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中学生英语 2024年第7期 29-31页

作者： melissa Breyer 张宁(译) 不详

无论猫是因为它们的胡须而可爱,还是因为它们长在猫身上而可爱,有一点是肯定的:这两者构成了一个令人无法抗拒的可爱组合。以下是关于这些特殊毛发的一些鲜为人知的事实。

关键词：胡须可爱猫事实

Water Vapor Information from Satellite and Its Applications

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Advances in Atmospheric Sciences 2024年第1期41卷 188-189页

作者： B.j.SOHN School of Earth and Environmental Sciences Seoul National UniversitySeoul 08826Korea

Water vapor is a critical component of the hydrological cycle because it plays a vital role in transporting water from one part of the cycle to *** vapor evaporated from surfaces such as oceans,lakes,and rivers conden... 详细信息

关键词： motion oceans lakes

SCFD1 in amyotrophic lateral sclerosis:reconciling a genetic association with in vivo functional analysis

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Neural Regeneration Research 2024年第6期19卷 1201-1202页

作者： Ruben j.Cauchi Centre for Molecular Medicine and Biobanking Biomedical Sciences BuildingDepartment of Physiology and BiochemistryFaculty of Medicine and SurgeryUniversity of MaltaMsidaMalta

Amyotrophic lateral sclerosis(ALS)is a neurodegenerative disease characterized by progressive loss of upper and lower motor neurons,resulting in muscle weakness and spasticity,eventually leading to death due to respiratory *** by our group of a casecontrol cohort from an isolated island population have found that genetics plays a significant role in disease etiology(Farrugia Wismayer et al.,2023).

关键词： sclerosis respiratory

Racial and Ethnic Differences in Orthorexia Nervosa Symptomatology and Other Disordered Eating

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Open j.urnal of Psychiatry 2024年第4期14卷 287-299页

作者： Dilan H. Arreguin Kendria S. Shields-Rhodes melissa L. Harel Crystal D. Oberle Department of Psychology Texas State University San Marcos TX USA

While some research has explored racial and ethnic differences in disordered eating, this study may be the first to examine these differences in orthorexia nervosa, involving obsessive-compulsive thoughts and behaviors concerning healthy eating, which negatively impact one’s life. Adult participants, recruited from college courses and social media, completed an online survey with the Orthorexia Nervosa Inventory (ONI) and the Eating Attitudes Test-26 (EAT-26). Regarding racial and ethnic background, 743 were White, 249 were Hispanic, 87 were Black, 61 were Asian or Pacific Islander, and 110 were biracial/multiracial. A MANCOVA revealed that the racial and ethnic groups did not differ on the ONI subscales assessing orthorexic behaviors, impairments, and emotions, after accounting for gender, BMI, and EAT-26 total scores that were covariates. In contrast, a second MANCOVA did reveal group differences on the EAT-26 subscales, after accounting for gender, BMI, and ONI total scores that were covariates. Black participants scored significantly lower than the other racial and ethnic groups on the subscale assessing dieting behaviors characteristic of anorexia nervosa, and the subscale assessing binge-eating and purging behaviors characteristic of bulimia nervosa. Further, Hispanic participants scored significantly lower than White participants on the latter subscale. These findings suggest that while orthorexic symptomatology does not differ based on race and ethnicity, a Black race and Hispanic ethnicity may be protective factors against disordered eating, perhaps related either to cultural norms concerning body image or to the resiliency and social support among the Black and Hispanic communities.

关键词： Race Ethnicity Orthorexia Disordered Eating

Enhancing Ulcerative Colitis Diagnosis:A Multi-Level Classification Approach with Deep Learning

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 1129-1142页

作者： Hasan j.Alyamani Department of Information Systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis,a condition with significant clinical ***,endoscopic assessment is susceptible to inherent variations,both within and between observers,compromising the reliability of individual *** study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease *** initiate this endeavor,a multi-faceted approach is embarked *** dataset is meticulously preprocessed,enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization(CLAHE).A diverse array of data augmentation techniques,encompassing various geometric transformations,is leveraged to fortify the dataset’s diversity and facilitate effective feature extraction.A fundamental aspect of the approach involves the strategic incorporation of transfer learning principles,harnessing a modified ResNet-50 *** augmentation,informed by domain expertise,contributed significantly to enhancing the model’s classification *** outcome of this research endeavor yielded a highly promising model,demonstrating an accuracy rate of 86.85%,coupled with a recall rate of 82.11%and a precision rate of 89.23%.

