bluuebunny/crossref_metadata_2025_split huggingface dataset:
An improved feature selection algorithm for cow subclinical mastitis
Authors: DAI YONGQIANG , WANG ZHIHUI , LIU HUAN , LIU LEILEI 
Published: May 2023

Abstract
Background
Features of Dairy Herd Improvement dataset used for diagnosing subclinical mastitis in dairy cows contain important information about whether cows have subclinical mastitis, but they may also contain features that are unrelated or weakly related to the disease. The existence of these irrelevant or weakly correlated feature data increases the prediction time using machine learning models on the one hand, and reduces the accuracy of prediction on the other hand. In order to improve the prediction efficiency of the machine learning model of subclinical mastitis in dairy cows, feature selection is needed for Dairy Herd Improvement data.
Results
In this paper, an improved moth-flame feature selection algorithm was proposed and applied to the classification and prediction of subclinical mastitis in dairy cows. By introducing the dynamic adjustment strategy of flight direction and the position crossover strategy, the algorithm continuously generates new individuals while dynamically adjusting the flight direction of moths, which effectively avoids the feature selection algorithm falling into local optimum. By adaptively adjusting the number of flames, the population diversity is enhanced in the global exploration stage of the algorithm, and the premature convergence of the feature selection algorithm is avoided.
Conclusion
The improved feature selection algorithm and other comparison algorithms are experimentally verified on University of California Irvine (UCI) data sets and dairy cow subclinical mastitis disease data sets. The experimental results showed that the algorithm had better feature screening ability than other algorithms, and effectively improved the prediction performance of dairy cow recessive mastitis disease.
Implementation of a Machine Learning Approach to Model and Assess Student Spatial Intelligence for Advancing STEM Education
Authors: Zafari Mostafa , Koochi Fatemeh , Sadeghi-Niaraki Abolghasem , Choi Soo-Mi , Tamer Abuhmed 
Published: May 2023

Abstract
Spatial intelligence (SI) is the leverage that helps students to have a deeper understanding of concepts of science, technology, engineering and mathematics (STEM) and obtain outstanding academic achievement in STEM. The main objective of this research is to find effective factors in SI. Then, based on those factors, a machine learning (ML) model is developed for estimating students’ SI. To do that, data of 40 features such as demographic, behavioral, environmental and interest were collected from 396 high school students. Chi2, Boruta and Genetic algorithms were employed for identifying the most important features. Subsequently, 18 features were used to develop ML models. The ML models (Random Forest, Support Vector Machines, Multi-Layer Perceptron) achieved accuracy rates of 0.89, 0.84, and 0.78 on the test set. The stack model further increased accuracy to 0.92. The findings of this research have important implications in STEM. The model can estimate students' academic achievement in STEM by measuring their SI and using this for major selection, reducing the dropout rate, predicting student performance, and identifying and helping weaker students. Furthermore, by improving students' SI using the identified features, the quality of education can be enhanced, leading to more efficient and effective learning outcomes for students.
Facial expression intensity estimation using label-distribution-learning-enhanced ordinal regression
Authors: Xu Ruyi , Wang Zhun , Chen Jingying , Zhou Longpu 
Published: May 2023

Abstract
Facial expression intensity estimation has promising applications in health care and affective computing, such as monitoring patients’ pain feelings. However, labeling facial expression intensity is a specialized and time-consuming task. To overcome the lack of labeled data, a variety of ordinal regression (OR) models have been presented to estimate the relative intensity of each expression image within a sequence in an unsupervised setting. However, these models cannot estimate absolute intensity without actual intensity labels. To overcome this problem, this paper introduces the label-distribution-learning-enhanced OR (LDL-EOR) approach for facial expression intensity estimation. LDL-EOR learns relative intensity with OR and absolute intensity by using the label distribution to resist the noisy labels caused by the biases of manual and automatic labeling. This design aims to improve the accuracy of absolute intensity estimation while keeping the cost of manual labeling low. The label distribution is converted into a continuous intensity value by calculating the mathematical expectation, which makes the prediction results meet both relative and absolute intensity constraints. Ensuring the feasibility of LDL-EOR in different supervised settings, this paper presents a unified label distribution generation framework to automatically rela-bel training data frame by frame. The generated soft labels are used to supervise the LDL-EOR model and enhance its robustness to the noise existing in the original labels. Numerous experiments were conducted on three public expression datasets (CK+, BU-4DFE, and PAIN) to validate the superiority of LDL-EOR relative to other state-of-the-art approaches.
Arterial systolic hypertension and End Stage Renal Diseases in young patients: an epidemiologic survey on the Sicilian Registry of Nephrology, Dialysis, and Transplantation.
Authors: Calabrese Vincenzo , Cernaro Valeria , Gembillo Guido , Longhitano Elisa , Conti Giovanni , Battaglia Giorgio , Santoro Domenico , Casuscelli Chiara 
Published: May 2023

