bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physical vulnerability of reinforced concrete buildings under debris avalanche impact based on GF-discrepancy and DEM-FEM
Authors: Pu Jian , Huang Yu , Guo Zhen , Bi Yandong 
Published: August 2023

Abstract
Debris avalanches caused by landslides often lead to building damage, and insufficient research has been conducted on the vulnerability of buildings, especially reinforced concrete (RC) buildings, to such impact disasters. Here, a vulnerability assessment framework for a two-story RC building based on the generalized F-discrepancy (GF-discrepancy)-based point selection strategy and discrete element method (DEM)-finite element method (FEM) is proposed. Considering the randomness of granular flow, including the impact height, impact velocity, and density, these three random variables are uniformly selected using GF-discrepancy, for a total of 134 samples. A deterministic analysis of each sample is performed to obtain the responses of the 134 samples according to the DEM-FEM coupling method, which can fully reflect the failure characteristics of RC buildings under mass flow impact. Given the qualitative vulnerability assessment, we select the inter-story displacement angle and the displacement of walls and columns in the responses as quantitative indicators defining the four damage states and the vulnerability of the building. The former is used to evaluate the overall damage state of the building, while the latter is applied to evaluate the local damage situation of the building as a correction to the first indicator. Ultimately, the vulnerability of the building is obtained corresponding to different impact indictors related to three random variables. This method provides not only the vulnerability of RC buildings under particle flow impact but also insight into vulnerability assessments of buildings in areas that are not currently in danger of such disasters.
Usefulness of lordosis load test and urinary biochemistry in diagnosis of orthostatic proteinuria
Authors: Tasaki Yuko , Yamamiya Mari , Taniyama Yuichi , Kasahara Ria , Yachi Yusuke , Fukuda Masaki , Obata Misato , Inoue Mika , Sakazume Shinobu , Ohta Kazuhide 
Published: August 2023

Abstract
Introduction Renal disease is commonly suspected in patients with proteinuria. Renal biopsy might be considered based on the patient’s clinical history and the results of diagnostic tests. However, as orthostatic proteinuria is benign and requires no treatment, it is important to obtain a diagnosis without renal biopsy whenever possible. Therefore, up to now, for the diagnosis of orthostatic proteinuria, in addition to resting urinalysis evaluation (disappear of proteinuria), we have performed the lordosis load test and performed urine biochemistry of the samples showing peak proteinuria in lordosis load test.
Method We retrospectively enrolled all patients who visited the pediatric department and underwent the lordosis load test at Kanazawa Medical Center between 2011 and 2020. In the present study, samples with the highest concentrations of protein after the lordosis load test were subjected to general urinary biochemistry and urinary sediment analysis. Patients were followed up with the lordosis load test for several years.
Results General urinary tests, urinary sediment and urinary biochemistry including N-acetyl-beta-D-glucosaminidase (NAG), alpha1-microglobulin(α1MG), and beta 2-microglobulin (β2MG) were normal in all patients with orthostatic proteinuria except one case who was premature baby.
Conclusion If proteinuria disappears after 2 hours of rest, and urinary biochemistry of the samples showing peak proteinuria in lordosis load test is normal, orthostatic proteinuria can be diagnosed more accurately.
Acute phase protein concentration in pharyngeal swabs from clinically healthy commercial dairy calves
Authors: Petersen Mette Bisgaard , Capion Nynne 
Published: August 2023

