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Unveiling DNA methylation in Alzheimer’s disease:a review of array-based human brain studies

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Neural Regeneration Research 2024年第11期19卷 2365-2376页

作者： Victoria Cunha alves eva Carro Joana Figueiro-Silva Neurodegenerative Diseases Group Hospital Universitario 12 de Octubre Research Institute(imas12)MadridSpain Network Center for Biomedical Research Neurodegenerative Diseases(CIBERNED)MadridSpain PhD Program in Neuroscience Autonoma de Madrid UniversityMadridSpain Neurotraumatology and Subarachnoid Hemorrhage Group Hospital Universitario 12 de Octubre Research Institute(imas12)MadridSpain Neurobiology of Alzheimer’s Disease Unit Functional Unit for Research Into Chronic DiseasesInstituto de Salud Carlos IIIMadridSpain Institute of medical Genetics University of ZurichZurichSwitzerland Department of molecular Life Science University of ZurichZurichSwitzerland

The intricacies of Alzheimer’s disease pathogenesis are being increasingly illuminated by the exploration of epigenetic mechanisms,particularly DNA *** review comprehensively surveys recent human-centered studies that investigate whole genome DNA methylation in Alzheimer’s disease *** examination of various brain regions reveals distinctive DNA methylation patterns that associate with the Braak stage and Alzheimer’s disease *** entorhinal cortex emerges as a focal point due to its early histological alterations and subsequent impact on downstream regions like the ***,ANK1 hypermethylation,a protein implicated in neurofibrillary tangle formation,was recurrently identified in the entorhinal ***,the middle temporal gyrus and prefrontal cortex were shown to exhibit significant hypermethylation of genes like HOXA3,RHBDF2,and mCF2L,potentially influencing neuroinflammatory *** complex role of BIN1 in late-onset Alzheimer’s disease is underscored by its association with altered methylation *** the disparities across studies,these findings highlight the intricate interplay between epigenetic modifications and Alzheimer’s disease *** research efforts should address methodological variations,incorporate diverse cohorts,and consider environmental factors to unravel the nuanced epigenetic landscape underlying Alzheimer’s disease progression.

关键词： Alzheimer’s disease ANK1 BIN1 DNA methylation epigenome-wide association studies HOXA3 mCF2L RHBDF2

Plant community on a volcano mountaintop reveals unique high-altitude vegetation in southeastern Brazil

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Journal of mountain Science 2024年第9期21卷 3018-3030页

作者： Igor musauer KeSSOUS Ruy JoséValka alves Nílber Gonçalves da SILVA Amilcar Walter SAPOReTTI JUNIOR Biodiversity Laboratory Federal Institute of EducationScience and Technology of Southern Minas Gerais(IFSULDEMINAS)Av.Dirce Pereira Rosa300-Jardim Esperança37713-100Poços de CaldasMGBrazil Department of Botany National MuseumFederal University of Rio de JaneiroQuinta da Boa Vista s.n.São Cristóvão20949-040Rio de JaneiroRJBrazil Gothenburg Global Biodiversity Centre Carl Skottsbergs Gata 22BSE 41319GothenburgSweden

mountains exhibit a high degree of endemism and diversity,however,quantifying their biodiversity can be *** to islands,species isolation in mountainous regions results in comparable patterns of evolution and extinction,rendering their biodiversity unique and highly susceptible to anthropogenic *** topographic relief in mountains plays a crucial role in creating habitat complexity,which in turn contribute to high plant ***,we investigated plant diversity in the volcano mountaintop vegetation on the Poços de Caldas Plateau,a region situated in the ecotone between the Atlantic Forest and Cerrado,characterized by natural radiation and significant anthropogenic *** employed an automated approach through the filtering of georeferenced and non-georeferenced data to obtain a list of plant species in the ***,we statistically investigated the similarity among different high-altitude vegetations belonging to the campos de altitude from the Atlantic Forest and campos rupestres from the *** plateau exhibits high plant diversity,including 1,659 specific and infraspecific taxa,especially belonging to Asteraceae and *** analyses suggest that geographical distance is a strong predictor of dissimilarity and that the Poços de Caldas Plateau is more floristically related to the campos rupestres,despite being associated with campos de *** region possesses a unique set of biodiversity,indicating that it may be a distinct ***,we hypothesize that Pleistocene events likely influenced the conformation of the current floristic composition in the region through species interchange between the Cerrado and Atlantic *** study also highlights the few taxa assessed for conservation status and anthropogenic threats that this habitat is facing.

