bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discrepancies in temporal pCO2 variability from Earth System Models and pCO2-products related to high-latitude mixed layer dynamics and equatorial upwelling
Authors: Danek Christopher , Hauck Judith 
Published: January 2024

Abstract

The air-sea CO2 flux FCO2 is an important component of the global carbon budget and understanding its response to climate change is crucial to adjust mitigation pathways. Multi-linear regression supports the expectation that the balance between the CO2 partial pressures of air and the sea surface (pCO2) is the most important driver of temporal FCO2 variability. Discrepancies between state-of-the-art Earth System Models (ESMs) and gridded pCO2-products suggest that systematic biases exist across an ensemble of ESMs. In the equatorial regions, upwelling variability of carbon-rich water is biased in ESMs as modeled and observed sea surface temperature are generally uncorrelated. In the high latitudes, the climate change induced trend towards lighter sea water is overestimated in ESMs, which yields - in contrast to observations - shallower mixed layers over the contemporary period and hence a suppressed carbon supply from depth. While mixed layer depth variability and trends appear biased throughout the global ocean, this is not a determining factor for pCO2 variability in subtropical gyres. The results highlight the importance of accurately modeling hydrographic properties to obtain robust estimates of FCO2 and its variability.
The Exposome of Major Depressive Disorder in an Egyptian Sample: A Pilot Study
Authors: Deif Reem , Salama Mohamed 
Published: January 2024

Abstract

Background
Major depressive disorder (MDD) has been recognized as a global public health concern affecting the lives of 264 million people with increasing prevalence worldwide. Inspired by the exposomic research, this study aims to investigate the dynamic and complex interplay between different demographic, lifestyle, environmental factors and bimolecular factors that are potentially involved in the pathogenesis of MDD in a sample of Egyptian adults living in Cairo.
Methods
The sample included 107 adults from both genders between the ages of 18 and 50. Convenience sampling was used to recruit participants from different social and community platforms. Participants were excluded on the basis of having comorbid psychotic or neurodegenerative disorders, terminal conditions and cognitive disabilities that might interfere with their clinical presentation. A comprehensive questionnaire was developed and then refined to collect demographic, psychosocial, lifestyle and environmental data in addition to a mini mental state examination (MMSE). Additionally, the Arabic version of the Beck Depression Inventory-II (BDI-II) was used to assess the severity of depressive symptoms and to generate a symptoms profile. The Arabic Mini International Neuropsychiatric Interview (MINI 7.0.2) was used to diagnostically differentiate between participants with MDD and healthy controls in addition to identifying cases of past episodes and recurrent episodes of MDD. Participants were also required to give blood samples for the examination of a wide range of biomarkers including EGF, FGF-2, FGF-9, FGF-21, FGF-22, IFN-γ, IGF-1, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-17, TNF-α, VEGFC, and VEGFD in addition to complete blood parameters.
Results
Results show several significant correlations between different inflammatory and neurotrophic biomarkers. Significant correlations were also established between different lifestyle factors and biomarkers, and MDD outcomes.
Conclusion
Despite its limitations, this study offers valuable insights about the complexity of MDD in an Egyptian sample combining psychosocial, environmental and biomolecular data. Such findings highlight the pressing need for a more personalized approach in the study of MDD. It shows real potential of investing in precision mental health research for the development and enhancement of personalized intervention and prevention strategies.
Machine-learning-based on multimodality radiomics analysis for the Preoperative Prediction for local relapse in osteosarcoma
Authors: Luo Zhendong , Liu Renyi , Li Jing , Li Yulin , Shen Xinping 
Published: January 2024

