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محمد والفتوحات الإسلامية
لقد حقق البروفسور (كبرييلي) في كتابه (محمد والفتوحات الإسلامية) نجاحا كبيرا في دمج المعلومات التاريخية والتفصيلات الكثيرة في الرواية العربية للفتوح الإسلامية، تلك الروايات التي هي في كثير من الأحيان متضاربة في المحتوى والسرد والسند، فقدم لنا رواية موضوعية وعلمية، لا تخلو من مناقشات جدلية للروايات ولطبيعة الأحداث التاريخية ومقارنتها مع الروايات الفارسية، أو الأرمنية أو البيزنطية أو الإستشراقية الأخرى، فجاء عرضه موحدا ومتناسقا. لا يجد فيه القارئ قفزات أو إنتقالات أو ثغرات سواء كان ذلك فيما يتعلق بالكرونولوجية الزمنية للأحداث أم في تماسك رواية الفتح في كل جبهة. كما بيد أن الذي يميز الكتاب الحالي (محمد والفتوحات الإسلامية) أن فيه ربط عميق ومفصلي بين النبي محمد صلى الله عليه وسلم وهو ممثل لطرف الشريعة أو الدين الإسلامي وما بين الفتوحات الإسلامية التي هي تمثيل عن السياسة أو الدولة وهذه الخاصية التي انفرد بها الدين الإسلامي كانت من بين أبرز العوامل التي حفزت الإستشراق بإستحضار الإسلام بوصفه مادة قابلة للتحليل والكشف عن هذه الظاهرة التي هددت لزمن طويل الوجود السياسي والديني للغرب ولا سيما زمان العصور الوسطى، فاتخذت من هذا المنحى الدراسات أبعاد متباينة منها متوتر ومتشنج رأى في الفتوحات الإسلامية مشروع لتأسيس إمبراطورية ثيوقراطية، فيما أنجزت دراسات امتازت بالموضوعية والإتزان العلمي في الطرح والتناول وربما كتاب \"محمد والفتوحات الإسلامية\" يصنف ضمن هذا التناول.
BOOK
Creating a Dashboard for Interactive Data Visualization with Dash in Python
This lesson shows how to create interactive web-based dashboards using Python's Dash library. Using two news media case studies, this lesson provides a practical guide for making digital humanities research outputs more accessible and engaging.
Journal Article
A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning
Continuously monitoring global population spatial dynamics is crucial for implementing effective policies related to sustainable development, including epidemiology, urban planning, and global inequality. However, existing global gridded population data products lack consistent population estimates, making them unsuitable for time-series analysis. To address this issue, this study designed a data fusion framework based on cluster analysis and statistical learning approaches, which led to the generation of a continuous global gridded population dataset (GlobPOP). The GlobPOP dataset was evaluated through two-tier spatial and temporal validation to demonstrate its accuracy and applicability. The spatial validation results show that the GlobPOP dataset is highly accurate. The temporal validation results also reveal that the GlobPOP dataset performs consistently well across eight representative countries and cities despite their unique population dynamics. With the availability of GlobPOP datasets in both population count and population density formats, researchers and policymakers can leverage the new dataset to conduct time-series analysis of the population and explore the spatial patterns of population development at global, national, and city levels.
Journal Article
Dual-locked spectroscopic probes for sensing and therapy
Optical imaging probes allow us to detect and uncover the physiological and pathological functions of an analyte of interest at the molecular level in a non-invasive, longitudinal manner. By virtue of simplicity, low cost, high sensitivity, adaptation to automated analysis, capacity for spatially resolved imaging and diverse signal output modes, optical imaging probes have been widely applied in biology, physiology, pharmacology and medicine. To build a reliable and practically/clinically relevant probe, the design process often encompasses multidisciplinary themes, including chemistry, biology and medicine. Within the repertoire of probes, dual-locked systems are particularly interesting as a result of their ability to offer enhanced specificity and multiplex detection. In addition, chemiluminescence is a low-background, excitation-free optical modality and, thus, can be integrated into dual-locked systems, permitting crosstalk-free fluorescent and chemiluminescent detection of two distinct biomarkers. For many researchers, these dual-locked systems remain a ‘black box’. Therefore, this Review aims to offer a ‘beginner’s guide’ to such dual-locked systems, providing simple explanations on how they work, what they can do and where they have been applied, in order to help readers develop a deeper understanding of this rich area of research.