Abstract
Background: Audits allow analyzing of the delivery of care and the prevalence of diseases. This study investigated kidney diseases’ impact on ERSD in patients below 30 years.
Methods: This study evaluated patients who started dialysis before 30 years retrieved in Sicilian Registry of Nephrology, Dialysis and Transplantation. The population was divided into two groups, according to the presence or absence of specific diagnosis. Baseline features were reported as mean±sd, median[IQR], n(%). Student-T-test or Mann-Whitney-test or Pearson-Chi-Square-test were performed. Logistic regression analysis was performed to detect the association between the variables and the unknown diagnosis, and each variable related with a pvalue less than 0.2 was added in multivariate model. ROC-curve were performed included multivariate predicted value as independent variable.
Results: 145patients started dialysis before the 30years. Between patients with and without diagnosis, ACEI intake and blood pressure differed enough to be considered as possible confounding. Logistic regression showed blood pressure and ACEI seemed to be related to the unknown diagnosis. Roc-curve provided an AUC=0.689.
Conclusion: Although KDIGO didn’t include hypertension among biopsy indications, our data suggested to perform biopsy in young patients with hypertension and worsening in renal function could improve kidney diagnosis management.
Procedure-Specific Risks of Robotic Simultaneous Resection of Colorectal Cancer and Synchronous Liver Metastases
Authors: Radomski Shannon N. , Chen Sophia Y. , Stem Miloslawa , Done Joy Zhou , Atallah Chady , Safar Bashar , Efron Jonathan E. , Gabre-Kidan Alodia 
Published: May 2023

Abstract
An estimated 25% of patients with colorectal cancer (CRC) present with distant metastases at the time of diagnosis, the most common site being the liver. Controversy exists regarding the safety of a simultaneous versus staged approach to resections in these patients, but reports have shown that minimally invasive surgery (MIS) approaches can mitigate morbidity. This is the first study utilizing a large national database to investigate colorectal and hepatic procedure-specific risks in robotic simultaneous resections for CRC and colorectal liver metastases (CRLM). Utilizing the ACS-NSQIP targeted colectomy, proctectomy, and hepatectomy files, 1,550 patients were identified who underwent simultaneous resections of CRC and CRLM from 2016–2020. Of these patients, 311 (20%) underwent resections by an MIS approach, defined as an either laparoscopic (n = 241, 78%) or robotic (n = 70, 23%). Patients who underwent robotic resections had lower rates of ileus compared to those who had an open surgery. The robotic group had similar rates of 30-day anastomotic leak, bile leak, hepatic failure, and post operative invasive hepatic procedures compared to both the open and laparoscopic groups. The rate of conversion to open was significantly lower for robotic compared to laparoscopic group (9% vs. 22%, p = 0.012). This report is the largest study to date of robotic simultaneous CRC and CRLM resections reported in the literature and supports the safety and potential benefits of this approach.
Effect of surface diffusion on rapid gas transport in carbon nanotubes
Authors: Wang Xudi , Xu Feng , Liu Wenhui , Zheng Yiming , Bi Hailin , Cao Qing 
Published: May 2023

