Horizontal Comparison Research Articles

Method for Dynamic Updating of Source Emission Inventories Based on the Response Relationship Between Anthropogenic Source Emissions and Air Quality

Pollution source emission inventories are the basis for analyzing the causes of pollution, identifying the contribution of pollution sources, and scientifically formulating air pollution prevention strategies. The current inventory construction methods mainly focus on improving the accuracy and spatial and temporal resolution of the inventory, and there is an urgent need to look into dynamic updating methods to address the problem of lagging source emission inventories. In order to develop an effective and versatile method for the dynamic updating of source emission inventories, a meteorological normalization method based on random forests was chosen to capture the response relationship between pollutants and anthropogenic emissions. Based on the response relationship and the base emission inventory, the method for updating emission inventories based on the relationship between emissions and air quality （REQEI） was developed. Taking MEIC as the example, the REQEI_MEIC inventory was constructed using this method. The applicability and reasonableness of the REQEI_MEIC inventory was examined through the horizontal comparison method and the model validation method, so as to prove the feasibility of the inventory construction method. The results showed that the differences in pollutant emissions between the REQEI_MEIC and MEIC inventories were small, and the model validation effects of the two inventories were generally consistent. In some areas, the emissions of the REQEI_MEIC were closer to the actual emissions, and the pollutant modeling effect was more favorable. The inventory dynamic updating method can construct a relatively accurate pollutant emission inventory on the basis of greatly reducing the workload. The method quickly extrapolates the inventory through the relationship between anthropogenic source emissions and air quality response, accelerates the speed of inventory updating, is suitable for realizing the rapid dynamic updating of existing inventories, and can to a certain extent reduce the limitations imposed by the spatial and temporal limitations of emission inventories on the analysis of the causes of pollution.

RCEP rules on cross-border data flows: Asian characteristics and implications for developing countries

ABSTRACT Data, as an essential production factor and a fundamental strategic resource in the digital economy era, have profoundly transformed production methods, lifestyles, and social governance, becoming one of the critical factors influencing the global competitive landscape. The United States and the European Union are actively making comprehensive arrangements around data flow issues, integrating their interests and values into data governance rules to influence other countries. Against the backdrop of increasingly intense global rule-making competition in digital trade, the Regional Comprehensive Economic Partnership (RCEP), led by the Association of Southeast Asian Nations (ASEAN) and actively promoted by China, covering 15 countries in the Asia-Pacific region, is sending a strong and powerful Asian voice regarding cross-border data flow rules. This article attempts to highlight the Asian characteristics of the data cross-border flow rules within RCEP through a horizontal comparison of regional trade agreements. These characteristics primarily include the principle of free cross-border data flow; fully protecting the host country’s national security through exceptional clauses; relatively lenient regulation of personal information protection; and adhering to the principle of non-reciprocity to respect and embrace countries at different development levels. Consequently, it is concluded that RCEP has constructed an Asian paradigm for cross-border flow of data that matches the development status of the Asia-Pacific countries and is worthy of emulation by other developing nations.

Recognition on the vital parts of the human body in traumatology, forensic medicine and acupuncture from Laoguanshan unearthed bamboo slips of metal-weapon-injury induced lethal symptoms

Eleven bamboo slips of metal-weapon-injury induced lethal symptoms, unearthed in Laoguanshan, reflect the understanding of the vital parts of human body by ancient medical masters. Through the longitudinal research of Laoguanshan unearthed bamboo slips of metal-weapon-injury induced lethal symptoms, and the handed-down literature on this aspect, the doubts remained have been clarified on the annotation and the interpretation of Laoguanshan medical bamboo slips; and the reliable road signs been discovered on the path for collating the sources of handed-down literature on metal-weapon injury, and this path had been failed to deepening. Through the horizontal comparison of metal-weapon injury with forensic medicine and acupuncture, it is found that the understanding of the vital parts of the human body, obtained through various ways in thousands of years, is highly agreed with among metal-weapon injury, forensic medicine and acupuncture, except for the differences in the terminology among different disciplines, and the discrepancy in ancient and modern literature because of the misunderstandings of the previous literature by later generations within the same discipline. Therefore, the multi-dimensional evidences have been obtained to support the recognition of the vital parts of the human body in traumatology, reflected in the Laoguanshan bamboo slips of metal-weapon-injury induced lethal symptoms. Additionally, the reliability of the relevant discipline theories, e.g. acupuncture and forensic examination, has been strongly confirmed. It provides a very typical case for solving major academic problems by applying the "dual-attestation method" to research unearthed and handed-down literature. Moreover, it explores a novel approach to the academic study of traditional Chinese medicine, especially to the effective communication among different disciplines.

