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التخفيف من حدة الفقر في الصين المعاصرة
استنادا إلى نظرة عامة على أوضاع الفقر، يقدم هذا الكتاب مسار التخفيف من حدة الفقر والتنمية في الصين، ويشرح نموذج التنمية والتخفي من حدة الفقر بخصائص صينية والتمسك بمباديء (سيطرة الحكومة ومشاركة المجتمع والاعتماد على الذات والتنمية الموجهة والتنمية الشاملة) كما يقدم الكتاب تلخيصا شاملا لإنجازات الصين العظيمة وخبراتها الهامة وإسهاماتها الرئيسية في قضية التخفيف من حدة الفقر في العالم، ويعرض بإيجاز نظرات وممارسات التخفيف المستهدف من الفقر في العصر الجديد من أجل توفير مراجع لكسب المعركة ضد الفقر في الصين وقضية التخفيف من حدة الفقر في العالم.
Book
A Bibliometric Analysis and Visualization of Medical Big Data Research
With the rapid development of “Internet plus”, medical care has entered the era of big data. However, there is little research on medical big data (MBD) from the perspectives of bibliometrics and visualization. The substantive research on the basic aspects of MBD itself is also rare. This study aims to explore the current status of medical big data through visualization analysis on the journal papers related to MBD. We analyze a total of 988 references which were downloaded from the Science Citation Index Expanded and the Social Science Citation Index databases from Web of Science and the time span was defined as “all years”. The GraphPad Prism 5, VOSviewer and CiteSpace softwares are used for analysis. Many results concerning the annual trends, the top players in terms of journal and institute levels, the citations and H-index in terms of country level, the keywords distribution, the highly cited papers, the co-authorship status and the most influential journals and authors are presented in this paper. This study points out the development status and trends on MBD. It can help people in the medical profession to get comprehensive understanding on the state of the art of MBD. It also has reference values for the research and application of the MBD visualization methods.
Journal Article
Regulatory effect of inflammatory mediators in spinal cord injury
Spinal cord injury (SCI) is a severe disabling central nervous system injury that can lead to severe sensory and motor dysfunction, and even paralysis. Depending on the mechanism of injury, SCI can be divided into primary injury and secondary injury. While secondary injury is the most critical stage in the pathophysiological process of SCI, which is the uncontrolled destructive cascade that follows. At present, symptoms are mainly alleviated and endogenous repair mechanisms are improved through drug intervention, surgical decompression and rehabilitation therapy, but they cannot directly promote nerve regeneration and functional recovery. Recently, an increasing number of studies have shown that the inflammatory response is a core link in secondary injury and plays a crucial role in regulating the pathological progression of acute and chronic SCI. Inflammatory mediators are key participants in the inflammatory response, which can trigger various neuropathological conditions and neurological dysfunction and are related to the severity of the injury. They are being explored as potential therapeutic targets for SCI and related diseases. Therefore, reducing the production of pro-inflammatory mediators is feasible and will also become a research hotspot in the future. This article summarizes the main sources of inflammatory mediators related to injury, their expression regulation, the key signaling pathways that regulate their production (such as Toll-like receptors, NF-κB, MAPK pathways, etc.), and their impact on the pathophysiology of SCI. In addition, treatment methods such as chemical antagonists, plant extracts and hormone therapy have been introduced to inhibit the expression of inflammatory mediators in order to control and improve the inflammatory microenvironment. This article mainly relies on preclinical research evidence to deeply analyze the core position of inflammatory mediators, providing a theoretical basis and direction guidance for the development of more effective SCI anti-inflammatory treatments.
