Data Sorting Research Articles

Analisis Persepsi Pengguna Media Sosial Tentang Pembelajaran Online dan Offline Sebagai Kajian Desain Pembelajaran Blended yang Efektif dan Berkualitas

This research was conducted with the aim of examining the perception of twitter or X users about online and offline learning as a basis for considering blended learning design. The research was carried out using the Atlas.ti rocky thematic analysis approach. The stages of thematic analysis are data collection, category construction, sorting categories and data, naming categories, and finding meaning in each stage of analysis. The results of the study show that there are four groups of perceptions among students regarding the learning method they want: (1) students who prefer online learning, (2) students who prefer face-to-face learning, (3) students who are neutral, and (4) students who want a combination of online and face-to-face learning. Some of the factors that affect this perception include physical, psychological, and convenience factors offered by each learning method. This study also found a tendency to change perceptions among students. In order for online learning to provide optimal results, several important conditions are needed, namely guaranteed learning quality, student readiness to participate in learning independently and responsibly, and adequate online learning facility support

Spatial Remodeling of Industrial Heritage from the Perspective of Urban Renewal: A Case Study of Coal Mine Site in Jiaozuo City

Resource-oriented cities are faced with the problems of the decline of traditional industries, exhaustion of resources, and wastage of space. Faced with these problems, urban renewal has become an important role and is widely used in the reuse of old and abandoned spaces. As a historical witness of the industrial revolution and urbanization process, coal mine industrial heritage not only has the value of material heritage but also carries rich historical and cultural information. However, with the adjustment of industrial structure, much coal mine industrial heritage has gradually lost its original production function and become neglected idle space in cities, and industrial buildings and equipment in these spaces have been abandoned or dismantled. The study takes the Wangfeng Mine site in Jiaozuo City, Henan Province as an example, combined with the urban development history and current situation of Jiaozuo city, it discusses the remodeling strategy of industrial heritage space from the perspective of urban renewal. Firstly, through case analysis, historical data sorting, and field research, the study integrated the historical development context of the Jiaozuo coal mine site and its impact on the urban spatial pattern, secondly, discussed the practical problems in the reuse process of industrial sites, and finally proposed specific spatial remodeling strategies based on the conjugation theory. This included determining how to deal with the three pairs of conjugated relations between protection and development, function and ecology, and history and modernity so as to make the spatial remodeling strategy of industrial sites more scientific and sustainable. To promote the sustainable and healthy development of urban industrial heritage space.

Indigenous communities and tourism-integrated climate change outcomes on subsistence within the hinterlands: a development management perspective

PurposeThe study focused on rural commodities, climate change and tourism activities for socioeconomic welfare and enhanced productivity within disadvantaged indigenous communities and remote areas. It relates primary and secondary data details on the Musina Municipality’s rural biodiversity, tourism management and integrated pastoral livelihoods, alongside climate change issues locally and abroad.Design/methodology/approachThe study employs focus group discussions and interviews to gather data. Descriptive statistics, cross-tabulation analysis and central tendencies, along with manual data sorting, provide non-inferential data analysis.FindingsThis study discloses a harmful connection between unsustainable integrated rural activities and tourism products and climate change-linked environmental consequences within such environs. Ultimately, the study has highlighted the need for proper biodiversity resource management and an agricultural approach to diminish climate change hazards and permit the indigenous communities of the municipality. Thus, there is a need for awareness and practices in responsible tourism, decent rural ecotourism and agro-tourism for enhanced productivity and sustainability achievements.Originality/valueMany rural citizens in the world naturally live in low-income areas. Southern Africa and Africa, with specific reference to the Musina Municipality in Limpopo Province, South Africa, are no exception. Despite the abundance of assorted natural and cultural biodiversity and rural tourism qualities, such regions are nonetheless prone to climate change consequences and the deprivation of socioeconomic sustainability.

