bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using In Vivo Intact Structure for System-wide Quantitative Analysis of Changes in Proteins
Authors: III John Yates , Son Ahrum , Kim Hyunsoo , Diedrich Jolene , Bamberger Tom , McClatchy Daniel 
Published: July 2023

Abstract
Mass spectrometry-based methods can provide a global expression profile and structural readout of proteins in complex systems. Preserving the in vivo conformation of proteins in their innate state is challenging during proteomic experiments. Here, we introduce an approach using perfusion of reagents to create a whole animal in vivo protein footprinting method that adds dimethyl labels to exposed lysine residues on intact proteins to maintain information on protein conformations. When this approach was used to measure dynamic structural changes during Alzheimer’s disease (AD) progression in a mouse model, we detected 433 proteins that underwent structural changes attributed to AD, independent of aging, across 7 tissues. We identified structural changes of co-expressed proteins and linked the communities of these proteins to their biological functions. Our findings show that structural alterations of proteins precede changes in expression, thereby showing the value of in vivo protein conformation measurement. Our method represents a new strategy for untangling mechanisms of proteostasis dysfunction caused by protein misfolding. In vivo whole-animal footprinting should have broad applicability for discovering conformational changes in systemic diseases and therapeutic interventions.
Wear behavior and CO2 emissions analysis of drum mower blades during Alfalfa harvest
Authors: Refai Mohamed , Abdelkader Tarek Kh. , Sayed Hassan A. A. , Wan Q. , Abdelhamid Mahmoud A. 
Published: July 2023

Abstract
The productivity and efficiency of harvesting forage crops depend on the sharpness and quality of the mower blades. Therefore, studying blades wear during the harvesting process is crucial to sharpening and maintaining blades. The research aims to create mathematical models to predict the wear of mower blades and assess the wear rate of mower blades, fuel consumption, and CO2 emissions during harvesting operations. The wear of blades was measured and characterized by the weight loss method and scanning electron microscopy (SEM) before and after the field experiment. The results showed that the weight of the mower blade decreased from 103.82 to 98.39 g after 37.5 working hours. In addition, the wear of blades increased fuel consumption and operation cost with time. Also, CO2 emissions were 17.672 kg/h at the beginning of the experiment and increased to 29.516 kg/h after 37.5 working hours. From the obtained mathematical equations, the wear of the blade sharp part occurs after 34±3 work hours have passed, so the blades must be resharpened after this period.
Bioinformatics analysis revealed aging-related diagnostic genes and therapeutic targets in pulmonary arterial hypertension
Authors: Cao Ping , Zhang Wangmeng , Jia Jing , Liu Guoli , Wang Jiyan , Li Xin 
Published: July 2023

Abstract
Pulmonary arterial hypertension (PAH) is increasingly recognized as an aging-related disease. The objective of this study was to identify the aging-related genes and microRNAs (miRNAs) in PAH to explore potential diagnostic biomarkers and therapeutic targets for PAH. Microarray data for GSE113439 and GSE53408 were downloaded from the the Gene Expression Omnibus (GEO) as experimental and validation sets, respectively. Overlapped with the Aging Atlas database, a total of 21 differentially expressed aging-related genes (DEARGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on DEARGs using R software. Construct and visualize protein-protein interactions (PPI) and obtain hub genes using Cytoscape software. GSE53408 dataset verified the expression level and diagnostic value of hub genes, identified the final diagnostic genes TOP1, TOP2A, HSP90AA1 and HIF1A. By constructing the miRNA-mRNA network, it was found that miRNA-186-5P was the common target miRNA of the four genes. TOP1, TOP2A, HSP90AA1 and HIF1A, as well as their common target miRNA-186-5p, may play a role in the pathologic process of PAH and may become new potential targets for the diagnosis and treatment of aging-related PAH.
Real-time patient management monitoring system based on edge computing using IoT pulse oximeter
Authors: Joo Moon-Il , Kang Min-Soo , Kang Dong-Yoon , Kim Hee-Cheol 
Published: July 2023