Intra-articular injection of chitosan combined with low-dose glucocorticoid for the treatment of knee osteoarthritis in early and middle stages.

This study explores the clinical efficacy of intra-articular injection of chitosan combined with low-dose glucocorticoid for the treatment of knee osteoarthritis in early and middle stages. The visual analog scale (VAS) score, Lysholm score, Hospital for Special Surgery (HSS) score, and changes in the levels of inflammatory cytokines IL-1, IL-6, and TNF-α in the joint fluid before and after treatment in the 3 groups were compared, and the clinical efficacy was evaluated. All cases were followed up, with a follow-up time of 7 to 12 months, and no lost cases. The horizontal comparison showed that the VAS score, Lysholm score, HSS score, and levels of inflammatory cytokines IL-1, IL-6, and TNF-α in the joint fluid after treatment in each group were better than before treatment, and the difference was statistically significant (P < .05). The longitudinal comparison showed that there was no significant difference in VAS score, Lysholm score, HSS score and levels of inflammatory cytokines IL-1, IL-6, and TNF-α in synovial fluid among the 3 groups before treatment (P > .05); However, after treatment, there were significant differences among the 3 groups (P < .05), group C was better than group A and group B, group B was better than group A, and the differences were statistically significant (P < .05). The difference in clinical efficacy among the 3 groups was statistically significant (P < .05). The clinical efficacy of chitosan combined with low-dose glucocorticoid intra-articular injection in the treatment of knee osteoarthritis in early and middle stages is significant, with the characteristics of small trauma, rapid onset, and lasting efficacy, and it avoids the adverse reactions of topical or oral nonsteroidal anti-inflammatory drugs. As a first-line treatment option, it is recommended for promotion and use in clinical practice.

Figure Skating Tickets Under Digital Marketing

With the holding of the Beijing Winter Olympics and the vision of "300 million people on ice and snow", figure skating has received more and more attention, and the audience and market are also growing, so the research on figure skating ticket marketing is more meaningful. This paper takes figure skating event ticket marketing as the research object, adopts literature data method, system analysis method, combined with marketing theory, to sort out the whole process of figure skating ticket marketing. This paper finds out the main factors affecting the Chinese figure skating event ticket market by referring to the relevant literature on the key word "sports event ticket marketing" at home and abroad. Understand the current situation of ticketing market development of other sports events, and make a horizontal comparison of ticketing marketing. Find out and analyze the similarities and differences with figure skating event ticket marketing, and then explore the sales strategy suitable for figure skating event tickets to improve the attendance rate of figure skating event tickets.

Analysis and Research on the Turning Points in the Development of Chinese and Western Civilizations

The 17th century was a significant stage in global history, with the West ushering in the Scientific Revolution and the rise of Enlightenment thinking, and China experiencing the transformations of the Ming and Qing dynasties. These advances have had a profound impact on the development of contemporary society. However, most of the existing studies focus on a single civilization, and there are fewer comprehensive studies on the interaction between Chinese and Western civilizations. The study examines the development of civilisation in ancient China and the West (Europe) through the analysis of existing historical data on China and the West and compares the performance of civilisation in China in the 17th century with that of the West during the same period through a horizontal comparison of the historical processes of the Middle Ages, including the change of polity, the development of the economic system, and the way of education. The results show that China's level of civilisation was higher than that of the West before the 17th century, but the West's civilisation gradually surpassed China's after that. Despite the different paths and speeds of development between China and the West, the turning point in the 17th century had a profound impact on the course of world history (turning point: the 17th century, when China's civilisational development gradually lagged behind that of the West, i.e. the West's entry into a capitalist society).