Journal Article
The impact of China’s artificial intelligence development on urban energy efficiency
Energy efficiency has become a central concern amidst shifting global economic conditions, intensifying climate variability, and geopolitical tensions that have fundamentally reshaped energy consumption and production patterns. Improving energy efficiency is vital for addressing these challenges and advancing the United Nations sustainable development goals (SDGs). Artificial intelligence (AI) has emerged as a transformative tool in this context, offering innovative solutions to complex energy-related problems. While prior research has examined the energy impacts of digital technologies broadly, few studies have isolated the specific contributions of AI. Addressing this gap, our study investigates the influence of AI development on energy efficiency and explores the mechanisms by which AI drives this improvement. Using a fixed-effects model based on prefecture-level data in China, we find that AI significantly enhances energy efficiency. This effect is primarily mediated through two channels: (1) promoting green technological innovation and (2) facilitating the rationalization of industrial structures. Moderation analyses reveal that AI’s positive impact is more pronounced in cities with strong informal environmental regulations and less significant in those with weaker oversight. Additionally, AI adoption yields greater efficiency gains in declining and regenerating resource-based cities compared to their growing and mature counterparts. These findings highlight AI’s pivotal role in advancing energy efficiency and provide actionable guidance for policymakers. To fully realize these benefits, decision-makers should strengthen informal environmental governance and prioritize AI deployment in transitioning resource-based cities. Such measures can help address pressing global energy challenges and accelerate progress toward sustainable development.
Journal Article
The Preparation, Determination of a Flexible Complex Liposome Co-Loaded with Cabazitaxel and β-Elemene, and Animal Pharmacodynamics on Paclitaxel-Resistant Lung Adenocarcinoma
Paclitaxel is highly effective at killing many malignant tumors; however, the development of drug resistance is common in clinical applications. The issue of overcoming paclitaxel resistance is a difficult challenge at present. In this study, we developed nano drugs to treat paclitaxel-resistant lung adenocarcinoma. We selected cabazitaxel and β-elemene, which have fewer issues with drug resistance, and successfully prepared cabazitaxel liposome, β-elemene liposome and cabazitaxel-β-elemene complex liposome with good flexibility. The encapsulation efficiencies of cabazitaxel and β-elemene in these liposomes were detected by precipitation microfiltration and microfiltration centrifugation methods, respectively. Their encapsulation efficiencies were all above 95%. The release rates were detected by a dialysis method. The release profiles of cabazitaxel and β-elemene in these liposomes conformed to the Weibull equation. The release of cabazitaxel and β-elemene in the complex liposome were almost synchronous. The pharmacodynamics study showed that cabazitaxel flexible liposome and β-elemene flexible liposome were relatively good at overcoming paclitaxel resistance on paclitaxel-resistant lung adenocarcinoma. As the flexible complex liposome, the dosage of cabazitaxel could be reduced to 25% that of the cabazitaxel injection while retaining a similar therapeutic effect. It showed that β-elemene can replace some of the cabazitaxel, allowing the dosage of cabazitaxel to be reduced, thereby reducing the drug toxicity.
Journal Article
Selenium, Selenoproteins, and Female Reproduction: A Review
Selenium (Se) is an essential micronutrient that has several important functions in animal and human health. The biological functions of Se are carried out by selenoproteins (encoded by twenty-five genes in human and twenty-four in mice), which are reportedly present in all three domains of life. As a component of selenoproteins, Se has structural and enzymatic functions; in the latter context it is best recognized for its catalytic and antioxidant activities. In this review, we highlight the biological functions of Se and selenoproteins followed by an elaborated review of the relationship between Se and female reproductive function. Data pertaining to Se status and female fertility and reproduction are sparse, with most such studies focusing on the role of Se in pregnancy. Only recently has some light been shed on its potential role in ovarian physiology. The exact underlying molecular and biochemical mechanisms through which Se or selenoproteins modulate female reproduction are largely unknown; their role in human pregnancy and related complications is not yet sufficiently understood. Properly powered, randomized, controlled trials (intervention vs. control) in populations of relatively low Se status will be essential to clarify their role. In the meantime, studies elucidating the potential effect of Se supplementation and selenoproteins (i.e., GPX1, SELENOP, and SELENOS) in ovarian function and overall female reproductive efficiency would be of great value.
