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الاستراتيجيات العسكرية في الصين القديمة
يدور موضوع الكتاب حول \"الاستراتيجيات العسكرية في الصين القديمة\" هذا العنوان يدخل في حقل الكتب العسكرية أو ما يعرف بـ (الأدب العسكري) وهو حسب مؤلفه الصيني \"لي تشينغ بين\" أحد أعظم ميراث ثقافي للأمة الصينية، أدب غني بالدلالات الثقافية والمزايا الفريدة التي تعرف إليها المؤلف بعد أن بحث في الأدب العسكري القديم في بلاده بما في ذلك أحد أعظم أعماله وهي فن الحرب لما يفوق الثلاثين عاما. لقد صرح أن هذا الأدب يتمتع بحكمة كبيرة، واستراتيجيات بالإضافة إلى مفاتيح النجاح ويمكن أن يتم الرجوع إلى الكتب العسكرية القديمة لتقييم الاستراتيجيات الفعالة من قبل العديد من الأشخاص، بمن فيهم القادة العسكريون، السياسيون، الدبلوماسيون، رجال الأعمال، وحتى الناس العاديون. ولأن الكتب العسكرية تلعب دور ناقل الثقافة، لذلك، يفترض المؤلف أنه من الأفضل لكل شخص متعلم أن يقرأ هذا النوع من الكتب بغض النظر عن مهنته. كتاب \"الاستراتيجيات العسكرية في الصين القديمة\" هو نقطة في بحر العدد الهائل من الكتب الصينية الكلاسيكية القديمة بالإضافة للأدب العسكري العميق، لقد اختار المؤلف ما يزيد عن ثلاثمائة بند في ثمانين كتابا عسكريا قديما وأضاف الشروحات الصينية والترجمات الإنجليزية المتوافقة في هذا الكتاب بهدف مساعدة القراء في فهم ودراسة الأدب العسكري القديم. يتضمن هذا الكتاب ترجمة الأصل الإنجليزي \"Military Strategies in Ancient China\" نقلته إلى العربية نهى حسن ويأتي باللغتين العربية والصينية مما يسهم في تعلم اللغة الصينية للناطقين بالضاد.
Book
An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data
Finding effective and objective biomarkers to inform the diagnosis of schizophrenia is of great importance yet remains challenging. Relatively little work has been conducted on multi-biological data for the diagnosis of schizophrenia. In this cross-sectional study, we extracted multiple features from three types of biological data, including gut microbiota data, blood data, and electroencephalogram data. Then, an integrated framework of machine learning consisting of five classifiers, three feature selection algorithms, and four cross validation methods was used to discriminate patients with schizophrenia from healthy controls. Our results show that the support vector machine classifier without feature selection using the input features of multi-biological data achieved the best performance, with an accuracy of 91.7% and an AUC of 96.5% (
p
< 0.05). These results indicate that multi-biological data showed better discriminative capacity for patients with schizophrenia than single biological data. The top 5% discriminative features selected from the optimal model include the gut microbiota features (
Lactobacillus
,
Haemophilus
, and
Prevotella
), the blood features (superoxide dismutase level, monocyte-lymphocyte ratio, and neutrophil count), and the electroencephalogram features (nodal local efficiency, nodal efficiency, and nodal shortest path length in the temporal and frontal-parietal brain areas). The proposed integrated framework may be helpful for understanding the pathophysiology of schizophrenia and developing biomarkers for schizophrenia using multi-biological data.
Journal Article
الاقتصاد الصيني
يتناول كتاب (الاقتصاد الصيني) والذي قام بتأليفه (وو دي لي، سوي فو مين، تشنغ لي) في حوالي (127) صفحة من القطع المتوسط موضوع (اقتصاد الصيني) مستعرضا التالي : يتحدث عن الإنجازات الملحوظة التي حققها الاقتصاد الصيني منذ أكثر من ثلاثين عاما هي مدة الإصلاح والانفتاح، وارتفاع مكانته الدولية بصورة متزايدة. وعن الاتجاه المستقبلي لاقتصاد الصين وإسهامات الاقتصاد الصيني في الاقتصاد العالمي ؟ ويمكن للقارئ أن يحصل على أجوبة لكل هذه الأسئلة من ذلك الكتاب.
Book
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Despite progress in perceptual tasks such as image classification, computers still perform poorly on cognitive tasks such as image description and question answering. Cognition is core to tasks that involve not just recognizing, but reasoning about our visual world. However, models used to tackle the rich content in images for cognitive tasks are still being trained using the same datasets designed for perceptual tasks. To achieve success at cognitive tasks, models need to understand the interactions and relationships between objects in an image. When asked “What vehicle is the person riding?”, computers will need to identify the objects in an image as well as the relationships
riding(man, carriage)
and
pulling(horse, carriage)
to answer correctly that “the person is riding a horse-drawn carriage.” In this paper, we present the Visual Genome dataset to enable the modeling of such relationships. We collect dense annotations of objects, attributes, and relationships within each image to learn these models. Specifically, our dataset contains over 108K images where each image has an average of
35
objects,
26
attributes, and
21
pairwise relationships between objects. We canonicalize the objects, attributes, relationships, and noun phrases in region descriptions and questions answer pairs to WordNet synsets. Together, these annotations represent the densest and largest dataset of image descriptions, objects, attributes, relationships, and question answer pairs.