Abstract

PURPOSE:
This study aimed to identify patients with local relapse (≤ 2 years) in osteosarcoma after surgical resection and make better clinical decisions by constructing a preoperative predictive model based on radiograph and multiparametric magnetic resonance imaging (MRI).
MATERIALS AND METHODS:
A retrospective study of 92 consecutive patients (training set, n = 61; testing set, n = 31) with extremity high-grade osteosarcoma were enrolled. The imaging features for each patient were extracted from radiograph, multiparametric MRI (T1WI, T2WI and T1WI-CE). In order to select features, three steps including minimal-redundancy-maximum-relevance (mRMR), least absolute shrinkage and selection operator (LASSO) regression and the random forest recursive feature elimination (RF-RFE) were performed. The classification performance was evaluated with four classifiers: extreme gradient boosting (XGB), logistic regression (LR), support vector machine (SVM) and random forest (RF). The receiver-operating characteristic curve (ROC) and the area under the curve (AUC) were used to evaluate the performance of the classifiers. DeLong’s test was utilized for comparing the AUCs.
RESULTS:
The performance (AUC, sensitivity, specificity, and accuracy) of four classifiers (RF, SVM, LR and XGB) using radiograph-MRI as image inputs were stable (all Hosmer–Lemeshow index > 0.05) with the fair to good prognosis efficacy. The RF classifier using radiograph-MRI features as training inputs exhibited better performance (AUC = 0.806, 0.868) than that using MRI-only (AUC = 0.774, 0.771) and radiograph-only (AUC = 0.613 and 0.627) in the training and testing sets (p < 0.05) while the other three classifiers showed no difference between MRI only and radiograph-MRI models.
CONCLUSION:
The tumoral radiograph and multiparametric MRI radiomics model can promisingly predict local relapse in extremity high-grade osteosarcoma. Our results highlighted the potential value of the tumoral radiomic model in osteosarcoma management.
WITHDRAWN: Epidemic patterns of the different influenza virus types and subtypes/lineages for 10 years in Chongqing, China
Authors: Fu Xiaoqing , Long Jiang , Xiong Yu , Li Zhifeng , Yang Jule , Tian Dechao , Li Zhourong , Yang Shuang , Qi Li 
Published: January 2024

Abstract
Objectives To optimize seasonal influenza control and prevention programs in regions with potentially complicated seasonal patterns.
Methods Descriptive epidemiology was used to analyze the etiology of influenza, and chi-square tests were used to compare the epidemic patterns among different influenza virus types and subtypes/lineages.
Result From January 2010 to December 2019, a total of 63,626 ILI cases were reported in Chongqing and 14,136 (22.22%) were laboratory-confirmed influenza cases. The positive rates of influenza A and influenza B, which were 13.32% and 8.86%, respectively. The positive rate of influenza A reached the highest in winter (23.33%), while the positive rate of influenza B reached the highest in spring (11.88%). Children aged 5-14 years old had the highest positive rates of influenza. The influenza virus types/subtypes positive was significantly different by seasons and age groups (p＜0.001), not by gender (p=0.436). The vaccine strains were matched to the circulating influenza virus strains in all other years except for 2018 (circulating strain was B/Yamagata).
Conclusions The study showed significant variations in epidemic patterns, including seasonal epidemic period and age distributions, among different influenza types, subtypes/lineages in Chongqing. Influenza vaccines matched well to the circulating influenza virus strain. In order to prevent and mitigate the influenza outbreak in this area, high risk population, especially children aged 5-14 years, should be encouraged to get vaccinated against influenza before the epidemic season.
Evaluation and simulation of athlete training techniques using optical imaging technology based accelerometer
Authors: Jingchen Zhang 
Published: January 2024