Supporting prescriber progression: a group concept mapping study

Abstract Introduction Education reforms allow pharmacists to become prescribers earlier in their career and from 2026, new registrants will be independent prescribers.1 In NHS Scotland, an operational framework supports the development of pharmacist independent prescribing.2 We wanted to supplement the operational framework by identifying our core areas of prescribing to articulate prescribing progression and inform education and training provision. Aim To develop a core prescribing framework to support safe prescribing and a spiral approach to expanding scope of practice. Methods We conducted a participatory mixed-method approach using group concept mapping methodology.3 Phase 1 (brainstorming): all hospital pharmacists working in a patient-facing clinical role were invited to enter statements on a cloud-based platform (Padlet®) using the prompt ‘In my day-to-day practice I prescribe and/or make prescribing recommendations about the following medicines / conditions …’. The statements were triangulated with electronic inpatient pharmacist prescribing data over the previous three months. Phase 2 (sorting and rating): a project group comprised of pharmacists with different levels of practice and areas of clinical expertise, individually sorted the statements into groups based on the statements’ conceptual similarity and rated each statement by level of practice (post-registration foundation, advancing, advanced) and importance for including in a core framework (5-point Likert scale). R software applied multidimensional scaling to sorting data to create a similarity matrix, cluster map and Go-Zones. ChatGPT generated cluster titles. The project group discussed the results and following a few revisions, consensus was achieved on the content of the prescribing framework. This study was not considered research and was approved by the pharmacy quality improvement team in line with local governance process. Results Forty-three pharmacists participated in the brainstorming phase and generated 158 statements. Fourteen pharmacists participated in the sorting and rating phase. Multidimensional scaling analysis identified three clusters of prescribing activities: initiating, adjusting and deprescribing. The data identified activities involving initiating medicines and autonomous decision making rated at advancing/advanced level practice while adjusting/deprescribing medicines (often with the caveat of within guidelines, protocols or team decisions) was rated at post-registration foundation level. The prescribing framework includes the activities considered important and is organised by cluster and level of practice. Discussion / Conclusion This study provides a structured conceptualisation of prescribing across the levels of practice. The prescribing framework reflects the needs of our patients and hospital inpatient service and provides a scaffolded approach to progressing from inexperienced to more advanced prescribing roles. Post-registration foundation prescribing activities focus on processes or types of prescribing, whilst advanced are more autonomous and complex. Limitations we didn’t collect clinical area of practice as part of the demographic information for the brainstorming phase and some specialities may not be represented. Further work includes a training needs analysis and developing entrustable professional activities for core and higher risk areas of prescribing (e.g. post-operative pain).

Enabling coastal analytics at planetary scale

Coastal science has entered a new era of data-driven research, facilitated by satellite data and cloud compute. Despite its potential, the coastal community has yet to fully capitalize on these advancements due to a lack of tailored data, tools, and models. This paper demonstrates how cloud technology can advance coastal analytics at scale. We introduce GCTS, a novel foundational dataset comprising over 11 million coastal transects at 100-meter resolution. Our experiments highlight the importance of cloud-optimized data formats, geospatial sorting, and metadata-driven data retrieval. By leveraging cloud technology, we achieve up to 700 times faster performance for tasks like coastal waterline mapping. A case study reveals that 33% of the world’s first kilometer of coast is below 5 meters, with the entire analysis completed in a few hours. Our findings make a compelling case for the coastal community to start producing data, tools, and models suitable for scalable coastal analytics.

Enhanced data point importance: Layered significance of variables in multivariate calibration

BackgroundThe Enhanced Data Point Importance (EDPI) method, a systematic approach for evaluating the importance of data points in multivariate calibration, is introduced. Factor decomposition methods allow for the evaluation of the impact of variables on maintaining the structural pattern of data in the abstract space. Essential data points play a key role in these patterns and the method of Data Point Importance (DPI) aims to evaluate the essential data points in terms of their importance. All other points are rated by zero. In this contribution, DPI is extended to include inner points to evaluate the importance of these points in the absence of the essential points. The EDPI method employs convex peeling to sort data points systematically. ResultsEDPI method was applied to near-infrared and Raman spectroscopy data sets, including corn and alcohol mixtures and simulated data, to rank and select important variables. EDPI effectively identified variables that contributed to the preservation of the data structure and highlighted key spectral regions with different degrees of selectivity. In the alcohol dataset, EDPI revealed important physicochemical insights by focusing on specific regions where non-analytes spectra overlapped. It performed in a similar way to the Variable Importance in Projection (VIP) method, but with fewer variables selected. SignificanceThe experimental results obtained from calibrating near-infrared and Raman spectroscopic datasets using partial least squares highlight the effectiveness of the proposed EDPI strategy when contrasted with the conventional variable importance in projection (VIP) method for variable selection.