Dual-locked optical probes change their optical signals when they respond to two biomarkers of interest. This facilitates real-time imaging of multiple interrelated biomarkers in living systems and, thus, provides opportunities to better understand pathological events and enhanced diagnostic specificity.
Journal Article
Tiliroside Ameliorates Ulcerative Colitis by Restoring the M1/M2 Macrophage Balance via the HIF-1α/glycolysis Pathway
Macrophages polarized to different phenotypes critically contribute to colitis development by coordinating inflammatory and anti-inflammatory processes. Herein, targeting the balance between the pro-inflammatory M1 and the anti-inflammatory M2 macrophage phenotypes can be a novel therapeutic approach for colitis. In the present study, we firstly demonstrated that tiliroside possessed the ability to alleviate the clinical symptoms of colitis as evidenced by decreased disease activity index (DAI) scores, longer colon length, reduced myeloperoxidase (MPO) activity, and improvement of colonic pathological damage in vivo . Furthermore, we showed that tiliroside modulated the balance between M1 and M2 macrophages toward a more anti-inflammatory status in colonic lamina propria but has little effect on the T cell population and epithelial barrier function in colitis mice. The macrophage depletion study further showed the protective effect of tiliroside was macrophage dependent in vivo . Mechanistically, our study demonstrated that tiliroside regulated cellular metabolism by inhibiting aerobic glycolysis in LPS and IFNγ stimulated macrophages. At the molecular level, tiliroside facilitated the proteasomal degradation of HIF-1α and downregulated mRNA expressions of HIF-1α dependent glycolytic enzymes in macrophages. Collectively, our data highlight the aberrant M1/M2 macrophage polarization in the initiation and development of ulcerative colitis and put forth the stage for considering tiliroside as a metabolic regulator in reprogramming macrophage polarization, which may serve as a promising therapeutic approach for treatment of inflammation-associated and metabolic disorders.
Journal Article
Upregulated m7G methyltransferase METTL1 is a potential biomarker and tumor promoter in skin cutaneous melanoma
The m7G methyltransferase METTL1 has been implicated in the occurrence and progression of several cancers. However, its clinical significance in cutaneous melanoma (SKCM) remains poorly understood. To address this gap, we conducted comprehensive data mining using publicly available datasets and two single-cell datasets. Additionally, we employed CCK8 assays, clone formation assays, and cell migration and invasion experiments to validate our findings from the data mining. Our results revealed that METTL1 is significantly upregulated in SKCM and is associated with a stem cell-like phenotype. Patients with high METTL1 expression exhibited worse prognosis. Furthermore, we identified that the high expression of METTL1 in SKCM is driven by copy number amplification and regulated by the transcription factor MYC. In vitro cellular studies confirmed that METTL1 knockdown significantly inhibited SKCM cell proliferation, clone formation, migration, and invasion. Notably, we observed a strong negative correlation between METTL1 expression and CD8+ T-cell infiltration in SKCM tissues. Moreover, our analysis revealed a significant negative correlation between METTL1 expression levels and the response to immunotherapy in SKCM patients, suggesting that METTL1 may serve as a potential biomarker for predicting immunotherapy response in SKCM. In summary, this study enhances our understanding of the role of m7G RNA modification in tumor progression and highlights METTL1 as a novel therapeutic target and biomarker for SKCM immunotherapy.
