Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, and 0.09%, respectively. While the areas of Warm Temperature and Dessert will increase by 4.5% and 0.75%, respectively. The results of this study provide useful information on future climate Köppen-Geiger maps and areas that will most likely be affected by climate change in the following decades
Olfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od
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his project try to explain the using ability of spatial techniques for land cover change detection on regional level with the time parameter and did select for explain these abilities study case (Hewaizah marsh ) . this area apply to many big changes with the time. These changes made action on characters and behaviors of this area as well as all activities in it . This Project concerting to recognize the Using importance of remote sensing and GIS Methodology in data collecting for the changes of land use and the methodology for the analyses and getting the results for the next using as a base data for development and drawing the plans as well as in regional planning .This project focus on practical
... Show MoreStructure type and disorder have become important questions in catalyst design, with the most active catalysts often noted to be “disordered” or “amorphous” in nature. To quantify the effects of disorder and structure type systematically, a test set of manganese(III,IV) oxides was developed and their reactivity as oxidants and catalysts tested against three substrates: methylene blue, hydrogen peroxide, and water. We find that disorder destabilizes the materialsthermodynamically, making them stronger chemical oxidantsbut not necessarily better catalysts. For the disproportionation of H2O2 and the oxidative decomposition of methylene blue, MnOx-mediated direct oxidation competes with catalytically mediated oxidation, making the most
... Show Moreتتطلب كرة القدم الحديثة تطوير الصفات البدنية والمهارية للوصول باللاعب إلى لمستويات العليا، ولما كانت هذه الصفات مرتبطة مع بعضها البعض، فانها تتطلب ان يتم تطويرها معا في نفس الوقت دون تنمية كل صفة على حده، وإن توافر الحد الأدنى من الصفات البدنية كمتطلبات أساسية للأداء المهاري يعتبر الهدف الأساسي للتخطيط لأي برنامج تدريبي، وإن الصفات البدنية لها مفهوم شاسع وواسع الاستعمال في مجال البحوث الرياضية، وقد أعطيت ع
... Show Moreتهدف الدراسة الحالية الى استعمال الانموذج اللوجستي ثنائي المعلم في تدريج مقياس الشخصية الافتراضية المتعدد الابعاد لطلبة الجامعة وفقا لنظرية الاستجابة للفقرة، والخروج بتعميم لنتائج البحث والوقوف على الاجراءات العلمية المناسبة وتوفير تطبيق عملي علمي صحيح لاعتمادها من قبل الباحثين. وقد اتبعث الباحثة الاسلوب العلمي من خطوات واجراءات في عملية بناء المقياس حيث حدت ابعاد الشخصية الافتراضية المتمثلة بسبع ابعا
... Show MoreThese With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t
... Show MoreTraumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
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