Physical Environmental Factors Research Articles

Ecological factors and morphological traits of Coffea Liberia Hiern in Kalipuro District, Banyuwangi Regency

This study aimed to analyze the ecological factors and morphological traits of Liberica coffee in Kalipuro District, Banyuwangi Regency. Ecological and morphological factors were measured, and observations were recorded accordingly. The observation of significant morphological characters has been thoroughly conducted The observed ecological factors were microclimate factors, including altitude, air temperature, humidity, light intensity, rainfall rate, soil pH, soil temperature, and soil moisture. The Paleontological Statistics (PAST) program was used to perform multivariate analysis to group liberica coffee variants based on morphological traits and physical factors of the plantation. The study found that physical environmental factors had a relatively significant influence on morphological variation in each population. The light intensity and relative humidity were the physical environmental factors related to morphological traits, such as leaf shape index, number of flowers per inflorescence, and leaf surface index based on principal component analysis (PCA). Unstable weather conditions can influence environmental factors, which, in turn, can profoundly impact morphological characteristics, specifically the flowering season. The study revealed a statistically significant correlation between light intensity and the number of flowers per inflorescence.

A taste alteration-related scale assesses megestrol to improve chemotherapy-induced anorexia.

We evaluated the efficacy of megestrol in improving chemotherapy-related anorexia by analyzing the related scales of taste alteration. We conducted the current study on a group of advanced patients with cancer with two or more chemotherapy cycles. The chemotherapy-induced taste alteration scale (CiTAs) scale helped assess the megestrol effects on basic taste perception, aversive taste changes, unpleasant symptoms, and associated concerns. Furthermore, the Short Nutritional Assessment Questionnaire scale (SNAQ) helped measure the impact of megestrol on malnutrition likelihood in patients experiencing chemotherapy-induced anorexia. The World Health Organization Quality of Life (WHOQOL)-BREF Scale was used to evaluate the quality of life of participants, producing scores related to physical health, psychological well-being, environmental factors, and social relationships. The CiTAs scale assessment indicated that administering megestrol significantly enhanced taste perception among advanced patients with cancer undergoing chemotherapy. Notably, the megestrol group patients showed significantly higher Short Nutritional Assessment Questionnaire (SNAQ) scores than the control group. The megestrol group patients also exhibited higher physiological (PHYS) scores than their control group counterparts. However, this distinction was not statistically significant. The study findings indicate that patients who received megestrol demonstrated significantly higher scores in psychological (PSYCH) and environmental(ENVIR) domains than the control group. Furthermore, megestrol administration was associated with significantly elevated SOCIL and ENVIR levels in patients. The proficient efficacy evaluation of megestrol in enhancing appetite, mitigating malnutrition likelihood, and improving the quality of life of chemotherapy-induced anorexic patients can be achieved through taste-related scales.

Analysis of the characteristics and causes of city gas explosion accidents based on DT-AR algorithm

In order to effectively prevent and control accidents, it is essential to trace back the causes of gas explosions in cities. The DT-AR(decision tree-association rule) algorithm is proposed as a quantitative analysis of gas accident features and causality. First, 210 gas explosion accident investigation reports were taken as samples. The gas accident causation system is divided into three aspects, including environmental factors, management factors and physical factors. Management factors were sorted into organizational-level and individual-level factors from the investigation reports. Second, the CART decision tree model was used to compare location features, organizational causality features, and individual causality features of the piped and bottled gas accidents, and a decision tree model with the gas system fault site as the root node was built to filter the key feature variables. In order to reveal factor correlations and deep-level causation, the Apriori algorithm is used to mine accident association rules. The combinations on the branches of the decision tree are used as constraints to filter the critical causality rule, which improves the efficiency of association rule screening and enhances prediction accuracy. The results demonstrate that the DT-AR algorithm can evaluate the importance of variables, quickly locate effective combinations of factors, and mine the complete causal chain. The association rule is screened based on the constraint of the key element combination of the decision tree, which compensates for the low efficiency of the Apriori algorithm for association rule mining. In addition, the accident-caused excavation results provide an effective path for gas companies, outsourced service companies and administrative departments to implement gas safety chain supervision, which can address the problem of gas accident safety management failures and provide decision support for accident prevention.

