bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of feature selection techniques on aging-related bug prediction models: An empirical investigation
Authors: Zhang Chen , Domenico Cotroneo , Roberto Pietrantuono , Roberto Natella , Yu Xiao , Xie Wenzhi , Jia Kai , Xiang Jianwen 
Published: May 2023

Abstract
Software aging refers to the accumulation of error conditions over time in long-running software systems, which can lead to decreased performance and an increased likelihood of failures. Aging-Related Bug Prediction (ARBP) was introduced to predict the Aging-related Bugs (ARBs) hidden in the systems by using features extracted from source code. ARBs include memory leaks, storage problems, unreleased files, socket exceptions, unreleased file handles, disk fragmentation and so on. Previous research in Software Defect Prediction (SDP) indicated that using feature selection techniques to select a subset of representative features to use could enhance the performance of classification models. However, considering the difference between ARB features and SDP features, blindly applying the method performed well in SDP to pre-process the ARBs dataset may not necessarily improve the performance of the ARBP model, and could potentially result in a decline in performance. To address this limitation, 22 feature selection methods with 21 classifiers embedded in the most used ARBP model on four benchmark datasets from real-world software projects, and six different evaluation indicators were employed to assess the performance of ARBP models comprehensively. Our experiment results showed that: (1) The filter-based feature ranking method called SVMF performed the best on the ARBP, and the filter-based feature subset selection method ConBF performs the worst on the ARBP task. (2) Using the statistic-based classifiers as the base classification model embedded with the SVMF can perform the best, the Naive Bayes classifier always achieves the best performance. Researchers are recommended to first consider CountLineBlank, CountLineComment, and MaxCyclomaticModified features for the ARBP task.(3) The feature selection method ConBF, which performed the best in conventional SDP was not optimal for our specific task. This highlights the unique nature of aging-related features and underscores the need for a tailored feature selection method. Based on these findings, we recommend using SVMF with the Naive Bayes classifier when building ARBP models, in our study, this combination can improve the Balance performance by 18\% and Recall by 25.9% compared with no feature selection for ARBP.
Visualization and analysis of knowledge domains for recent developments in coal mechanical properties studies
Authors: Wang Chen , Xu Xiaomeng , Zhang Yihuai , Arif Muhammad , Zhang Siyuan , Lan Meijuan , Yu Binshan 
Published: May 2023

Abstract
Studying the dynamic and static mechanical properties of coal and their impact is critical in coal mining design, mining work progress, and mining safety, especially for the prevention and control of dynamic disasters such as rock bursts, coal and gas outbursts, etc. To better understand the research progress and trends of coal's mechanical properties and to promote theoretical research on the prevention and control of dynamic disasters, the bibliometric method was introduced to analyze the research progress on the mechanical properties study of coal. A total of 3,450 documents collected in the Web of Science (WOS) core database were reviewed and analyzed in this work. The analysis focused on the annual quantitative distribution of literature, national/regional distribution, organizational distribution, author distribution, distribution of significant source journals, and research hotspots and frontiers. We used CiteSpace and Vosviewer to map knowledge areas. The results indicate that the number of research papers on the mechanical properties of coal has increased exponentially. China, America, Australia, India, Spain, Poland, England, Japan, South Korea, and Turkey are the most active countries for research on the mechanical properties of coal. The research results from China, America, and Australia are the most influential, and C&BM, FUEL, INT J ROCK MECH MIN, INT J COAL GEOL, RM&RE, C&CR, and JCP are the primary sources of research publications on the mechanical properties of coal. The basic theory and research system of coal mechanical properties investigation have been completed, and there are many future research directions and broad branches. Several current hot spots include the coal mechanical property model, mechanical property-related permeability model, establishment and prediction of coal strength-temperature relationships, research on the proportioning scheme of granite and coal bottom ash in concrete mixes, and research on the improvement effect of fly ash on concrete manufacturing properties.
Assessment the Awareness of the Syrian Population toward the Risk Factors and Symptoms of Colorectal Cancer: Cross Sectional Study
Authors: Alibrahim Hidar , Swed Sarya , Bohsas Haidara , Albarakat Majd M. , Jawish Nagham , Nasif Mohamad Nour , Sawaf Bisher , Habib Mhd Baraa , Esber Muhammad , Hammo Aleen , Abdo Bana , fathey Sherihan , Rashid Gowhar , Hafez Wael 
Published: May 2023

