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Developing a Model for Parkinson’s Disease Detection Using Machine Learning Algorithms

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Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif Al Mudawi department of Computer science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost

Multiscale spatiotemporal meteorological drought prediction:A deep learning approach

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Advances in Climate Change Research 2024年第2期15卷 211-221页

作者： Jia-Li ZHANG Xiao-Meng HUANG Yu-Ze SUN department of Earth system science Ministry of Education Key Laboratory for Earth System ModellingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China

Reliable monitoring and thorough spatiotemporal prediction of meteorological drought are crucial for early warning and decision-making regarding drought-related *** utilisation of multiscale methods is effective for a comprehensive evaluation of drought occurrence and progression,given the complex nature of meteorological ***,the nonlinear spatiotemporal features of meteorological droughts,influenced by various climatological,physical and environmental factors,pose significant challenges to integrated prediction that considers multiple indicators and time *** address these constraints,we introduce an innovative deep learning framework based on the shifted window transformer,designed for executing spatiotemporal prediction of meteorological drought across multiple *** formulate four prediction indicators using the standardized precipitation index and the standard precipitation evaporation index as core methods for drought definition using the ERA5 reanalysis *** indicators span time scales of approximately 30 d and one ***-term indicators capture more anomalous variations,whereas long-term indicators attain comparatively higher accuracy in predicting future *** focus on the East Asian region,notable for its diverse climate conditions and intricate terrains,to validate the model's efficacy in addressing the complexities of nonlinear spatiotemporal *** model's performance is evaluated from diverse spatiotemporal viewpoints,and practical application values are analysed by representative drought *** results substantiate the effectiveness of our proposed model in providing accurate multiscale predictions and capturing the spatiotemporal evolution characteristics of *** of the four drought indicators accurately delineates specific facets of the meteorological drought ***,three representative drought events,namely flash drought,sustained drought and severe drought,

关键词： Meteorological drought Spatiotemporal prediction Multiscale Swim transformer Deep learning

A hybrid memory architecture supporting fine-grained data migration

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Frontiers of Computer science 2024年第2期18卷 31-41页

作者： Ye CHI Jianhui YUE Xiaofei LIAO Haikun LIU Hai JIN National Engineering Research Center for Big Data Technology and system Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China department of Computer science Michigan Technological UniversityMichigan 49931USA

Hybrid memory systems composed of dynamic random access memory(DRAM)and Non-volatile memory(NVM)often exploit page migration technologies to fully take the advantages of different memory *** previous proposals usually migrate data at a granularity of 4 KB pages,and thus waste memory bandwidth and DRAM *** this paper,we propose Mocha,a non-hierarchical architecture that organizes DRAM and NVM in a flat address space physically,but manages them in a cache/memory *** the commercial NVM device-Intel Optane DC Persistent Memory Modules(DCPMM)actually access the physical media at a granularity of 256 bytes(an Optane block),we manage the DRAM cache at the 256-byte size to adapt to this feature of *** design not only enables fine-grained data migration and management for the DRAM cache,but also avoids write amplification for Intel Optane *** also create an Indirect Address Cache(IAC)in Hybrid Memory Controller(HMC)and propose a reverse address mapping table in the DRAM to speed up address translation and cache ***,we exploit a utility-based caching mechanism to filter cold blocks in the NVM,and further improve the efficiency of the DRAM *** implement Mocha in an architectural *** results show that Mocha can improve application performance by 8.2%on average(up to 24.6%),reduce 6.9%energy consumption and 25.9%data migration traffic on average,compared with a typical hybrid memory architecture-HSCC.