Medical education and artificial intelligence: Question answering for medical questions based on intelligent interaction

SummaryComputer assisted medical diagnosis technology is widely used in the field of medical assistance to assist doctors in making diagnostic decisions. But as the number of patients increases, the diagnostic pressure on doctors gradually increases, and more efficient computer‐aided medical diagnosis technology is needed to improve the accuracy of doctors' diagnosis. Today's computer‐based medically assisted diagnostic technologies suffer from the inability to fully simulate physical attributes and environmental factors, the large computational resources required for high‐precision models, the need for professional training for user operation, and the limited intuition for innovative design. For improving diagnostic efficiency, this study designs a medical Question answering intelligent interaction system in view of artificial intelligence algorithms. The system is constructed with an active interactive intelligent Q&A model consisting of a medical reasoning module and a medical examination recommendation module. Then, it uses local Bayesian network algorithm as the foundation to establish an intelligent strategy optimization network. And it puts forward the answer selection model of medical Question answering in view of hierarchical interaction for natural language processing tasks in the medical context. The performance test results show that when the diagnostic end threshold of the medical reasoning module is 0.8, the shortest diagnostic path is 3.33. When the diagnostic threshold is 0.85, the maximum length of the diagnostic path is 4.66, and the maximum difference between the diagnostic paths is 1.33, which is basically not affected by the diagnostic end threshold. The local Bayesian network algorithm can reduce the impact of noise features and extract more valuable information. The accuracy of the multilevel interactive answer selection model on the Stanford Natural Language Inference dataset without using external resources reached 89.2%. The ablation test results show that the overall accuracy of the model is 89.64%. The visualization results of the attention weight distribution test between interaction layers show that under different levels of interaction, the attention distribution will undergo significant changes.

Interplay of Environmental Factors, Genetic Susceptibility, and Sleep Disturbances predict Bipolar Disorder’s Relapses: preliminary results from a pilot study

IntroductionPredicting acute affective episodes in individuals with Bipolar Disorder (BD) remains a clinical challenge. Specific environmental stressors, including air pollution, noise, and temperature variations might worsen affective symptoms or sleep in the general population, but their role in BD relapses is often overlooked. Indeed, they might exacerbate BD by perturbing circadian rhythms – fundamental aspects of BD.ObjectivesWe thereby present the protocol of this pilot study and future preliminary data. We aim to longitudinally assess sleep alterations, mood fluctuations, and environmental exposure to several factors (air pollutants, climate, noise, artificial light-at-night, green space access) in patients with BD and to check the association of these variables with BD relapses.MethodsIn this pilot study, we will recruit 40 patients with BD in a 6-month prospective study. Patients were assessed during baseline, at 3 and 6 months. Data recollected will consist of a subjective (questionnaires) and objective (through meteorological stations) evaluation of physical environmental factors around the home residence; clinical assessment of mood and circadian rhythms, and continuous tracking of sleep-wake patterns, energy, and movement using actigraphy.ResultsExpected results will show that exposure to a worse environment (higher pollution, noise, light exposure, climate) will be associated with worse BD outcomes (i.e., relapse, mood symptoms, sleep alterations).ConclusionsWe will be sharing preliminary data from our ongoing study, offering insights into early patterns and findings that shed light on our objectives.Disclosure of InterestNone Declared

Tools to measure barriers to medication management capacity in older adults: a scoping review

