bluuebunny/crossref_metadata_2025_split huggingface dataset:
Landslide susceptibility assessment of Kure City (Hiroshima Prefecture, Japan) with machine learning random forest and frequency ratio methods using XRAIN radar-acquired rainfall data
Authors: Maria Dos Santos Rodrigues Neto Jose , Bhandary Netra Prakash 
Published: June 2023

Abstract
In this paper, we perform an efficiency comparison between two methods of producing landslide susceptibility maps (LSM): the machine learning technique random forest (RF), which is evidenced to be the most efficient for landslide susceptibility assessment tasks (Yilmaz, 2009; Youssef & Pourghasemi, 2021) and the statistics-based frequency ratio (FR) method. The area considered for this study is southern part of Hiroshima Prefecture in Japan, an area known to suffer from rainfall-induced landslide disasters, the most recent one in July 2018. Both the above methods require a collection of landslide conditioning factors (LCFs), which in this study are: 1) geology, 2) altitude, 3) slope angle, 4) slope aspect, 5) drainage density, 6) land use, 7) distance from lineaments, and 8) mean annual precipitation. The rainfall LCF data comprise of XRAIN (eXtended RAdar Information Network) radar records, which are novel in this task of LSM production. The accuracy of the produced LSMs was assessed by the receiver operating characteristic’s (ROC) area under curve (AUC), which is 0.84 for the FR method and 0.92 for the RF method. It is also noteworthy that the RF method is substantially swifter and more practical than the FR method, and it allows for multiple and automatic experimentations with different parameters, providing fine and accurate results with the given data. The results also evidence that machine learning techniques such as the RF method are most advisable for dealing with hazard assessment problems such as the one exemplified in this study, and that XRAIN radar-acquired mean annual precipitation data are effective when used as a LCF in producing LSMs.
MPI+X:Massive Parallelization and Dynamic Load Balance of a Production-level Unstructured DSMC Solver
Authors: Zhe Dai , Liang Deng , Jin Li , Yueqing Wang , Ruitian Li , Jian Zhang 
Published: June 2023

AbstractThis paper presents implementing and balancing a production-level unstructured DSMC solver using two variants of the hybrid programming model. Both approaches can be implemented with minimal modifications to the source code. Specifically, we port and optimize RariHV, a production-level unstructured DSMC application, to scalable homogeneous and heterogeneous systems using two variants of the hybrid MPI+X programming model: MPI+OpenMP and MPI+OpenACC. Additionally, a physics-awared mesh repartition during the execution is proposed to alleviate the load imbalance issues. Results demonstrate that the load balancing strategy has an improvement in performance of up to 50%, and the hybrid MPI+X parallelism method can provide considerable scalability benefits on multi-core and many-core platforms.
Alteration of Twilight Sky Brightness Profile by Light Pollution
Authors: Faid Muhamad Syazwan , Nawawi Mohd Saiful Anwar Mohd , Saadon Mohd Hafiz Mohd , Wahab Raihana Abdul , Ahmad Nazhatulshima , Shar Nur Nafhatun Md , Hamidi Zety Sharizat 
Published: June 2023

Abstract
The phenomenon of twilight been stipulated as naturally dependent on the variables of solar depression, aerosol concentration and ozone composition. The unique color spectrum of twilight is attributed by ozone layer and aerosol, whereas its brightness is heavily relying on the altitude of sun below horizon. While all the natural dependent is being researched extensively, the impact of light pollution on the brightness of the twilight is not being explored thoroughly. The objective of this study is to find out the alteration of light pollution towards the natural behaviour of twilight sky brightness. Total of 84 data of twilight brightness was collected from 2014 until 2022 using Sky Quality Meter, and the specific location with profile classified as urban, suburban and pristine is investigated to study the impact of light pollution on twilight brightness. The result demonstrates that the stability of twilight brightness, which naturally factored by solar depression within the range of 18°, discovered to be heavy influenced by the zenith light pollution of the location sky, as evidenced by location that has zenith pollution of 17.11, 19.77, and 21.39, has horizontal twilight brightness of 14.84, 19.55 and 21.2 and solar depression during brightness stability at 11.5°, 15.67° and 17.49°.
Identification and Validation of a m5c-related lncrna signature predict prognosis and immune response of clear cell renal cell carcinoma
Authors: Ao Shan , Liang Leqi , Yang Riwei , Chen Zugen , Peng Lei , Deng Tuo 
Published: June 2023