关键词： Ulcerative colitis deep learning CLAHE transfer learning geometric transformations

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Rethinking the egg

National Science Review 2024年第6期11卷 81-82页

作者： Michael j.Benton School of Earth Sciences University of Bristol

Our image of early dinosaur eggs must change. Early dinosaur eggs are portrayed as soft-shelled, like those of modern lizards or snakes [1], and yet all the evidence is that early dinosaurs at least laid leathery-shel...

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Intelligent Machine Learning Based Brain Tumor Segmentation through Multi-Layer Hybrid U-Net with CNN Feature Integration

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Computers, Materials & Continua 2024年第4期79卷 1301-1317页

作者： Sharaf j.Malebary Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityP.O.Box 344Rabigh21911Saudia Arabia

Brain tumors are a pressing public health concern, characterized by their high mortality and morbidity ***, the manual segmentation of brain tumors remains a laborious and error-prone task, necessitatingthe development of more precise and efficient methodologies. To address this formidable challenge, we proposean advanced approach for segmenting brain tumorMagnetic Resonance Imaging (MRI) images that harnesses theformidable capabilities of deep learning and convolutional neural networks (CNNs). While CNN-based methodshave displayed promise in the realm of brain tumor segmentation, the intricate nature of these tumors, markedby irregular shapes, varying sizes, uneven distribution, and limited available data, poses substantial obstacles toachieving accurate semantic segmentation. In our study, we introduce a pioneering Hybrid U-Net framework thatseamlessly integrates the U-Net and CNN architectures to surmount these challenges. Our proposed approachencompasses preprocessing steps that enhance image visualization, a customized layered U-Net model tailoredfor precise segmentation, and the inclusion of dropout layers to mitigate overfitting during the training ***, we leverage the CNN mechanism to exploit contextual information within brain tumorMRI images,resulting in a substantial enhancement in segmentation *** experimental results attest to the exceptionalperformance of our framework, with accuracy rates surpassing 97% across diverse datasets, showcasing therobustness and effectiveness of our approach. Furthermore, we conduct a comprehensive assessment of ourmethod’s capabilities by evaluating various performance measures, including the sensitivity, j.ccard-index, andspecificity. Our proposed model achieved 99% accuracy. The implications of our findings are profound. Theproposed Hybrid U-Net model emerges as a highly promising diagnostic tool, poised to revolutionize brain tumorimage segmentation for radiologists and clinician

关键词： Brain tumor Hybrid U-Net CLAHE transfer learning MRI images

First-principles calculations to investigate structural,electronic,magnetic,optical and thermodynamic properties of RE_(2)Rh_(3)Ge(RE=Pr,Sm)

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j.urnal of Rare Earths 2024年第7期42卷 1385-1393,I0007页

作者： A.Ezaier R.Masrour M.Hamedoun j.Kharbach A.Rezzouk A.Hourmatallah N.Benzakour K.Bouslykhane Laboratory of Solid Physics Faculty of Sciences Dhar El MehrazSidi Mohamed Ben Abdellah UniversityBP 1796FezMorocco Equipe de Physique du Solide LaboratoiresLIPIEcole Normale SupérieureBensoudaFèsMorocco

In this paper,we analyzed the physical characteristics of the ternary alloys RE_(2)Rh_(3)Ge(RE=Pr and Sm)using the first principles calculation based on functional density theory integrated in the Wien2k *** calculated formation energies of Pr_(2)Rh_(3)Ge and Sm_(2)Rh_(3)Ge are−5.3827 and−5.2782 eV/atom,respectively,showing that these alloys may exist *** results of the band structure and density of states indicate that all of the compounds tested are magnetic metals,and their magnetism is mostly related to the contribution of Pr and Sm *** total magnetic moments of Pr_(2)Rh_(3)Ge and Sm_(2)Rh_(3)Ge are 4.07245 and 11.16161μB/f.u,*** parameters such as heat capacity at constant pressure,entropy,Debye temperature,lattice volume,compressibility coefficients,and Grüneisen parameter alloys were calculated using the Gibbs algorithm and studied in depth over a large temperature range of 0-900 *** Debye temperature increases with increasing pressure and decreases with decreasing ***,the Debye temperatures calculated at p=0 GPa and T=300 K are equal to be 342 and 322 K for Pr_(2)Rh_(3)Ge and Sm_(2)Rh_(3)Ge,*** optical characteristics such as the real and imaginary portions of the dielectric function,the absorption coefficient,the energy-loss function,and the refractive index were investigated and discussed in more depth.