BackgroundMedication management capacity is a crucial component of medication adherence, particularly among older adults. Various factors, including physical abilities, cognitive functions, sensory capabilities, motivational, and environmental factors, influence older adults' ability to manage medications. It is, therefore, crucial to identify appropriate tools that allow clinicians to determine which factors may impact medication management capacity and, consequently, nonadherence to medications.Purpose1)To identify tools that measure physical, cognitive, sensory (vision, hearing, touch), motivational, and environmental barriers to medication self-management in older adults, and 2) to understand the extent to which these tools assess various barriers.MethodsThe scoping review was conducted using Arksey and O'Malley's scoping review framework and the PRISMA Extension for Scoping Reviews checklist. In June 2022, the relevant literature was identified by searching PubMed (MEDLINE), Ovid Embase, Ovid IPA, EBSCOhost CINAHL, APA PsycINFO, and Scopus.Results and discussionIn total, 7235 studies were identified. Following the removal of duplicates, 4607 articles were screened by title and abstract, of which 4253 did not meet the inclusion criteria. Three reviewers reviewed the full texts of the remaining 354 articles; among them, 41 articles, 4 theses and 1 conference abstract met the inclusion criteria. From the included studies, 44 tools were identified that measured a combination of physical, cognitive, sensory, motivational, and environmental barriers (n=19) or only cognition (n=13), vision (n=5), environmental factors (n=3), auditory (n=1), and motivational factors (n=1). The review also examined the psychometric properties of the identified tools and found that most of them had reported validity and reliability data. Several tools have demonstrated promise in assessing a combination of barriers with validity and reliability. These tools include the Self-Medication Assessment Tool (SMAT), ManageMed Screening (MMS), Self-Medication Risk Assessment Tool (RAT), HOME-Rx revised, and Medication Management Ability Assessment (MMAA).ConclusionThis scoping review identified 44 validated tools to measure various challenges that older adults encounter with medication management. However, no tool measures all five barriers (physical, cognitive, sensory, motivational, and environmental) to medication-taking at home. Therefore, utilizing a combination of tools would be most appropriate to measure these different aspects comprehensively. Further research is needed to develop a new comprehensive tool that simultaneously measures various barriers to medication self-management.

Exploring Public Space Satisfaction in Old Residential Areas Based on Impact-Asymmetry Analysis

The renovation of public space environments in old residential areas has become the focal point in Chinese urban renewal and promotion of urban sustainable development; thus, an urgent need for research expansion is attached to identifying the environmental factors of public space and their impacts from the perspective of residents’ needs and satisfaction. Taking Hefei, China, as an example, and based on a satisfaction survey of the public space environment in old residential areas, this study discerned critical factors affecting public space satisfaction through gradient-boosting decision trees and impact-asymmetry analysis methods, after which the asymmetric relationship between public space environment factors and resident satisfaction was tested and the priority and goal of public space environment renovation were obtained. The results indicate that the following: (1) Compared with physical environment factors, current social environment factors, including uncivilized behavior, space occupation, and hygiene and cleanliness, exert a greater impact on the overall satisfaction. (2) The hypothesis that there exists a general nonlinear relationship between environmental factors and satisfaction is verified, with all social environment factors proving to be nonlinear and physical environment factors being highly related to social environment creation, such as nursing space for the old and young, reading and learning space, and display and communication space. (3) A priority hierarchy for the improvement of environmental factors should be established, which basically conforms to Maslow’s hierarchy of needs theory. The role of social environment renovation should be highlighted, along with the necessity to bolster community governance and public space management. At the level of the physical environment, more space should be available for the activities of residents, display and communication, and reading and learning. This study can provide a corresponding theoretical basis and planning inspiration for meeting the multiple needs of residents for public space, improving life happiness, and promoting the sustainable development of cities in the renovation of public space environments in old residential areas.

Physical-Environmental Characterization of Areas for the Cultivation of Guaraná (Paullinia cupana) in Bahia, Brazil

Brazil is the world's leading producer of guarana and Bahia is the largest producing state, which suggests the need for cultivation planning. In this study, the physical-environmental factors of six municipalities in Lower Southern Bahia, Brazil were characterized to identify favorable areas for guarana cultivation. A database with the basic physical-environmental conditions was used to characterize and identify such areas. As described in the literature, the thresholds of conditioning factors for successful cultivation were selected using Structured Query Language (SQL) based on Geographic Information Systems (GIS), with logical operators and overlay tools. The factors considered in the analysis were soils (drainage and texture), climate (precipitation and temperature), and topography (slope). The results indicate the existence of favorable areas for guarana cultivation in Lower Southern Bahia, Brazil, which can significantly contribute to the planning and optimization of fruit cultivation in the region. A total of 23,489.7 hectares were considered favorable areas for guarana cultivation. This value is double the area allocated for cultivation in Brazil and more than four times the area allocated for harvesting in Bahia.