关键词： Atlantic Forest Biogeography Cerrado Community ecology Grassland

Time-Series embeddings from Language models:A Tool for Wind Direction Nowcasting

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Journal of meteorological Research 2024年第3期38卷 558-569页

作者： Decio alves Fabio meNDONCA Sheikh Shanawaz mOSTAFA Fernando mORGADO-DIAS University of madeira Campus Universitário da Penteada9020-105FunchalPortugal Interactive Technologies Institute/Laboratory for Robotics and engineering Systems and Agência Regional para o Desenvolvimento da Investigação Tecnologia e InovaçãoEdif.Madeira TecnopoloCaminho da Penteada piso-29020-105FunchalPortugal

Wind direction nowcasting is crucial in various sectors,particularly for ensuring aviation operations and *** this context,the TeLmo(Time-series embeddings from Language models)model,a sophisticated deep learning architecture,has been introduced in this work for enhanced wind-direction *** by using three years of data from multiple stations in the complex terrain of an international airport,TeLmo incorporates the horizontal u(east-west)and v(north-south)wind components to significantly reduce forecasting *** a day with high wind direction variability,TeLmo achieved mean absolute error values of 5.66 for 2-min,10.59 for 10-min,and 14.79 for 20-min forecasts,processed within a swift 9-ms/step *** degree-based analysis,in comparison,yielded lower performance,emphasizing the effectiveness of the u and v *** contrast,a Vanilla neural network,representing a shallow-learning approach,underperformed in all analyses,highlighting the superiority of deep learning methodologies in wind direction *** is an efficient model,capable of accurately forecasting wind direction for air traffic operations,with an error less than 20°in 97.49%of the predictions,aligning with recommended international *** model design enables its applicability across various geographical locations,making it a versatile tool in global aviation meteorology.

关键词： wind nowcasting wind components wind direction time series prediction deep learning

A review on the scale-up of high-shear wet granulation processes and the impact of process parameters

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Particuology 2024年第9期92卷 180-195页

作者： Ana Rita alves marta Filipe Simões Sérgio Simões João Gomes University of Coimbra CERESDepartment of Chemical EngineeringFaculty of Sciences and TechnologyRua Sílvio Lima3030-790CoimbraPortugal Bluepharma-Indústria Farmacêutica São Martinho do BispoCoimbra3045-016Portugal Faculty of Pharmacy University of CoimbraAzinhaga de Santa Comba3000-548CoimbraPortugal

Wet granulation is one of the most important agglomeration processes,and high-shear granulation(HSG)one of the most employed technologies in the pharmaceutical *** most critical process parameters of HSG are discussed in this *** main concern in scaling up the wet granulation process is the differences between scales,which prevent the particles from having the same experience across all *** scale-up of wet granulation processes is commonly divided into two categories:engineering and attribute-based *** engineering-based scale-up approach is a strategy based on dimensional analysis and an attribute-based supported on the principles of“equifinality”,where process variables are adjusted to obtain equivalent granule *** work presents the effect of different HSG process parameters on the scale-up,as well as the use of process analytical tools(PAT)and modelling *** aim is to review applied scale-up approaches in HSG and discuss benefits and *** is proven why the scale-up for oral solid pharmaceutical products is still considered a hot topic and a very challenging task for development and engineering teams.