Abstract
Edge computing can provide core functions such as data collection and analysis without connecting to a centralized server. The convergence of edge computing and IoT devices has enabled medical institutions to collect patient data in real-time, which improved the efficiency of short- and long-term patient management. Medical equipment measures a large amount of biosignal data for analyzing diseases and patient health conditions. However, analyzing and monitoring biosignal data using a centralized server or cloud limit the medical institutions’ ability to analyze patients’ conditions in real time, preventing prompt treatment. Therefore, edge computing can enhance the efficiency of patient biosignal data collection and analysis for patient management systems. Analyzing biosignals using edge computing can eliminate the waiting time present in cloud computing. Hence, this study aims to develop an IoT pulse oximeter to use edge computing at medical institutions and proposes an architecture for providing a real-time monitoring service. The proposed system utilizes five types of raw (IR AC, IR DC, red AC, red DC, AMB), pulse, and SpO2 data measured using IoT pulse oximeters. Edge nodes are installed at every ward to collect, analyze, and monitor patient biosignal data through a wireless network. The collected biosignal data are transmitted to the cloud for managing and monitoring the data of all patients. This system enables medical institutions to collect and analyze raw biosignal data in real time, where an integrated management system can be established by connecting various IoT-based medical equipment.
Quantitative assessment of the cervical lymph nodes affected by medication-related osteonecrosis of the jaw using diffusion-weighted imaging
Authors: Muraoka Hirotaka , Kaneda Takashi , Kondo Takumi , Sawada Eri , Tokunaga Satoshi 
Published: July 2023

Abstract
Purpose
This study aimed to quantitively assess the apparent diffusion coefficient (ADC) values of cervical lymph nodes that were affected by medication-related osteonecrosis of the jaw (MRONJ).
Method
This retrospective study analyzed the ADC map of 70 patients with or without MRONJ (Stage 0 to 3) between April 2019 and March 2022. The mean ADC values of the submandibular (level ⅠB) and superior internal jugular (level IIA) nodes in normal participants and patients with MRONJ were calculated, and differences were analyzed using the Mann–Whitney test. Moreover, receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of ADC values to predict lymph nodes (LNs) that were affected by MRONJ. P < 0.05 was considered statistically significant.
Results
The mean ADCs (×10-3 mm2/s) of level IB in the normal and MRONJ groups were 0.75 ± 0.08 and 0.94 ± 0.15, respectively. The mean ADCs of level IIA in the normal and MRONJ groups were 0.8 ± 0.07 and 0.99 ± 0.16, respectively. ROC analysis revealed cutoff ADC values of 0.83 (level IB) and 0.93 (level IIA) for distinguishing between the normal and MRONJ groups. The sensitivity, specificity, accuracy, and area under the ROC curve values were 0.66–0.82, 0.86–0.97, 0.81–0.84, and 0.86–0.88, respectively.
Conclusion
This study revealed that the ADC value of cervical LNs that were affected by MRONJ was significantly different from those of the normal group. Thus, it may be a characteristic finding of MRONJ.
Stability of coupled memristive reaction-diffusion neural networks with time-varying delay
Authors: Li Chunquan , Xiong Zhijun 
Published: July 2023

Abstract
This article investigates the stability problem of time-delay coupled memristor reaction diffusion neural networks(DCMRNN). First, we give a delayed memris-tor reaction-diffusion neural network model. Then, a delay coupled memristor reaction diffusion neural network is obtained through linear coupling. Then, using Green’s formula and inequality techniques, an extended Lyapunov functional method is used to construct appropriate Lyapunov functional, and sufficient conditions are obtained to ensure the stability of DCMRNN; Finally, the effectiveness of the results was verified through two numerical examples.
Variation of photosynthesis along the canopy profile of sugarcane and energy canes
Authors: Cruz Larissa P. , Pacheco Vinícius S. , Nogueira Cíntia C. M. , Pissolato Maria D. , Almeida Rafael L. , Machado Eduardo C. , Ribeiro Rafael V. 
Published: July 2023