Work Environment and Performance of Junior Business Counselors in DTI Region 02, Philippines

The study focused on evaluating the influence of the work environment on the performance of Junior Business Counselors (JBCs) in the LGU-based Negosyo Center of the Department of Trade and Industry (DTI) in Region 02. Aligned with Sustainable Development Goal 8 (SDG 8) on “Decent Work and Economic Growth,” the research directly contributes to promoting inclusive economic growth, productive employment, and decent work, in line with the United Nations’ objectives. The study used a descriptive-correlational design with 49 purposively selected respondents. Survey questionnaires were employed to examine the physical work environment factors, encompassing size and layout, furnishings, equipment, and location of the workplace. Findings showed that respondents were comfortable in the presence of a working area and receiving space, however, in terms of the office space per se respondents showed discontentment. Moreover, findings also indicated a significant relationship between furnishings and the level of JBC performance, along with a slight but meaningful association between the physical work environment and performance. Thus, efforts should be directed towards optimizing the available space and providing additional amenities to better align with the needs and expectations of JBCs, fostering a positive work environment and potentially enhancing overall performance. Keywords: work environment, employee performance, descriptive-correlational design, LGU-based Negosyo Center

The hidden biotic face of microbialite morphogenesis – a case study from Laguna de Los Cisnes, southernmost Patagonia (Chile)

ABSTRACTMicrobialites provide geological evidence into Earth's early ecosystems, recording long‐standing interactions between co‐evolving life and the environment. Yet, after more than 100 years of research, the complex interplay between environmental and biological forces involved in microbialite growth is still debated. Laguna de Los Cisnes, located in Chilean Tierra del Fuego, Patagonia, provides a unique opportunity to study these interactions. This lake, which became ice‐free around 10 000 years ago, features carbonate microbialites developed by algal–microbial communities. Macroscopically, the organo‐sedimentary deposits exhibit a consistent primary crater‐like architecture, showcasing macrostructural variations such as dish‐shaped, hemispherical, columnar and lenticular morphologies. This study explores the environmental and biological factors shaping microbialite macrostructure by analysing the distribution of dominant morphotypes across the basin. Concurrently, it examines the internal mesostructure and microstructure of microbialites in association with prevailing algal–microbial communities. The incremental development of these communities contributes to the distinct crater‐like morphology observed in microbialites from Laguna de Los Cisnes. The mineral encrustation of the green alga Percursaria percursa emerges as a primary driver of lithification, evidenced by the preservation of microfossils within the microstructure of the microbialites. Simultaneously, physical environmental factors, including waves, Langmuir cells and accommodation space influence the location of the algal–microbial carbonate factory, determining the spatial distribution and temporal succession of different crater architecture variants. Laguna de Los Cisnes, hosting well‐preserved subfossil outcrops and living microbialites, serves as a remarkable living laboratory for understanding microbialite morphogenesis. This study contributes to a novel model that captures the fundamental role of algal–microbial communities in determining the primary macrostructural architecture of microbialites before environmental factors come into play, merely reshaping this architecture into different morphotypes.

The effects of assistance dogs on social acknowledgements and engagement of people with visible disabilities – A case study

Abstract Stigmatization of people with visible disabilities is a well-recognized concept, as is the knowledge that Assistance Dogs (ADs) may serve as social lubricants. This case study explored the interplay of these two concepts in the everyday life of a person (Mary) with a visible disability and her AD (Cino). This mixed methods study collected both quantitative observational data and qualitative interview data. Four episodes of Mary interacting in the community with and without Cino (AD) were observed using an observation checklist. These were complimented by four in-depth interviews with Mary and one with a close family member. Interview transcripts were used to construct a thematic understanding of the complex ways in which Mary’s life and experience of living with significant disability are impacted by having Cino to support her. Observational data identified that the presence of Mary’s AD considerably increased social acknowledgements of Mary from members of the public during community interactions. Two major themes (The dog makes a difference, and Lack of understanding, awareness, and support) each with four subthemes, emerged from the interviews. The complex mesh of experiences related to the support of her AD(s), both positive and negative, are mapped in the subthemes. While both positive and negative aspects of AD ownership were identified and explored, Mary assesses the net effect of having Cino, as ultimately positive, outweighing numerous complications and drawbacks in life lived with disability. The findings contribute to a more nuanced understanding of the way ADs can impact both positively and negatively in the lives of people living with disability. These insights provide points that can be used in discussing potential AD support with people exploring this option. They also caution against simplistic, “do ADs really work?” approaches in research as Mary’s lived experiences show that this is nuanced by multiple personal, clinical, social, physical, and broad environmental factors.