Abstract

Traditional acceleration sensors are widely used in training and evaluation, but they have some limitations, such as accuracy and applicability. Optical imaging technology is considered a potential alternative method due to its high accuracy and comprehensiveness. However, there is currently a lack of research on the application of optical imaging technology in the evaluation of athlete training techniques. In order to evaluate the performance of optical imaging technology and traditional accelerometer in athlete training technology evaluation, real-time data collection of athlete movements was conducted using traditional accelerometer and optical imaging equipment. Traditional acceleration sensors require more caution during the implantation process, while optical devices can obtain data through non-contact means, which allows athletes to train more naturally and comfortably without being disturbed by external factors. The research results show that acceleration sensors based on optical imaging technology perform better in terms of accuracy. Optical imaging technology can provide more accurate pose recognition and joint angle measurement, which is beneficial for enhancing the analysis of technical details. By comparing the data from traditional acceleration sensors and optical imaging technology, we can gain a deeper understanding of the athlete's movement patterns and technical level.
Terrihabitans rhizophilus sp. nov., isolated from the rhizosphere soil of plant in temperate semi-arid steppe
Authors: Bao Runze , Guo Huiling , Liang Yungang , Tang Kai , Feng Fuying , Meng Jianyu 
Published: January 2024

Abstract
The bacterial strain was isolated from the rhizosphere of Elymus dahuricus Turcz. in temperate semi-arid steppe, located in the northern of Inner Mongolia Autonomous Region, China. Strain PJ23T is Gram-stain-negative, aerobic, light-pink, short rod-shaped, and does not form spores. Cell growth could be observed at 4-29 ℃ (optimum, 24 ℃), pH 6.0-8.6 (optimum, 8.0) and in the presence of 0-5 % (w/v) NaCl (optimum, 2.5 %). The major fatty acids of strain PJ23T were Summed feature 8 (C18:1 ω6c and/or C18:1 ω7c) 39.42 %) and C16:0 (9.60 %). The polar lipid profile was composed of phosphatidylcholine, two unidentified glycolipids, one unidentified aminophospholipid, and two other unidentified polar lipids. The sole respiratory quinone was ubiquinone-10. Phylogeny on full length of 16S rRNA gene sequences retrieved from the genomes showed that, the strain was closely related to Terrihabitans soli IZ6T and Flaviflagellibacter deserti SYSU D60017T with the sequence similarities of 96.79% and 96.15%, respectively. The G+C content was 65.23 mol% calculated on draft genome sequencing. Between the strains PJ23T and T. soli IZ6T, the average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) was 73.39 % and 15.7 %, these values are lower than the proposed and generally accepted species boundaries of dDDH and ANI. Based on phenotypic, chemotaxonomic, and phylogenetic characteristics, strain PJ23T represents a novel species of Terrihabitans, for which the name Terrihabitans rhizophilus sp. nov. is proposed. The type strain is PJ23T (= KCTC 92977T=CGMCC 1.61577T).
Efficiency Estimation of Complex Networks and Regional Economic Development Based on GIS Optical Remote Sensing Technology
Authors: Li Jun , Li Dongsheng 
Published: January 2024

Abstract

This paper proposes a method for estimating global network efficiency based on fractal characteristics, which uses complex network topology to solve the problem of low efficiency and complex calculation of fractal characteristics. Analyzed the relationship between network efficiency and node relevance, integrated the fractal characteristics of complex network topology, and improved the overall efficiency, and proposed a fast judgment method of complex network fractal characteristics based on node relevance. The experimental results show that the method can accurately and effectively estimate the network efficiency, and the calculation time is reduced by more than 90% compared with the original method. Then this article analyzes the development of regional technology and economy, and the development of regional circular economy is a strategic choice for China to realize the transformation of the second economic growth mode. Like any economic model, the development of a regional circular economy is also a strategic choice to realize the transformation of the second economic growth mode. In practice, the technical support of the regional circular economy does not come from one or more technological innovations. The resulting technology cluster is an organic whole with key technologies as the core, interconnected, mutually promoted, and mutually restrictive, that is, the technology of institutional innovation. It exists objectively in the region and is the material basis for supporting circular economy. According to the characteristics of fractal, the network efficiency of complex networks is improved and applied to regional economic development. It is used to solve the shortcomings of complex network calculation and long time, so as to improve regional economic construction, promote regional economic development, and make contributions to regional economy.
Application of Low Resolution Face Recognition Based on Infrared Spectral Imaging in Motion Training Action Analysis
Authors: Jinglong Ding 
Published: January 2024