Abstract

BackgroundThis cross-sectional research seeks to examine the level of knowledge of CRC risk factors and symptoms in Syria.MethodsAn online cross-sectional study was conducted from 1 August to 25 August 2022. The sample inclusion criteria of study participants were Syrian nationals aged 18 or older from all Syrian governorates.ResultsAmong 702 Syrian national participants (n = 430, 61.3%) were females. About half of the inquired participants have shown a good knowledge of colorectal cancer symptoms (n = 301, 42.9%). However, only (n = 123, 17.6%) participants have shown a good understanding of colorectal cancer risk factors. Most participants were somewhat confident in their ability to recognize colorectal cancer symptoms (43.60%), whereas just 4.60% of people were highly confident in their ability to recognize them. Only (24.10%) of the participants were not confident in identifying colorectal cancer symptoms. Only 22.90% of participants believe that colorectal cancer occurs around age 60. (42.20%) of participants are unaware of the NHS colorectal cancer screening program.ConclusionAccording to our findings, there is insufficient understanding of the colorectal cancer symptoms and risk factors among the general population in Syria that may contribute to delays in detecting the diagnosis of colorectal cancer. Consequently, there is a greater need to increase colorectal cancer awareness and education programs on the disease's signs and symptoms and its risk factors.
Development of A RPA-CRISPR/Cas12a Based Rapid Visual Detection Assay for Porcine Parvovirus 7
Authors: Wen Shubo , She Lemuge , Dang Sheng , Liao Ao , LV Xiangyu , Zhang Shuai , Zhang Kaiyue , Li Xiaorui , Song Yang , Li Xiangyang , Zhai Jingbo 
Published: May 2023

Abstract
Background Porcine Parvovirus (PPV) are small, enveloped viruses with single stranded genomic DNA. Till now seven genotypes of PPV have been detected worldwide. They are PPV1 to PPV7 with later was first discovered in 2016 in America and then in Asia and European. It has been reported that PPV7 was a co-infector with Porcine Circovirus 2 (PCV2), PCV3 and Porcine reproductive and respiratory syndrome virus (PRRSV). A rapid, sensitive and specific PPV7 detection method that could be applied in poorly equipped laboratory or event in field could be helpful to reveal its distribution and control the spread of this virus. CRISPR/Cas based systems have exhibited outstanding capacities in the detection of pathogenic microorganisms due to the trans-cleavage activities of the Cas proteins.Results Herein, we established a recombinase polymerase amplification (RPA)-CRISPR/Cas12a based rapid viral detection assay for PPV7. Specific RPA primers and five CRISPR RNAs (crRNAs) were designed and synthesized based on the highly conserved region within the NS1 gene of PPV7. The concentration of crRNA and ssDNA were further optimized. Furthermore, we evaluated the sensitivity, specificity, and clinical effectiveness of the RPA-Cas12a based detection assay. The results indicated that this method could be applied for real-time detection. The detection sensitivity of the novel assay was 100 copies/µl, and there were no cross-reactions with other genotypes of PPV, PCV2, PCV3, PRRSV and pseudorabies virus. The RPA-Cas12a based assay could work well in the detection of clinical samples.Conclusions In summary, we developed a visual, sensitive and specific viral diagnostic method based on CRISPR-Cas12a system for PPV7.
Incidence, Risk Factors and Outcomes of Catheter Related Bloodstream Infections Among Adult Filipino Hemodialysis Patients: A Retrospective Cohort Study
Authors: Pasilan Renz Michael , Tomacruz-Amante Isabelle Dominique , Dimacali Coralie Therese 
Published: May 2023