Engagement in physical activity among African American women caregivers: a cross-sectional study

Family caregivers and African Americans often do not achieve the recommended 150 minutes of moderate-intensity aerobic activity per week. Factors associated with engaging in physical activity among African American caregivers have not been systematically examined. This cross-sectional study examined how contextual factors were associated with meeting the recommended amount of physical activity among African American women caregivers. We used a population-based sample of 1,478 African American women caregivers in the U.S. from the 2015, 2017, and 2019 Behavioral Risk Factor Surveillance System. We used survey-weighted multivariate regression analyses to examine associations between condition-specific factors, physical and social environment, and individual and family factors and meeting the national aerobic physical activity guideline (i.e., participating in 150 minutes (or vigorous equivalent minutes) of physical activity per week). Over half (53.9%) of African American women caregivers in the U.S. did not meet the guideline. Being age 65 years or older was associated with decreased odds of meeting the guideline compared to being between the ages of 25-44 years (OR = 0.50, 95% CI[0.26-0.99]). Compared to college graduates, women with partial college education had higher odds of meeting the guideline (OR = 2.08, 95%CI[1.24–3.51]). Having health insurance was associated with increased odds of meeting the guideline (OR = 2.28, 95%CI[1.12–4.63]). Our findings suggest several contextual factors are independently associated with meeting the national guideline. Understanding the relationships between contextual factors and engaging in physical activity among African American women caregivers can inform interventions aimed at protecting and promoting the health of these women.

The Interplay Between Mental Health and the Business Environment in Asia

Mental health is not just a psychological issue, but it also affects Business Environment. The basic research question is to see if businesses environment and mental health have any strong relationship. We propose a model that suggests mental health depends on various factors, including mental well-being itself, economic conditions, education, physical health, and, importantly, creating new businesses. This study addresses the intriguing question of whether starting a business is beneficial or detrimental to mental health It depends on a lot of things, like how someone was feeling before, the state of the economy, their education, and even the fairness of the legal system. Our econometric model using Generalized Method of Moments (GMM) carefully takes all these factors into account to understand the bigger and novel picture of the question put forth, while taking care of the issue of endogeneity that may arise in such type of data sets. We measure our main dependent variable i.e. mental health through emotional well-being and depression, while business creation is assessed by environment, ease, clustering, skills, and worker availability. Furthermore, this groundbreaking study on a panel of Asian countries shows that income levels alone are not enough to predict mental health outcomes. Legal fairness and business-friendly environments play a surprising role in shaping mental wellness. By analyzing physical health, macroeconomic determinants, and environmental factors, the research highlights the complex interplay that affects mental health outcomes. The study's novel variables and large panel data analysis approach offer new insights into the policies and incentives that can optimize mental health outcomes for all citizens.

Improved reference condition independent method for output performance estimation of PV modules under varying operating conditions

Traditional methods for estimating output property of the photovoltaic (PV) modules are strongly influenced by the selection of reference condition and transforming equations, which determine the calculated physical parameters under real operating conditions. The differences in the carrier transport properties of PV cells under varying operating conditions, such as the number and velocity of minority carriers at the junction edge and their recombination speed, lead to large deviations in the estimation of the output characteristics, especially under low irradiance conditions. To enhance the accuracy of performance estimation, we propose an improved method that is independent of reference condition. This method eliminates the impact of reference conditions and improves the transformation equations under all irradiance levels. Transformation equations of single diode model are established in different irradiance intervals based on the dependence of physical parameter on irradiance and temperature. Especially in the low irradiance range, all effects of irradiance and temperature are considered for each physical parameter in improved transformation equations. To optimize the unknown parameters in the transformation equations, the artificial hummingbird algorithm is used to fit experimental I–V data. The experimental results of six different types PV modules under a wide range of operating conditions are used to verify the effectiveness of the proposed method. The proposed method offers immediate benefits, including independence from reference condition and a more precise relationship between physical parameters and environmental factors in the estimation of PV output properties. Comparing the results to the traditional method by Laudani, the proposed method demonstrates superior capability in estimating I–V characteristics and accurately identifies the maximum power point under various operating conditions, which is of significant value for engineering applications.