Abstract
Many studies on carbon nanotubes (CNTs) have revealed that gas transport behaves differently at the nanoscale compared to the macroscale. While traditional gas transport models do not account for the effect of adsorption, as the adsorbed gases at the macroscopic level are relatively minor and can be ignored, the significant specific surface area of nanochannels leads to a significant increase in the proportion of adsorbed gases. Therefore, the impact of adsorption on gas transport must be taken into consideration. In this study, the diffusion and adsorption behaviors of different gas molecules inside CNTs of different diameters were simulated based on equilibrium molecular dynamic and Grand canonical Monte Carlo methods. The transport diffusion coefficients of gases were calculated using flux correlation functions, and the surface diffusion coefficients of gases were derived by combining with rarefied gas kinetics. The results show that the transport diffusion coefficients of gases in carbon nanotubes are several times or even one order of magnitude higher than those calculated by Knudsen's equation, and the surface diffusion of adsorbed molecules in carbon nanotubes is responsible for the rapid transport, and for the first time, the surface diffusion coefficient of different adsorbed gases in CNTs at different pressures and diameters is derived.
Twenty-seven-gauge vitrectomy: A consecutive, single-centre case series with exclusive use over a 4-year period.
Authors: Ng Eugene , Masalkhi Mouayad , Steel David H. , Pavičić-Astaloš Jasna , Nolan Claire , Mernagh Sarah , Ankamah Emmanuel 
Published: May 2023

Abstract
Background: To assess the safety and effectiveness of the exclusive use of 27-gauge instruments for all vitreoretinal diseases requiring vitrectomy.
Methods: In this retrospective study, 1020 consecutive surgeries were performed on 958 eyes of 848 patients using 27-gauge instruments from March 2017 to June 2021. Patients with a minimum follow-up of 3 months were included. Surgical case-mix, best-corrected visual acuity (BCVA), intraocular pressure (IOP), intra- and post-operative complications, and surgery times were recorded.
Results: The study patients were followed up for averagely 11 months. Of the 1020 vitrectomies, 958 were primary procedures. Of the 148 retinal detachment (RD) cases, 138 (93%) required a single vitrectomy. Primary macular hole closure was achieved in 143 of 145 (99%) cases. The average surgical times were 55 and 38 minutes for RD surgeries and for all other indications, respectively.
BCVA improved significantly at the final visit (20/49) compared with the pre-operative visit (20/78) (p<0.01). IOP was similar at the pre-operative (14.8mmHg) and final (14.3mmHg) visits. Complications recorded include transient hypotony in 39 eyes, iatrogenic retinal breaks in 2 eyes, and a vitreous bleed in 1 other eye.
Conclusion: This study revealed that 27-gauge vitrectomy instruments can be used for a wide range of indications, with exclusive use in certain settings. The outcomes were similar to other gauges, including for rhegmatogenous retinal detachment, with minimal complications.
The Influencer Effect of Dexmedetomidine on Radioiodine Relevant to Lacrimal Gland Impairment Running Title: Dexmedetomidine on Radioionized Lacrimal Gland
Authors: Şingar Evin , Akbulut Aylin , Koca Gökhan , Yazıhan Nuray , Atılgan Hasan İkbal , Yumuşak Nihat , Demir Ayten , Burcu Ayse , Korkmaz Meliha 
Published: May 2023

Abstract
Purpose
To assess the potential influencing effects of Dexmedetomidine (DEX) at impaired lacrimal glands after high-dose radioiodine treatment (RAI).
Materials and methods
Thirty-six rats were arbitrarily seperated into 3 groups; Sham, RAI and DEX group. DEX group were given DEX and RAI, Sham group were given same millimeters of saline and RAI group were given RAI only. All forms of lacrimal glands including harderian glands (HG), extraorbital (EG) and intraorbital (IG) lacrimal glands were evaluated for immunohistochemic, histopathologic assessments and also for tissue cytokines, oxidant and antioxidant levels.
Results
DEX significantly ameliorated histopathologic changes such as; periacinar fibrosis, acinar atrophy, lymphocytic infiltration, ductal proliferation, lipofuscin-like accumulation, and nucleus changes caused by RAI in all lacrimal gland forms (p < 0.05 for all of the parameters). However, periductal fibrosis was improved significantly only in EG (p = 0.049) and mast cell infiltration was improved significantly only in IG (p = 0.038) in DEX groups. There was a significant decrease in the elevated caspase-3 and TUNEL levels after RAI administration in the DEX group in all lacrimal gland forms (p < 0.05 for all parameters). DEX attenuated NF-kb, TNF-α, IL-6 levels and significantly diminished total oxidant status and raised total antioxidant status levels (p < 0.05 for all of the parameters).
Conclusions
The results of this study demonstrated that following RAI, DEX diminished inflammation, tissue cytokine levels and apoptosis and ameliorated impaired histopathologic pattern of the lacrimal glands.
Deciphering spatial domains from spatial multi-omics with SpatialGlue
Authors: Long Yahui , Ang Kok Siong , Liao Sha , Sethi Raman , Heng Yang , Zhong Chengwei , XU Hang , Husna Nazihah , Jian Min , Ng Lai Guan , Chen Ao , Gascoigne Nicholas , Xu Xun , Chen Jinmiao 
Published: May 2023