Research on design thinking of pleated clothing inspired by fractal geometry

PurposeThis paper summarizes the design thinking of pleated clothing, uses virtual software to simulate the pleated clothing process and clothing effect and applies the fractal geometry principle to conduct relevant experiments, which verifies the possibility of simulation software assisting pleated clothing design, improves research and development efficiency, lays a foundation for future process parameter collection to upgrade the pleated clothing database and realizes the diversity of digital innovative design of pleated clothing.Design/methodology/approachAccording to the principle of self-similarity and fractal dimension in fractal geometry, the design thinking of pleated clothing is put forward and the simulation folding of 3D digital technology is expanded. The design method takes traditional craft and digital technology as an example. The two-dimensional design thinking of pleated clothing is geometric crease thinking of fabric swatch and geometric expansion of basic clothing pattern. Three-dimensional modeling design thinking, such as based on the human body shape, geometric shape and folding mode. As well as digital design thinking, such as the angle of the fabric element and the perspective of garment pattern change.FindingsThis paper analyzes the Y structure of the similar shape “binary tree” in origami art, the principle of infinite folding with 45? As the unit and the point set capacity theory of Cantor concentric circles in the fractal dimension principle expands the design thinking of pleated clothing, applies a large number of experimental cases of design thinking inspired by the fractal geometry of pleated clothing and validates the possibility of simulation software assisting pleated clothing design.Research limitations/implicationsWe argue here that digital technology should continue to be used in a similar way for research and development in other clothing design-related processes in the future. When it comes to the possibilities for digital innovation in relation to pleated clothing, there is a lack of data for modeling the characteristics of such clothing and establishing the processing requirements. Thus, there is scope here for innovation breakthroughs in terms of both the art and the technology associated with clothing design, not to mention how the two are integrated. This paper has laid some potential foundations for this through its elaboration of fractal-inspired design in the context of pleated garments.Practical implicationsNumerous experiments were undertaken and digital simulation software was used to explore various potential designs in the paper. This confirmed the possibility of using simulation software to assist in the design of pleated clothing, which offers the scope for improved research and more efficient development. However, if the processing parameters for changes in the pleated fabric are not set in the software, it is impossible to automatically generate auxiliary clothes. The collection of processing parameters and the creation of a more comprehensive pleated clothing database should therefore be the focus of future research.Social implicationsThe paper is oriented toward future clothing design. There is some impact on research, practice and/or society. This opens up the possibility of using fractal geometry in the design of the folds and dimensional energy in pleated clothing. On the whole, the innovation point is clear and the idea is novel. By seeking the principles of science and technology, sensing the infinite possibilities, improving the design efficiency and inspiring innovative design thinking methods, in order to meet the diversity and personality needs of the external shape of the human body.Originality/valueThe concave and convex texture of pleated fabric is geometric and decorative. It has a direct reference value for pleated clothing design by using the concepts of partial and whole in fractal geometry and the quantity and energy conversion in fractal dimension space. Due to the influence of clothing intelligent manufacturing policy, there is a lack of data sorting for the modeling characteristics and process requirements of pleated clothing, and there is innovative design thinking that needs to be integrated with technology and art, which lays a foundation for the future collection of process parameters to upgrade the pleated clothing database.

APPLICATION OF MACHINE LEARNING METHODS TO ENHANCE THE PERFORMANCE OF BIG DATA SORTING ALGORITHMS

The use of machine learning methods to optimize big data sorting algorithms has become an urgent research topic due to the growing volume of information and the requirements for their rapid processing. Machine learning provides opportunities to automate and improve traditional sorting methods, allowing you to reduce the cost of computing resources and time. This is achieved by analyzing the characteristics of the data and preprocessing them using classification and regression. The main advantages of using machine learning in sorting big data include improving the accuracy and adaptability of algorithms to different types of data, which is especially important for areas with large amounts of information, such as finance, medicine and logistics. Progressive machine learning algorithms such as supporting vectors, decision trees, and gradient boosting demonstrate high efficiency and potential for further development and integration.

Research on the Amount of Information Needed to Restore the Original Order of Four or Eight Elements Lists, when Using Different Sorting Algorithms

Data sorting is essential in most software applications, but sometimes elements need to be restored to their original order after processing. If this restoration happens long after sorting or on a different computer, additional information is needed to restore the order. This work explores the information needed to restore sequences of 4 and 8 elements. The following sorting algorithms were studied: parallel neighbour (odd even) sort, insertion sort, bubble sort, shell sort, merge-insertion sort, and merge sort. For each algorithm, the amount of information required in bytes to restore the original order of the elements was determined.