Unbiased employee performance evaluation using machine learning

Most of the companies’ sustainability and growth depend on how well its employees perform. However, the measurement of employees’ performance until now is inconclusive and inexhaustive. To accurately assess and predict an employee's performance, numerous external factors (physical/environmental, social, and economic) related to an employee's life have been taken into account in this work. The purpose of this research is to explore an unbiased AI algorithmic solution to predict future employee performance considering physical, social, and economic environmental factors that affect employee performance. We collected data of 1109 employees from the ‘For-Profit Organization’ in Bangladesh from both employers and employees to cover all the factors that justified the unbiased outcome. We utilized a few machine learning tools in this study including the Logistic Regression classifier, the Gaussian Naive Bayes, the Decision Tree classifier, the K-Nearest Neighbors (K-NN), the SVM classification, etc., in order to predict the employee performance evaluation. Then, we compared the effectiveness of those machine learning models by analyzing their precisions, recall, F1-score, and accuracy. This work can be utilized to obtain bias-free employee performance reviews. This fair employee performance assessment can aid decision-makers in making moral choices regarding employee promotions, career advancement, and training needs, among other things. The study also describes notes for future researchers.

Environmental physical factors produce mitotic aberration and multicellularity in the ovarian cancer cell line SKOV3

The spread of ovarian cancer (OC) to the coelomic cavity triggers the secretion and accumulation of ascitic fluid (AF). Although its biochemical composition has been well studied, less is known about the implications of physical factors such as the pH and the mechanical properties of the AF for the malignancy of tumor cells. In this work, we investigated the effect of pH and the mechanical properties of AF on cell proliferation and mitotic morphology. We employed biopsies from patients with OC and the SKOV3 cell line as an in vitro model of OC with HeLa cells as controls. Sections of each tumor were stained with HE, analyzed, and related to clinical data. AF from patients with OC exhibited an alkaline pH (ranging from 7.3 to 7.8). Compared to control conditions, the 3 AFs significantly enhanced the proliferation of SKOV3 and HeLa cells. These effects were more pronounced at a more alkaline pH. In addition, we found that AFs have different densities that correlated with a significant increase in multinucleated tumor cells and severe morphological defects in cells undergoing mitosis. In agreement with these data, we found that higher concentrations of soft agar provoked significantly higher numbers of multinucleated and morphologically abnormal SKOV3 cells with no effect on HeLa cells.We conclude that an alkaline pH and greater rigidity could enhance the metastatic potential of OC cells. We propose that these two physical factors could be parameters of clinical importance as predictors of malignancy.

Targeted approach to assessing the impact of living conditions and social factors of the habitat on the medico-demographic status of rural territories in the Arctic zone of the Russian Federation

BACKGROUND:According to the Federal Law “On Sanitary-Epidemiological Well-being of the Population” the “environmental factors that have or may have an impact on humans and on health of future generations” along with chemical, physical and biological factors, also include “social factors". Within framework of section “State of Public Health in Connection with the State of Natural Environment and Living Conditions” of the system of state sanitary and epidemiological regulation, a significant number of normative and methodological documents have been approved aimed at assessing the impact of chemical, physical and biological environmental factors on population health, while not a single document has been developed concerning “social factors of habitat” or “living conditions”. In the “Strategy for the Development of the Arctic Zone of the Russian Federation (AZRF) until 2035” , the “main dangers, challenges and threats that form risks for development of AZRF” include clear signs of deterioration in medico-demographic situation, where, along with migration outflow, reduction of population number, high mortality rate, “lag behind all-Russian values of indicators characterizing quality of life”, poor state of social, housing, communal, transport infrastructure were noted.
 OBJECTIVES:development of the concept of “living conditions” as a set of “social factors of habitat” formed by “social infrastructure” of a settlement; development of conceptual model of determinants of human health, indicating place of living conditions (social infrastructure) in the frame of habitat; scientific substantiation of concept of “harmful effects of social factors of habitat”; development of targeted approach to assessing the impact of living conditions on medico-demographic status of rural areas of AZRF using scoring system for assessing living conditions, which makes it possible to rank individual villages according to the value of infrastructure indices and the integral index of living conditions (IILC).
 PRACTICAL SIGNIFICANCE:Implementation in practice of the proposed targeted methodological approach will make it possible to scientifically substantiate the need to take differentiated measures (managerial decisions) in relation to the identified “risk territorie”, “risk group”, and “risk pathologies”, aimed at improving living conditions, preserving public health, ensuring sanitary-epidemiological well-being, reducing the intensity of negative trends in demographic processes in the regions of AZRF.