Abstract

As a conscious activity, the importance of sports in social life is self-evident. However, how to use modern scientific and technological means to improve sports fun and athletes' competitive ability has become the current research hotspot. The current sports detection system has a high restriction on Athletes' movements. Therefore, it is an inevitable direction of future development to integrate intelligent technology into sports movement detection, and face recognition technology has become the best choice with its unique technical advantages. This paper constructs an application system that combines the low-resolution face recognition technology of the Internet of things with sports training action analysis. The system determines the design idea of the system framework by optimizing the face recognition model and the embedded algorithm, and the Softmax loss function is applied to the system to optimize the recognition accuracy and credibility. In addition, the system determines the parameter response value by analyzing the elbow and knee joints in the video. Finally, according to the test of system reliability, it is found that the system with GPU as the processor has the lowest resource occupancy and the highest reliability, which indicates that the system not only avoids the problem of low accuracy of traditional identification equipment, but also makes the action detection result more reliable.
Investigation of shared molecular mechanisms underlying sepsis and heart failure via integrated analysis of multiple microarray data
Authors: Chen Dongling , Song Yinwei , Zhang Huaiqi , Ye Yang 
Published: January 2024

Abstract
Objective: This study aimed to mine shared genes and related molecular mechanisms of sepsis and heart failure (HF).
Methods: Differentially expressed genes (DEGs) in sepsis and HF samples were identified using discovery datasets (GSE28750 and GSE57345). Weighted gene coexpression network analysis (WGCNA) of the DEGs was performed to identify sepsis- and HF-related gene coexpression modules. Shared genes of the two diseases were identified, followed by functional enrichment analysis, protein‒protein interaction (PPI) analysis, and expression validation using validation datasets (GSE65682 and GSE84796). Moreover, diagnostic performance, immune cell infiltration, and gene set enrichment analyses for hub-shared genes were conducted.
Results: In total, 5407 and 2042 DEGs in sepsis and HF samples, respectively, were identified based on GSE28750 and GSE57345. WGCNA revealed five sepsis-related modules containing 2972 genes and three HF-related modules containing 982 genes; 170 shared genes of the two diseases were obtained. Four hub-shared genes of the two diseases were identified, including RRS1, IMP4, RPLP0, and NOP16, by PPI analysis and expression validation with external datasets. The four hub-shared genes had high diagnostic performance, with AUC [Editor1] values higher than 0.7 in the four datasets. Moreover, there was a significantly negative correlation between RRS1 and M0 macrophages and between IMP4 macrophages and plasma cells in the two diseases; these genes were significantly enriched in ribosome assembly and biogenesis processes.
Conclusion: Four genes, RRS1, IMP4, RPLP0, and NOP16, may be key common regulators in sepsis and HF and serve as diagnostic biomarkers and therapeutic targets for these two diseases.
Abbreviations are typically defined the first time the term is used within the abstract and again in the main text and then used exclusively throughout the remainder of the document. Please consider adhering to this convention. The target journal may have a list of abbreviations that are considered common enough that they do not need to be defined.
Laboratory study on use of lime and waste materials in improving geotechnical properties of clay
Authors: Juneja Gaurav 
Published: January 2024