Abstract
Energy cane (Saccharum spp. hybrid) is a sustainable feedstock for the sucroenergetic sector due to its capacity of producing more biomass than sugarcane (Saccharum spp. hybrid). As biomass is formed by carbohydrates, photosynthesis is a key physiological process to understand the biomass production by plants. Herein, one sugarcane (IACSP95-5000) and two energy canes (Vertix 2 and Vertix 3) genotypes were cultivated under greenhouse conditions to evaluate the photosynthetic capacity of top leaves and to measure the actual photosynthesis of all green leaves of the main tiller. All genotypes showed similar maximum and actual photosynthesis in the top leaves, which was not correlated to their biomass production. In fact, the effects of leaf aging on canopy CO2 uptake, differential tillering and respiration rate seem to explain biomass production. IACSP95-5000 showed a sharp decrease in several photosynthetic traits and in abundance of key photosynthetic enzymes along the canopy profile, resulting in the lowest biomass yield. Vertix 2 and Vertix 3 exhibited a canopy with higher photochemical activity and lower variation in abundance of key photosynthetic enzymes with leaf aging as well as more well-developed tillers as compared with IACSP95-5000. Moreover, Vertix 2 – bred for high fiber content – exhibited a more homogeneous photosynthesis with leaf aging and higher growth respiration rate, two physiological traits associated with the highest biomass production among genotypes evaluated.
Synthesis, antiproliferative activity, 3D-QSAR and molecular docking studies of novel L-carvone-derived pyrimidine-urea compounds
Authors: Meng Yupei Meng , Zhang Yunxue Zhang , Duan Wengui Duan , Lin Guishan Lin , Cui Yucheng Cui , Li Baoyu Li 
Published: July 2023

Abstract
In order to explore novel antiproliferative compounds, twenty L-carvone-derived pyrimidine-urea compounds 4a – 4t were synthesized through the multi-step reaction of L-carvone, and structurally characterized by FT-IR, 1H-NMR, 13C-NMR, and HRMS. Besides, the in vitro antiproliferative activities of the target compounds against HepG2, Hela, and MCF-7 cells were evaluated by MTT assay. According to the results, the target compounds showed certain inhibitory activities against the tested cancer cell lines, and five compounds (4b, 4h, 4k, 4l, and 4t) exhibited better inhibition activities against Hela cell than the positive control (5-FU). Among them, compound 4b held significant antiproliferative activities against Hela and HepG2 cells, and thus deserved further study as a leading compound of new anticancer drugs. In addition, an effective and reasonable 3D-QSAR model was built by CoMFA method to analyze the relationship between the structures of the target compounds and their antiproliferative activities (expressed as pIC50) against Hela cell, and proven to have good predictive ability. Molecular docking was carried out to study the binding modes of compound 4b and Survivin which can enter the butt pocket like potential Survivin inhibitor GDP366, forming hydrogen bonding and hydrophobic interactions similar to each other.
Analysis of mechanical response mechanism and energy evolution characteristics of saturated coal with a single pre-existing hole
Authors: Lai Xingping , Fang Xianwei , Shan Pengfei , Gu Helong , Zhan Shuai , Liu Xudong 
Published: July 2023

