Optical Full Adder Based on Integrated Diffractive Neural Network.

Light has been intensively investigated as a computing medium due to its high-speed propagation and large operation bandwidth. Since the invention of the first laser in 1960, the development of optical computing technologies has presented both challenges and opportunities. Recent advances in artificial intelligence over the past decade have opened up new horizons for optical computing applications.

Associations Between Thyroid Hormones Levels and Gray Matter Volume of Frontal Lobe Involved into Violence in Male Schizophrenia Patients.

Background: Thyroid dysfunction and frontal lobe gray matter volume (GMV) alterations are associated with violence in schizophrenia (SCZ); however, little is known about the relationship between thyroid dysfunction and frontal lobe GMV. This study aimed to evaluate whether thyroid hormone levels were associated with frontal lobe GMV in male patients with schizophrenia and violence.

Methods: Fifty-five male patients with SCZ underwent triiodothyronine (T3), thyroxine (T4), thyroid-stimulating hormone (TSH), free triiodothyronine (fT3), and free thyroxine (fT4) tests and structural magnetic resonance imaging (sMRI) scans.

Investigation of peripheral inflammatory biomarkers in association with violence in schizophrenia.

Background: Violent behavior carried out by patients with schizophrenia (SCZ) is a public health issue of increasing importance that may involve inflammation. Peripheral inflammatory biomarkers, such as the systemic immune inflammation index (SII), the neutrophil lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR) and the monocyte lymphocyte ratio (MLR) are objective, easily accessible and cost-effective measures of inflammation. However, there are sparse studies investigating the role of peripheral inflammatory biomarkers in violence of patients with SCZ.

Identification of male schizophrenia patients using brain morphology based on machine learning algorithms.

Background: Schizophrenia is a severe psychiatric disease, and its prevalence is higher. However, diagnosis of early-stage schizophrenia is still considered a challenging task.

Aim: To employ brain morphological features and machine learning method to differentiate male individuals with schizophrenia from healthy controls.

Large-scale photonic chiplet Taichi empowers 160-TOPS/W artificial general intelligence.

The pursuit of artificial general intelligence (AGI) continuously demands higher computing performance. Despite the superior processing speed and efficiency of integrated photonic circuits, their capacity and scalability are restricted by unavoidable errors, such that only simple tasks and shallow models are realized. To support modern AGIs, we designed Taichi-large-scale photonic chiplets based on an integrated diffractive-interference hybrid design and a general distributed computing architecture that has millions-of-neurons capability with 160-tera-operations per second per watt (TOPS/W) energy efficiency.

WITHDRAWN: Exploring the Potential Mechanism of Yixiang Capsule Immune-enhancing Function based on Network Pharmacology, Molecular Docking, and Animal Function Experiment.

Unlabelled: Since the authors are not responding to the editor’s requests to fulfill the editorial requirement, therefore, the article has been withdrawn. Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused. The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.

Prediction of violence in male schizophrenia using sMRI, based on machine learning algorithms.

Background: Violent behavior in patients with schizophrenia (SCZ) is a major social problem. The early identification of SCZ patients with violence can facilitate implementation of targeted intervention.

Methods: A total of 57 male SCZ patients were recruited into this study.

Global evaluation of carbon neutrality and peak carbon dioxide emissions: current challenges and future outlook.

With the acceleration of urbanization and industrialization, carbon neutrality and peak carbon dioxide emissions have become common sustainability goals worldwide. However, there are few literature statistics and econometric analyses targeting carbon neutrality and peak carbon dioxide emissions, especially the publication trends, geographic distribution, citation literature, and research hotspots. To conduct an in-depth analysis of existing research fields and future perspectives in this research area, 1615 publications from the Web of Science Core Collection, between 2010 and 2020, were evaluated by using three analysis tools, under the framework of the bibliometrics method.

The Prediction and Influential Factors of Violence in Male Schizophrenia Patients With Machine Learning Algorithms.

Background: Early to identify male schizophrenia patients with violence is important for the performance of targeted measures and closer monitoring, but it is difficult to use conventional risk factors. This study is aimed to employ machine learning (ML) algorithms combined with routine data to predict violent behavior among male schizophrenia patients. Moreover, the identified best model might be utilized to calculate the probability of an individual committing violence.

Sustainable development and health assessment model of higher education in India: A mathematical modeling approach.

The Coronavirus Disease 2019 has resulted in a transition from physical education to online learning, leading to a collapse of the established educational order and a wisdom test for the education governance system. As a country seriously affected by the pandemic, the health of the Indian higher education system urgently requires assessment to achieve sustainable development and maximize educational externalities. This research systematically proposes a health assessment model from four perspectives, including educational volume, efficiency, equality, and sustainability, by employing the Technique for Order Preference by Similarity to an Ideal Solution Model, Principal Component Analysis, DEA-Tobit Model, and Augmented Solow Model.