A comparative study of strategic petroleum reserve policies of major countries in the world

Petroleum security is the guarantee of national security that plays an important role in national energy security, while petroleum strategic reserve is the most basic guarantee of national petroleum security. At present, the number of selected countries in the study of petroleum strategic reserves is insufficient, as there are too much vertical comparison and the horizontal comparison analysis is not enough. Based on this, on the basis of comparing the strategic petroleum reserves of major countries in the world in terms of storage methods, address selection, policy formulation, management system and utilization mechanism, this paper conducts longitudinal comparison and horizontal comparative analysis and research, trying to find out their common policy characteristics and advantages from different strategic petroleum reserve policies, modes and practices of various countries, and carries out eliminating the rough and learning from the strong. The experience gained can be used for reference by other countries.

Decellularized adipose-derived matrix from Superficial layers of abdominal adipose tissue exhibits superior capacity of adipogenesis compared to deep layers

The adipogenic property of decellularized adipose-derived matrix (DAM) varies widely across reports, making it difficult to make a horizontal comparison between reports and posing challenges for the stable clinical translation of DAM. It is possibly due to differences in donor characteristics, but the exact relationship remains unclear. Despite extensive research on the differences between superficial and deep layers of abdominal subcutaneous fat, a main donor of DAM, little is known about their extracellular matrix (ECM) which is promising in regenerative medicine. In this study, we first confirmed the distinct compositional profiles and adipogenic potential between superficial and deep DAM (S-DAM and D-DAM). Both in vitro and in vivo assays confirmed superior adipogenic induction potential in S-DAM over D-DAM. Total amounts of ECM proteins like collagen and laminin were similar, however, the predominant types differed, with collagen I dominating S-DAM and collagen XIV prevailing in D-DAM. S-DAM was enriched with mitochondrial and immunological proteins, whereas D-DAM featured more neuronal, vascular, muscular, and endocrine-related proteins. More proteins involved in mRNA processing were found in D-DAM, with Protein-Protein Interaction (PPI) analysis revealing HNRNPA2B1, HNRNPA1, and HNRNPC as the most tightly interacting members. These findings not only deepen our comprehension of the structural and functional heterogeneity of adipose tissues but also become one of the reason for the large variability between batches of DAM products, providing guidance for constructing more efficient and stable bio-scaffolds.

A Corpus-Based Critical Discourse Analysis of News Reports on the 2023 Israel-Hamas War

This study analyzed news reports of the 2023 Israel-Hamas war in three media outlets (Al-Jazeera, China Daily, and CNN). An armed conflict between Israel and Hamas (Palestinian militant groups) has been taking place mainly in the Gaza Strip since 7 October 2023. The 2023 Israel-Hamas war has been the most violent and deadliest for Palestinians in the history of the conflicts between Israel and Palestine. Such a severe global issue has attracted significant international concerns and has been reported extensively. However, due to different ideologies, media outlets used different language to describe the war. This study compiled three corpora with 1,586,438 words for a horizontal comparison and analysis. Combining corpus linguistics (CL) and critical discourse analysis (CDA), this study aimed to reveal how these three media outlets constructed language to depict the war, demonstrating their political stances and revealing their ideologies from a more comprehensive perspective. Based on the findings from analyzing the linguistic features of the three corpora, this study hopes to provide a framework and methodological implications for future studies on news reports, especially on war topics.

