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The living record of scientific history : conversations with CN Yang
Professor Chen-Ning Yang is best known for his achievements in Physics. He has also made significant contributions to the development of mathematics, as mathematics is extensively used in his research. In his long and fruitful academic career, he has witnessed many important events in the fields of Physics and Mathematics, and has collaborated or interacted with many great scientists in history. This book records eight interviews with Professor Chen-Ning Yang, which were conducted by the authors from 2016 to 2019. Through Professor Yang's unique perspective, major scientific events in the 20th century were revisited vividly, elaborating the development and mutual influences of mathematics and physics, as well as unveiling the academic work, the daily lives, and the personalities of scientists, as well as their collaboration and competition, some stories unknown to the public before are also revealed in this book.
BOOK
The m6A mRNA demethylase FTO in granulosa cells retards FOS-dependent ovarian aging
Multifunctional
N
6-methyladenosine (m6A) has been revealed to be an important epigenetic component in various physiological and pathological processes, but its role in female ovarian aging remains unclear. Thus, we demonstrated m6A demethylase FTO downregulation and the ensuing increased m6A in granulosa cells (GCs) of human aged ovaries, while FTO-knockdown GCs showed faster aging-related phenotypes mediated. Using the m6A-RNA-sequence technique (m6A-seq), increased m6A was found in the FOS-mRNA-3′UTR, which is suggested to be an erasing target of FTO that slows the degradation of FOS-mRNA to upregulate FOS expression in GCs, eventually resulting in GC-mediated ovarian aging. FTO acts as a senescence-retarding protein via m6A, and FOS knockdown significantly alleviates the aging of FTO-knockdown GCs. Altogether, the abovementioned results indicate that FTO in GCs retards FOS-dependent ovarian aging, which is a potential diagnostic and therapeutic target against ovarian aging and age-related reproductive diseases.
Journal Article
Schizophrenia Detection Using Machine Learning Approach from Social Media Content
Schizophrenia is a severe mental disorder that ranks among the leading causes of disability worldwide. However, many cases of schizophrenia remain untreated due to failure to diagnose, self-denial, and social stigma. With the advent of social media, individuals suffering from schizophrenia share their mental health problems and seek support and treatment options. Machine learning approaches are increasingly used for detecting schizophrenia from social media posts. This study aims to determine whether machine learning could be effectively used to detect signs of schizophrenia in social media users by analyzing their social media texts. To this end, we collected posts from the social media platform Reddit focusing on schizophrenia, along with non-mental health related posts (fitness, jokes, meditation, parenting, relationships, and teaching) for the control group. We extracted linguistic features and content topics from the posts. Using supervised machine learning, we classified posts belonging to schizophrenia and interpreted important features to identify linguistic markers of schizophrenia. We applied unsupervised clustering to the features to uncover a coherent semantic representation of words in schizophrenia. We identified significant differences in linguistic features and topics including increased use of third person plural pronouns and negative emotion words and symptom-related topics. We distinguished schizophrenic from control posts with an accuracy of 96%. Finally, we found that coherent semantic groups of words were the key to detecting schizophrenia. Our findings suggest that machine learning approaches could help us understand the linguistic characteristics of schizophrenia and identify schizophrenia or otherwise at-risk individuals using social media texts.
Journal Article
الصين تربط العالم : الخلفية التي تستند إليها مبادرة الحزام والطريق = China connects the world : what behind the belt and road initiative /
يتناول كتاب (الصين تربط العالم : الخلفية التي تستند إليها مبادرة الحزام والطريق) والذي قام بتأليفه (وانغ ييوي) في حوالي (350) صفحة من القطع المتوسط موضوع (العلاقات الاقتصادية الخارجية للصين) مستعرضا أبرز المحتويات التالية : الفصل الأول : العالم المترابط، الفصل الثاني : مبادرة الحزام والطريق : منطق العولمة، الفصل الثالث : مبادرة الحزام والطريق : منطق الحضارة، الفصل الرابع : مبادرة الحزام والطريق : المنطق الاستراتيجي.