关键词： non-volatile memory hybrid memory system data migration fine-grained caching

Increasing phosphorus fertilizer value of recycled iron phosphates by prolonged flooding and organic matter addition

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Pedosphere 2024年第3期34卷 631-640页

作者： Rochelle Joie SARACANLAO Hannah VAN RYCKEL Mieke VERBEECK Maarten EVERAERT Erik SMOLDERS Division of soil and Water Management Department of Earth and Environmental ScienceKU LeuvenKasteelpark Arenberg 20Heverlee B-3001(Belgium) soil Service of Belgium.Willem De Croylaan 48 Leuven 3001(Belgium)

Iron(Fe)minerals are commonly used to remove phosphorus(P)from waste streams,producing P-loaded Fe(Ⅲ)oxides or Fe(Ⅱ)phosphate minerals(e.g.,vivianite).These minerals may be used as fertilizers to enhance P circularity if solubilized in ***,we tested the P fertilizer value of recycled Fe phosphates(FePs)in a pot trial and in an incubation experiment,hypothesizing that P release from FePs is possible under Fe(Ⅲ)-reducing ***,a pot trial was set up with rice(Oryza sativa)in all combinations of soil flooding or not,three P-deficient soils(acid,neutral,and calcareous),and six FePs(three Fe(Ⅲ)Ps and three Fe(Ⅱ)Ps)referenced to triple superphosphate(TSP)or zero *** P uptake responded to TSP application in all treatments but only marginally to *** redox potential did not decrease to-200 mV by flooding for a brief period(13 d)during the pot trial.A longer incubation experiment(60 d)was performed,including a treatment of glutamate addition to stimulate reductive conditions,and P availability was assessed with CaCl_(2)extraction of *** addition and/or longer incubation lowered soil redox potential tosoil and in the neutral soil amended with Fe(Ⅲ)*** can be concluded that prolonged soil flooding and organic matter addition can enhance the P fertilizer efficiency of ***,application of FeP in powder form may enhance P availability.

关键词： agronomic efficiency circular economy P-loaded Fe(Ⅲ)oxides paddy soil vivianite redox

Resistance and resilience of soil biological indicators:A case study with multi-walled carbon nanotube

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Pedosphere 2024年第3期34卷 664-675页

作者： Shagufta YASMEEN Nintu MANDAL Anupam DAS Pritam GANGULY Sanjay KUMAR Rajiv RAKSHIT department of soil science and Agricultural Chemistry Bihar Agricultural UniversitySabourBhagalpur 813210(India) department of Agronomy Bihar Agricultural UniversitySabourBhagalpur 813210(India)

soil ecosystem is experiencing stresses due to climate change,and soil inhabitants try to demonstrate their inherent resistance and resilience against those *** of nanomaterials as agricultural inputs could bring shifts in resistance and resilience patterns of soil microbes and associated enzymes,especially under short-term heat *** this background,the impacts of multi-walled carbon nanotube(MWCNT)on the resistance and resilience of soil biological indicators were *** incubation experiment was conducted with varied MWCNT concentrations(0,50,100,250,and 500 mg kg-1soil)for 90 d after 24-h heat stress at 48±2?C to assess the impacts of MWCNT on soil enzyme activities and microbial populations vis-à-vis their resistance and resilience indices under short-term exposure to heat *** activities were reduced after exposure to heat *** indices of enzyme activities were enhanced by MWCNT application on day 1 after heat stress,whereas there was no recovery of enzyme activities after 90-d *** soil enzyme activities,resistance index values of soil microbial populations followed the similar trend and were improved by MWCNT ***-walled carbon nanotube has the potential to improve resistance indices of soil enzyme activities and microbial populations under heat stress,although they could not recover to their original state during periodical incubation after heat *** study helps to understand the relative changes of biological indicators under MWCNT and their ability to withstand heat stress.

关键词： enzyme activity heat stress microbial population nanomaterial recovery

Reply to “Beyond microbial carbon use efficiency”

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National science Review 2024年第4期11卷 35-37页

作者： Feng Tao Johannes Lehmann Ying-Ping Wang Lifen Jiang Bernhard Ahrens Kostiantyn Viatkin Stefano Manzoni Benjamin Z.Houlton Yuanyuan Huang Xiaomeng Huang Yiqi Luo department of Ecology and Evolutionary Biology Cornell University soil and Crop sciences Section School of Integrative Plant ScienceCornell University CSIRO Environment Max Planck Institute for Biogeochemistry department of Physical Geography and Bolin Centre for Climate Research Stockholm University department of Global Development Cornell University Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences department of Earth system science Ministry of Education Key Laboratory for Earth System Modelling Institute for Global Change Studies Tsinghua University

In their commentary, Xiao et al.[1]cautioned that the conclusions on the critical role of microbial carbon use efficiency (CUE) in global soil organic carbon (SOC) storage in the paper by Tao et al.[2] might be too *** claimed that Tao et al.’s study lacked mechanistic consideration of SOC formation and excluded important data *** et al. brought up important points,which can be largely reconciled with our findings by understanding the differences in expressing processes in empirical studies and in models.