Physical and geographical correlates of deviant behavior

AIM: To study the potential role of physical environmental factors in the development of deviant behavior in population groups residing in different territories.
 MATERIAL AND METHODS: At the initial phase of the study, we identified the key physical and geographical factors of the environment and assessed the indicators of social and criminal tension in 14 regions of Russia. In total, 1815 male and female students, aged 18–28 years, who were native residents of the selected regions, participated in the field research. During the field stage, the psychological state of the participants was assessed using the Freiburg multifactorial personality questionnaire. This assessment included evaluating character accentuations, suggestibility, frustration, irritability, adventurousness, as well as social activity and destructiveness. Additionally, the participants’ «prosociality-asociality» and type of behavioral activity (A–B) were examined. The subjects’ experience with psychoactive substances was self-reported. Associations between the variables were studied by correlation analysis.
 RESULTS: The average annual temperature was inversely associated with crime rates (p=0.012), number of abortions (p=0.0001), degree of alcoholization (p=0.004), and the proportion of smokers (p=0.011) in the population. Positive correlations were observed between annual temperature, and the level of narcotic substances consumption (p=0.05 and p=0.23 for men and women, respectively), spontaneous aggressiveness (p=0.63 and p=0.024), frustration (p=0.63 and p=0.024), irritability (p=0.068 and p=0.004), asociality (p=0.004 and p=0.247). Lower temperatures were associated with, greater single dose of alcohol (p=0.086 and p=0.033 in men and women, respectively), suggestibility (p=0.189 and p=0.049), emotivity (p=0.21 and p=0.05). The comfort of the environment was inversely associated with suicide rates (p=0.039). In men, comfort was positively associated with consumption of narcotic substances (p=0.05), reactive aggressiveness (p=0.024), irritability (p=0.041), asociality (p=0.011), adventurism (p=0.001), and severity of cardiotype A (p=0.018) while political activity correlated inversely with comfort (p=0.035).
 CONCLUSION: Our findings suggest that physical and geographical factors correlate with social, psychological and behavioral deviations among Russian students.

Context-aware environment online monitoring for safety autonomous vehicle systems: an automata-theoretic approach

Intelligent Transport System (ITS) is a typical class of Cyber-Physical Systems (CPS), and due to the special characteristics of such systems, higher requirements are placed on system security. Runtime verification is a lightweight verification technique which is used to improve the security of such systems. However, current runtime verification methods often ignore the effects of the physical environment (e.g., the effects of rain, snow, and other weather changes on road conditions), which results in the inability of the monitor to effectively monitor the system according to the changes in the environment. To address this problem, this paper proposes a method for constructing a runtime monitor with environmental context-awareness capability. First, the physical environment factors affecting the system are formally described and constructed into an environment model, then the system statute is transformed into a Büchi automaton, and then a synthesis algorithm combining the environment model and the Büchi automaton is designed based on the network of automatons, and the corresponding monitor is generated. Finally, the proposed method is applied and verified on simulation and real objects. The experimental results show that the monitors generated based on the method of this paper can effectively monitor unsafe events in different environments, thus improving the safety of intelligent driving systems.

Monitoring the electrical potential difference of pine tree

The subject of the study is the time series of the difference in electrical potentials along the trunk of a pine tree and the time series of meteorological and geomagnetic parameters consistent with them, measured by hardware and software complexes of the geophysical observatory "Petrozavodsk" and the Botanical Garden of Petrozavodsk State University in 2017-2022, as well as the time series of the K-index database global geomagnetic activity. The existence of characteristic regimes in the difference in electrical potentials of pine trees is shown, depending on the season, temperature, precipitation, humidity, determined by physical environmental factors and physiological processes in the tree. The reaction of the electrical potential difference of pine trees to meteorological parameters, thunderstorms, and space weather phenomena: magnetic storms and solar eclipses is analyzed. The results of these observations are qualitatively interpreted using known features of electric field of the Earth.