Macro View Research Articles

The Translation, Dissemination, and Evolution of Poetry from the High Tang Dynasty in France

The 17th to 18th centuries marked the beginning of cultural exchange between China and the West, during which Jesuit missionaries played a significant role. They introduced the latest Western thoughts and scientific advancements to China while providing detailed descriptions of China in their letters sent back to Europe. Additionally, they translated many Chinese texts, with French Jesuits contributing the most influential works. Among these translations were various collections of Tang poetry translated into French. In the 19th century, the first collection of Tang poetry in French was published in France. Subsequently, an increasing number of French translators, sinologists, and Chinese scholars became involved in the translation of Tang poetry, enriching the variety of French translations. The translation and dissemination of Tang poetry in France have become an important aspect of Sino-French cultural exchange, garnering attention from numerous scholars. While there have been significant research contributions from scholars in both countries, much of the work has been conducted from a macro view, lacking micro-level studies focused on specific periods of Tang poetry, particularly regarding the poetry of the High Tang period. In light of this, this paper organizes and analyzes different versions of French translations of Tang poetry, primarily selecting works by prominent High Tang poets such as Li Bai, Du Fu, and Wang Wei. Through comparative analysis, the paper aims to explore how the translations reflect the French translators' understanding of High Tang poetry and the cultural concepts behind them.

The macro view of solar policy: The case for supporting utility-scale power

New solar energy generation is drastically needed as a source of clean electricity as the U.S. and the globe make the transition away from fossil fuels. Yet, even as solar costs have dramatically declined, solar sources still provide less than 5% of global electricity. We examine issues in solar policy leading to this low adoption rate. Examining the variables of cost, baseload power and intermittency, and land use, we evaluate the tradeoffs among policy support for utility-scale, commercial and residential solar systems. We argue that utility-scale solar power makes far more sense if there is adequate grid integration, so that such installations can be placed in locations that minimize land use tradeoffs. By focusing policy support on a few large solar installations, governments can vastly increase the solar contribution to electricity generation.

BANKING AND BANKING REFORMS IN CHINA IN A MODEL OF COSTLY STATE VERIFICATION

AbstractWe present a macro view of China's financial system where a monopolistic banking sector coexists endogenously with bonds and private loans. In equilibrium smaller firms raise finance from private lending, larger firms through bank loans, and the largest by issuing bonds. The model predicts that expanding credit supply increases bank loans but reduces bond finance and private lending, in absolute terms and relative to total credit. In addition, removing the interest rate ceiling on bank lending—a recent reform in China—induces larger loans and higher lending rates, lowering the share of bank loans in total credit. Empirical evidence is presented to support these predictions.

Drug self-delivery systems: A comprehensive review on small molecule nanodrugs

Drug self-delivery systems are nanostructures composed of a drug as the main structural unit, having the ability of intracellular trafficking with no additional carrier. In these systems, the drug itself undertakes the functional and structural roles; thereby, the ancillary role of excipients and carrier-related limitations are circumvented and therapeutic effect is achieved at a much lower dose. Such advantages –which are mainly but not exclusively beneficial in cancer treatment– have recently led to an upsurge of research on these systems. Subsequently, various terminologies were utilized to describe them, referring to the same concept with different words. However, not all the systems developed based on the self-delivery approach are introduced using one of these keywords. Using a scoping strategy, this review aims to encompass the systems that have been developed as yet –inspired by the concept of self-delivery– and classify them in a coherent taxonomy. Two main groups are introduced based on the type of building blocks: small molecule-based nanomedicines and self-assembling hybrid prodrugs. Due to the diversity, covering the whole gamut of topics is beyond the scope of a single article, and, inevitably, the latter is just briefly introduced here, whereas the features of the former group are meticulously presented. Depending on whether the drug is merely a carrier for itself or carries a second drug as cargo, two classes of small molecule-based nanomedicines are defined (i.e., pure nanodrugs and carrier-mimicking systems, respectively), each having sub-branches. After introducing each branch and giving some examples, possible strategies for designing each particular system are visually displayed. The resultant mind map can create a macro view of the taken path and its prospects, give a profound insight into opportunities, spark new ideas, and facilitate overcoming obstacles. Taken together, one can foresee a brilliant future for self-delivery systems as a pioneering candidate for the next generation of drug delivery systems.