Abstract
It is very important to elucidate the mechanical mechanism of the effect of water injection and large-diameter borehole pressure relief on coal rock deformation and failure for improving the pertinence and effectiveness of coal mine dynamic disaster prevention measures. In order to obtain the mechanical response mechanism and energy evolution characteristics of saturated coal with a single pre-existing hole, uniaxial compression test was carried out, and the failure process and acoustic emission characteristics of coal were monitored by using high-speed camera and acoustic emission monitoring system. The results show that the strength of coal samples deteriorated by 23.49%, 9.47% and 47.95% respectively by water saturation, single pre-existing holemeasures and the coupling effect of the two measures. The final failure mode of coal samples with different measures is shear failure mode. The law of fracture development and expansion and energy accumulation and release in different coal samples is roughly the same, but the speed of energy accumulation and release in different stages is different. Water saturation and single pre-existing hole measures can affect the impact risk of coal samples, and water saturation can significantly reduce the impact tendency of coal samples, and reduce the impact energy index of complete coal samples by 56.59%. The impact tendency index of natural coal sample is slightly increased by single pre-existing hole measures, and the impact energy index of intact coal sample is reduced by 46.78% by the coupling of saturated water and cavity measures. It can provide technical support for coal mine power disaster prevention and control.
A Novel Arithmetic Ant Colony Hybrid Optimization Algorithm for Numerical Computing
Authors: Wang Hongbo , Mo Yuanbin 
Published: July 2023

Abstract
The problem of finding all extremal points of a multimodal function and integrating complex functions are among the challenging problems in the field of intelligent optimization. To solve these numerical computation problems, a hybrid optimization algorithm named AOA-ACO, which combines the arithmetic optimization algorithm (AOA) and the ant colony optimization (ACO), is proposed in this paper. AOA is a newly proposed meta-heuristic algorithm in recent years, which has strong global exploration ability and local exploitation ability, and its optimization process has excellent characteristics of randomness and dispersion. ACO, on the other hand, has the characteristics of distributed computing and uses a positive feedback mechanism, but it is difficult to escape local optimum. Based on the characteristics of these two algorithms, AOA-ACO retains the position updating strategy of AOA and incorporates AOA's multiplication and division strategy and addition and subtraction strategy into the ACO optimization process, to enhance the balance between the algorithm's global exploration ability and local exploitation ability while maintaining its diversity, thereby improving the algorithm's computational accuracy y and convergence speed. The numerical experimental results show that compared with other intelligent optimization algorithms, AOA-ACO can calculate extremal points and integrals more accurately and with faster convergence speed.
AMS(2010)68W40
Distinct brain morphometry patterns revealed by deep learning improve prediction of aphasia severity
Authors: Teghipco Alex , Newman-Norlund Roger , Fridriksson Julius , Rorden Christopher , Bonilha Leonardo 
Published: July 2023

Abstract
Emerging evidence suggests that post-stroke aphasia severity depends on the integrity of the brain beyond the stroke lesion. While measures of lesion anatomy and brain integrity combine synergistically to explain aphasic symptoms, significant interindividual variability remains unaccounted for. A possible explanatory factor may be the spatial distribution of brain atrophy beyond the lesion. This includes not just the specific brain areas showing atrophy, but also distinct three-dimensional patterns of atrophy. Here, we tested whether deep learning with Convolutional Neural Networks (CNN) on whole brain morphometry (i.e., segmented tissue volumes) and lesion anatomy can better predict which individuals with chronic stroke (N=231) have severe aphasia, and whether encoding spatial dependencies in the data might be capable of improving predictions by identifying unique individualized spatial patterns. We observed that CNN achieves significantly higher accuracy and F1 scores than Support Vector Machine (SVM), even when the SVM is nonlinear or integrates linear and nonlinear dimensionality reduction techniques. Performance parity was only achieved when the SVM was directly trained on the latent features learned by the CNN. Saliency maps demonstrated that the CNN leveraged widely distributed patterns of brain atrophy predictive of aphasia severity, whereas the SVM focused almost exclusively on the area around the lesion. Ensemble clustering of CNN saliency maps revealed distinct morphometry patterns that were unrelated to lesion size, highly consistent across individuals, and implicated unique brain networks associated with different cognitive processes as measured by the wider neuroimaging literature. Individualized predictions of severity depended on both ipsilateral and contralateral features outside of the location of stroke. Our findings illustrate that three-dimensional network distributions of atrophy in individuals with aphasia are directly associated with aphasia severity, underscoring the potential for deep learning to improve prognostication of behavioral outcomes from neuroimaging data, and highlighting the prospective benefits of interrogating spatial dependence at different scales in multivariate feature space.
Main genes in breast cancer primary tumor and first metastasis in lymph nodes revealed by information-theory-based genetic networks analysis
Authors: Martínez-Vargas Irving , León-Pineda Moises , Alvarado-Mentado Matías 
Published: July 2023