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Social Media-Based Surveillance systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan department of Computer science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia department of Information system College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

Predicted Critical State Based on Invariance of the Lyapunov Exponent in Dual Spaces

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Chinese Physics Letters 2024年第1期41卷 68-76页

作者：刘通夏旭 department of Applied Physics School of ScienceNanjing University of Posts and TelecommunicationsNanjing 210003China Academy of Mathematics and system sciences Chinese Academy of SciencesBeijing 100190China

Critical states in disordered systems,fascinating and subtle eigenstates,have attracted a lot of research ***,the nature of critical states is difficult to describe quantitatively,and in general,it cannot predict a system that hosts the critical *** propose an explicit criterion whereby the Lyapunov exponent of the critical state should be 0 simultaneously in dual spaces,namely the Lyapunov exponent remains invariant under the Fourier *** this criterion,we can exactly predict a one-dimensional quasiperiodic model which is not of self-duality,but hosts a large number of critical ***,we perform numerical verification of the theoretical prediction and display the self-similarity of the critical *** to computational complexity,calculations are not performed for higher dimensional ***,since the description of extended and localized states by the Lyapunov exponent is universal and dimensionless,utilizing the Lyapunov exponent of dual spaces to describe critical states should also be ***,we conjecture that some kind of connection exists between the invariance of the Lyapunov exponent and conformal invariance,which can promote the research of critical phenomena.

关键词： state exponent critical

Cadmium found in peanut(Arachis hypogaea L.) kernels mainly originates from root uptake rather than shell absorption from soil

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Pedosphere 2024年第4期34卷 726-735页

作者： Xin TANG Yurong WANG Changfeng DING Yuepeng YIN Zhigao ZHOU Taolin ZHANG Xingxiang WANG CAS Key Laboratory of soil Environment and Pollution Remediation Institute of Soil Science Chinese Academy of Sciences University of Chinese Academy of sciences Ecological Experimental Station of Red soil Chinese Academy of Sciences

Roots and shells are two potential organs through which peanut plants absorb cadium(Cd) from soils; however, the relative contributions of the two uptake pathways(root uptake and shell absorption) to kernel Cd accumulation and their translocation characteristics are poorly understood. In this study, the relative contributions of the two pathways to Cd accumulation in two peanut cultivars, Xianghua2008(XH) and Yueyou43(YY), were accurately assessed by labeling rooting and podding zone soils with113Cd and111Cd isotopes(0.3 mg kg-1dry soil), respectively, in a split-pot design. The results showed that approximately 96% of the Cd accumulated in the peanut kernels was derived from root uptake, while only 4% originated from shell absorption. Only 1% of the Cd accumulated in whole peanut plants was attributed to shell absorption, of which 41%–44% was retained in shells and 56%–59% was translocated to kernels. In contrast, the Cd absorbed by roots was efficiently translocated into all plant organs, of which 80%–84% was distributed in shoots. Although YY accumulated 1.3 times more Cd in whole plants than XH, the relative contributions of the two pathways to Cd accumulation in each plant organ were barely affected by peanut cultivars. Due to the strong retention effect of shells, shell-derived Cd was approximately 2 times higher than root-derived Cd in shells. These results would improve the understanding of Cd accumulation processes in peanut plants, revealing that the root uptake pathway contributes predominantly to the Cd concentration in peanut kernels, based on which strategies and technology for the reduction of Cd in peanut plants could be designed and developed.

关键词： absorption relative contribution split-pot soil stable isotope labeling translocation pathways