关键词： Magnetic metals Functional density theory Density of states Magnetic moment Optical and thermodynamic properties Rare earths

Unmixing detrital zircon U-Pb ages reveals tectonic and climatic depositional influences on the Carboniferous Ansilta Formation,Calingasta-Uspallata Basin,Western Argentina

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Geoscience Frontiers 2024年第4期15卷 61-77页

作者： j.R.Malone j.E.Malone j.L.Isbell D.H.Malone j.P.Craddock K.N.Pauls Department of Geological Sciences Jackson School of GeosciencesUniversity of Texas at AustinAustinTX 78712USA Iowa Geological Survey University of IowaIowa CityIA 52240USA Department of Geosciences University of Wisconsin-MilwaukeeMilwaukeeWI 53211USA Department of Geography Geology and the EnvironmentIllinois State UniversityNormalIL 61790-4400USA

The Late Paleozoic Ice Age(LPIA)was a principal control of sedimentation across Gondwana from the late Devonian through early *** assess the hypothesis that glacial to interglacial transitions in western Argentina were the primary control influencing sediment routing patterns among the various Carboniferous-Permian basins in western *** Carboniferous Ansilta Formation consists of glaciomarine,nearshore,and fluvial systems deposited during the LPIA along the eastern margin of the Calingasta-Uspallata Basin in *** lower,glacially influenced succession of the Ansilta Formation records at least five glacial advances;the upper succession of consists of progradational shallow marine,deltaic,and fluvial *** combine 1225 new U-Pb zircon ages from six samples of the Carboniferous Ansilta Formation in the Calingasta-Uspallata Basin with 5864 U-Pb ages from 147 pub-lished samples in the detrital Pymix forward mixture model to characterize provenance *** the glacially influenced lower Ansilta Formation,sediment was derived locally from the Protoprecordillera,which was a prominent highland with alpine glaciers flowing west and east into the Calingasta-Uspallata and Paganzo basins,***,there was little or no connection between these two basins during Serpukhovian-Bashkirian *** fluvial/deltaic upper Ansilta had distal sediment sources in the Sierras ***,our results support the collapse of the Protoprecordillera topographic barrier,enabling drainage patterns connecting the Paganzo and Calingasta-Uspallata basins by late Pennsylvanian-early Permian time.

关键词： Late Paleozoic Ice Age Argentina Calingasta-Uspallata Basin Ansilta Formation Detrital zircon provenance

Efficient Vision Transformers for Autonomous Off-Road Perception Systems

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j.urnal of Computer and Communications 2024年第9期12卷 188-207页

作者： Max H. Faykus III Adam Pickeral Ethan Marquez melissa C. Smith j.n C. Calhoun Holcombe Department of Electrical and Computer Engineering Clemson University Clemson SC USA

The development of autonomous vehicles has become one of the greatest research endeavors in recent years. These vehicles rely on many complex systems working in tandem to make decisions. For practical use and safety reasons, these systems must not only be accurate, but also quickly detect changes in the surrounding environment. In autonomous vehicle research, the environment perception system is one of the key components of development. Environment perception systems allow the vehicle to understand its surroundings. This is done by using cameras, light detection and ranging (LiDAR), with other sensor systems and modalities. Deep learning computer vision algorithms have been shown to be the strongest tool for translating camera data into accurate and safe traversability decisions regarding the environment surrounding a vehicle. In order for a vehicle to safely traverse an area in real time, these computer vision algorithms must be accurate and have low latency. While much research has studied autonomous driving for traversing well-structured urban environments, limited research exists evaluating perception system improvements in off-road settings. This research aims to investigate the adaptability of several existing deep-learning architectures for semantic segmentation in off-road environments. Previous studies of two Convolutional Neural Network (CNN) architectures are included for comparison with new evaluation of Vision Transformer (ViT) architectures for semantic segmentation. Our results demonstrate viability of ViT architectures for off-road perception systems, having a strong segmentation accuracy, lower inference speed and memory footprint compared to previous results with CNN architectures.

关键词： Semantic Segmentation Off-Road Vision Transformers CNNs Autonomous Driving