Abstract
Background
Early diagnosis of disease in calves are crucial for fast recovery and prudent use of antibiotics. Acute phase proteins (APP) are up- or downregulated in response to tissue injury and have been studied widely in human medicine. There is growing interest to use APPs as biomarkers for different diseases and as a tool to initiate and monitor treatment in veterinary medicine too. Pharyngeal swabs, tracheal aspirate (TA) and blood samples were collected from 84 clinically healthy commercial dairy calves and analyzed for the APPs serum amyloid A (SAA), haptoglobin (Hp) and lipopolysaccharide binding protein (LBP).
Results
We found detectable concentrations of SAA, Hp and LBP in pharyngeal swabs from calves, as well as in TA and serum. We found no correlations between APP concentrations in serum and TA nor pharyngeal swabs.
Conclusions
SAA, Hp and LBP can be measured in saliva and TA from calves. However, a considerably technical variation in the sampling method for both pharyngeal swab and TA exist, and further validation of the methods are needed.
The Effects Of Habitat On The Distribution Of Urban Ruderal Vegetation
Authors: YALÇINALP Emrah , DİHKAN Asena , Meral Alperen , AKBULUT Sefa 
Published: August 2023

Abstract
Ruderal habitats consist mostly of neutrophile plants that grow on specific areas such as remnant areas, ruins, and wall sides. The plants hold an important place in urban ecology due to their resistance to environmental conditions and anthropogenic impacts. Considering the past 20-year period, today’s rural areas will soon become urban areas in most parts of the world. Thus, this study will contribute to the phytoecological and phytosociological studies that will elaborately examine urban ruderal habitats in near future. The study was carried out in 30 different locations in five different land use types in Trabzon, Turkey. It aims to determine the ruderal vegetation diversity and the effect of habitat on ruderal vegetation. The results of the study revealed 83 species across 33 families. Despite the species diversity of the samples from the roadsides differed from that of other regions, the ruderal vegetation was distributed homogeneously, leading to the conclusion that habitat did not affect vegetation.
Radiative Forcing Bias Calculation Based on COSMO (Core-Shell Mie model Optimization) and AERONET data
Authors: Tiwari Pravash , Cohen Jason , Wang Xinying , Wang Shuo , Qin Kai 
Published: August 2023

Abstract
Direct radiative forcing (DRF) of aerosols is driven by aerosol concentration, size, and mixing state, and solar radiation. This work introduces Core-Shell Mie model optimization(COSMO) to compute top of the atmosphere (TOA) forcing based on inversely constrained BC size and mixing state from AERONET, over two rapidly developing areas: Lumbini and Taihu. COSMO has wider variability and less negative TOA than AERONET (13.0 ± 8.1 Watt/m2 at Lumbini and 15.6 ± 12.4 Watt/m2 at Taihu). These differences are driven by particle aging and size-resolved BC emissions, with up to 17.9% of cases warmer than the maximum AERONET TOA, and 1.9% net-warming. A linearized correction is deduced which can be immediately implemented by climate models, and suggested ranges of BC size- and mixing- observations are made for future campaigns. Given that the COSMO TOA bias and uncertainty are larger than the forcing of locally emitted GHGs, active consideration of BC is necessary to reduce climate uncertainty in developing areas.
Identification of immune cells and key genes related to periodontitis
Authors: Sun Yingyuan , Wang Chunxiao 
Published: August 2023

Abstract
Background
The aim of this study was to identify the immune cellular and molecular mechanisms of periodontitis and the important role of key genes in the pathogenesis of periodontitis.
Methods
GSE16134, GSE10334, and GSE23586 were obtained from the Gene Expression Omnibus (GEO) database, and CIBERSORT was applied to examine the constitution of 22 kinds of immune cells in all samples. Weighted gene coexpression network analysis (WGCNA) was employed to identify candidate module genes associated with periodontitis. The least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) algorithms were constructed to screen key genes. The key genes-related signaling pathways were explored through gene set variation analysis (GSVA). Moreover, the R package "RcisTarget" was adopted to predict transcription elements, and Cytoscape software was used to visualize the miRNA network. Constructing a nomogram model on the basis of the key genes expression level for the diagnosis of periodontitis.
Results
There were 427 periodontitis samples and 136 healthy samples. Periodontitis samples’ CD4 memory resting T cells were significantly higher, and WGCNA demonstrated that genes in the black module had the highest correlation with CD4 memory resting T cells. Seven genes, including AHNAK2, ALOX12B, CBR3, FAM57A, KLK8, KRT3, and TGM5, were associated with T cells in periodontitis. The identified key genes showed a strong correlation between immune cell infiltration levels and immune factors, primarily participating in multiple signaling pathways, including but not limited to the ESTROGEN RESPONSE EARLY, MYC TARGETS V2, G2M CHECKPOINT, and PI3K AKT MTOR signaling pathways. 73 miRNAs and 163 mRNA‒miRNA relationship pairs were identified, which were subsequently visualized. We constructed a nomogram model on the basis of the expression levels of the seven genes for diagnostic value, and the area under the AUC curve of the nomogram model was 0.937.
Conclusions
Periodontitis-related immune cells and key genes were identified, and the important role of key genes in the pathogenesis of periodontitis was explored through a series of bioinformatics analyses.
China’s sustainable carbon neutral supply chain management: A reference to global emission reduction
Authors: Chen Yongxiu , Lee Chien-Chiang , Zhu Shanzhan 
Published: August 2023