Abstract

Background: Despite efforts to improve the management of catheter-related bloodstream infections (CRBSI) in literature, temporary CVCs continue to be used for maintenance hemodialysis outside of acute care settings, particularly in the Philippines.
Methods: We conducted a retrospective cohort study to investigate the incidence, outcomes, risk factors, and microbiological patterns of CRBSI among adult kidney disease patients undergoing hemodialysis at the Philippine General Hospital, the country's largest tertiary referral center. We included all adult patients who received a CVC for hemodialysis from January 1, 2018 to August 31, 2019, and followed them for six months to observe the occurrence of CRBSI and its outcomes.
Results: Our study documented a CRBSI incidence rate of 6.72 episodes per 1000 catheter days, with a relapse rate of 6.60%, a reinfection rate of 15.74%, and a mortality rate of 6.09%. We identified autoimmune disease, dialysis frequency of > 3x per week, use of CVC for either blood transfusion or IV medications, renal hypoperfusion, drug-induced nephropathy, and hypertensive kidney disease as significant risk factors for CRBSI. Gram-negative bacteria, including Burkholderia cepacia, Enterobacter, and Acinetobacter spp, were the most common organisms causing CRBSI. Multidrug resistant organisms (MDROs) comprised almost half of the isolates (n=89, 44.5%), with Coagulase negative Staphylococcusspecies, having the highest proportion among gram positive organisms and Acinetobacterspp. among gram negative isolates.
Conclusion: Our findings emphasize the need for more stringent measures and interventions to prevent the propagation of identified pathogens, such as a review of sterile technique and adequate hygiene practices, continued surveillance, and expedited placement and utilization of long-term access for patients on maintenance hemodialysis. Furthermore, CVC use outside of hemodialysis should be discouraged, and common antibiotic regimens such as piperacillin-tazobactam and fluoroquinolones should be reviewed for their low sensitivity patterns among gram-negative isolates. Addressing these issues can improve outcomes for hemodialysis patients and reduce the burden of CRBSI in our institution.
Verifying Programs with Logic and Extended Proof Rules: Deep Embed v.s. Shallow Embed
Authors: Wang Zhongye , Cao Qinxiang , Tao Yichen 
Published: May 2023

Abstract

Many foundational program verification tools have been developed to build machine-checkable program correctness proofs, a majority of which are based on Hoare logic. Their program logics, their assertion languages, and their underlying programming languages can be formalized by either a shallow embedding or a deep embedding. Tools like Iris and early versions of VST choose different shallow embeddings to formalize their program logics. But the pros and cons of these different embeddings were not yet well studied, and we mainly focus on the impact of the program logic's embedding on logic's proof rules.
This paper considers a set of useful extended proof rules, and four different logic embeddings: one deep embedding and three dominant shallow embeddings. We prove each rule's validity under these embeddings and discuss their main challenges. Furthermore, we propose a method to lift existing shallowly embedded logics to deeply embedded ones to greatly simplify proofs of extended rules in a proof system. We evaluate our results on two existing verification tools. We lift the originally shallowly embedded VST to our deeply embedded VST to support extended rules, and we implement Iris-CF and deeply embedded Iris-Imp based on the Iris framework to evaluate our theory in real verification projects.
Machine learning-based prediction model of acute kidney injury in patients with acute respiratory distress syndrome
Authors: Wei Shuxing , Zhang Yongsheng , Dong Hongmeng , Chen Ying , Wang Xiya , Zhu Xiaomei , Zhang Guang , Guo Shubin 
Published: May 2023

