Multiple Correspondence Analysis Research Articles

The impact of corporate governance and corporate social responsibility on SA REITs’ performance

ABSTRACT Corporate governance (CG) is one of the most sought after areas of research globally. This paper employs a corporate governance index (CGI) formulated from the KING III and IV reports to examine the link between corporate performance and the quality of CG and corporate social responsibility (CSR) of SA REITs listed on the Johannesburg Stock Exchange (JSE). The CGI index is created from King III and IV to measure the compliance of 33 SA REITs listed on the JSE as of January 2023. These REITs are assessed from 2013. The empirical investigation using multiple correspondence analysis (MCA) reveals that CG practices have a positive influence on firm performances measured by TSR (such as total share return). The results imply that CG’s standard principles influences the firm performance of SA REITs with a higher magnitude. The CSR index is created from the King reports, and the MCA was also used. This indicates that an SA REIT that complies with CSR regulations will improve returns.

Utilization of maternal health facilities and rural women’s well-being: towards the attainment of sustainable development goals

BackgroundThe sustenance of any household is tied to the well-being of the mother's health before, during, and after pregnancy. Maternal health care has continued a downward slope, increasing maternal mortality in rural communities in Nigeria. Presently, few empirical findings connect maternal healthcare facilities' use to mothers' well-being in Nigeria. Using maternal health facilities and the well-being of rural women is crucial in achieving the United Nations’ Sustainable Development Goals 1, 2, and 3 (No poverty, zero hunger, good health, and well-being).ObjectiveThe objective of the study was to examine the level of maternal healthcare utilization and its effect on mothers’ well-being status among mothers in rural Nigeria.MethodsIn this study, secondary data extracted from the Nigeria’s 2018 National Demographic Health Survey was used. Data was analyzed with Multiple correspondence analysis, Fuzzy set analysis, and Extended ordered logit model.ResultsWomen in rural Nigeria were moderate users of maternal health care services and had moderate well-being indices (0.54 ± 0.2, 0.424 ± 0.2, respectively). Mothers' moderate well-being status was increased by using maternal health care facilities, having a larger household, and having mothers who worked exclusively in agriculture.ConclusionWe concluded that mothers in rural Nigeria use maternal healthcare facilities moderately, and their well-being level was improved using maternal healthcare facilities. Therefore, Nigeria’s Ministry of Health should raise awareness about the vitality of mothers using health care services before, during, and after pregnancy. In order to promote greater female participation in full-scale agricultural production, it is imperative for the Nigerian government to allocate substantial resources in the form of subsidies and incentives. The Nigerian government should source these resources from various channels, including expanded development cooperation. Additionally, policymakers should focus on designing developmental programmes specifically tailored for rural households and the health sector.

Exploring the Relationships among HRM Investment, Strategy Implementation, and Firm Performance with Multiple Correspondence Analysis

This study visually explores the relationships among human resource management (HRM) investment, strategy implementation, and firm performance for small- and medium-sized enterprises (SMEs) in Korea. This exploratory research focuses on the significance of strategy implementation, an often overlooked factor in the relationship between HRM and firm performance, as well as HRM investment, which can enable the development of organizational capabilities. We conducted a multiple correspondence analysis to understand the interrelationship between HRM investment, competitive strategy implementation, and firm performance. We differentiated the results by group type according to the level of HRM investment, competitive strategy implementation, and firm performance. We found that firms with high HRM investment achieve the highest performance by implementing an ambidextrous strategy that simultaneously pursues cost leadership and differentiation. Ultimately, this study’s results suggest that for firms to create a competitive advantage through the strategic capitalization of human resources, long-term and continuous investment in HRM is necessary, even if short-term visible effects are not observed while the HRM system is being built, to eventually establish the organization’s capacity to support strategy execution. This study’s potential contribution is to extend the resource-based view by establishing the role of strategy implementation in linking HRM systems as organizational capabilities to performance.

Multiple Correspondence Analysis for Assessment of the Socioeconomic and Social Impact of the COVID-19 Pandemic in Gezira State, Sudan