Implementation and research of gesture recognition in HCI field

Since the first Neural Network computer was made by Marvin Minsky and his schoolmates in 1951, the development of artificial intelligence (AI)has undergone various and huge changes. It generally evolves into a field that has infinite possibilities and a major branch of computer science that can not be ignored. With the trend of computerization and the rapid evolution of the Internet of Things (IoT), gesture recognition emerged. Various prototypes are blossoming in the laboratories, and some of them have become certain products that have practical applications in later days. At the same time, more and more deep learning technology has been applied to gesture recognition systems that greatly improve the quality of the service. The purpose of this review is to summarize and analyze the existing algorithms of Dynamic Gesture Recognition systems, which have several different methods that are based on multiple signal extractors. This study focuses on the 3D Convolutional Neural Network(CNN), which plays an important role in the Dynamic Gesture Recognition optimization algorithm and data analysis algorithm. In this paper, we reviewed past papers in the gesture recognition field, which include the sEMG method, microwave method, and vision recognition method. During the process of data collecting and summarizing the past papers, we mainly focused on the accuracy differences between recognition methods and the efficiency differences in data processing algorithms. (CNN-based, LSTM based, etc.) Then, we analyzed the main difficulties and challenges of these methods, which are briefly listed in the Introduction part. Data processing algorithms are also being studied, and a horizontal comparison between CNN-based, LSTM-based, and transformer-based algorithms is also being made. Besides this, for those problems that already have a reliable solution, we also summarized the possible solutions and listed them out. We found that the gesture recognition system has already been systematically studied and is partly used in some fields. However, the algorithm and modeling methods can still be optimized and it also needs further study to be more widely used.

Comparative study: perceptions of multiple education stakeholders on children with disabilities and goals of special education in Oman and the Philippines

PurposeThis comparative study explored the perceptions of educational stakeholders in Oman and the Philippines concerning children with disabilities and the goals of special education. Stakeholders' perspectives can influence their professional behaviours and attitudes, which, in turn, can profoundly impact children with disabilities who already face numerous challenges. Hence, comprehending the viewpoints of these stakeholders is vital for fostering socially just education for individuals with disabilities.Design/methodology/approachThis study employed a qualitative comparative case study approach with a horizontal comparison strategy, and both convenience and purposeful sampling techniques were used for participant selection. The study involved 53 participants from both countries, including policymakers, teacher educators, in-service teachers and student teachers from general and special education domains. Data were gathered through individual interviews and themes were subsequently discerned via data analysis.FindingsDespite the different cultural and historical contexts and distinct roles of stakeholders in both countries, the results indicate more parallels than disparities in their perceptions. The primary congruence underscored in this research was imperative to critically assess the language and ideology surrounding the goals of special education, such as mainstreaming and normalisation.Originality/valueAlthough numerous studies have probed the perceptions of various educational stakeholders concerning children with disabilities and educational goals, there is limited research that encompasses the perspectives of the seven distinct stakeholder groups. The consistency of language usage across both countries and among all stakeholders underscores the need for a rigorous cross-country examination involving all educational participants.

Convolutional Neural Networks Applied to Lung Image Detection: Model Comparison and Optimal Selection

The topic of pulmonary health has become a prevalent concern among the public, making monitoring lung health a crucial subject. Numerous researchers have proposed models or methods for detecting pulmonary images, and their effectiveness has been confirmed. However, in the domain of pulmonary image detection, there is a systematic comparison to identify the most suitable and efficient method. Therefore, the theme of this study is to discover, through comparative analysis, the model method most fitting for current pulmonary image detection. The research methodology is outlined as follows: firstly, introduce popular model methods in the current context; secondly, summarize and record the accuracy of each model in pulmonary image recognition; and finally, conduct a horizontal comparison to derive conclusions regarding the optimal model method. This study reveals that Feature Fusion exhibits an outstanding accuracy of 97.79% in pulmonary image recognition, securing the top position. In contrast, Transformer has the lowest accuracy, yet it still reaches 78.9%. Therefore, Feature Fusion emerges as the most promising model method currently deserving widespread promotion in the field of pulmonary image detection.

Prediction of consumers' purchase intension for electric vehicles based on machine learning model

In recent years, electric cars have gradually begun to attract consumers' attention, and car companies have gradually shifted their research and development focus to electric cars instead of conventional cars. As a matter of fact, how to accurately predict consumers' desire to purchase their own electric cars is a problem that still needs to be solved and addressed. With this in mind, this study uses improved SVM, CNN and LSTM models for horizontal comparison, and attempts to use machine learning models to solve this problem. According to the analysis, the experimental results show that the machine learning model is suitable for predicting consumer purchase desire, and the prediction accuracy of SVM is higher than the other two models. This paper uses this experiment to provide reference for relevant car companies that need to know consumers' purchasing desires. Overall, these results shed light on guiding further exploration of electric vehicles car purchase intention prediction.

