The efficacy and tendency of the gender digital divide and Smart Aging Policy in China.

China is one of the most rapidly aging countries in the world, challenging the sustainable aging. The booming of digital technology is a double-edged sword. According to the Smart Aging Policies (SAPs), digital technology is supposed to be an effective way to address the challenges of the elder care system.

The impact of patentees assessment based on the heterogeneous patent innovation network.

As a vital factor in technological innovation, patentee plays a significant role in the process of scientific and technological innovation, researching patentee has attracted the attention of experts and scholars. Previously, scholars have mainly quantified patent indicators or constructed homogeneous information networks to analyze patentees, but these methods cannot objectively measure the impact of patentees. Therefore, this study proposes a novel approach to assessing patentee impact based on a heterogeneous information network.

Epidemic monitoring in real-time based on dynamic grid search and Monte Carlo numerical simulation algorithm.

Building upon the foundational principles of the grid search algorithm and Monte Carlo numerical simulation, this article introduces an innovative epidemic monitoring and prevention plan. The plan offers the capability to accurately identify the sources of infectious diseases and predict the final scale and duration of the epidemic. The proposed plan is implemented in schools and society, utilizing computer simulation analysis.

Improving the identification of miRNA-disease associations with multi-task learning on gene-disease networks.

MicroRNAs (miRNAs) are a family of non-coding RNA molecules with vital roles in regulating gene expression. Although researchers have recognized the importance of miRNAs in the development of human diseases, it is very resource-consuming to use experimental methods for identifying which dysregulated miRNA is associated with a specific disease. To reduce the cost of human effort, a growing body of studies has leveraged computational methods for predicting the potential miRNA-disease associations.

CEO's functional experience and firm performance based on text mining.

The impact of a chief executive officer's (CEO's) functional experience on firm performance has gained the attention of many scholars. However, the measurement of functional experience is rarely disclosed in the public database. Few studies have been conducted on the comprehensive functional experience of CEOs.

An intelligent medical guidance and recommendation model driven by patient-physician communication data.

Based on the online patient-physician communication data, this study used natural language processing and machine learning algorithm to construct a medical intelligent guidance and recommendation model. First, based on 16,935 patient main complaint data of nine diseases, this study used the word2vec, long-term and short-term memory neural networks, and other machine learning algorithms to construct intelligent department guidance and recommendation model. Besides, taking ophthalmology as an example, it also used the word2vec, TF-IDF, and cosine similarity algorithm to construct an intelligent physician recommendation model.

Disease- and Drug-Related Knowledge Extraction for Health Management from Online Health Communities Based on BERT-BiGRU-ATT.

Knowledge extraction from rich text in online health communities can supplement and improve the existing knowledge base, supporting evidence-based medicine and clinical decision making. The extracted time series health management data of users can help users with similar conditions when managing their health. By annotating four relationships, this study constructed a deep learning model, BERT-BiGRU-ATT, to extract disease-medication relationships.

Double chain system for online and offline medical data sharing private and consortium blockchain: A system design study.

With the informatization development and digital construction in the healthcare industry, electronic medical records and Internet medicine facilitate people's medical treatment. However, the current data storage method has the risk of data loss, leakage, and tampering, and can't support extensive and secure sharing of medical data. To realize effective and secure medical data storage and sharing among offline medical institutions and Internet medicine platforms, this study used a combined private blockchain and consortium blockchain to design a medical blockchain double-chain system (MBDS).

Projective quasi-synchronization of coupled memristive neural networks with uncertainties and impulsive effect.

The dynamic behavior of memristive neural networks (MNNs), including synchronization, effectively keeps the robotic stability against numerous uncertainties from the mimic of the human brain. However, it is challenging to perform projective quasi-synchronization of coupled MNNs with low-consumer control devices. This is partly because complete synchronization is difficult to realize under various projective factors and parameter mismatch.

The Acceptability of Traditional Culture under the Background of Deep Learning.