Abstract
Carbon emissions dominate the main issues in the process of energy consumption, and numerous countries are committed to reducing such emissions with a focus on carbon neutrality. To narrow down the research gap, this research considers carbon emission reduction in industry by applying supply chain management (SCM) under monopolistic competition with carbon neutral indicators. We develop a mathematical model within an agent-based simulation model and perform the design experimental methods to achieve the optimal decision-making of supply chain carbon neutral indicators. Findings show that green-credit policies and preferences of green products are effective carbon neutral indicators in SCM that help reduce global carbon emissions. Our research not only offers a reference and inspiration for the China government to reduce carbon emissions, but also helps government decision-makers explore the optimum level and decision-making of green credit and preferences of green products in a supply chain environment. Lastly, it enables manufacturers to achieve profit maximization and move towards carbon neutrality.
Automatic segmentation model of primary central nervous system lymphoma based on multiple sequences of magnetic resonance images using deep learning
Authors: Lu Guang , Zhou Wei , Zhao Kai , Miao Lixin , Wang Wenjia , Wang Qingyu , Zhang Xuefen , Gong Yuping , Mou Weiwei 
Published: August 2023

Abstract
Purpose and Background. Accurate quantitative assessment of PCNSL by gadolinum-contrast Magnetic resonance imaging (MRI) is closely related to therapy planning, surveillance and prognosis, However, precise volume assessment by manual segmentation is time-consuming and subject to high intra- and interrater variabilities by imaging readers, with poor consistency. In order to solve this problem, we constructed a multimodal artificial intelligence deep learning segmentation model based on multi-sequence MRI images of patients with PCNSL and identified its efficiency, so as to quantitatively calculate volume and other indicators, and compare the consistency and accuracy with doctors' labeling methods.
Materials and Methods. A total of 41 PCNSL patients from six Chinese medical centers with pathologically confirmed PCNSL were analyzed. Region of interest (ROI) was manually segmented on contrast-enhanced T1-weighted and T2 scans. Fully automated voxelwise segmentation of tumor components was performed using a 3D convolutional neural network (DeepMedic) trained on gliomas (n = 220). deep-learning model (DLM) segmentations were compared to manual segmentations performed in a 3D voxelwise manner by two readers (radiologist and neurosurgeon; consensus reading) from T1 CE and FLAIR, which served as the reference standard. The Dice similarity coefficient (DSC) were used to evaluate the performance of the models. Successful detection of PCNSL was defined if the DLM obtained a spatial overlap with the manual segmentation of the tumor core (at least one voxel, DSC >0). Mann-Whitney U test was applied to compare continuous variables, while chi-squared test was used for categorical variables between groups. A two-tailed P value <0.05 indicated statistical significance.
Results. The DLM detected 66 of 69 PCNSL, representing a sensitivity of 95.7%. Compared to the reference standard, DLM achieved good spatial overlap for total tumor volume (TTV, union of tumor volume in T1 CE and FLAIR; average size 77.16 ± 62.4 cm3, median DSC: 0.76) and tumor core (contrast enhancing tumor in T1 CE; average size: 11.67 ± 13.88 cm3, median DSC: 0.73). High volumetric correlation between automated and manual segmentations was observed (TTV: r= 0.88, P < 0.0001; core: r = 0.86, P < 0.0001). Performance of automated segmentations was comparable between pre-treatment and follow-up scans without significant differences (TTV: P = 0.242, core: P = 0.177).
Conclusion. Compared to manual segmentation on routine clinical MRI images, our automatic segmentation model of PCNSL based on multiple sequences of MRI images displayed comparable segmentation in both pretherapy and the process of the treatment, despite the complex and multifaceted appearance of this lymphoma subtype , implying its immense potential to be used in the whole follow-up monitoring process of PCNSL.
Robotic Arm Trajectory Based on Machine Learning for tracking the wound
Authors: Simango Doubt , Mushiri Tawanda , Yahya Abid , Ndaimani Augustine 
Published: August 2023