Al-Ittija̅h al-Ḥadi̅th fi̅ Ta’li̅mi al-Lughah al-‘Arabiyyah li an-Na̅ṭiqi̅n bi Ghai̅riha̅ wa Taḥdiya̅tiha fi̅ ‘Aṣri al-‘Au̅lamah

The orientation of modern Arabic learning has not been implemented optimally in accordance with the desired goals, it has been proven that it has not produced students who can master Arabic. The purpose of this research is to reveal, first: modern orientation in learning Arabic, second: challenges of learning Arabic in the modern era, and third: opportunities for the development of Arabic learning in the modern era. The design of this study uses a qualitative approach with a literature study research type. Research data is collected by reviewing books, journals and other sources relevant to the theme. Data analysis is carried out simultaneously from data collection, sorting, presentation and conclusion. The results of this study are: (1) the modern orientation in learning Arabic is characterized by making Arabic as a means of communication, teaching Arabic language skills as a whole, and learning practices are based on applied linguistic theory (2) it was found that the challenges of learning Arabic in the modern era are the lack of a complete understanding of the orientation of modern Arabic learning, the reality that Arabic language teachers have not mastered applied linguistic theory, and Arabic language learning has not been able to keep up with the development of modern technology, and (3) the opportunity for the development of Arabic language learning in the modern era is the breadth of access to information technology that can be used for learning Arabic. The conclusion of this study is that any challenge in learning Arabic can be turned into an opportunity to develop a more effective learning model.

Composition of New York State (United States) Disposed Waste and Recyclables in 2021: An Advanced Analysis of Waste Sort Data

Understanding the composition of disposed municipal solid waste (MSW) and recyclables can lead to better waste management. New York State (United States) has never had a state-wide waste characterization sorting program. In 2021, sampling was conducted at 11 locations, representing 25% of the state population outside of New York City. Twenty-three tonnes from 173 discrete samples were sorted into 41 categories. The resulting data were analyzed by single constituent approaches and more novel multivariate distance techniques. The analyses found that disposed MSW was 22.8% paper, 20.5% food, and 16.8% plastics. Recyclable paper and glass–metal–plastic containers were 18.2% (11.7% paper, 6.5% containers) and yard waste was 6.5%, meaning about 25% of the disposed MSW could have been recovered. Multivariate analysis determined that the disposed MSW was similar to that from other United States jurisdictions such as Wisconsin, Pennsylvania, New York City, and Syracuse (NY), and different from California and United States Environmental Protection Agency model data. Recyclables composition was different from disposed MSW composition. Dual-stream recyclables were sorted better than single-stream recyclables. Corrugated cardboard was the most common paper recyclable and plastics were the most common container recyclable. The data are being used to help guide planning for an expected packaging extended producer responsibility law for the State.

Abstract B089: A community-based participatory approach to developing a salon-based HPV self-collection intervention

Abstract Background: Black women in the US experience higher rates of cervical cancer mortality due to delayed diagnosis from lower screening rates. Contributing to this disparity, especially for those who are 40-64 years old, are provider bias, costs, and limited access. Recent FDA approval of HPV self-collection and current innovative research efforts for clinical and simulated home- based HPV self-collection bring promise of increasing access. However, like other innovations, equitable dissemination of HPV self-collection will be challenging. Our project seeks to distribute HPV self-collection kits in unconventional settings like hair salons. We conducted a community-based participatory study using concept mapping to gather diverse insights to design a salon-based HPV self-collection intervention. Methods: We employed GroupWisdom and REDCap online platforms to engage with our participants. Participants were members of the Black Community Advisory Council of Tucson (Black CACTus). Concept mapping steps involved: 1) Brainstorming statements from a prompt, 2) Sorting statements into piles according to meaning by each participant, 3) Rating the importance and feasibility of statements, 4) Reviewing the cluster map, and 5) Reviewing a draft/proposed intervention. Results: Black CACTus members (n=10) included hairstylists (n=3), salon clients (n=4), and healthcare providers (n=3). All participants identified as Black women, with two also identifying as Latina and White. Participants were 23-53 years old. Brainstorming yielded 39 statements. A six-cluster map was generated using the sorting data. Cost-related factors like "free" or "covered by insurance," as well as convenience, were rated as highly important by all participants. Development of clear communication and education about screening benefits, test results, and timely delivery of results were regarded as the most feasible. Conclusions: To equitably increase cervical cancer screening we must look beyond traditional clinical settings to trusted community locales like hair salons. Including the voice of the community and cultural and contextual factors is vital when tailoring cancer screening initiatives, particularly for Black women. Our study used concept mapping, in a collaborative, iterative process with vested community members to identify intervention elements and implementation strategies that have the potential to increase access to and uptake of cervical cancer screening among Black women. Citation Format: Kelly N.B. Palmer, Namoonga M. Mantina, Adebola Adegboyega, Itunu O. Sokale, Kathleen Pryor, Azaria Suero-Davis, Trevon Brooks, Jennifer Hatcher. A community-based participatory approach to developing a salon-based HPV self-collection intervention [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B089.