Crouching bacteria, hidden tetA genes in natural waters: Intracellular damage via double persulfate activation (UVA/Fe2+/PDS) effectively alleviates the spread of antibiotic resistance

In this study, we elucidated the chemical and biological inactivation mechanisms of peroxydisulfate (PDS) activated by UVA and Fe2+ (UVA/Fe2+/PDS) in wild-type antibiotic-resistant bacteria (ARB) isolated from a river in Inner Mongolia. Among the screened wild-type ARB, the relative abundance of unidentified Enterobacteriaceae, Stenotrophomonas, and Ralstonia was high. A ratio of 1:1 for Fe2+ and PDS under 18 W·m−2 UVA radiation (sunny days) completely inactivated the environmental ARB isolates. In the macro view of the inactivation process, Fe2+ first activates PDS rapidly, and later the UVA energy accumulated starts to activate PDS; HO• then becomes the main active species at a rate-limiting step. From a micro perspective, damage to the cell wall, intracellular proteins, inactivation of antioxidant enzymes, and genetic material degradation are the inactivation series of events by UVA/Fe2+/PDS, contributing to the 97.8 % inactivation of ARB at the initial stage. No regrowth of sublethal ARBs was observed. The transfer of tetracycline resistance genes from ARB to lab E. coli was evaluated by horizontal gene transfer (HGT), in which no HGT occurred when ARB was eliminated by UVA/Fe2+/PDS. Moreover, the sulfate and iron residuals in the effluents of treated water were lower than the drinking water standards. In summary, PDS, UVA, and Fe2+ activation effectively inactivated wild ARB with a low concentration of reagents, while inhibiting their regrowth and spread of resistance due to the contribution of intracellular inactivation pathways.

Macro View of the Place and Impact of Artificial Intelligence on the Design, Content, Delivery, and Student Engagement in Graduate Leadership Education Programs

Accelerated development and engagement of artificial intelligence are among the most significant global challenges in transforming the social and economic environment, resulting in the heightened emphasis on inclusive, collaborative, ethical decision‐making and responsible leadership. Higher education is an integral part of the global landscape of society and is influenced by its changing context. Accordingly, leadership educators must respond to the changes in the global and institutional environments and the new leadership paradigm in designing and implementing their leadership education programs. Here, we consider the macro level of the “place” within which higher education institutions are situated and reflect upon the impact of Artificial Intelligence on the design and delivery of leadership education programs.

Damage critical transformation mechanisms in milling nickel-based superalloy honeycomb composites using different tool structures

Nickel-based superalloy honeycomb composite (NBSHC) has been developed into an indispensable material for aerospace and defense industries due to light weight, high temperature resistance and extremely high specific strength. Nevertheless, NBSHC is particularly difficult to machine, combing superalloy with thin-walled structure properties, and is prone to damage such as burr, tearing and core deformation. To realize the efficient and low-damage processing of NBSHC, the different tool structures were used during the milling NBSHC experiments under ice-freeing conditions. The material removal mechanisms of different cutters were revealed based on the micro and macro view, and verified by the experiment results. Then, the cutting force and damage behavior of different tools under different parameters during milling NBSHC process were analyzed. For the first time, the damages critical transformation mechanisms during milling NBSHC process were summarized based on above investigations. Results showed that: Since the contact area between saw blade or disc cutters and NBSHC workpiece was a surface, and the in-plane force was small. The qualities of NBSHC machined by saw blade and disc cutters were excellent. Due to the large in-plane force, discontinuity cutting and tearing from removed material, the quality of NBSHC machined by end-milling cutter was extremely terrible. Large cutting force, large contact volume, frequent impacts induced by discontinuity cutting and tearing from the removed material sharply increased the plastic deformation, thus deteriorating the quality of NBSHC and contributing to the transformation of slight damages into severe damages. This work provided significant theories and guidelines for efficient and low-damage machining of NBSHC in aerospace and defense fields.

Growing crisis of urban rat infestation in Karaj city, Iran: Insights from hotspot mapping and social network analysis

To control the increasing growth of rat populations in metropolitan areas, several factors need to be considered to mitigate the risks posed by rats. Identifying rat density hotspots with more efficient methods and assessing people's experiences and attitudes toward them can be useful in prioritizing rat control efforts. We focused on the two most common species of rats (Rattus rattus and Rattus norvegicus) in the metropolis of Karaj, the fourth most populous and the largest immigrant-friendly city in Iran. The urban rat infestation is one of the problems caused by the high population growth in Karaj and the insufficient development of urban infrastructure and waste collection. It has led to discontent and public concern about rat infestations and there is a need to address the associated threats. We applied the Kernel Density Function and Optimized Hotspot Analysis to the presence points of the aforementioned types of rats and found that while Optimized Hotspot projects a macro view of hotspots at the city level, the Kernel Density Function prioritizes neighborhoods for initial actions. In addition, social network analysis with complementary regression models was conducted to determine people's experiences. The results show that fear of rats and concern about their presence form the basis of people's attitudes toward rats and lead to feelings of hatred. Moreover, economic harm reinforces people's motivation to control or eliminate this species. Despite their unpleasant feelings toward rats, people have a great influence on the growth of rat infestations by creating food sources through improper waste disposal. They prefer to use traps and poison instead of disposing of household waste and following the principles of cleanliness as preventive measures and believe that the lack of proper garbage collection by the municipality is the most important reason for the growth of rat populations. They are not sufficiently aware of their position in addressing this crisis. Our findings argue for the formation of a stronger network between the relevant authorities and residents, especially those living in the hotspots, to educate them about their role in rat control and to gain their cooperation in improving the city's waste management system.