Abstract
Due to uncontrolled bleeding in victims and frequently delayed emergency response times to road accidents had frequently causes severe casualties. To solve this problem, the robotic arm used in this paper, based on machine learning, is programmed to monitor and react to bleeding in accident victims. A clotting agent is applied to the wounds by the robotic arm at the touch of a button, stopping the bleeding and possibly saving lives. The system's image processing and wound classification were done in a Python-based Jupyter environment. SolidWorks was used to design the robotic arm, which was programmed to respond to input from a Python model. The robotic arm's kinematics was tested in the Simulink environment, displaying the joints' successful operation. The robotic arm design was further analyzed in the Simcape environment, where the arm's trajectory was evaluated. The results showed that the robotic arm could effectively move toward the detected wound, following the training trajectory. Object tracking was successfully performed in Matlab under the Simcape environment, as evidenced by the alignment between the expected and actual trajectory line graphs. The study concludes that the machine learning-based robotic arm can accurately move to any desired position within its workspace, enabling the precise application of the clotting agent on the wound. This system holds significant potential for improving emergency response times and outcomes in road accidents.
The Relationship of Pre-Pregnancy Body Mass Index with Maternal Anthropometric Indices, Weight Retention and the Baby's Weight and Nutrition in the First 6 Months Post-partum
Authors: Ahmadibeni Ayda , Kashani Parhoon , Hallaj Mohammad Sadegh , Ghanbari Saeed , Javadifar Nahid 
Published: August 2023

Abstract
Purpose:
Pre-pregnancy body fat mass is one of the important indicators of the mother's and the infant's health. Therefore, the purpose of this study was to investigate relationship of pre-pregnancy body mass index (PPBMI) with maternal anthropometric indices and weight retention as well as the baby's weight and nutrition in the first 6 months post-partum.
Materials and methods:
This is a prospective cohort study including 397 mothers giving birth to healthy babies and referring to health centers in Ahvaz (southwest of Iran) in 2022. The following data were extracted from the participants' electronic record: body mass index (BMI) before or at the beginning of pregnancy, gestational weight gain, and weight at the time of delivery. In addition to demographic information, the following data were also evaluated: maternal anthropometric indices including weight, hip and waist circumference, and conicity index during the first 10 days post-partum, along with the weight and nutrition pattern of the baby 2, 4 and 6 months post-partum.
Results:
The mean age of the mothers was 29.96 ± 5.7 years. The frequency of mothers according to BMI classification (i.e., underweight, normal, overweight, and obese) was 4.3%, 38.5%, 37%, and 20.3%, respectively. In this study, PPBMI had a significant relationship with weight, waist and hip circumference, conicity index, gestational weight gain, and maternal weight retention 2, 4 and 6 months post-partum. However, this relationship was not significant when it came to the weight of the baby at birth, and 2, 4 and 6 months post-partum (P < .05). According to the results of this study, the greatest amount of weight loss was observed in mothers with normal BMI, the greatest decrease in hip circumference was in obese mothers, and the greatest values of waist circumference and conicity index belonged to underweight mothers. Also, the highest frequency of mothers with excessive weight gain was in the obese mothers, while the highest values of post-partum weight retention (> 6 kg) were observed inunderweight mothers. The results of this study also showed that the highest frequency of low birth weight (LBW) was found in babies born to underweight mothers and the lowest frequency of breastfeeding until 6 months was observed in obese mothers.
Conclusion:
In this study, the greatest decrease in anthropometric indices such as weight, waist circumference, hip circumference, and conicity index was observed in obese mothers while the lowest decrease was experienced by overweight women. Also, the results of the present study re-emphasize the importance of focusing on provision of educational and counseling services to mothers in order to improve their nutrition and weight, especially before pregnancy.
Effect of shearing on production stability and die life in automatic multi-stage cold forging of an automobile wheel nut
Authors: Byun Jong Bok , Hamid Nurhidayah binti Abd , Cho Gyu Seob , Chung Wan Jin , Kang Sung Muk , Lee Kwang Hee , Joun Man Soo 
Published: August 2023