Book
Theoretical Insights of CSR Research in Communication from 1980 to 2018: A Bibliometric Network Analysis
Communication, as a discipline that generates a rich body of literature on CSR, has become a critical contributor to CSR knowledge in social science. However, limited research exists to understand how CSR knowledge is constructed and diffused in the discipline. This study thus intends to unpack the knowledge construction process of CSR research in the communication discipline from a network perspective. Invisible college was adopted as the conceptual framework. Article and theory/concept networks were constructed with 290 peer-reviewed articles from 61 communication journals between 1980 and 2018. Results showed that in the past four decades, CSR literature in communication has been growing and maturing, as evidenced by the increasing volume and diversity of theories and concepts applied. Furthermore, this body of literature tends to gravitate toward certain selected groups of theories and concepts, resulting in denser article networks over time. Our findings reflected a substantial influence of management (e.g., stakeholder theory, legitimacy theory) and psychological perspectives (e.g., attribution theory) on CSR research in communication. Additionally, the results showed that public relations concepts and theories (e.g., relationship management theory) have influenced CSR research across different communication subfields such as advertising and organization communication. The study expects the continuation of the plurality of voices as to how communication researchers will approach CSR and what specific topics may gain popularity in future research.
Journal Article
On-chip topological beamformer for multi-link terahertz 6G to XG wireless
Terahertz (THz) wireless communication holds immense potential to revolutionize future 6G to XG networks with high capacity, low latency and extensive connectivity. Efficient THz beamformers are essential for energy-efficient connections, compensating path loss, optimizing resource usage and enhancing spectral efficiency. However, current beamformers face several challenges, including notable loss, limited bandwidth, constrained spatial coverage and poor integration with on-chip THz circuits. Here we present an on-chip broadband THz topological beamformer using valley vortices for waveguiding, splitting and perfect isolation in waveguide phased arrays, featuring 184 densely packed valley-locked waveguides, 54 power splitters and 136 sharp bends. Leveraging neural-network-assisted inverse design, the beamformer achieves complete 360° azimuthal beamforming with gains of up to 20 dBi, radiating THz signals into free space with customizable user-defined beams. Photoexciting the all-silicon beamformer enables reconfigurable control of THz beams. The low-loss and broadband beamformer enables a 72-Gbps chip-to-chip wireless link over 300 mm and eight simultaneous 40-Gbps wireless links. Using four of these links, we demonstrate point-to-4-point real-time HD video streaming. Our work provides a complementary metal-oxide-semiconductor-compatible THz topological photonic integrated circuit for efficient large-scale beamforming, enabling massive single-input multiple-output and multiple-input and multiple-output systems for terabit-per-second 6G to XG wireless communications.
An on-chip topological beamformer for multi-link terahertz 6G to XG wireless communication achieves complete 360° azimuthal beamforming with gains of up to 20 dBi, radiating THz signals into free space with neural-network-driven customizable beams enabling up to eight simultaneous 40-Gbps wireless links.
Journal Article
Kaposiform hemangioendothelioma: current knowledge and future perspectives
Kaposiform hemangioendothelioma (KHE) is a rare vascular neoplasm with high morbidity and mortality. The initiating mechanism during the pathogenesis of KHE has yet to be discovered. The main pathological features of KHE are abnormal angiogenesis and lymphangiogenesis. KHEs are clinically heterogeneous and may develop into a life-threatening thrombocytopenia and consumptive coagulopathy, known as the Kasabach-Merritt phenomenon (KMP). The heterogeneity and the highly frequent occurrence of disease-related comorbidities make the management of KHE challenging. Currently, there are no medications approved by the FDA for the treatment of KHE. Multiple treatment regimens have been used with varying success, and new clinical trials are in progress. In severe patients, multiple agents with variable adjuvant therapies are given in sequence or in combination. Recent studies have demonstrated a satisfactory efficacy of sirolimus, an inhibitor of mammalian target of rapamycin, in the treatment of KHE. Novel targeted treatments based on a better understanding of the pathogenesis of KHE are needed to maximize patient outcomes and quality of life. This review summarizes the epidemiology, etiology, pathophysiology, clinical features, diagnosis and treatments of KHE. Recent new concepts and future perspectives for KHE will also be discussed.
Journal Article