Background COVID-19 spread in Sudan like other countries in the world. The first COVID-19 case in Sudan was confirmed on 13 March 2020. It has been shown that Sudan's economy was affected before the COVID-19 pandemic because of currency increases, high inflation, and the incapability of the authorities to propose support. Methods The study aimed to assess the economic and social influence of COVID-19 in Al Gazira State, Sudan. This study used the primary data collected from Gezira state in Sudan. A structured questionnaire was used for data collection in 2020-2021, and the sample size was 800 participants. An analysis of multiple correspondences was used to analyze the data concerning COVID-19. The study was validated by ensuring that the survey follows sound research methodologies. This includes clearly defining research questions, using appropriate data collection methods, and applying rigorous analytical techniques. Besides that, it is important to explore the impact of the socioeconomic, demographic, and geographic variables. Results The educational level distribution shows that 36.7% of urban and 26.6% of rural residents have completed secondary education. Furthermore, all participants, 100% in urban regions and 99% in rural areas, were aware of the COVID-19 epidemic. Likewise, all participants in urban areas and 99.5% in rural areas were informed about the lockdowns and measures to curb the spread of COVID-19. Concerning the decision to refrain from attending social gatherings amid COVID-19, 87.6% of participants in urban areas and 75.3% in rural regions opted to cancel such events. Similarly, 86.2% in urban areas and 73.4% in rural areas believe avoiding handshakes is necessary to mitigate the spread of COVID-19. Regarding concerns about job loss during the COVID-19 lockdown period, 52.4% of rural participants did not express anxiety about potential job loss. Conversely, 55.3% of respondents in rural areas were indeed anxious about possibly losing their jobs. The results obtained from the multiple correspondence analysis revealed a relationship between the socioeconomic and demographic variables concerning COVID-19 epidemics. Conclusion This study concluded that socioeconomic, demographic, and geographic variables have a combined influence on the COVID-19 epidemic. One potential technical contribution to the assessment of the economic and social impact of the COVID-19 pandemic could be the application of sophisticated data analysis and modeling techniques to comprehend the complex interrelationships among the numerous components impacted by the pathogen. Predictive models, machine learning, data analytics, simulation studies, and geographic analysis are a few examples of similar techniques.

The institutional logics of love: the order of passion in an intimate field

AbstractWe use Multiple Correspondence Analysis to capture the institutional logics of love and intimacy among a random sample of American university students. Comparing the theoretical assumptions of field theory and the institutional logics approach we explore whether institutional logics of intimacy exist, what kinds of practices are gathered in these logics, and whether these institutional logics are shaped by the actors’ field capitals, viz. gender and social class. Using survey data collected from a random sample of 1315 students from a large Pacific university (PU) we find that institutional logics of intimacy come in multiple forms: abstinence, loving sex and hookup sex, each characterized by its specific doings, feelings, and sayings. Our analyses further suggest that the logics of intimate practice have their own internal order, or grammar, which is only weakly conditioned by persons’ class or gender positions in the social structure. Although the perduring logics of intimacy are largely autonomous from persons’ positions in the field, the effects we do find largely echo Armstrong and Hamilton’s account of college life as a class project of young privileged women whose social networks formed through the Greek party scene (Armstrong and Hamilton in Paying for the Party. How College Maintains Inequality, Harvard University Press, Cambridge, 2013). Constellations of meaningful practice, not distributions of capitals among persons, overwhelmingly organize the pathways of practice.

Flood vulnerability assessment in rural and urban informal settlements: case study of Karonga District and Lilongwe City in Malawi

AbstractFlood vulnerability assessment (FVA) informs the disaster risk reduction and preparedness process in both rural and urban areas. However, many flood-vulnerable regions like Malawi still lack FVA supporting frameworks in all phases (pre-trans-post disaster). Partly, this is attributed to lack of the evidence-based studies to inform the processes. This study was therefore aimed at assessing households’ flood vulnerability (HFV) in rural and urban informal areas of Malawi, using case studies of Traditional Authority (T/A) Kilupula of Karonga District (KD) and Mtandire Ward in Lilongwe City (LC). A household survey was used to collect data from a sample of 545 household participants. Vulnerability was explored through a combination of underlying vulnerability factors (UVFs)-physical-social-economic-environmental and cultural with vulnerability components (VCs)-exposure-susceptibility and resilience. The UVFs and VCs were agglomerated using binomial multiple logit regression model. Variance inflation factor (VIF) was used to check the multicollinearity of variables in the regression model. HFV was determined based on the flood vulnerability index (FVI). The data were analysed using Multiple Correspondence Analysis (MCA), artificial neural network (ANN) and STATA. The results reveal a total average score of high vulnerability (0.62) and moderate vulnerability (0.52) on MCA in T/A Kilupula of Karonga District and Mtandire Ward of Lilongwe City respectively. The FVI revealed very high vulnerability on enviroexposure factors (EEFs) ($$0.9$$ 0.9 ) in LC and$$(0.8$$ ( 0.8 ) in KD, followed by ecoresilience factors (ERFs) (0.8) in KD and$$(0.6$$ ( 0.6 ) in LC and physioexposure factors (PEFs) ($$0.5)$$ 0.5 ) in LC besides 0.6 in KD for the combined UVFs and VCs. The study concludes that the determinants of households’ flood vulnerability are place settlement, low-risk knowledge, communication accessibility, lack of early warning systems, and limited access to income of household heads. The study recommends that an FVA framework should be applied to strengthen the political, legal, social, and economic responsibilities of government for building the resilience of communities and supporting planning and decision-making processes in flood risk management.