Abstract
In this study, the effects of earing in a sheared billet of S25C steel formed during rod shearing in an automatic multi-stage cold forging (AMSCF) process for an automobile wheel nut were experimentally and numerically investigated. Precision forging simulations with an emphasis on rod shearing were conducted using the implicit elastoplastic finite element method with a tetrahedral MINI-element scheme. AMSCF of an automobile wheel nut involves the use of a converging or near-conical die that shows a gradual reduction in its cross-sectional area. Our results showed that the shearing-induced earing plays the role of a pivot during balancing of the material inside the die cavity in the early stroke, before significant material contact. Earing formation resulted in a wobble motion of the material that accompanied the rigid-body motion. This ultimately led to a change in the center of mass of the material and unbalanced loading. Earing had a significant influence on the local high-cycle fatigue (HCF) fracture of die insets, especially in the cold forging of nut-like short products. The stress concentration on the die was attributed to asymmetric localized contact between the material and “critical die corner,” leading to changes in the mass center. Taken together, our results indicate that sheared billet characterization should account for earings with roll-overs and inclined surfaces to not only better predict the HCF life of die parts but also to optimize the forging outcome, particularly for safety products such as automobile wheel nuts.
A protocol for in vitro multiplication of Morella sp: a protected species in the Tambillo Community Protected Area - Ecuador
Authors: Murillo-Borrero Kevin , Corozo-Quiñónez Liliana , Durán Mateo David León , Ponce Fátima Macías , Pinoargote Miryan , Saltos-Rezabala Luis Alberto 
Published: August 2023

Abstract
The objective of this research was to develop a protocol for the in vitro establishment and multiplication of Morella sp. (Myricaceae). Tender apical shoots of Morella sp. were used as explants, which were disinfected under aseptic conditions with a 2% NaOCl solution for 4 minutes. Ninety percent of the apical shoots were free from contaminants. In the in vitro multiplication stage, the increase in the number of leaves was observed, being directly proportional to the concentration of the basal medium with WPM salts and vitamins + 0.25 mg.L-1 gibberellic acid (GA3) and different doses of 6-benzylaminopurine (BAP). The explants cultured in the basal medium with WPM salts and vitamins at 100% supplemented with 0.25 mg.L-1 GA3 + 1.5 mg.L-1 BAP, generating an average of 6.4 leaves per explant. Regarding in vitro rooting, no statistically significant differences (p > 0.05) were found in the number of roots per explant among the evaluated treatments of indole-3-butryic acid (IBA) and indole-3-acetic acid (IAA). However, the number and length of roots per explant were higher in the treatments supplemented with IBA, these showed the highest number of roots per explant (2.4 roots) at a dose of 0.75 mg.L-1 and a higher average length of 3.7 cm at a dose of 1 mg.L-1 IBA. The results obtained in this research lay the basis for further optimization of the micropropagation protocol for mass production of Morella sp. plants and to achieve the goal of reforesting Tambillo, the first community protected area in Ecuador.