Epidemiology and SARIMA model of deaths in a tertiary comprehensive hospital in Hangzhou from 2015 to 2022

BackgroundBy analysing the deaths of inpatients in a tertiary hospital in Hangzhou, this study aimed to understand the epidemiological distribution characteristics and the composition of the causes of death. Additionally, this study aimed to predict the changing trend in the number of deaths, providing valuable insights for hospitals to formulate relevant strategies and measures aimed at reducing mortality rates.MethodsIn this study, data on inpatient mortality at a tertiary hospital in Hangzhou from 2015 to 2022 were obtained via the population information registration system of the Chinese Center for Disease Control and Prevention. The death data of inpatients were described and analysed through a retrospective study. Excel 2016 was utilized for data sorting, and SPSS 22.0 software was employed for data analysis. The statistical inference of single factor differences was conducted via χ2 tests. The SARIMA model was established via the forecast, aTSA, and tseries software packages (version 4.3.0) to forecast future changes in the number of deaths.ResultsA total of 1938 inpatients died at the tertiary hospital in Hangzhou, with the greatest number of deaths occurring in 2022 (262, 13.52%). The sex ratio was 2.22:1, and there were significant differences between sexes in terms of age, marital status, educational level, and place of residence (P < 0.05). The percentage of males in the groups aged of 20 to 29 and 30 to 39 years was significantly greater than that of females (χ2 = 46.905, P < 0.001). More females than males died in the widowed group, and divorced and married males experienced a greater number of deaths than divorced and married females did (χ2 = 61.130, P < 0.001). The proportions of male students with a junior college and senior high school education were significantly greater than that of female students (χ2 = 12.310, P < 0.05). The primary causes of mortality within the hospital setting included circulatory system diseases, injury, poisoning, tumours, and respiratory system diseases. These leading factors accounted for 86.12% of all recorded deaths. Finally, the SARIMA (2, 1, 1) (1, 1, 1)12 model was determined to be the optimal model, with an AIC of 380.23, a BIC of 392.79, and an AICc of 381.81. The MAPE was 14.99%, indicating a satisfactory overall fit of this model. The relative error between the predicted and actual number of deaths in 2022 was 8.02%. Therefore, the SARIMA (2, 1, 1) (1, 1, 1)12 model demonstrates good predictive performance.ConclusionsHospitals should enhance the management of sudden cardiac death, acute myocardial infarction, severe craniocerebral injury, lung cancer, and lung infection to reduce the mortality rate. The SARIMA model can be employed for predicting the number of deaths.

Intelligence model on sequence-based prediction of PPI using AISSO deep concept with hyperparameter tuning process

Protein–protein interaction (PPI) prediction is vital for interpreting biological activities. Even though many diverse sorts of data and machine learning approaches have been employed in PPI prediction, performance still has to be enhanced. As a result, we adopted an Aquilla Influenced Shark Smell (AISSO)-based hybrid prediction technique to construct a sequence-dependent PPI prediction model. This model has two stages of operation: feature extraction and prediction. Along with sequence-based and Gene Ontology features, unique features were produced in the feature extraction stage utilizing the improved semantic similarity technique, which may deliver reliable findings. These collected characteristics were then sent to the prediction step, and hybrid neural networks, such as the Improved Recurrent Neural Network and Deep Belief Networks, were used to predict the PPI using modified score level fusion. These neural networks’ weight variables were adjusted utilizing a unique optimal methodology called Aquila Influenced Shark Smell (AISSO), and the outcomes showed that the developed model had attained an accuracy of around 88%, which is much better than the traditional methods; this model AISSO-based PPI prediction can provide precise and effective predictions.

