equitable clean cooking:-solar Injera stoves with sensible heat storage
Authors: Tesfay Asfafaw Haileselassie , Kahsay Mulu Bayray , Hailu Mesele Hayelom , Nydal Ole Jørgen 
Published: September 2023

Abstract
Energy poverty is at its highest risk in Africa and yet introducing clean and modern energy in rural Africa demands huge resource. Most African rural use biomass energy in traditional cook stoves. Similarly, Ethiopia’s rural are using traditional stoves with their associated risks. Injera, the highly consumed food in the country is the most energy intensive cooking activity. Authors’ previous researches have proved that it is possible to bake Injera by using solar stoves. However, optimization and safety issues need further study. This paper has focused on demonstrating safe and affordable indirect solar Injera stoves that considered end users economy, ergonomics and versatility of the system. Solar Injera stove with integrated latent heat storage gives good degree of freedom in terms of baking time. However, its high cost remained challenging to implement in rural communities. This research uses a sensible heat storage that lasts for about 30 minutes of baking and avoids the high cost and high-risk concerns of Authors’ previous innovation. Similar to the other works of the authors, this study has also demonstrated Injera baking in the range of 130–150 ºC is best baking temperature range. The symmetry nature of the charging and discharging nature makes these innovations ideal for continuous heat collection and baking. Consequently, it makes it easy to revolutionize clean and affordable solar Injera stoves.
T1 Hypointense Brain Lesions in NMOSD and Its Relevance with Disability: A Single Institution Cross-sectional Study
Authors: Hashemi Mohamad Ghazanfari , Talebi Vahid , Kasbi Naghmeh Abbasi , Abbasi Mehrshad , Asgari Nasrin , Sahraian Mohammad Ali 
Published: September 2023

Abstract
1. Background: T1 hypointense lesions are considered a surrogate marker of tissue destruction. Although there is a dearth of evidence about T1 hypointense brain lesions, black holes, in patients with Neuromyelitis Optica Spectrum Disorder (NMOSD), the clinical significance of these lesions is not well determined.
2. Objectives: The impact of T1 hypointense brain lesions on the clinical status and the disability level of patients with NMOSD, was sought in this study.
3. Methods: A total of 83 patients with the final diagnosis of NMOSD were recruited.
Aquaporin-4 measures were collected. The expanded disability status scale (EDSS) and MRI studies were also extracted.
T1 hypointense and T2/FLAIR hyperintense lesions were investigated. The correlation of MRI findings, AQP-4, and EDSS was assessed.
4. Results: T1 hypointense brain lesions were detected in 22 patients. Mean ± SD EDSS was 3.7± 1.5 and was significantly higher in patients with brain T1 hypointense lesions compared to those without them (p-value = 0.01). Noticeably, patients with more than four T1 hypointense lesions had EDSS scores ≥ 4. The presence of T2/FLAIR hyperintense brain lesions correlated with EDSS, as well (3.6±1.6 vs 2.3±1.7; p-value = 0.01). EDSS was similar between those with and without positive AQP-4 (2.7± 1.6 vs. 3.2± 1.7; p-value= 0.17). Also, positive AQP-4 was not more prevalent in patients with T1 hypointense brain lesions compared to those without them (50.9 vs 45.4%; p-value= 0.8).
5. Conclusion: We demonstrated that the presence of the brain T1-hypointense lesions corresponds to a higher disability level in NMOSD.
Knowledge graph-based small sample learning for label of medical imaging reports
Authors: Zhang Yuxuan , Gu Zongyun , Jia Pengcheng , Li Tiancheng , Lu Wenhao , Ge Mingxin , Chen Linyu , Li Chuanfu 
Published: September 2023

Abstract
Background: Through the utilization of knowledge graph and small sample learning, the study effectively tackled the challenges of data scarcity and automatic annotation in the field of medical image recognition with the application of artificial intelligence technology.
Methods: Initially, 2000 X-ray reports of the lumbar spine were labeled manually employing a knowledge graph approach. These reports were subsequently split into a training dataset of 1000 cases and a test dataset of 1000 cases. Following this, distinct levels of data augmentation, namely the synonym/apposition method, were applied to the training dataset. Subsequently, the deep learning model BERT (Bidirectional Encoder Representation of Transformer) was utilized for the training process. Afterward, the BERT model is tested on the specified test dataset, and subsequently, the nodes showing insufficient performance are supplemented with iterative target data. Finally, the method is evaluated by using various metrics including AUC(Area Under Curve), F1 score, precision, recall and relabelled rate.
Results: Before conducting data augmentation, the AUC value was 0.621, the F1 value was 32.1%, the average precision was 0.383, and the average recall was 0.303. Following data augmentation, the AUC value improved to 0.789, the F1 value improved to 70.3%, the average precision improved to 0.879, and the average recall improved to 0.580. After targeted data supplementation, the AUC reached 0.899, the F1 value reached 85.7%, the average precision reached 0.952, and the average recall reached 0.803.
Conclusions: The current study achieves its objective by training an automatic annotation model using a knowledge graph-based approach to annotate medical imaging reports on a small sample dataset. Furthermore, this approach enhances both the efficiency and accuracy of medical imaging data annotation, providing a significant research strategy for applying artificial intelligence in the field of medical image recognition.