The cultural values of a country impact its national psychology and identity. Citizens' values and public opinions are conveyed to state leaders over the media and other information channels, both directly and indirectly influencing decisions on foreign policy. The traditional cultural values that affect the psyche of the Chinese people are harmony, generosity, morality, courtesy, wisdom, honesty, loyalty, and filial piety.

Analysis on the Moderating Effect of Innovation and Entrepreneurship Education Mode and Locus of Control of College Teachers and Students Based on Comic Style Recognition.

This study was carried out to explore the moderating effect of comic education and locus of control (LOC) in innovation and entrepreneurship education in colleges and universities. Firstly, the theoretical knowledge of comic education, innovation and entrepreneurship education, and LOC was briefly introduced, and the significance of comics for innovation and entrepreneurship education was discussed. Secondly, the existing innovation and entrepreneurship education modes in colleges and universities in China were introduced.

Dynamic analysis of a dual-channel closed-loop supply chain with fairness concerns under carbon tax regulation.

In this work, we study a dual-channel closed-loop supply chain (CLSC) where the manufacturer sells the new products via one fair caring retailer in the traditional channel and distributes the remanufactured products through her own direct channel in the presence of the carbon tax regulation. After solving the single-period Stackelberg game model by backward induction and analyzing the impacts of key parameters on the optimal pricing strategies and the performance of channel members, a multi-period dynamic Stackelberg game model with heterogeneous players is further established. The local stability of the Nash equilibrium point and complexity properties of the model are investigated by numerical simulation.

Patients' Self-Disclosure Positively Influences the Establishment of Patients' Trust in Physicians: An Empirical Study of Computer-Mediated Communication in an Online Health Community.

With the development of telemedicine and e-health, usage of online health communities has grown, with such communities now representing convenient sources of information for patients who have geographical and temporal constraints regarding visiting physical health-care institutions. Many previous studies have examined patient-provider communication and health-care service delivery in online health communities; however, there is a dearth of research exploring the relationship between patients' level of self-disclosure and the establishment of patients' trust in physicians. Consequently, this study aims to explore how patients' self-disclosure affects the establishment of patients' trust in physicians.

Optimal pricing and green decisions in a dual-channel supply chain with cap-and-trade regulation.

The issue of low carbon emission reduction is getting more and more attention. This paper focuses on analyzing the equilibriums and digging deep into the impacts of cap-and-trade regulation, joint emission abatement scheme, and online direct channel on the performances of supply chain. By constructing two decentralized models in the single/joint emission abatement schemes under cap-and-trade regulation in a dual-channel supply chain, we find that consumer's environmental preference effectually motivates both the manufacturer and retailer to reduce emissions with joint emission abatement scheme.

Adaption of distance learning to continue the academic year amid COVID-19 lockdown.

This work investigates the use of distance learning in saving students' academic year amid COVID-19 lockdown. It assesses the adoption of distance learning using various online application tools that have gained widespread attention during the coronavirus infectious disease 2019 (COVID-19) pandemic. Distance learning thrives as a legitimate alternative to classroom instructions, as major cities around the globe are locked down amid the COVID-19 pandemic.

Mechanism and Model for Optimizing Polytetrafluoroethylene Distribution to Improve the Electrical and Thermal Conductivity of Treated Carbon Fiber Paper in Fuel Cells.

Employing polytetrafluoroethylene (PTFE)-treated carbon fiber paper (CFP) as the substrate of the gas diffusion layer (GDL) is a common practice to improve water management in proton exchange membrane fuel cells (PEMFCs), but the resulting increase in electrical and thermal resistance is a critical problem that restricts the performance output of PEMFCs. Hence, studying the mechanism and prediction model for both the electrical and thermal conductivity in CFP is essential. This work established a mathematical graph theory model for CFP electrical and thermal conductivity prediction based on the observation and abstraction of the CFP characteristic structures.

Optimal decisions and Pareto improvement for green supply chain considering reciprocity and cost-sharing contract.