Comparison of clinical pharmacist practitioners' headache care roles across clinical contexts within the Veterans Health Administration: Optimizing pharmacist integration.

Studies show interdisciplinary treatment is highly effective for addressing chronic pain syndromes, including headache disorders. Increasingly, advanced practice pharmacists work collaboratively with physicians to apply their unique skills to enhance patient outcomes. This qualitative study aimed to elucidate the potential in the Veterans Health Administration (VHA) for increased roles of clinical pharmacist practitioners (CPPs)-advanced practice pharmacists with a scope of practice-in collaborative, interdisciplinary headache care teams. Our research question was: How do CPPs integrate with interdisciplinary headache care teams in Headache Centers of Excellence (HCoE) and non-HCoE VHA facilities, and how can their roles be configured to optimize headache specialty care services? This cross-sectional qualitative study used purposive sampling to recruit CPPs providing headache care within HCoEs and in non-HCoE VHA facilities for virtual, recorded, individual interviews. Multi-stage qualitative data analysis entailed: team discussions; immersion/crystallization for close reading of transcripts to identify emerging patterns of HCoE/non-HCoE comparison of CPPs' experiences; team data sorting using spreadsheets; and further immersion into sorted data for final identification of comparisons and interpretation of the data. A total of 15 CPPs involved in headache care were interviewed, with about half working in HCoEs and half in non-HCoE VHA facilities across the United States. CPPs' roles within and outside HCoEs have considerable overlap as both groups co-manage patients with headache with physicians. CPPs have independent and collaborative responsibilities as they extend headache specialists' services by providing direct patient care and referring to additional providers for headache treatment. When their roles differ within and outside HCoEs it is largely due to level of integration on interdisciplinary headache or pain teams. CPPs in HCoEs collaborate with headache neurologists and interdisciplinary teams; some outside HCoEs do as well, while others work with primary care. CPPs' weekly time dedicated specifically to headache tends to be greater in HCoEs. Nevertheless, most interviewees in both groups stated patient need exceeds CPP availability at their facilities for conducting detailed chart reviews, initial visits to understand the context of patients' headache, and scheduled follow-ups over time to monitor and adjust treatment. CPPs also consult with and educate physicians on headache pharmacy, particularly regarding appropriate use of non-formulary medications. Findings from this study suggest that CPPs' roles in headache care are valuable to clinical colleagues and their patients and should be leveraged and expanded within HCoEs and non-HCoE VHA facilities. When substantively integrated into interdisciplinary headache care teams, CPPs offer unique knowledge, headache management and patient behavior change skills, extend headache specialists' services, and provide both patient and physician education. These combined responsibilities contribute to enhancing patient outcomes and facilitating ongoing access to high quality, evidence-based headache care.

Banking on ESG: How ownership influences financial outcomes in 5-ASEAN countries

This study investigates the effect of Environmental, Social, and Governance (ESG) scores on bank performance in five Association of Southeast Asian Nations (ASEAN) countries: Indonesia, Malaysia, Singapore, Thailand, and the Philippines. This study aims to examine the effect of ESG scores on bank financial performance and investigate whether the influence of bank ownership can strengthen both. This study uses a sample of 26 banks in 5-ASEAN countries during 2016–2021. This amount is the result of data sorting conducted on 86 banks by adjusting to the research sample criteria. Using multiple linear regression analysis, this study shows that ESG scores have a significant positive effect on bank financial performance as measured by Return on Assets (ROA), Return on Equity (ROE), and Price to Book Value (PBV). Furthermore, this study found that the positive impact of ESG scores on bank performance is stronger for state-owned banks compared to private banks. However, bank ownership does not affect the relationship between ESG scores and ROA. These findings suggest that law enforcement by the government through regulators plays an important role in encouraging banks to view ESG as a driving value to improve their performance.

Evolution and Control of Air Pollution in China over the Past 75 Years: An Analytical Framework Based on the Multi-Dimensional Urbanization

China’s approach to air pollution control has been shown successful in East Asian countries and even elsewhere in the world. The analysis of the evolution and control of air pollution in China over the past 75 years can be used as a reference for developing countries suffering from air pollution resulting from urbanization. Based on the sorting and mining of relevant indicators, data and policy texts from the areas of population, economy, space and social urbanization, the findings suggest that the presence of air pollution and its changing forms indeed have complex interactive relationships with the process of urbanization. Specifically: (1) the feature of air pollution has changed from “single pollutant and pollution source to multiple pollutants and pollution source, local pollution to regional pollution, light pollution to heavy compound pollution” as a result of urbanization, the emphasizing of construction and the neglect of governance, the emphasizing of economics and the neglect of ecology, and the emphasizing of immediate interests over long-term interests; (2) the interactive relationship between air pollution and urbanization has also gone through three stages from being irrelevant each other to “urbanization determines air pollution” and then “air pollution restricts urbanization”; (3) this has forced air pollution control to shift from the traditional “treating symptoms” to “high-quality urbanization”, thus promoting air pollution and urbanization to move “from confrontation to unification”. Therefore, air pollution control is not a simple technical issue; one of the keys lies in exploring how to adjust the urbanization model, so as to achieve the “win–win” of urbanization and air pollution control.

Simulation‐Based Assessment of Fine Sediment Transport to Support River Restoration Measures

ABSTRACTA three‐dimensional coupled hydrodynamic and sediment transport model was employed to simulate the suspended sediment transport at a section of the Danube River, in Hungary. The case study is characterised by a highly complex hydromorphological system due to the nearby tributary inflow, the high number of river regulation structures as well as the several side‐arms connected to the Danube mainstem. The numerical model is set up, parameterised and validated against thorough field data of flow velocities and sediment concentrations measured at different hydrological regimes. Through the selected case study, the paper introduces (i) why 3D description is necessary at a reach‐scale analysis of complex hydromorphological systems; (ii) what sort of field data is needed to parameterise and validate a hydrodynamic and sediment transport model considering the spatial inhomogeneity of the flow and sediment features and (iii) an example for a quantitative impact assessment of side‐arm revitalisation measures on the sedimentation processes, playing a crucial role in the quality of riverine habitats.

Lexical semantic study of the Bubakan Manten Tradition in Mojodelik Village, Bojonegoro, East Java, Indonesia

This research aims to analyze the lexicon contained in the bubakan manten traditional procession in Mojodelik village on AM Production's YouTube account and analyze the lexical and cultural meaning contained in the bubakan manten traditional procession in Mojodelik village on AM Production's YouTube account. This research uses a qualitative descriptive method with a lexical semantic approach. The data in this research is in the form of a lexicon contained in the bubakan manten tradition, which contains lexical and cultural meanings. The primary data source in this research is the video of the bubakan manten tradition in Mojodelik Village, which is available on the AM Production Purwosari YouTube account, entitled Live Streaming Season 2 Langen Tayub Mustiko Laras Mojodelik Gayam, as well as interviews with the resource person who served as the leader in the implementation of bubakan manten, namely Mr. Jimin and Mr. Pandholi. Data collection techniques in this research used note-taking and interview techniques. Data analysis techniques used include sorting data for analysis, classifying lexicon forms, explaining the lexical and cultural meaning of the lexicon, and conclusion. The results of the research are a lexicon of places, equipment, food, and plants. The lexical meaning of the bubakan tradition is to open the way for marriage, while the cultural meaning contained in the bubakan tradition is to ask for safety and to be kept away from bad things.

Toddlers Family Assistance Model: As An Effort To Stunting Prevention Education In Kuantan Singingi District, Indonesia

This research aims to find out what the toddlers family assistance model is as an effort to stunting prevention education in Kuantan Singingi Regency. The method used is descriptive qualitative. The results showed that family assistance starts with careful planning and coordination with various related parties, implementing and preparing target data for toddlers, collecting data on families of toddlers at risk of stunting, sorting data on babies at risk of stunting until the evaluation carries out recording and reporting to the top level. Family assistance model starts from the Stunting Reduction Acceleration Team (TPPS) at the central level, namely the BKKBN, down to the provincial level, namely representatives of the provincial BKKBN, then at the Regency/City level, namely the Regional Apparatus Organization (OPD) in the field of Regency or City Population Control, at the sub-district level, namely the Family Planning Counseling Center ( KB), village or sub-district level and the Family Assistance Team (TPK) as field agents directly provide assistance to toddlers and toddlers at risk of stunting, in addition to facilitating referrals and social assistance. Based on data, the stunting rate is decreasing from 2019-2023 in Kuantan Singingi Regency.