Journal Article
Dynamic financial and monetary security risk assessment based on information service security assessment model and blockchain
With the rapid development of blockchain technology, the financial and monetary (FM) blockchain fields also began to collide. Therefore, this study aims to explore the relationship between the two fields and efficiently evaluate the security of financial information. Firstly, this study introduces the theoretical basis of blockchain in the dynamic linkage mechanism of FM and gives the overall framework of digital currency based on blockchain. Meanwhile, the relationship between blockchain and digital finance is empirically analyzed and designed. Secondly, the framework of financial information service security assessment (ISSA) is created using blockchain technology, and the frame of security risk evaluation is verified by taking electronic invoice information as the research object. Finally, the results show that: (1) foreign exchange (forex) events and major stock index decline events have a significant impact on the return of Bitcoin (BTC) in the short term. Moreover, more than 70% of uncertainty events will make BTC’s abnormal return (AR) significantly positive; (2) Under the influence of forex uncertainty events, only one BTC’s AR is remarkably negative in short order, while the other seven times are markedly positive. In the uncertainty events of major stock indexes, only two times are significantly negative, and the other six times are positive. This indicates that uncertain events in the short run make prominent AR of BTC; the proposed blockchain-based ISSA model and assessment index are scientific, feasible, and operable.
Journal Article
Grounded theory-based model of the influence of digital communication on handicraft intangible cultural heritage
Digital technologies have altered social interaction and information transmission, creating new cultural communication media and models. Despite extensive investigations into the effect of digital communication on handicraft intangible cultural heritage (ICH), research on the relationship between the factors that influence the digital communication of handicraft ICH is relatively scarce. This study used open-ended interviews and textual analysis to obtain data concerning these influencing factors. A grounded theory approach found that five core factors have significant effects on the digital communication of handicraft ICH. These are digital communication awareness, cultural communication initiative, adaptability of digital technology, audience acceptance and cognition, and uncontrollable factors. Furthermore, a theoretical “awareness-behavior-attitude” model based on an analysis of the relationships between the five factors was constructed. Finally, the action mechanism of the theoretical model was identified and tested, revealing that the action modes of each influencing factor were inconsistent. Antecedent factors were directly proportional to awareness-behavior, situational factors were inversely proportional to awareness-behavior, and regulatory factors were inversely proportional to behavior-attitude. In addition, situational factors and regulatory factors were found to have a positive impact on antecedent factors.
Journal Article
Transarterial chemoembolization with PD-(L)1 inhibitors plus molecular targeted therapies for hepatocellular carcinoma (CHANCE001)
There is considerable potential for integrating transarterial chemoembolization (TACE), programmed death-(ligand)1 (PD-[L]1) inhibitors, and molecular targeted treatments (MTT) in hepatocellular carcinoma (HCC). It is necessary to investigate the therapeutic efficacy and safety of TACE combined with PD-(L)1 inhibitors and MTT in real-world situations. In this nationwide, retrospective, cohort study, 826 HCC patients receiving either TACE plus PD-(L)1 blockades and MTT (combination group, n = 376) or TACE monotherapy (monotherapy group, n = 450) were included from January 2018 to May 2021. The primary endpoint was progression-free survival (PFS) according to modified RECIST. The secondary outcomes included overall survival (OS), objective response rate (ORR), and safety. We performed propensity score matching approaches to reduce bias between two groups. After matching, 228 pairs were included with a predominantly advanced disease population. Median PFS in combination group was 9.5 months (95% confidence interval [CI], 8.4–11.0) versus 8.0 months (95% CI, 6.6–9.5) (adjusted hazard ratio [HR], 0.70,
P
= 0.002). OS and ORR were also significantly higher in combination group (median OS, 19.2 [16.1–27.3] vs. 15.7 months [13.0–20.2]; adjusted HR, 0.63,
P
= 0.001; ORR, 60.1% vs. 32.0%;
P
< 0.001). Grade 3/4 adverse events were observed at a rate of 15.8% and 7.5% in combination and monotherapy groups, respectively. Our results suggest that TACE plus PD-(L)1 blockades and MTT could significantly improve PFS, OS, and ORR versus TACE monotherapy for Chinese patients with predominantly advanced HCC in real-world practice, with an acceptable safety profile.
Journal Article