Abstract
Objective
M5C-related LncRNAs (Long non-coding RNAs) were related to the occurrence and development of tumors. In this study, we investigated whether m5C-related LncRNAs could predict the prognosis of clear cell renal cell carcinoma (ccRCC) patients.
Methods
Co-expression analysis and Cox regression analysis were used to construct prognostic features, and then a series of model validation was performed to evaluate the prognostic value of the model. Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome Enrichment (KEGG), immune-related function and tumor mutation burden (TMB) analyses were also performed. Finally, the potential sensitivity of drugs to ccRCC was predicted.
Results
A total of 9 m5C-related LncRNAs were obtained and a prognostic model was established. Our model has independent prognostic value and is closely related to tumor immune characteristics and immune escape, which can be used to predict the sensitivity of drugs including Entinostat, SB216763, and Sapitinib. Our in vitro experiments showed that GNG12-AS1 inhibited cell proliferation and migration in ccRCC cell lines.
Conclusions
In summary, the 9 m5C-related LncRNAs can accurately predict the prognosis of ccRCC patients, which may provide new ideas for clinical application and immunotherapy of ccRCC patients, and GNG12-AS1 is a promising prognostic biomarker for predicting survival outcome of ccRCC.
Comprehensive Feature Extraction Model to Classify Interacting and Non-Interacting Proteins in Human Viruses using Random Forest Classifier
Authors: Raj Sini S , S Vinod Chandra S 
Published: June 2023

Abstract
Protein-protein interactions are crucial for the entry of viruses into the cell. Understanding the mechanism of interactions is essential in studying human-virus association, developing new biologics and drug candidates, as well as viral infections and antiviral responses. Experimental methods to analyze human-virus protein-protein interactions are time-consuming and labor-intensive, so machine learning based methods are being developed to predict interactions and determine large-scale interactomes between species. The present work highlights the importance of features in the classification of interacting and non-interacting proteins. To achieve this, we have extracted all possible features like Amino Acid Composition (AAC), Dipeptides Composition (DPC), Grouped Amino Acid Composition (GAAC), Pseudo-Amino Acid Composition (PAAC) etc. that can be fetched from a protein sequence which lies in a higher dimension space. We have used a random forest classifier to understand the biological relevance of these high-dimensional features and thereafter to decide whether these features really contribute to the protein-protein interactions. As part of this, the classifier was applied to three datasets, two with dimensionality reduction and one without dimensionality reduction. The datasets in which dimensionality reduction is applied produce 100% accuracy and one without dimensionality reduction gave 85% accuracy. Thus it is evident that dimensionality reduction fails to capture the complexity of biological relevance and the underlying associations between human and viral proteins.
ZIP genes are involved in the retransfer of zinc ions during the senescence of zinc-deficient rice leaves
Authors: Ma Yangming , Wen Yanfang , Wang Cheng , Wu Ziniu , Yuan Xiaojuan , Xiong Ying , Chen Kairui , He Limei , Zhang Yue , Wang Zhonglin , Li LeiLei , Yang Zhiyuan , Sun Yongjuan , Chen Zhongkui , Ma Jun 
Published: June 2023

Abstract
Zinc (Zn) is essential for human health, but rice often lacks sufficient amounts. Leaf senescence is a vital developmental stage during which nutrients are redistributed to other organs. However, Zn retransfer during deficiency is often overlooked. In this hydroponic experiment, we studied the effect of Zn deficiency on rice seedlings, specifically focusing on the fourth leaf under control and deficient conditions. Growth phenotype analysis showed that the growth of rice nodal roots was inhibited under Zn deficiency, and the fourth leaf exhibited accelerated senescence and increased Zn ion transfer. We conducted transcriptome analysis on the fourth leaf at two time points. The fourth leaf at the second time point under control conditions was used as the control and compared to when Zn ion content markedly decreased under control and deficiency conditions. Analyzing differentially expressed genes showed that Zn deficiency regulates more ZIP family genes involved in Zn ion retransfer in the leaves. OsZIP3 upregulation under Zn-deficient conditions may not be induced by Zn deficiency, whereas OsZIP4 is only induced during Zn deficiency. Gene Ontology enrichment analysis showed that Zn-deficient leaves mobilized more biological pathways (BPs) during aging, and the enrichment function differed from that of normal aging leaves. The most apparent “zinc ion transport” BP was stronger than that of normal senescence, possibly due to Zn-deficient leaves mobilizing large amounts of BP related to lipid metabolism during senescence. These results provide a basis for further functional analyses of genes and the study of trace element transfer during rice leaf senescence.
Design of wearable antenna sensors and Path loss Modeling for Internet of Wearable Things applications
Authors: Amiri Marwen , Hamdi Abdelaziz , Meddeb Aref 
Published: June 2023