With the rapid development of green consumption demand, more and more consumers choose to purchase green products. Incorporating consumers' environmental awareness into a green supply chain, this paper studies the decisions and coordination of the green supply chain under the retailer's reciprocal preference. The decentralized models with and without reciprocity are constructed and analyzed with consideration of product green degree and pricing.

Explaining mobile government social media continuance from the valence perspective: A SEM-NN approach.

Different from many previous studies explain mobile social media usage from a technical-center perspective, the present study investigates the factors that influence citizens' mobile government social media (GSM) continuance based on the valence framework. The research model was calculated by using data collected from 509 citizens who are the mobile GSM users in China. A structural equation modeling (SEM)-neural network (NN) method was employed to test the research model.

Conventional to online education during COVID-19 pandemic: Do develop and underdeveloped nations cope alike.

Background: Educational institutes around the globe are facing challenges of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Online learning is being carried out to avoid face to face contact in emergency scenarios such as coronavirus infectious disease 2019 (COVID-19) pandemic. Students need to adapt to new roles of learning through information technology to succeed in academics amid COVID-19.

Comparing like with like: China ranks first in SCI-indexed research articles since 2018.

China's rising in scientific research output is impressive. The academic community is curious about the time when the cross-over in the number of annual scientific publication production between China and the USA can happen. By using Web of Science Core Collection's Science Citation Index Expanded database, this study finds that China still ranks the second in the production of SCI-indexed publications in 2019 but may leapfrog the USA to be the first in 2020 or 2021, if all document types are considered.

The Voice of Drug Consumers: Online Textual Review Analysis Using Structural Topic Model.

Many web-based pharmaceutical e-commerce platforms allow consumers to post open-ended textual reviews based on their purchase experiences. Understanding the true voice of consumers by analyzing such a large amount of user-generated content is of great significance to pharmaceutical manufacturers and e-commerce websites. The aim of this paper is to automatically extract hidden topics from web-based drug reviews using the structural topic model (STM) to examine consumers' concerns when they buy drugs online.

Exploring the Effect of Market Conditions on Price Premiums in the Online Health Community.

Online health communities allow doctors to fully use existing medical resources to serve remote patients. They broaden and diversify avenues of interaction between doctors and patients using Internet technology, which have built an online medical consultation market. In this study, the theory of supply and demand was adopted to explore how market conditions of online doctor resources impact price premiums of doctors' online service.

Down-regulation of tissue factor inhibits invasion and metastasis of non-small cell lung cancer.

Tissue factor (TF) is clinically identified as a marker for the detection of various types of cancer as well as the prediction of prognosis for cancer patients. This present study aims to explore the possibility and feasibility to use plasma TF as a biomarker for the prediction of prognosis of patients with non-small cell lung cancer (NSCLC). A total of 100 patients with NSCLC at stage I to IV was included in the study, in whom the expression of plasma TF was detected.

Recent updates and future perspectives about amygdalin as a potential anticancer agent: A review.

The overall incidence of cancer is increasing in recent years. Despite advances in various comprehensive treatments, the mortality of advanced malignant tumors remains at a high level. Numerous pharmacological studies have confirmed that many Chinese herbal medicines possess remarkable antitumor activities.

Evaluation of Serum Paired MicroRNA Ratios for Differential Diagnosis of Non-Small Cell Lung Cancer and Benign Pulmonary Diseases.

Background And Objective: To clarify whether there are different expressions between lung cancer and benign pulmonary diseases, we studied seven microRNAs (miRNAs) in serum from patients with non-small cell lung cancer (NSCLC), benign pulmonary nodules and four pulmonary inflammation diseases.

Methods: We detected the expression of miRNAs using quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR).

Results: We found that five miRNA ratios-miR-15b-5p/miR-146b-3p, miR-20a-5p/miR-146b-3p, miR-19a-3p/miR-146b-3p, miR-92a-3p/miR-146b-3p, and miR-16-5p/miR-146b-3p-show higher expression in the NSCLC group than the benign pulmonary nodule group, and 13 ratios of miRNAs were significantly upregulated in the NSCLC group compared with the pulmonary inflammation diseases group.