Abstract
Background
Acute kidney injury (AKI) can make cases of acute respiratory distress syndrome (ARDS) more complex, and the combination of the two can significantly worsen the prognosis. Our objective, therefore, is to utilize machine learning techniques to construct models that can promptly identify the risk of AKI in ARDS patients, and provide guidance for early intervention and treatment, ultimately leading to improved prognosis.
Method
We obtained data regarding ARDS patients from the Medical Information Mart for Intensive Care III (MIMIC-III) database and utilized 11 machine learning (ML) algorithms to construct our predictive models. We selected the best model based on various metrics, and visualized the importance of its features using Shapley additive explanations (SHAP). We then created a more concise model using fewer variables, and optimized it using hyperparameter optimization (HPO). Additionally, we developed a web-based calculator to facilitate clinical usage.
Result
A total of 928 ARDS patients were included in the analysis, of whom 179 (19.3%) developed AKI during hospitalization. A total of 43 features were used to build the model. Among all models, XGBoost performed the best. We used the top 10 features to build a compact model with an area under the curve (AUC) of 0.838, which improved to an AUC of 0.848 after the HPO.
Conclusion
Machine learning algorithms, especially XGBoost, are reliable tools for predicting AKI in ARDS patients. The compact model still retains excellent predictive ability, and the web-based calculator makes clinical usage more convenient.
Effective Probabilistic Feature for Adaptive Learning Model to Accelerate Approximate Nearest Neighbor Search
Authors: Jiang Jianfeng , Xu Shen , Gao Ying 
Published: May 2023

Abstract
The quantization-based approaches are the effective methods for solving the problems of approximate nearest neighbor search. However, many quantization-based approaches usually employ an uniformed number of nProbes as termination condition to performing search process for each query. This will result in extra time consumption due to the fact that the search for many queries is terminated rapidly before completely retrieve the points contained in its nProbes nearest subspace. To this end, we propose to train an uniformed learning prediction model using effective input features generated by locality sensitive hashing, such that adaptively predicts the termination condition for each query to speedup the query process. Many experiments show that our proposal is superior to other state-of-the-art methods.
A hospital based study using micro-environmental modelling demonstrating the association between Coronary Artery Calcification score and cumulative air pollutant exposure: An explorative study
Authors: Viramgami Ankit , Madia Mehul M , Mansuri Moinuddhin , Rana Yashpal , Sheth Megha , Patel Samir , Garachh Millin , Vyas Pooja , Kotak Preet , Patel Niyati , Patel Dinesh , Balachandar Rakesh 
Published: May 2023

Abstract
Background & Objective: Exposure to air pollutant is a threat to human health. Present study explored the association between air pollutant exposure from all potential sources using micro-environment modelling and the risk of cardiovascular illness.
Methods: Present hospital based study recruited consecutive consenting patients, requiring coronary artery calcification (CAC) evaluation, after obtaining institutional human ethics approval. Fifty participants each with CAC scores <100, 100–399 and ≥400, categorized as low, intermediate and high risk respectively were recruited. Details on basic demographics, exposure to the air pollutants from individual microenvironments viz. indoors, workplace and outdoors were collected by interview. The cumulative exposure risk hours, from individual microenvironments and total exposure was estimated using mathematical modelling. Additionally cumulative PM2.5 exposure was estimated for a fraction of the participants. The association between exposure to air pollutants and risk for the coronary artery disease was evaluated with standard statistics.
Observations: Increasing age and male sex were significantly associated with CAC scores. Air pollutant exposure at outdoors and workplace were independently (p < 0.05) associated with higher CAC risk. Cumulative PM2.5 exposure residential locations, exhibited a trend of association (p > 0.05) with high risk CAC group
Conclusion: Exposure to air pollutant from workplace and outdoors were significantly associated with higher risk for coronary artery diseases. Age and male sex were independently and significantly associated with higher risk for coronary artery diseases. Current study reinforce the detrimental cardiovascular effects of air pollutant exposure independently using micro-environmental modelling and quantitative PM2.5 estimation.
Reproductive characteristics of reciprocal hybrid lineages derived from hybridization between Megalobrama amblycephala × Culter alburnus
Authors: Ding Xue , Zhang Yifei , Li Die , Xu Jia , Wu Chang , Cui Xiaojuan , Sun Yuandong 
Published: May 2023