A scoping review of mathematical models covering Alzheimer's disease progression.

Alzheimer's disease is a complex, multi-factorial, and multi-parametric neurodegenerative etiology. Mathematical models can help understand such a complex problem by providing a way to explore and conceptualize principles, merging biological knowledge with experimental data into a model amenable to simulation and external validation, all without the need for extensive clinical trials. We performed a scoping review of mathematical models describing the onset and evolution of Alzheimer's disease as a result of biophysical factors following the PRISMA standard. Our search strategy applied to the PubMed database yielded 846 entries. After using our exclusion criteria, only 17 studies remained from which we extracted data, which focused on three aspects of mathematical modeling: how authors addressed continuous time (since even when the measurements are punctual, the biological processes underlying Alzheimer's disease evolve continuously), how models were solved, and how the high dimensionality and non-linearity of models were managed. Most articles modeled Alzheimer's disease at the cellular level, operating on a short time scale (e.g., minutes or hours), i.e., the micro view (12/17); the rest considered regional or brain-level processes with longer timescales (e.g., years or decades) (the macro view). Most papers were concerned primarily with amyloid beta (n = 8), few described both amyloid beta and tau proteins (n = 3), while some considered more than these two factors (n = 6). Models used partial differential equations (n = 3), ordinary differential equations (n = 7), and both partial differential equations and ordinary differential equations (n = 3). Some did not specify their mathematical formalism (n = 4). Sensitivity analyses were performed in only a small number of papers (4/17). Overall, we found that only two studies could be considered valid in terms of parameters and conclusions, and two more were partially valid. This puts the majority (n = 13) as being either invalid or with insufficient information to ascertain their status. This was the main finding of our paper, in that serious shortcomings make their results invalid or non-reproducible. These shortcomings come from insufficient methodological description, poor calibration, or the impossibility of experimentally validating or calibrating the model. Those shortcomings should be addressed by future authors to unlock the usefulness of mathematical models in Alzheimer's disease.

Mental models in practice: The macro view and the cone of influence

Mental models in practice: The macro view and the cone of influence

A systematic review of critical thinking instructional pedagogies in EFL writing: What do we know from a decade of research

This article critically reviews 23 empirical studies on how to teach critical thinking (CT) in English as a foreign language (EFL) writing class from 2013 to 2022. Through a systematic process of a micro and macro view, two main parts are identified respectively, namely, 1) main elements that need to be considered for CT-integrated research (macro settings), e.g., CT-related models, teaching implementations and assessments, and 2) main features of CT instructional implementation in EFL writing (micro settings), e.g., types of CT instruction, the nature of CT cultivation and the way teachers provided instruction. Besides, a piece of methodological information is also summarized. To gain insights into how to integrate CT in writing, six predominant techniques that engaged during the process are also concluded: a. explicit CT concepts teaching, b. creating a social learning environment, c. appropriate scaffolding materials, d. questioning techniques, e. teacher or peer feedback, and f. online technological techniques. This review sheds light on the gap between pedagogical rhetoric and classroom practices due to the lack of CT attention in current language education. It also provides implications for future research for conducting CT-integrated pedagogies in EFL writing.

A Theory of Change for Artistic Activism

Abstract Artistic activism intervenes in, and through, culture to animate ideas with emotions—charge them with affect—to motivate action, and change material conditions. Artistic activism also animates lived experience through emotions and, through its representation, gives rise to ideas and ideals. Yet we have no theory of change for how this might work. This article provides a model to think through and reflect upon “artistic activism,” or whatever name it goes by, as a complex practice that combines the affective power of the arts with the effective aims of activism. This gives us a wide-angle lens with which to see how artistic activism might create change. The model is then applied to a real-world creative activism example: the Undocubus, an intervention by young undocumented immigrants in the southern United States. The model’s macro view aids with thinking through and assessing more specific and necessarily contextual micro theories of change that are applied, consciously or unconsciously, by artistic activists and those they work with. The applied micro-view tests out its alignment with an example of practice. Most importantly, a comprehensive theory of change for artistic activism can provide clarity and direction as to where to intervene to maximize change.