关键词： High-shear wetgranulation Parametric-based Attribute-based Physics-based modelling Impeller design Scale-up

enhanced quantum resources via two distant atom-cavity systems under the influence of atomic dissipation

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Communications in Theoretical Physics 2024年第2期76卷 62-73页

作者： m Setodeh Kheirabady m K Tavassoly m Rafeie e Ghasemian Laser and Optics Group Faculty of PhysicsYazd UniversityYazd 89195-741Iran Department of electrical engineering Faculty of Intelligent Systems Engineering and Data SciencePersian Gulf UniversityBushehrIran

Quantum resources such as entanglement and coherence are the holy grail for modern quantum technologies. Although the unwanted environmental effects tackle quantum information processing tasks, suprisingly these key quantum resources may be protected and even enhanced by the implementation of some special hybrid open quantum systems. Here, we aim to show how a dissipative atom-cavity-system can be accomplished to generate enhanced quantum *** do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atoms interacting with a single-mode cavity field. In practical applications, a classical laser field may be applied to drive each atomic subsystem. After driving the system, a Bell-state measurement is performed on the output of the system to quantify the entanglement and coherence. The obtained results reveal that the remote entanglement and coherence between the atoms existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglement between two atoms inside each dissipative cavity attenuates due to the presence of unwanted environmental ***, the local coherence may show the same behavior as the remote ***, the system provides the steady state entanglement in various interaction regimes,particularly in the strong atom-cavity coupling and with relatively large detuning. more interestingly, our numerical analyses demonstrate that the system may show a memory effect due to the fact that the death and revival of the entanglement take place during the interaction. Our proposed model may find potential applications for the implementation of long distance quantum networks. In particular, it facilitates the distribution of quantum resources between the nodes of large-scale quantum networks for secure communication.

关键词： remote entanglement and coherence atomic dissipation steady state entanglement Bell-statemeasurement

effect of resistance training volume on body adiposity,metabolic risk,and inflammation in postmenopausal and older females:Systematic review and meta-analysis of randomized controlled trials

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Journal of Sport and Health Science 2024年第2期13卷 145-159页

作者： Paulo Ricardo Prado Nunes Pamela Castro-e-Souza Anselmo alves de Oliveira Bruno de Freitas Camilo Gislaine Cristina-Souza Lucio marques Vieira-Souza marcelo Augusto da Silva Carneiro Department of Body and Human movement Minas Gerais State University(UEMG)37902-092 PassosMGBrazil University Center of Planalto de Araxa(UNIARAXA) 38180-129 AraxaMGBrazil Physical Activity Health and Ageing Research Group(GPASE)Minas Gerais State University(UEMG)37902-092 PassosMGBrazil exercise and Nutrition Research Group(GPeN) Minas Gerais State University(UEMG)37902-092 PassosMGBrazil Sport Sciences and Physical exercise Study and Research Group(GePCeeX) Minas Gerais State University(UEMG)37902-092 PassosMGBrazil metabolism Nutrition and Exercise LaboratoryPhysical Education and Sport CenterLondrina State University(UEL)86050-070 LondrinaPRBrazil Postgraduate Program in Physical education Federal University of Sergipe(UFS)49107-230 Sao CristovaoSEBrazil