Journal Article
Capsule neural network and adapted golden search optimizer based forest fire and smoke detection
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural network (CNN) together with an adapted golden search optimizer (AGSO). By using advanced deep learning and optimization strategies, the method effectively identifies complex patterns linked to wildfires. Testing this model on wildfire smoke imagery and the BowFire dataset reveals that the proposed methodology outperformed traditional feature selection and classification methods. The integration of the modified CNN and AGSO facilitated rapid response and mitigation efforts, enhancing the accuracy and dependability of forest fire identification. This research highlights the importance of advanced computational techniques in reducing risks, ensuring safety, and progressing automatic forest fire detection systems. The combination of capsule neural networks with the golden search optimizer illustrates the potential of merging cutting-edge technologies to tackle intricate environmental issues efficiently.
Journal Article
Urban Forests and Green Environments for Sustainable Cities: Knowledge Landscape, Research Trends, and Future Directions
With the intensification of global urbanization and climate change challenges, urban green spaces and urban forests are playing an increasingly critical role in supporting sustainable urban development. Based on the Web of Science Core Collection, this study employed bibliometric analysis and visualization methods (VOSviewer 1.6.19 and Bibliometrix v5.0.1 (R package)) to systematically map the global knowledge landscape of urban green space and urban forest research from 2000 to 2025, identifying key thematic clusters and research fronts. The results show a shift in research focus from traditional green infrastructure and ecosystem service assessment to an integrated approach emphasizing multifunctionality, climate adaptation, public health, and governance innovation. Furthermore, research efforts are concentrated in rapidly urbanizing regions, and global spatial distribution remains a significant issue. Based on this, this paper proposes a strategic research agenda to promote the development of this field, including four key directions: (1) embedding social equity and people-oriented values into green space planning and management; (2) leveraging digital technologies and artificial intelligence to strengthen urban ecological governance; (3) promoting the transition of green infrastructure from fragmented to systematic ecological networks; and (4) deepening the role of urban green space in climate adaptation and sustainable urban transformation. By systematically combing through the knowledge system and governance logic of urban forests and greening, this article aims to reveal the key role of urban ecosystems in addressing climate change and promoting social well-being, and provide operational scientific basis and policy inspiration for the sustainable transformation of global cities.
Journal Article
Dynamic analysis on single-rotor multi-input helicopter main gearbox related with structural parameters
Combined with the finite element method and the lumped mass method, the integral node dynamic model of a single-rotor multi-input helicopter main gearbox is established. The influence of shaft parameters on dynamic characteristics is analyzed, and each torsional shaft is regarded as a finite element node to derive the system dynamic equation. In addition, the dynamic model of the meshing pair element is established by lumped mass method, and these elements not only include internal excitations such as time-varying meshing stiffness and transmission error, but also carry the external load. The differential equations of the system are solved by the Fourier series method. The dynamic responses of the converging element and the planetary gear train are obtained. The load-sharing coefficients of these elements are calculated by the influence of the shaft structural parameters. A parameter optimization method is proposed to improve the system load characteristics, which provides a theoretical support for the design of helicopter main transmission system.
Journal Article
Study on key parameters of a new abrasive flow machining (AFM) process for surface finishing
The conventional abrasive flow machining (AFM) and its derivatives (i.e., magneto, electro-chemical, and ultrasonic-aided AFMs) demand special machining devices, which limits the application and dissemination of AFM. A new AFM is developed in this study, which demands no extra special devices except for a tool bar made with cemented carbide. The effect of dynamic viscosity of abrasive medium, standoff distance, and tool bar rotating speed on pressure and velocity distributions of flow field is investigated using a numerical model. Moreover, experiments are conducted to explore the influence of abrasive-laden medium and process key parameters on this new AFM finishing effect. The results indicate that the pressure and velocity of flow field reach their maximum at the middle of the minimum standoff distance between tool bar and workpiece. The optimum abrasive grain size utilized in this AFM is found to be related to the minimum standoff distance between tool bar and workpiece during finishing process. The obtained optimum tool bar rotating speed, traverse speed, and number of processing cycles are 19,200 r/min, 500 mm/min, and 500 cycles, respectively. This new AFM is anticipated to become an efficient and economic tool for surface finishing.
Journal Article