Abstract
The Internet of Wearable Things (IoWT) is a revolutionary technology of Wireless Body Area Networks (WBAN). IoWT applications are widely employed in diverse sectors including medical, civil, and military domains. In these emerging applications, human bodies are equipped with wearable and interconnected sensors, which can be used on, inside, or around the human body. However, the deployment of these devices in close proximity of the human body faces several electromagnetic factors such as channel fading due to several reasons like energy absorption, reflection, multipath, and shadowing by the body. These electromagnetic phenomena can degrade the quality of the communication link budget between wearable sensor systems in WBAN. Therefore, investigation in channel modeling between wearable sensors has become a major challenge in Wireless Body Area Networks (WBAN), especially when using these devices for real-time monitoring and remote control of vital signs and physiological data of patients in medical applications.
This paper presents a novel approach of a rigorous and effective mathematical voxel-based channel model for channel modeling between wearable wireless antenna sensors in free space and human body environments. Also, this work presents a design flow and performance analysis of the proposed 3D-voxel human body model and the designed wearable antenna at 2.4 GHz. Moreover, a performance evaluation studies between IEEE 802.15.6 CM3 channel model based on the proposed analytical voxel based-human body at 2.4 GHz for various distances between the coordinator and the on-body wearable antenna sensors are presented. These studies reveal a good agreement between IEEE 802.15.6 CM3A and our model.
Does Surgical Resection Improve the Survival of Patients with Gastric Cancer Liver Metastases? A Population-Based, Propensity Score–Adjusted Analysis
Authors: Yuan Zheping , Li Xiawei 
Published: June 2023

Abstract
Purpose The use of surgery in the management of patients with gastric cancer liver metastases (GCLM) has been debatable. We aimed to assess whether surgical resection is associated with improved patient survival.Methods Patients with GCLM were identified in the Surveillance, Epidemiology, and End Results database between 2010 and 2015. Adult gastric cancer patients (aged ≥ 18 years) with liver metastases living longer than one month were eligible for this analysis. The overlap weighting method based on lasso regression with penalty factors (OW_pLasso) was applied to reduce the selection bias. The survival times of patients who underwent surgery and those who did not were compared using OW_pLasso adjusted Kaplan-Meier curves and Cox proportional hazards models.Results A total of 3694 patients with GCLM were identified. Of those, 354 (9.58%) patients underwent cancer-directed surgery (CDS). After OW_pLasso adjustment, the median overall survival was 12 months [95% confidence interval (CI) 11–16] in the CDS group and 6 months [95% CI 5–6] in the Non-CDS group. In Cox regression analysis, primary cancer resection was associated with a significantly better overall survival [hazard ratio (HR) 0.562, 95% confidence interval (CI) 0.482–0.656]. The benefit of surgical resection persisted in patients with worse conditions (large size and high-grade tumors, advanced T stages, and limited lymph node metastases).Conclusions In this population-based cohort analysis of patients with gastric cancer and liver metastases, surgical resection was linked to a better overall survival. As a result, surgery has the potential to be an option for treating patients with liver metastases.
Quantifying uptake and completion of pulmonary rehabilitation programs in people with COPD known to tertiary care
Authors: Hug Sarah , Cavalheri Vinicius , Gucciardi Daniel F. , Hill Kylie 
Published: June 2023