Abstract

Integration of multiple data modalities in a spatially informed manner remains an unmet need for exploiting spatial multi-omics data. Here, we introduce SpatialGlue, a novel graph neural network with dual-attention mechanism, to decipher spatial domains by capturing the significance of each modality and neighbor graph in cross-omics and intra-omics integration. We demonstrate that SpatialGlue can accurately aggregate cell types into spatial domains at a higher resolution across different tissue types and technology platforms, as well as gain biological insights into cross-modality spatial correlations.
Information System Usage Behavior: Employees’ Identification, Gender, and Collectivism Perspective
Authors: Arshad Muhammad , Farooq Mariam , Farooq Omer , Afzal Sadia 
Published: May 2023

Abstract
We explore concurrent interactive effects by examining how employees’ cultural differences and gender interact with organizational identification to influence their adoption of a new information system (IS). Using social identity theory, we present an integrated model to understand the effect of organizational identification on employees' IS usage behavior through the mediation of attitude, along with the moderating role of gender and cultural orientations (i.e., collectivism). Data were obtained from 370 respondents working in different banks. The hypothesized model was tested using structural equation modeling. The results indicate that organizational identification positively influences employees’ adoption of new banking IS via the full mediation of attitude. Furthermore, both gender and employees' cultural orientation appear as important and significant boundary conditions of this process.
Orbital pathways for a Lunar-Ejecta Origin of the Near-Earth Asteroid Kamo`oalewa
Authors: Malhotra Renu , Rosengren Aaron , Castro-Cisneros Jose 
Published: May 2023

Abstract
The near-Earth asteroid, Kamo‘oalewa (469219), is one of a small number of known quasi-satellites of Earth. Numerical simulations show that it transitions between quasi-satellite and horseshoe orbital states on centennial timescales, maintaining this dynamics over megayears. Its reflectance spectrum suggest a similarity to lunar silicates. Considering its Earth-like orbit and its physical resemblance to lunar surface materials, we explore the hypothesis that it might have originated as a debris-fragment from a meteoroidal impact with the lunar surface. We carry out numerical simulations of the dynamical evolution of particles launched from different locations on the lunar surface with a range of ejection velocities. As these ejecta escape the Earth-Moon environment and evolve into heliocentric orbits, we find that a small fraction of launch conditions yield outcomes that are compatible with Kamo‘oalewa’s dynamical behavior. The most favored conditions are launch velocities slightly above the escape velocity from the trailing lunar hemisphere.
Making carbon nanotube films viscoelastic, ductile and repairable by forming a double network with branched polyethylenimine
Authors: Wang Xin , Zhang Xin , Zou Jingyun , Zhao Jingna , Zhang Yongyi , Li Qingwen , Zhang Xiaohua 
Published: May 2023

Abstract
Manipulating nanostructure assemblies is a key to promote their applications as structural and functional materials. For carbon nanotubes (CNTs), it is absent of the ability to reconstruct their entangled network. In this work, we report a strategy to realize efficient manipulation of CNT networks by forming a double network using branched polyethylenimine. The double network is highly viscoelastic and ductile for the efficient film stretching or creeping toward high CNT alignment, which can dramatically improve the mechanical strength of CNT films. Under the viscous drag from the polymer network, CNTs show enhanced movability to reconstruct new networks, making the film repairable. A key origin of such repairability lies in the branched polymeric structure. This double-networking strategy provides a new possibility to manipulate CNT assemblies toward high-performance applications.
Cepharanthine, a regulator of keap1-Nrf2, inhibits gastric cancer growth through oxidative stress and energy metabolism pathway
Authors: Lu Yangyang , Zhu Chunyang , Ding Yixin , Wang Bing , Zhao Shufen , Lv Jing , Chen Shuming , Wang Shasha , Wang Yan , Wang Rui , Qiu Wensheng , Qi Weiwei 
Published: May 2023