K-Means Method for Clustering Average Length of School (ALS) in Central Java

Average School Length (ALS) represents the level of performance of every person in a school region. The more years of education, the better the education obtained by the population; therefore, it becomes more essential as it can demonstrate the quality of the human resources in a given region. In addition, extensive research implies that the average length of schooling influences economic growth considerably. If the average length of education improves, then the number of unemployed and poor in an area decreases and affects economic growth positively and significantly. The study’s goal was to carry out an investigation utilizing artificial intelligence in the form of a cluster mapping on the averages of regeneration in central Java. This needs to be done to get a macro view of the level of development of the average school years through regional mapping over the last few years. The data set used can be found on the website of the Central Java Provincial Statistics Agency, which is the subject of the 2017-2019 average school year by sex. The solution approach is k-means, which is part of the data collection process. High and low clusters are the number used in this investigation. Prior to the k-means approach, pre-processing is conducted out by taking from 2017-2019 the average RLS number based on gender. The results of the computed average value were analyzed with k-means. The study found that out of 35 provinces, eight (23%) provinces were of the high cluster (cluster 1) and 27 of the low cluster (cluster 0) (77%). More than 70% of Central Java regions have remained common ALS, according to results. Keywords: K-Means, clustering, ALS

The war effect: a macro view of the economic and environmental situation of Ukraine

ABSTRACT Today, Ukraine find itself in a very difficult situation, on the one hand, the already unstable economy has just begun to recover after the coronavirus crisis; on the other hand, it is suffering colossal losses from Russian aggression. The article examines the current economic and ecological state of Ukraine, considering the influence of such drastic external factors as a military invasion with the aim of determining the prerequisites for the formation of an effective social and environmental policy and developing approaches to the improvement and stabilization of the national economy. To achieve the goals of the article, have been used intersectoral balance and in particular economic impact analysis (EIA), which was conducted on the example of the Ukrainian agricultural sector, because it is one of the three driving forces of its economy. The results of the study showed the scenarios of possible changes and their consequences for the economy of the state as a whole, and in the future can be used for study in order to develop new and improve existing methods of solving socio-economic problems at the national level and preserving natural capital, as one of the key elements on path to sustainable development.

Three years of COVID-19 and life satisfaction in Europe: A macro view

Every country in Europe experienced an adverse impact from the COVID-19 pandemic on life satisfaction, though on average, satisfaction with life in the summer of 2022 is about the same as the pre-pandemic value in the autumn of 2019. Typically, an upsurge in the severity of the pandemic (measured by the number of COVID-related deaths) is associated with declining life satisfaction and an ebbing, with increasing life satisfaction. Of the three waves of the pandemic between March 2020 and the autumn of 2022, the most severe impact typically occurred in 2021 during the second wave; in the third wave, the response declined due to the spread of effective vaccines and the takeover of omicron variants.

Analysis of the Scientific Production on the Green Hydrogen Theme Published in Scientific Journals Indexed by EBSCO

Purpose: to investigate the behavior and tendency of the formation of social networks of the scientific production on the Green Hydrogen theme published in scientific journals indexed in EBSCO. Theoretical framework: the theme of green hydrogen has been gaining attention and strength in the current context of global energy transition, as it is a clean alternative for generating energy for electricity, industry, heating, and transport sectors, and, in replacing fuels to carbon base, influencing sustainable development. Method: bibliometric analysis techniques were used, and predominantly social network analysis (SAR) through one-mode and two-mode network analysis. Results and conclusion: evolution of the theme in academia; weak ties in co-authorship and institutional networks; relevance of China and its originating institutions in the scientific production of the subject investigated; the most central keywords were: hydrogen, green hydrogen, renewable energy, production and hydrogen production; and the most fruitful themes were: production, sustainability, energy and carbon emissions. It concludes with a macro and contemporary view of the theme of green hydrogen in the international literary academic field. Research implications: the present study contributed to a better understanding and understanding of the formation of collaboration networks of the actors involved in the process of building international scientific knowledge, and, by verifying that green hydrogen presents opportunities for economic growth and job creation, this research also contributes to creating an entrepreneurial and social research agenda. Originality/value: to investigate the international scientific production on the theme of green hydrogen, as this is an emerging theme in the global academic literature, and, therefore, to verify that the referred theme gains strength through researchers and their respective studies.

Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball.

The present research objective was to analyze the offensive phase from Complex I in high-level male volleyball teams in a macro- and micro-level view, through the inter e intra-team variability analysis of eight best teams of the 2018 Men's Volleyball World Championship over the social network analysis and eigenvector centrality. The sample consisted of 22 matches and 2,743 offensive actions, resulting in 8 sub-networks with 368 nodes and 6221 edges. The results showed from macro view the variables that presented highest centrality values were Attack Zone 4 (range 0.56-0.90), Attack Tempo 2 (0.65-0.87), Power Attack (0.62-0.94), No Touch Block (0.61-1), Attack Effect Continuity (0.59-0.94), and Middle Blocker Centralized (0.60-0.95). In a micro view, Reception Effect, Play Position, Reception Zone, and Block Composition showed high variability in each sub-network. The intra- and inter-team variability presented the importance of to respect each team idiosyncrasies and to consider the different approaches to the game and success.

GiT: Graph Interactive Transformer for Vehicle Re-identification.

Transformers are more and more popular in computer vision, which treat an image as a sequence of patches and learn robust global features from the sequence. However, pure transformers are not entirely suitable for vehicle re-identification because vehicle re-identification requires both robust global features and discriminative local features. For that, a graph interactive transformer (GiT) is proposed in this paper. In the macro view, a list of GiT blocks are stacked to build a vehicle re-identification model, in where graphs are to extract discriminative local features within patches and transformers are to extract robust global features among patches. In the micro view, graphs and transformers are in an interactive status, bringing effective cooperation between local and global features. Specifically, one current graph is embedded after the former level's graph and transformer, while the current transform is embedded after the current graph and the former level's transformer. In addition to the interaction between graphs and transforms, the graph is a newly-designed local correction graph, which learns discriminative local features within a patch by exploring nodes' relationships. Extensive experiments on three large-scale vehicle re-identification datasets demonstrate that our GiT method is superior to state-of-the-art vehicle re-identification approaches.

FINANCIAL INCLUSION IN RURAL ECONOMY: EXPERIENCES AND THE WAY FORWARD

The objective of this study is to examine the status of financial inclusion in the rural economy and to understand the extent to which the policies of financial inclusion have been successful, especially in rural areas. To increase banking penetration and to promote financial inclusion, the Reserve Bank of India (RBI) and the Government of India (GoI) have made substantial efforts to ensure that all the adult citizens of the country have a bank account. Various studies and reports have measured the financial inclusion or exclusion index. The existing financial indices are computed based on the supply-side information on financial services and they fail to capture the demand-side dynamics (Dev, 2006). The present study tries to adopt the demand-side approach of assessing financial inclusion. This approach is more of a micro-level analysis rather than a macro view of access to the financial sector. With this background, the present study assesses whether banking facilities have reached the rural areas? Have people of rural areas particularly disadvantaged and low-income groups availed the benefits of banking facilities for their monetary transactions? What are the factors affecting access to financial services? The study adopts the empirical research strategy to measure the extent of financial inclusion. The scope of the research is restricted to rural and unbanked areas of the Kachchh district of Gujarat.

Evaluating the Comprehensive Benefit of Urban Renewal Projects on the Area Scale: An Integrated Method.

Globally, the challenges facing cities regarding urban decay, insufficient urban function, and fragmented urban development are enormous. Under this context, urban renewal provides opportunities to address these challenges and enhance urban sustainability. Thus, promoting urban renewal projects and improving their performance is a global topic. In many circumstances, urban renewal is planned and initiated on the project scale, but on the area scale, overall coordination of the projects can bring about comprehensive benefits to urban areas on a macro view. In practice, it still lacks a systematic evaluation approach to obtain a clear picture of such comprehensive benefits. In academia, the existing research studies are mainly focused on single-project evaluation. An integrated framework that provides a holistic assessment of area-scale project benefits is missing. Few fully consider the coupling coordination benefits between several urban renewal projects from an area-scale perspective. Thus, this paper aims to propose a framework for integrating an indicator evaluation system through a hybrid entropy weight method with Back Propagation (BP) neural network methods to evaluate the comprehensive benefit of urban renewal projects on the area scale, which is the level at which most development area-scale renewal projects take place in a city. The feasibility and effectiveness of this proposed framework are then verified in a case study of Chongqing, China. The results indicate that the proposed method that integrated multi-project characteristics can contribute to a bigger picture of benefit evaluation of urban renewal based on an area scale perspective. This therefore provides not only guidance for urban planners and policymakers to make better decisions, but also new insight for benefit evaluation in the field of urban development.