Abstract
The waste materials such as fly ash, construction demolition waste and plastic waste are generated in tremendous quantities and are dumped haphazardly thereby causing irreparable damage to the environment. Proper utilization of these wastes particularly in the construction sector will protect the environment from their harmful effects and will prove to be economical by the preservation of precious natural resources. This paper presents an investigation on utilization of lime, fly ash and construction demolition waste individually and in combination with each other for the stabilization of poor soil. The utilization of plastic waste along with soil-fly ash-construction demolition waste-lime composite was further investigated. The samples for unconfined compressive strength and split tensile strength were compacted at optimum moisture content to maximum dry density which was obtained from standard Proctor compaction tests. The samples were tested after 7 days, 28 days and 56 days curing periods. The results reveal that addition of admixtures increases the unconfined compressive strength and split tensile strength and the optimum mixes were selected based upon 7 days unconfined compressive strength. The increase in strength with addition of admixtures depends on the type of admixture used and formation of new minerals which can be observed from XRD graphs. The soaked California bearing ratio tests were conducted on the optimum mixes and soil-fly ash-C&D waste-lime mix was selected as the best sub-grade material compared to other material combinations based upon economical and environmental considerations.
Multi-objective Optimization and Development of Mathematical Model for Process Parameters of AmaranthGrains using Regression Analysis
Authors: Patil Sagar Dnyandev , Khot Aniket B. , Hatte Prafulla R 
Published: January 2024

Abstract
Purpose - There are several ways to heat amaranth grains, including oven puffing, gun puffing, extrusion puffing, oil puffing, pan popping, etc. Because of its size, puffing characteristics, poor volume expansion ratio, etc., amaranth grains cannot be popped in an oven, gun, extrusion, oil, or pan. In this study, the amaranth grains were popped or puffed using a Special Purpose Machine (SPM) with a heating plate. This device was created to get around all of the earlier listed restrictions. The temperature, angle, nozzle hole size, heating plate material, and other factors all affect the quality of amaranth grains. Major quality indicators of amaranth grains are the Popping Yield, Ratio of Volume Expansion, and Sensory Score. These quality indicators are examined for the effect of process characteristics on them. Therefore, these characteristics are complete to conduct additional research. The purpose of this study is to examine the more important process variables that affect the quality indicators of Amaranth grains.
Methodology – For examining how different process variables affect the grain quality of amaranth, the Taguchi method was used. The significant factors were found using Minitab 17 software.
Findings – The design of the experiment has been improved for the major process parameters, according to the experimental analysis and optimization study. To conduct the experimental research, L16 Orthogonal Array has been acquired. The original setup (P4Q2R3S2) for the GRA technique had a GRG of 0.778. By utilizing a new optimum combination (P3Q4R3S2), it was raised to 0.790. It indicates that the grade has increased by 1.89%. As a result, design factors have been successfully optimized utilizing the Gray Relational Analysis approach to produce improved machine parameters for the Lahi machine.
Originality: The Gray Relational Analysis approach used to for multi objective optimization which gives 1.89% improvements in quality of grains.
Rational design of ROS scavenging and fluorescent gold nanoparticles to deliver siRNA to improve plant resistance to Pseudomonas syringae
Authors: Wu Honghong , Qi Jie , Li Yanhui , Xue Yao , Li Guangjing , Xu Wenying , Xie Zhouli , Gu Jiangjiang , Li Zhaohu 
Published: January 2024

Abstract

Bacterial diseases are one of the common issues to result in crop loss world-widely, and the increasing usage of chemical pesticides has caused the occurrence of resistance in pathogenic bacteria and environmental pollution problems. Nanomaterials mediated gene silencing is started to display powerful efficiency and environmental friendliness for improving plant disease resistance. However, the internalization of nanomaterials and the physiological mechanism behind nano-improved plant disease resistance are still rarely understood. Herein, we engineered the polyethyleneimine (PEI) functionalized gold nanoparticles (PEI-AuNPs) with fluorescent property and ROS scavenging activity to act as siRNA delivery platform. Besides the loading, protection and delivering of nucleic acid molecules in plant mature leaf cells by PEI-AuNPs, its fluorescent property further enables the traceability of the distribution of the loaded nucleic acid molecules in cells. In addition, PEI-AuNPs delivery system successfully mediated defense regulated gene silencing, thus improving plant disease resistance by reducing bacterial number, balancing ROS content, enhancing antioxidant enzyme activity, and improving chlorophyll fluorescence performance. Our results showed the benefits of AuNP-based RNAi technology in improving plant disease resistance and the potential of plant nanobiotechnology to protect agricultural production.