Journal Article
pH is the primary determinant of the bacterial community structure in agricultural soils impacted by polycyclic aromatic hydrocarbon pollution
Acidification and pollution are two major threats to agricultural ecosystems; however, microbial community responses to co-existed soil acidification and pollution remain less explored. In this study, arable soils of broad pH (4.26–8.43) and polycyclic aromatic hydrocarbon (PAH) gradients (0.18–20.68 mg kg
−1
) were collected from vegetable farmlands. Bacterial community characteristics including abundance, diversity and composition were revealed by quantitative PCR and high-throughput sequencing. The bacterial 16S rRNA gene copies significantly correlated with soil carbon and nitrogen contents, suggesting the control of nutrients accessibility on bacterial abundance. The bacterial diversity was strongly related to soil pH, with higher diversity in neutral samples and lower in acidic samples. Soil pH was also identified by an ordination analysis as important factor shaping bacterial community composition. The relative abundances of some dominant phyla varied along the pH gradient, and the enrichment of a few phylotypes suggested their adaptation to low pH condition. In contrast, at the current pollution level, PAH showed marginal effects on soil bacterial community. Overall, these findings suggest pH was the primary determinant of bacterial community in these arable soils, indicative of a more substantial influence of acidification than PAH pollution on bacteria driven ecological processes.
Journal Article
Transverse-momentum-dependent wave functions and soft functions at one-loop in large momentum effective theory
A
bstract
In large-momentum effective theory (LaMET), the transverse-momentum-dependent (TMD) light-front wave functions and soft functions can be extracted from the simulation of a four-quark form factor and equal-time correlation functions. In this work, using expansion by regions we provide a one-loop proof of TMD factorization of the form factor. For the one-loop validation, we also present a detailed calculation of
O
(
α
s
) perturbative corrections to these quantities, in which we adopt a modern technique for the calculation of TMD form factor based the integration by part and differential equation. The one-loop hard functions are then extracted. Using lattice data from Lattice Parton Collaboration on quasi-TMDWFs, we estimate the effects from the one-loop matching kernel and find that the perturbative corrections depend on the operator to define the form factor, but are less sensitive to the transverse separation. These results will be helpful to precisely extract the soft functions and TMD wave functions from the first-principle in future.
Journal Article
Does MOOC Quality Affect Users’ Continuance Intention? Based on an Integrated Model
Massive open online course (MOOC) is an innovative educational model that has attracted widespread attention in recent years. Despite a growing number of registered users, many have given up continuously using MOOC platforms after the first-time user experience; thus, a high dropout rate has severely hindered the sustainable development of MOOC platforms. To address the problem, this study started with the quality factors of MOOC platforms and the confirmation of user expectations by integrating the D&M ISS model and the expectation confirmation model into one, with the goal of identifying the factors that affect users’ continuance intention to use MOOC platforms. In this study, online questionnaires were distributed to Chinese users with experience in using MOOC platforms, and a total of 550 valid samples were recovered. In addition, the theoretical model was tested using structural equation modeling (SEM). The research results showed that there are three critical antecedents affecting the confirmation of user expectations for a MOOC platform, including information quality, system quality, and service quality, of which service quality has the greatest impact on users’ expectation confirmation. If user expectations for an MOOC platform are positively confirmed, the perceived usefulness of the platform as well as the satisfaction with it will effectively be improved. Moreover, perceived usefulness has been proven to be a critical factor affecting users’ continuance intention to use MOOC platforms, which is followed by user satisfaction. Compared to the original ECM, the integrated research model has delivered significantly improved explanatory power for users’ continuance intention. Hence, this study makes up for the insufficiency of ECM in explaining the factors affecting users’ expectation confirmation and provides theoretical support for MOOC platform developers.
Journal Article