House price prediction based on different models of machine learning

Housing price prediction is a typical regression problem in machine learning. Common algorithms include linear regression, support vector regression, random forest, and extreme gradient boosting models based on integrated learning methods. Among the specific problems, different models in the specific problem will get different results. This research will compare these three models to show which model is more accurate and robust. Given the practical problem of housing price prediction, various characteristics of houses are carried out. The research will analyze and study, apply a variety of regression models, and compare the performance of the above three models on this problem, make the horizontal comparison of the advantages and disadvantages of different models, and analyze the difference in effect Line analysis and summary.

An Analysis of How First-Person Shooting Games Retain Players of All Skill Levels

In the context of computer games, especially FPS games, which are popular in the world today, famous FPS games, such as Apex, give people a lot of fun, and at the same time, the popularity of the game also brings good economic profits to the game company. The most critical condition for a game to be loved is that the game design is reasonable; this design will cover all aspects of the game and ultimately win the recognition of players. On this premise, it's important to explore the design of FPS games and how they can be enjoyed by players of all levels. This paper analyzes the influence of various design factors in FPS games on players of different levels. The paper demonstrates the pros and cons behind the game's gameplay, character or weapon design through a horizontal comparison, and combines it with relevant literature to prove this point. It may help games analyze the elements and design strategies that make it easier to retain players of all levels. The conclusion is that gameplay design, character characterization, and skill &amp; weapon design are all important factors that influence players, while balance is also important.

Autonomous-rail rapid transit tram: System architecture, design and applications

Autonomous-rail Rapid Transit (ART) tram is a new type of multiple-articulated rubber-tire transit that utilizes intelligent perception, path tracking, and trajectory following control technologies to eliminate reliance on physical railway tracks. The adoption of power batteries, hydrogen energy, wheel-edge motor drive, and other technologies has comprehensively realized the dual advantages of large-capacity rail transportation, which is punctual, high volume, energy-saving, and environmentally friendly, as well as the flexibility and low comprehensive cost of traditional bus operations. This has created a brand-new urban rail transit model. This article first introduces the ART tram systems architecture, operating principles, applicable scenarios. Secondly, it introduces the core subsystems of ART tram vehicle structure, electrical system, and energy storage system. Thirdly, it focuses on analyzing the structure composition and control principles of the Automatic All-Wheel Steering System, which includes two key core subsystems: path tracking control subsystems and trajectory following control subsystems. Then, a horizontal comparison is made between the performance advantages and disadvantages of ART and other transportation systems, and the application status of ART tram is summarized. Finally, some common issues related to the development of ART tram are discussed, and a development plan for future ART systems is proposed to better integrate ART tram into urban transportation and meet people's demands for intelligent, comfortable, fast, and environmentally friendly urban public transportation.

Mapping liveability: The “15-min city” concept for car-dependent districts in Auckland, New Zealand

This research explores the feasibility of aligning cities with post-COVID realities by retrofitting the emerging 15-min city model into the current urban setup. COVID-19's lasting global effects on trans-territorial mobility, particularly in car-dependent cities, prompt a rethinking of urban models and infrastructure for heightened resilience and post-pandemic liveability. Using network analysis and GIS mapping techniques, this research applies the 15-min city model to identify the most “liveable areas” in two car-dependent suburban neighbourhoods with contrasting service structures—dispersed in Remuera and centralised in Onehunga in Auckland City, New Zealand. “Liveable areas” are defined as areas with overlap coverage of all 6 essential services within a 15-min walk. The analysis involves a horizontal comparison of essential service coverage and a longitudinal analysis of the impacts of essential service coverage, both collectively and individually, within both neighbourhoods. Findings suggest the potential to retrofit both districts' urban infrastructure, while proximity to retail, healthcare, and leisure facilities are the services most urgently needing improvements. Noted issues include excessive big-box retail growth, uneven healthcare distribution, and private, non-everyday access to natural resources. This research methodically tests proximity-based planning for sustainable living, work, and recreation in car-dependent districts with centralised or dispersed urban structures.