Abstract
Pulmonary rehabilitation programs (PRPs) are important for people with symptomatic chronic obstructive pulmonary disease (COPD), but program attrition is common. Among people with COPD who appeared appropriate for a PRP, we prospectively mapped the rehabilitation journey, captured attrition and explored factors influencing attendance to pre-program assessment. 391 participants consented, of which 123 (31% [95% confidence interval {CI}] 27 to 36) were referred to a PRP (mean±SD or frequency[%]: age 68±10yr, 62 males[50%], BMI 27±8kg/m2, FEV1 45±19%predicted). Of those referred, 94 (76% [69 to 84]) attended a pre-program assessment. Ex-smokers (odds ratio [95%CI]; 2.6 [1.1 to 6.1]) and those who had a healthcare professional explain they would be referred (4.7 [1.9 to 11.7]) were more likely to attend a pre-program assessment. Of those who attended, 63 (67% [58 to 77]) commenced and 35 (56% [43 to 68]) completed a PRP. Substantial attrition occurs throughout the PRP journey. Understanding how HCPs can best contextualise PRPs to encourage uptake is an important area for further work.
Effect of Drying Methods and Pre-treatments on Bioactive Potential of Persimmon (Diospyros kaki L.)
Authors: Yildiz Elif , Yilmaz Aslihan , Gurbuz Ozan , Alibas Ilknur 
Published: June 2023

Abstract
In this research, persimmon samples (sliced, pureed) were dehydrated by convective (50 and 100°C) and microwave (100 W) drying techniques with different pre-treatment combinations of sugar addition (25%) and blanching (100°C, 5 min). Each pre-treatment consisting of sugar addition, slicing, and blanching resulted in a significant increase in color parameters compared to unpretreated samples. Color parameters measured at low drying temperatures were lower than high ones. Also, 100 W dried samples were higher in total anthocyanin content, and the pureed samples were 24.80% higher than sliced ones. The bioactive potential was evaluated regarding extractable, hydrolysable, and bioaccessible phenolic fractions (EPF, HPF, BPF) by total phenolic content and ABTS, CUPRAC, and DPPH antioxidant capacity assays. i) 50°C drying prevailed on drying at 100°C and 100 W, especially in terms of EPF and BPFs; ii) Sliced samples were higher for EPF and BPF, while pureed ones were higher in HPFs; iii) Blanched samples were relatively higher than unblanched ones in TPC. For antioxidant capacity assays, EPFs were higher in blanched samples and BPF in unblanched ones (TEACABTS, TEACCUPRAC). iv) Sugar addition negatively affected the bioactive potential in persimmon samples; no-sugar-added samples were higher, especially in BPF (p < 0.01; TPC, TEACABTS, TEACCUPRAC). v) The CUPRAC assay was the most appropriate method due to providing a view of more statistical distinction by picturing the same potential.
Polymer - Sn Composite : Development of Amperometric Hydrazine Sensor
Authors: Kempegowda Raghu G. 
Published: June 2023

Abstract
In the present work, an ease and green chemical protocol for the formation of polyaniline - Sn composite is proposed. The protocol involves the formation of composite by the simple mixing of tin nitrate and aniline at room temperature without using any agents for polymerisation process. The composite obtained has been well characterized with the aid of SEM with EDAX and XRD. Further, it has been used in the development of thin film electrodes on the surface of rigid glassy carbon electrode and subsequently employed as an electrochemical interface for the electroanalytical amperometric sensing of hydrazine model analyte system at trace concentration level. The developed interface showed good affinity towards the analyte in the dynamic range upto 400 µM with a detection limit of 0.1 µM (3ϭ). The stability, reproducibility has been proven to be good without any deviation in its electrochemical performance with least interference from commonly encountered foreign species. Finally, the practical utility of the developed sensor has been shown by determining the trace concentration levels of hydrazine from tap water.
Agreement of Two Biometers for Central Corneal Thickness Measurement in High Myopia Patients
Authors: Budiman Budiman , Tjokrovonco Ludwig Melino , Knoch Andrew M H , Sugiarti Emmy Dwi 
Published: June 2023