Farmers’ Adoption, Knowledge, and Perceptions of Tick Control Measures on Dairy Farms in Subtropical Areas of Continental Ecuador

The application of tick control strategies on tropical dairy cattle strongly relies on farmers’ uptake, knowledge, and perceptions of the efficacy of control measures. This study aims to identify common and uncommon tick control practices employed by dairy farmers in subtropical areas of Ecuador and associate them with the presence of infestation and acaricide resistance. Data were collected through a cross-sectional survey and participatory meetings. Multiple correspondence analysis was used to explore the association between management variables and the level of tick infestation and resistance. It was determined that the main method of acaricide control is still chemical, mainly using spray baths. Generally, when this form of application is used, acaricides are overdosed, in contrast to the pour-on method with underdosage. Among the measures farmers adopt when chemical treatment has failed is to use overdoses of products, mix different acaricides, and use focused treatments (wipe cloth) with irritant substances. The absence of a high level of infestation was related to acaricide dips every 3–4 weeks and the use of intensive grazing. On the other hand, the high infestation was related to the use of organophosphates, wipe cloth application, and the report of tick-borne diseases (TBDs). A small group of farmers have good knowledge and seek alternatives to chemical control, experimenting with biological controls, herbal extracts, manual tick removal, and paddock control. Additionally, farmers reported the presence of TBDs (47%) and the presence of animals poisoned by acaricides (6%), which died in 75% of those cases. Farmers frequently mentioned that tick infestation induces milk drop production and weight loss and is associated with the presence of TBDs. This information is crucial to improve tick control management in Ecuador, particularly through implementing practices that mitigate resistance to acaricides and ensure long-term solutions that help maintain the efficacy of tick control treatments.

Machine Learning in Allergic Contact Dermatitis: Identifying (Dis)similarities between Polysensitized and Monosensitized Patients

Background: Allergic contact dermatitis (ACD) is a delayed hypersensitivity reaction occurring in sensitized individuals due to exposure to allergens. Polysensitization, defined as positive reactions to multiple unrelated haptens, increases the risk of ACD development and affects patients’ quality of life. The aim of this study is to apply machine learning in order to analyze the association between ACD, polysensitization, individual susceptibility, and patients’ characteristics. Methods: Patch test results and demographics from 400 ACD patients (Study protocol Nr. 3765/2022), categorized as polysensitized or monosensitized, were analyzed. Classic statistical analysis and multiple correspondence analysis (MCA) were utilized to explore relationships among variables. Results: The findings revealed significant associations between patient characteristics and ACD patterns, with hand dermatitis showing the strongest correlation. MCA provided insights into the complex interplay of demographic and clinical factors influencing ACD prevalence. Conclusion: Overall, this study highlights the potential of machine learning in unveiling hidden patterns within dermatological data, paving the way for future advancements in the field.

Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students’ risk profiles

BackgroundSuicide is one of the leading causes of death among young people and university students. Research has identified numerous socio-demographic, relational, and clinical factors as potential predictors of suicide risk, and machine learning techniques have emerged as promising ways to improve risk assessment.ObjectiveThis cross-sectional observational study aimed at identifying predictors and college student profiles associated with suicide risk through a machine learning approach.MethodsA total of 3102 students were surveyed regarding potential suicide risk, socio-demographic characteristics, academic career, and physical/mental health and well-being. The classification tree technique and the multiple correspondence analysis were applied to define students’ profiles in terms of suicide risk and to detect the main predictors of such a risk.ResultsAmong the participating students, 7% showed high potential suicide risk and 3.8% had a history of suicide attempts. Psychological distress and use of alcohol/substance were prominent predictors of suicide risk contributing to define the profile of high risk of suicide: students with significant psychological distress, and with medium/high-risk use of alcohol and psychoactive substances. Conversely, low psychological distress and low-risk use of alcohol and substances, together with religious practice, represented the profile of students with low risk of suicide.ConclusionsMachine learning techniques could hold promise for assessing suicide risk in college students, potentially leading to the development of more effective prevention programs. These programs should address both risk and protective factors and be tailored to students’ needs and to the different categories of risk.