Abstract
Background Distant hybridization is an important breeding technique for creating new strains with superior traits by integrating two different genomes. Successful hybridization of Megalobrama amblycephala (BSB, 2n = 48) and Culter alburnus (TC, 2n = 48) was achieved to establish hybrid lineages (BT and TB), which provide valuable materials for exploring the mechanisms of distant hybridization fertility. In this study, the gonadal tissue transcriptomes of BSB, TC, BT-F1, and TB-F1 were sequenced using Illumina high-throughput sequencing technology to analyze the reproductive characteristics of BT and TB.Results Differential gene expression analysis showed that the differentially expressed genes in BT vs BSB and BT vs TC were mainly enriched in signaling pathways not directly associated with meiosis. The differentially expressed genes of TB vs BSB and TB vs TC were mainly enriched in pathways related to meiosis, and most of them were down-regulated, indicating that meiosis is suppressed in TB. UD (under-dominance) genes were enriched in pathways related to meiosis and DNA repair in TB. OD (over-dominance) genes were enriched in MAPK signaling pathway, and ELD-B (expression level dominance-BSB) genes were enriched in pathways related to steroid hormone synthesis in both BT and TB.Conclusions These results suggest that meiotic progression may not be affected in BT, whereas it is clearly inhibited in TB. Offspring of M. amblycephala maternal parent may have better genomic compatibility and fertility. Our study provides important information on the molecular mechanisms of breaking reproductive isolation in distantly hybridized fertile lineages.
Recurrent superior orbital fissure syndrome associated with VEXAS syndrome
Authors: Myint Katie , Patrao Namritha , Vonica Oana , Vahdani Kaveh 
Published: May 2023

Abstract
Purpose
To describe a case of recurrent orbital inflammation and superior orbital fissure syndrome associated with VEXAS (vacuoles, E1 enzyme, X-linked, auto-inflammatory, somatic) syndrome.
Case presentation
VEXAS syndrome is a recently identified multi-system inflammatory disease of late adult onset. The authors describe the case of a 76-year-old man who presented with recurrent episodes of orbital inflammation, with superior orbital fissure syndrome, dacryoadenitis and orbital myositis. He had a constellation of systemic disorders including recurrent chest infections, congestive cardiac failure, pulmonary emboli and skin rashes. The underlying diagnosis of VEXAS syndrome was confirmed by genetic testing, which revealed the UBA1 mutation.
Conclusion
VEXAS syndrome should be considered in the differential diagnosis of orbital inflammatory disease associated with multi-system inflammatory disorders.
Carbon Nanotube/Chitosan Hydrogel for Adsorption of Acid Red 73 in Aqueous and Soil Environments
Authors: Wei Jia , Yan Luchun , Zhang Zhifang , Hu Bing , Gui Wenjun , Cui Yanjun 
Published: May 2023

Abstract
Acid red 73 is an azo dye, and its residue can pollute the environment and seriously threaten human health and life. In this study, a composite adsorbent with a three-dimensional network structure was prepared by modifying chitosan hydrogel with multiwalled carbon nanotubes, and its ability to remove acid red 73 from aqueous and soil environments was evaluated. In the aqueous samples, 70 mg of the adsorbent realized a saturated adsorption capacity of 101.07 mg/g and a removal rate of 92.23% at pH = 5. The thermodynamics conformed with the Langmuir adsorption isotherm and pseudo second-order adsorption kinetic models. In the soil samples, 100 mg of the adsorbent realized 24.73mg/g adsorption capacity 49.45% removal rate. When the pH of the soil was between 4–7, the removal rate and adsorption capacity do not change much; hence, the pH is maintained between 5.2–6.8, which is very suitable for the growth of general plants. The experimental results demonstrated that the composite adsorbent maintained a microporous structure and good removal rate of acid red 73 over multiple adsorption cycles.