Abstract
Purpose
To compare the central corneal thickness (CCT) measurements made with swept-source optical coherence tomography (SS-OCT)-based biometers and the Scheimpflug camera in patients with high myopia.
Methods
This study assess the agreement between CCT measurements with SS-OCT and the Scheimpflug camera. We included 44 eyes with high myopia that underwent CCT examinations with SS-OCT and the Scheimpflug camera. The Bland-Altman test was used to evaluate the agreement between the two devices.
Results
Forty-four eyes with axial lengths ranging from 26.05 to 34.02 mm based on SS-OCT examinations were included in this study. The mean CCT was 527.98 ± 36.049 mm and 525.64 ± 35.421 mm, based on SS-OCT and the Scheimpflug camera, respectively. The Bland-Altman plot revealed good agreement between both devices, with a mean difference of 2.3409 mm and a 95% limit of agreement ranging from -8.09864 to 12.78046 mm at a 95% confidence interval.
Conclusions
CCT measurements using SS-OCT and the Scheimpflug camera differed significantly among patients with high myopia. Our findings suggest that CCT measurements made with either device should be interpreted with caution and should not be used interchangeably.
Research on the Impregnation Process and Mechanism of Silica Sol/Phenolic Resin Modified Poplar Wood
Authors: 王 鸿兴 , 张 银良 , 里 慧杰 , 侯 浩杰 , 刘 米格利 , 里 春峰 
Published: June 2023

Abstract
Phenolic resin impregnated modified materials have partially reduced the toughness of the wood. In this study, organic-inorganic composite modifiers were used to modify the wood. Silica sol/phenolic resin composite impregnating solution was prepared by an in-situ polymerization method and used to impregnate poplar wood under vacuum pressure. Orthogonal experiments were conducted, and the impact toughness of the modified poplar wood was used as the evaluation index. The results showed that the best impact toughness was achieved when the average particle size of silica sol was 8-15 nm, the pressure was 1.2 MPa, and the pressure time was 3 hours. The impact toughness of the impregnated modified poplar wood was improved by 84.1% compared to the untreated material. FT-IR results revealed the characteristic absorption peak of Si-O-Si in the impregnated poplar wood, confirming the formation of new chemical bonds. XPS analysis indicated that a chemical reaction occurred between the impregnating solution and the wood, resulting in the formation of Si-O-C. Furthermore, DMA analysis revealed that this chemical reaction significantly improved the thermal stability and toughness of the impregnated material, surpassing the original poplar wood. In addition, TG analysis revealed a significant improvement in thermal stability of the impregnated material compared to untreated poplar wood. Finally, SEM analysis demonstrated the successful infiltration and filling of the poplar wood by the composite impregnating solution.
Statistical analysis of DNA methylation patterns of tumor suppressor genes for breast cancer
Authors: Sun Shuying , Pritchard Ashley , McFall Emma , Tian Christine 
Published: June 2023

Abstract
Background
Breast cancer is associated with DNA methylation, an epigenetic event in which a methyl group is covalently bonded to a cytosine-guanine (CG) pair. Although previous research has studied methylation patterns of individual tumor suppressor genes (TSGs), there has not been a comprehensive analysis of all available TSGs for breast cancer. The purpose of this study is to conduct the first-ever comprehensive statistical analysis of methylation patterns for all 1,217 TSGs. The authors analyzed publicly available Illumina 450K array data for 53 living (53-Alive) and 32 deceased (32-Dead) breast cancer patients. First, they studied the overall methylation distribution. They then identified differentially methylated (DM) sites between tumors and matched normal tissues in both Alive and Dead samples. They analyzed co-methylation patterns related to these DM sites and reported corresponding TSGs and non-TSGs.
Results
Below are the key findings of this study. First, tumor tissues had more heterogeneous methylation sites than normal tissues (40% vs. <10%) in both Alive and Dead samples. Second, there were significantly more DM sites in Dead than in Alive samples. Third, co-methylation patterns were investigated by calculating the Spearman correlation coefficients between each DM site and all 391,459 CG sites for both Alive and Dead samples. In normal tissues, some DM sites tended to have strong co-methylation with many other CG sites. In tumor tissues, some of these strong co-methylations were lost and some new co-methylation relationships were developed. These patterns were seen in both Alive and Dead data. Fourth, there were more co-methylation changes between normal and tumor tissues in Dead than in Alive samples. 30 TSGs and 92 non-TSGs were identified as having notable differences between Alive and Dead data. Finally, ESR1, PAX6, ZIC1, TP73, PPP1CA, POU6F2, and TFAP2A were involved in many different co-methylation changes between normal and tumor tissues. These 7 TSGs played a key role as hub genes in different networks.
Conclusion
Significant differences were identified for various methylation-pattern changes between normal and tumor as well as between Alive and Dead samples. These differences can be used to identify novel TSGs and biomarkers to improve breast cancer study.