Abstract
Cephalanthine (CEP), a bioactive compound derived from Stephania Cephalantha Hayata, is cytotoxic to various malignancies. However, the underlying mechanism of gastric cancer is unknown. CEP inhibited the cellular activity of gastric cancer AGS and HGC27 cell lines in this study. CEP induced apoptosis, reduced Bcl-2 expression, and increased cleaved caspase 3, cleaved caspase 9, Bax, and Bad expression. CEP caused a G2 cell cycle arrest and reduced cyclin D1 and cyclin-dependent kinases 2 (CDK2) expression. Meanwhile, it increased oxidative stress, decreased mitochondrial membrane potential, and enhanced reactive oxygen species (ROS) accumulation in AGS and HGC27 cells. Mechanistically, CEP inhibited Kelch-like ECH-associated protein (Keap1) expression while activating NF-E2 related factor 2 (Nrf2) expression, increasing transcription of Nrf2 target genes quinone oxidoreductase 1 (NQO1), heme oxygenase 1 (HMOX1), and glutamate-cysteine ligase modifier subunit (GCLM). Furthermore, a combined analysis of targeted energy metabolism and RNA sequencing revealed that CEP could alter the levels of metabolic substances such as D (+) - Glucose, D-Fructose 6-phosphate, citric acid, succinic acid, and pyruvic acid, thereby altering energy metabolism in AGS cells. In addition, CEP significantly inhibited tumor growth in MFC BALB/c nude mice in vivo, consistent with the in vitrofindings. Overall, CEP can induce oxidative stress by regulating Nrf2/Keap1 and alter energy metabolism, resulting in anti-ovarian tumor effects. Our findings suggest a potential application of CEP in gastric cancer treatment.
Long COVID: Plasma levels of neurofilament light chain in mild COVID-19 patients with neurocognitive symptoms
Authors: Gutman Elisa , Salvio Andreza , Fernandes Renan , Duarte Larissa , Raposo-Vedovi Jessica , Alcaraz Helena , Teixeira Milene , Passos Giselle , de Medeiros Karoline , Hammerle Mariana , Pires Karina , Vasconcelos Claudia , Leon Luciane , Figueiredo Claudia , Alves-Leon Soniza 
Published: May 2023

Abstract

It is well known the potential of severe acute respiratory coronavirus type 2 (SARS-CoV-2) infection to induce post-acute sequelae, a condition called Long COVID. This syndrome includes several symptoms, but the central nervous system (CNS) main one is neurocognitive dysfunction. Recently it has been demonstrated the relevance of plasma levels of neurofilament light chain (pNfL), as a biomarker of early involvement of the CNS in COVID-19. The aim of this study was to investigate the relationship between pNfL in patients with post-acute neurocognitive symptoms and the potential of NfL as a prognostic biomarker in these cases. A group of 63 long COVID patients ranging from 18 to 59 years-old were evaluated, submitted to a neurocognitive battery assessment, and subdivided in different groups, according to results. Plasma samples were collected during the long COVID assessment and used for measurement of pNfL with the Single molecule array (SIMOA) assays. Levels of pNfL were significantly higher in long COVID patients with neurocognitive symptoms when compared to HC (p = 0.0031). Long COVID patients with cognitive impairment and fatigue symptoms presented higher pNfL levels when compared to long COVID patients without these symptoms, individually and combined (p = 0.0263, p = 0.0480, and 0.0142, respectively). Correlation analysis showed that levels of cognitive lost and exacerbation of fatigue in the neurocognitive evaluation had a significative correlation with higher pNfL levels (p = 0.0219 and 0.0255, respectively). Previous reports suggested that pNfL levels are related with higher risk of severity and predict lethality of COVID-19. Our findings demonstrate that SARS-CoV-2 infection seems to have a long-term impact on the brain, even in patients who presented mild acute disease. NfL measurements might be useful to identify CNS involvement in long COVID associated with neurocognitive symptoms and to identify who will need continuous monitoring and treatment support.