Purpose:This meta-analytical study aimed to explore the effects of resistance training(RT) volume on body adiposity,metabolic risk,and inflammation in postmenopausal and older ***:A systematic search was performed for randomized controlled trials in Pubmed,Scopus,Web of Science,and *** controlled trials with postmenopausal and older females that compared RT effects on body adiposity,metabolic risk,and inflammation with a control group(CG) were *** reviewers selected the studies,extracted the data,and performed the risk of bias and certainty of the evidence(Grading of Recommendations,Assessment,Development,and evaluation(GRADe)) *** body and abdominal adiposity,blood lipids,glucose,and C-reactive protein were included for meta-analysis.A random-effects model,standardized mean difference(Hedges’ g),and 95% confidence interval(95%CI) were used for ***:Twenty randomized controlled trials(overall risk of bias:some concerns;GRADe:low to very low) with overweight/obese postmenopausal and older females were *** groups were divided into low-volume RT(LVRT,~44 sets/week) and high-volume RT(HVRT,~77 sets/week).Both RT groups presented improved body adiposity,metabolic risk,and inflammation when compared to ***,HVRT demonstrated higher effect sizes than LVRT for glucose(HVRT=-1.19;95%CI:-1.63 to-0.74;LVRT=-0.78;95%CI:-1.15 to-0.41) and C-reactive protein(HVRT=-1.00;95%CI:-1.32 to-0.67;LVRT=-0.34;95%CI,-0.63 to-0.04)) when compared to ***:Compared to CG,HVRT protocols elicit greater improvements in metabolic risk and inflammation outcomes than LVRT in overweight/obese postmenopausal and older females.

关键词： C-reactive protein Fat mass Lipid profile menopause Strength training

Liquid crystal immunosensors for the selective detection of escherichia coli with a fast analysis tool

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Photonics Research 2024年第7期12卷 1564-1573页

作者： SANDRO C.OLIVeIRA mARIA S.SOAReS BÁRBARA V.GONÇalves ANDReIA C.m.RODRIGUeS AmADeU m.V.m.SOAReS RITA G.SOBRAL NUNO F.SANTOS JAN NeDOmA PeDRO L.ALmeIDA CARLOS mARQUeS CICeCO-Aveiro Institute of materials Physics DepartmentUniversity of Aveiro3810-193 AveiroPortugal i3N Physics DepartmentUniversity of Aveiro3810-193 AveiroPortugal Associate Laboratory i4HB-Institute for Health and Bioeconomy School of Sciences and TechnologyNOVA University of Lisbon1099-085 LisbonPortugal CeSAm-Centre for environmental and marine Studies and Department of Biology University of Aveiro3810-193 AveiroPortugal Department of Telecommunications VSB-Technical University of OstravaOstrava 70800Czech Republic i3N-CeNImAT School of Sciences and TechnologyNOVA University of Lisbon1099-085 LisbonPortugal UnIRe ISELPolytechnic Institute of Lisbon1549-020 LisbonPortugal Department of Physics VSB-Technical University of OstravaOstrava 70800Czech Republic

The consumption of contaminated food may cause serious illnesses,and traditional methods to detect escherichia coli are still associated with long waiting times and high costs given the necessity to transport samples to specialized *** is a need to develop new technologies that allow cheap,fast,and direct monitoring at the site of ***,in this work,we developed optical immunosensors for the selective detection of ***,based on liquid crystal technology,whose molecules can align in different manners depending on the boundary conditions (such as substrates) as well as the environment that they *** glass substrate was functionalized with *** antibody using cysteamine as an intermediate,and a vertical alignment was imposed on the liquid crystal molecules by using DmOAP during *** presence of bacteria disrupts the alignment of the liquid crystal molecules,changing the intensity of light emerging between cross polarizers,measured using a polarized optical microscope and a *** was possible to detect *** in suspensions in the concentration range from 2.8 cells/mL to 2.8×10^(9) cells∕*** was also evaluated,and the sensors were used to analyze contaminated water samples.A prototype was developed to allow faster,in-situ,and easier analysis avoiding bulky instruments.

关键词： crystal alignment analysis

Novel Framework for an Intrusion Detection System Using multiple Feature Selection methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.e.m.eljialy mohammed Yousuf Uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. machine learning (mL) techniques are extensively applied to build robust IDSs. many researchers have utilized different mL methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the mL model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： m.e.Al-Atroush A.e.Aboelela ezz el-Din Hemdan Civil and environmental engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(mL)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVms),and least squares support vector machines(LSSVms).It was found that despite mL approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset