Post-earthquake soil chemical analysis is critical for understanding environmental and agricultural impacts as well as public health concerns. Earthquakes often disrupt soil structures, leading to changes in pH levels, nutrient content, and the release of contaminants such as heavy metals and organic pollutants. These chemical alterations have far-reaching consequences for soil fertility, vegetation growth, and water quality. This study provides a comprehensive review of the changes in soil chemical properties caused by seismic events and highlights their implications for sustainable recovery and environmental resilience. Key mechanisms such as liquefaction, erosion, and industrial contamination are discussed, along with the effects on soil's physical and chemical stability. The paper identifies key challenges in post-earthquake soil assessments, including spatial variability of soil conditions, complex contaminant interactions, and technical limitations in testing and monitoring equipment. The absence of baseline soil data in many seismic regions further hinders accurate assessment. The study emphasizes the need for improved soil monitoring networks, international cooperation, and advancements in analytical techniques. Future research priorities are proposed, including the development of standardized methods for soil chemical assessments, exploration of sustainable remediation technologies, and integration of emerging technologies such as remote sensing and geographic information systems (GIS) to accelerate data collection. The findings underscore the importance of interdisciplinary research involving soil science, environmental health, and civil engineering to foster holistic solutions for mitigating earthquake-induced soil changes and improving post-disaster recovery strategies.

The education system aims to instill higher moral values in young people, but the results of so-called theoretical upbringing, unfortunately, indicate a discrepancy between the theory of moral upbringing and the actual behavior of young people in everyday life. As a rule, young people are often guided by fleeting mercantile interests, evading imposed moral norms as hypocritical, formal, etc. Consciousness, as an information system in terms of information processing, decision-making, and methods of their implementation, is fundamental to the thinking process. In terms of content, knowledge and beliefs are similar, but beliefs have a higher status in consciousness as an already established program of appropriate actions, and when a person encounters certain circumstances in life, beliefs in consciousness are automatically activated as already accepted decisions regarding thinking, behavior, and necessary actions. Knowledge also has a program of actions, but these are not yet decisions made for their implementation as beliefs. Research into the information model of consciousness makes it possible to consciously change beliefs — to purposefully reprogram consciousness as an information system. To control consciousness, to transform it, you need to consciously control your thinking — to give consciousness the appropriate command programs (three types). A person who understands how consciousness works and how to control one or another element of consciousness can free themselves from any internal problems and develop qualities and virtues, talents, apply them in life, and achieve significant results. The information model of consciousness has made it possible to develop an algorithm for forming beliefs and to develop appropriate methods and techniques, the effectiveness of which has been proven in practice. The possible risks of failures in the formation of beliefs have also been analyzed. The algorithm for the formation of beliefs in human consciousness should also be taken into account when creating tasks in textbooks on spiritual and intellectual development. The authors propose a scheme for working through the educational material, which involves the student performing five types of tasks. The study offers ways to solve an important task — the formation of deep moral beliefs in students as stable programs of thinking, behavior, and actions. The algorithm presented allows it to be applied in the educational process to achieve specific upbringing goals and to form graduates who will be able to meet the highest requirements of moral educational standards. The developed task scheme will improve the quality of learning material assimilation and contribute to the formation of appropriate beliefs and worldview. The results of testing allow innovators to implement the recommendations provided in the educational process.

Using FHIR for data sharing: A scoping review of challenges and facilitators in healthcare settings.

Sentiment analysis, a key component of natural language processing and data mining, plays a pivotal role in extracting subjective insights from textual data, particularly on social media platforms. In response to the growing importance of digital engagement, understanding public sentiment has become essential for formulating effective marketing strategies. This study aims to enhance the marketing strategy of energy products in subsidiaries of State-Owned Enterprises (SOEs) by employing a hybrid sentiment analysis model that integrates the Valence Aware Dictionary and Sentiment Reasoner (VADER) with Long Short-Term Memory (LSTM) neural networks. Utilizing a mixed-method approach that combines both quantitative and qualitative analyses, the study collects and processes data from multiple social media sources to identify and classify consumer sentiment. The results demonstrate that the hybrid VADER-LSTM model achieves an accuracy rate of up to 84%, enabling a more nuanced interpretation of consumer opinions. These insights inform the development of data-driven, responsive, and targeted marketing strategies. Furthermore, the study highlights the significance of fostering interactive communication between companies and consumers to enhance the impact of digital marketing efforts. Theoretical implications include a contribution to the academic discourse on information systems and digital marketing, while practical outcomes offer valuable guidance for SOEs in adopting adaptive, sentiment-informed marketing approaches within the energy sector.

IntroductionThis bibliometric analysis examines the global research landscape on viral marketing using data extracted from the Scopus database and analyzed with Biblioshiny, VOSviewer, and CiteSpace. Viral marketing, characterized by rapid message dissemination through digital networks and consumer sharing, has gained significant scholarly attention across diverse disciplines. ObjectiveThe annual scientific output reveals a steady growth in publications, reflecting increasing academic interest and the evolution of research themes over time. MethodAnalysis of top influential researcher’s highlights key contributors shaping the field’s theoretical and methodological advancements. Prominent scientific journals, particularly in marketing, consumer behavior, and information systems, serve as primary publication outlets, fostering interdisciplinary dialogue. ResultsGlobal research contributions by nation indicate that the United States, China, and India are leading producers, supported by active collaborations illustrated in the timeline network visualization of country partnerships. Co-citation analysis of cited authors and journals uncovers core intellectual foundations and interlinked knowledge domains. Bibliographic coupling of documents and co-occurrence of author keywords reveal thematic clusters that define the research focus, while thematic evolution and the thematic map highlight the transition from foundational studies to emerging topics such as social media analytics and influencer marketing. Trend topic analysis indicates growing emphasis on data-driven targeting, user engagement, and algorithmic influence modeling. ConclusionsThe study identifies research gaps in cross-cultural comparative studies, ethical considerations, and the integration of emerging technologies into viral marketing strategies, with practical implications for marketers seeking to optimize campaigns in a rapidly evolving digital environment.

Beyond molecular structure: Comparing Australian and European regulatory approaches to nano-identification and classification.

With the advancement of minimally invasive surgery and anesthesiology, ambulatory surgery has become a pivotal model for enhancing healthcare efficiency and optimizing resource allocation. This guideline seeks to establish a systematic, operable, and standardized framework for implementing ambulatory surgery in pediatric otorhinolaryngology and head and neck surgery across healthcare institutions in China. Formulated based on evidence-based medicine principles and integrating the latest literature and multidisciplinary expert consensus, it provides detailed recommendations pertaining to organizational structure, hardware configuration, information system development, multidisciplinary team building, patient and procedure selection criteria, perioperative process management, and quality control. The primary objectives are to ensure surgical safety and quality, and to promote the standardized and sustainable development of ambulatory surgery within this pediatric subspecialty.

The Engagement of Cultural Society, Waste Information System, Task Process and Green Environment Marketing within The Waste Management Supply Chain in the Urban Context of Semarang

Beyond the screen: Understanding consumer engagement with live-stream shopping from the perspective of the information system success model

Behavioral three-way decision based multi-attribute decision-making for credible hesitant fuzzy information systems

Optimizing climate crisis adaptation information: Establishment and evaluation of a taxonomic framework.

A three-way efficacy prediction method fusing temporal composite rough set and hybrid machine learning models on multigranulation temporal hybrid attribute information system

Geographic Information Systems have grown over time to become an integrative tool in public health, providing an effective way of bringing spatial data together in assessing some of the complex health challenges. The aim of this systematic review is to delve into the application of GIS in addressing public health challenges and identify the knowledge gaps on the existing limitations on the way to harnessing new technologies in GIS and maximizing their impact on population health. In 45 articles reviewed, the authors found evidence that GIS have been essential in the field of public health. Most studies explored their use in disease surveillance and outbreak response, especially in the tracking of patterns of disease. Others discussed how GIS can be used in health disparity research for visualizing geographical patterning of health inequities and for revealing ways to implement interventions that would reduce inequities. Very few of them reviewed applications in health service planning and resource allocation, pointing to potential means of optimizing the geographical distribution of healthcare resources and increasing access to underserved populations. Finally, the authors consider how GIS can help to create comprehensive health profiles of communities by providing insights into health disparities. Our study provides an overview for future research on this topic and discusses the progress and the continued challenges of the field of public health GIS with respect to data quality, capacity building, and ethical and community considerations in order that its full potential for creating a healthier, more equitable world can be met.

Objective To evaluate the completeness, consistency, and duplicity of self-mutilation reports among adolescents in Santa Catarina, from 2014 to 2023. Methods This study evaluated reports recorded in the Notifiable Diseases Information System (Sistema de Informação de Agravo de Notificação - SINAN). Completeness was assessed for 18 variables and classified as excellent (≥95.0%), good (90.0%–95.0%), fair (70.0%–90.0%), poor (50.0%–70.0%), and very poor (<50.0%). The consistency of seven variables was analyzed and classified into three categories: excellent (≥90.0%), fair (70.0%–89.0%), and low (<70.0%). Duplicity was checked using the variable “NDUPLIC_N” and by manual verification. Temporal trends were analyzed using Prais–Winsten regression, which classified them as stable, increasing, or decreasing. Results A total of 1,403 self-mutilation reports were identified. Completeness was excellent for 12 variables and good for three. Sexual orientation (75.8%) and gender identity (76.2%) were rated fair, while motivation of violence (46.1%) was rated very poor. An increasing trend in completeness was observed for three variables. Consistency was excellent for six variables and fair for one, with an increasing trend in “sex of the person attended versus sex of the perpetrator,” a decreasing trend in “presence of disability or disorder vs. type,” and stability for the others. No duplicate records were found. Conclusion The analyzed data showed good quality in the recording of self-mutilation among adolescents in SINAN of Santa Catarina. Strategies such as continuing education for health professionals and revisions to the reporting form are crucial for enhancing data quality and strengthening the planning of interventions to address this form of violence.

Refining estimation of antimicrobial use at national level: A quantitative surveillance study processing data from the Swiss national reporting system.

Spatial and temporal patterns and determinants of chronic disease multimorbidity among middle-aged and older adults in China: Evidence from two longitudinal cohort studies.

Objective To analyze spatial clusters and temporal trends regarding patients commuting to access cancer treatment in Brazil between 2015 and 2022. Methods This was a spatial analysis using data from hospital and outpatient information systems (2015-2022). Absolute and relative frequencies of treatments (surgery, chemotherapy, and radiotherapy) and commuting patterns were calculated. Cluster analysis (K-means) categorized distances into three intervals: low (2.1-261.4 km), medium (261.6-762.2 km), and high (764.0-3,865.8 km). Temporal trends were assessed by Prais-Winsten regression, estimating annual percentage change (β) and confidence intervals (95%CI) as a measure of dispersion. Results Of the 27,204,159 cancer services provided, 55.2% involved displacement to other municipalities. During the period, 3.6% of patients received surgical treatment, 7.1% received radiotherapy, and 89.3% received chemotherapy. There was a reduction in the distances traveled for hospitalization, from 93.0 km in 2015 to 84.2 km in 2022, with an annual decrease of 0.8% (95%CI -0.9; -0.7). For chemotherapy, the reduction was from 87.8 km to 83.5 km, with a variation of -0.4% per year (95%CI -0.4; -0.3). Distances for radiotherapy remained stable, with a slight variation of -0.3% (95%CI -0.9; 0.2). Conclusion The reduction in the distance traveled for hospitalization and chemotherapy contrasts with the stability in radiotherapy. The maintenance of long journeys for radiotherapy highlights disparities in the geographical distribution of these services. Thus, the urgency of decentralizing oncology services and investing in regional infrastructure is underscored to ensure access for the population, particularly those residing in rural and remote areas, and to guarantee equitable access to highly complex treatments.

From objective grouping to fuzzy reference intervals: A standardized machine learning approach for thyroid function tests.

A novel consensus model integrating asynchronous opinion evolution and dynamic trust-driven three-way decision for incomplete multi-scale information systems

Introduction: Agricultural land conversion poses a global threat to food security, particularly in developing nations experiencing rapid urbanization and population growth. This study aims to analyze the impact of rice field land conversion on food security threats in Padang City, West Sumatra, Indonesia, where population pressure continues to drive agricultural land loss.Methods: A quantitative approach was applied using four methodological stages: (1) calculating rice field changes across three time periods (2009, 2015, and 2022) using supervised classification of Landsat 7 and 8 imagery; (2) measuring agricultural land carrying capacity using standardized formulas; (3) determining rice availability based on harvested area and productivity data; (4) predicting rice requirements for food self-sufficiency. Data were obtained from Landsat imagery (2009, 2015, 2022), field surveys conducted in 2023, and Statistics Indonesia (BPS). Analysis was conducted using Geographic Information Systems (GIS) software and carrying capacity, rice availability, and demand formulas. The study encompassed all 11 administrative districts of Padang City, with sample areas identified as rice-producing zones.Results: Rice field area declined significantly from 6,827.40 hectares in 2015 to 4,809.35 hectares in 2022, representing a loss of 1,918.05 hectares, predominantly converted to built-up land. Agricultural land carrying capacity was calculated at 0.0125 (Class III), indicating that Padang City has not achieved food self-sufficiency. Rice availability was 1,026,762.57 tons, while rice demand reached 11,801,533.26 tons, resulting in a deficit of approximately 10.77 million tons.Conclusions: Rice field conversion significantly reduces agricultural productivity and threatens food security. Padang City experiences a major rice deficit and has not achieved self-sufficiency. Urgent interventions including farmer regeneration, creation of new agricultural zones, and implementation of sustainable agricultural land protection policies are necessary to address population pressure and land conversion challenges.