Abstract

In this paper we identify genes that could be principal in breast cancer primary tumor and its firstmetastasis in lymph nodes, within biopsies in GEO and GDCDP database. By applying Information-Theory-based algorithms for processing gene expression profile matrices, we got the genetic networks ofnext tissues: 1) breast cancer free, 2) breast cancer primary tumor, and 3) first metastasis of breastcancer in lymph nodes. The topology analysis in the genetic networks allows for identifying gene-nodesdegree and the mutual information between pairs of genes. The late gene ontology based analysis on themolecular and functional character of genes with highest degree and mutual information confirm theirrelevance in the mentioned processes and reveals specific signaling pathways signature in cancer-free tissueand in the tumor microenvironment associated with primary and metastasis requirements. As well, thestate-of-the-art review on genes functional role identify tumor-suppressor genes in cancer-free tissue andproliferation and migration-associated genes in cancer.
On the application of virtual reality technology in the teaching of "landscape architecture design"
Authors: Yu Anping 
Published: July 2023

Abstract
"Landscape Architecture Design" is an important basic design course for undergraduates majoring in landscape architecture in China. The teaching focus is to cultivate students' cognition and design of three-dimensional garden space. At present, the classroom teaching of "Landscape Architecture Design" has a limited space dimension of course teaching. Virtual reality (VR) technology has immersive, the three characteristics of interactivity and conception can help teachers to enrich the form of classroom teaching, cultivate students' spatial thinking, and enhance students' spatial simulation experience. Focusing on the key points of virtual reality (VR) technology, this paper discusses the application of virtual reality (VR) technology in The specific implementation method in the course of "Landscape Architecture Design": in the teaching preparation process, teachers can use virtual reality technology to build a three-dimensional panoramic courseware library of landscape architecture cases, and students can break the geographical restrictions and enter the virtual scene to experience all parts of the world. Excellent garden landscape, at the same time, teachers can select excellent garden space cases according to the teaching theme, and collect VR information; secondly, in the classroom teaching, teachers can use projection equipment or students to use simple VR glasses to watch the panoramic cases that have been made.
Probabilistic Liquefaction Potential of Kathmandu Valley Soil Based on Standard Penetration Tests
Authors: Subedi Mandip , KC Rajan , Acharya Indra Prasad , Sharma Keshab , Bhandary Netra Prakash 
Published: July 2023

Abstract
Despite being a liquefaction susceptible zone, Kathmandu Valley soil in Nepal has limited studies on liquefaction potential and most of them are based on the deterministic approach. Although this method is widely used, it ignores the uncertainties of seismic parameters such as peak ground acceleration, amax, and earthquake magnitude, Mw as well as the inherent variabilities of soil layers, in-situ testing procedures, and geotechnical properties. On the other hand, the probabilistic approach helps assess the liquefaction potential by considering all these uncertainties. In this study, we assess the liquefaction hazard in the Kathmandu Valley using the first-order second-moment (FOSM) method as a probabilistic approach for liquefaction hazard assessment. The assessment is done for three likely-to-recur scenario earthquakes utilizing the geotechnical data of 1510 boreholes. The soils are characterized geotechnically to further assess susceptibility criteria of liquefaction in the valley. The assessment reveals that the central part of the valley is more vulnerable to liquefaction than other parts and the liquefaction probability increases with increasing depth up to 9 m, after which has geared down the value. Moreover, a relationship between the probability of liquefaction (PL) and the factor of safety (FS) against liquefaction is established. The hazard maps prepared for different earthquake scenarios can be useful for future infrastructure planning in Kathmandu Valley.