The multi-variable stepwise algorithm for internal short circuit detection in a serial battery pack with inconsistent state of health

Internal short circuit of cells is one of the main causes of thermal runaway in electric vehicle battery systems. Therefore, one of the most effective ways to prevent thermal runaway is to detect and identify internal short-circuit lithium-ion batteries before thermal runaway using a battery management system. This paper investigates the detection and identification of internal short circuits in batteries by proposing a multi-variable stepwise analysis (MSA) method. The MSA method is proposed for detecting and identifying faulty batteries by combining horizontal and vertical comparison methods and aging cells' ohmic internal resistance variation characteristics. A less consistent pack containing aging cells was designed to perform internal short-circuit experiments. Based on setting the appropriate threshold and moving the window frame horizontally, comparing the deviation degree of the ohmic internal resistance of each cell in the battery pack and the average ohmic internal resistance of the normal battery, the aging battery in the battery pack can be effectively identified. State of health (SOH) is the percentage remaining of the battery's actual maximum capacity value. The deviation degree of ohmic internal resistance of aging batteries with SOH of 92% and 80% is maintained at more than 15% and 45%. For early internal shorts with an equivalent internal short-circuit resistance of 100 Ω, the internal short-circuit detection time is 3896 s. For the short circuit in the middle and later periods (<10Ω), the MSA algorithm can achieve rapid internal short-circuit detection within the 50 s window, reducing the risk of thermal runaway. The results verified that the method could effectively identify aging cells within the battery pack and detect internal short circuits for other cells, reducing false positives and effectively preventing thermal runaway.

Fluctuations in Detection Indicators and Their Significance for the Diagnosis of Early Pressure Injury in Rat Models.

The aim of this study was to identify the most meaningful diagnostic indicator for distinguishing blanchable erythema (BE) and stage 1 pressure injury (early PI) in an in vivo (rat) model. A prospective case-control design was used to complete a horizontal and vertical comparison of detection indicators during the process of fading of BE or the deterioration of early PI into ulcer in rat models. The sample comprised 5 hairless rats with 20 injuries, of which 10 were BE and the other 10 were early PI. Data were collected at Nagano College of Nursing in 2020 in Nagano, Japan. The BE and PI rat models were established by subjecting the dorsal skin of a hairless rat to compression between 2 neodymium magnets for 45 minutes and 3.45 hours, respectively. The affected skin was observed based on the following: (1) photography, (2) hardness, (3) temperature, (4) moisture, and (5) spectrophotometric (a* value and ultraviolet [UV] reflectance) measurements. All measurements of BE were performed at the beginning to 60 minutes after decompression, and those for early PI were performed until 48 hours after decompression. Multiple BE factors, such as the degree of erythema (macroscopy and a* value), hardness, temperature, and moisture, were found to have unstable fluctuations. Only UV reflectance gradually decreased from 6 hours and decreased significantly at 48 hours after decompression (P = .001 vs 1 hour). In contrast to early PI, erythema in BE obviously faded within 10 minutes. Study findings indicate that a continuous decrease in UV reflectance can reflect the worsening of hemorrhage in early (stage 1) PI. In contrast, other indicators including photography, skin hardness, temperature, and moisture fluctuated and did not prove predictive for PI progression. The obvious fading of erythema in BE a short time after decompression can be used for clinical observations.

A Study on the Motivation and Path of Digital Transformation in Pudong Development Bank

As technology continues to advance and society progresses, the market demand for digital transformation in the banking sector has been growing steadily. This article initiates an internal interview on the digital transformation project of Shanghai Pudong Development Bank (SPDB), and based on this, analyses the specific details and benefits of the project, and puts forward corresponding suggestions for SPDB to smoothly promote the digital transformation project. Through horizontal comparison, the analysis shows that digital transformation projects will bring significant economic and social benefits to SPDB, reducing cost expenditures. Overall, to effectively accomplish digital transformation, it is essential for researchers from diverse fields to collaborate and establish strong connections between various themes and disciplines. This interdisciplinary approach acknowledges the interdependence of business models and underscores the need for concerted efforts in integrating different areas of expertise.