Understanding the futsal game moments through the eyes of futsal coaches: a comparison of expert and novice coaches

ABSTRACT Coaches rely on the information detected in the performance environment to regulate the quantity and quality of the decisions made during matches. This study used an expert-novice paradigm to describe coaches’ gaze behavior in offensive and defensive game moments of futsal. Twenty coaches (ten expert and ten novices) participated in the study. The experimental conditions contrasted their gaze behavior when watching 71 video clips of the game, both when the team was attacking and when the team was defending. The dependent variables for gaze behaviour were organized in game moments and described using biplots from multiple correspondence analysis. Overall, the results revealed a relationship between the coaches’ level of expertise and the visual information searched at each futsal game moment. Expert coaches focused more on the information related to the players without the ball and the space, while novice coaches tended to focus their attention in the ball and in the attacker with the ball. It seemed clear that the process of visual exploration is specific for each game moment and that the level of coaches’ expertise shapes the visual information searched.

Liver Observation Segmentation on Contrast-Enhanced MRI: SAM and MedSAM Performance in Patients With Probable or Definite Hepatocellular Carcinoma.

Purpose: To evaluate factors impacting the Segment Anything Model (SAM) and variant MedSAM performance for segmenting liver observations on contrast-enhanced (CE) magnetic resonance imaging (MRI) in high-risk patients with probable hepatocellular carcinoma (HCC) (LR-4) and definite HCC (LR-5). Methods: A retrospective cohort of liver observations (LR-4/LR-5) on CE-MRI from 97 patients at high-risk for HCC was derived (2013-2018). Using bounding-boxes as prompts under 5-fold cross-validation, segmentation performance was evaluated at the model and liver observation-levels for: (1) model types: SAM versus MedSAM, (2) image sizes: 256 × 256 versus 512 × 512, (3) image channel composition: CE sequences at 3 phases of enhancement independently and combined, (4) liver observation size: >10 mm versus >20 mm, (5) certainty of diagnosis: LR-4 versus LR-5, and (6) contrast-agent type: hepatobiliary versus extracellular. Segmentation performance, quantified using Dice coefficient, were compared using univariate (Wilcoxon signed-rank and t-test) and multivariable analyses (multiple correspondence analysis and subsequent linear modelling). Results: MedSAM trained on 512 × 512 combined CE sequences performed best with mean Dice coefficient 0.68 (95% confidence interval 0.66, 0.69). Overall, all factors except contrast-agent type affected performance, with larger image size resulting in the highest performance improvement (512 × 512: 0.57, 256 × 256: 0.26, P < .001) at the model-level. Contrast-agents affected performance for patients with LR-4 observations using MedSAM-based models (P < .03). Larger observation size, image size, and higher certainty of diagnosis were associated with better segmentation on multivariable analysis. Conclusion: A variety of factors were found to impact SAM/MedSAM performance for segmenting liver observations in patients with probable and definite HCC on CE-MRI. Future models may be optimized by accounting for these factors.

Which support is provided in which country? Patterns among older adults in Europe

This paper proposes comparative research on support provided outside the household by older adults in Europe. In studying social support, the network perspective is widely used, investigating, in particular, the ego-centered support networks of individuals. The analysis is based on data from Wave 7 of the Survey of Health Ageing and Retirement in Europe (SHARE). It examines the characteristics of ego-support networks of individuals aged 65 and over in 12 European countries, which are grouped into a novel welfare regime typology. Through Multiple Correspondence Analysis, we jointly looked into the categorical variables describing the recipients (alters) of the support provided by older adults and the welfare regime classification. As a main result, countries grouped in “High degree of familialism by default” category specialized in supporting family-related alters, particularly with childcare or personal care. In contrast, the elders in countries belonging to “High degree of de-familialisation” typology provided a more varied but less demanding support, to non-relatives alters and less oriented to care. The analyses show that the SHARE provides a solid opportunity to face the topic.

Ancestry of the major long-range regulatory site of the α-globin genes in the Portuguese population with the common 3.7 kb α-thalassemia deletion

BackgroundThe α-Major Regulatory Element (α-MRE), also known as HS-40, is located upstream of the α-globin gene cluster and has a crucial role in the long-range regulation of the α-globin gene expression. This enhancer is polymorphic and several haplotypes were identified in different populations, with haplotype D almost exclusively found in African populations. The purpose of this research was to identify the HS-40 haplotype associated with the 3.7 kb α-thalassemia deletion (-α3.7del) in the Portuguese population, and determine its ancestry and influence on patients’ hematological phenotype.Methods and resultsWe selected 111 Portuguese individuals previously analyzed by Gap-PCR to detect the presence of the -α3.7del: 50 without the -α3.7del, 34 heterozygous and 27 homozygous for the -α3.7del. The HS-40 region was amplified by PCR followed by Sanger sequencing. Four HS-40 haplotypes were found (A to D). The distribution of HS-40 haplotypes and genotypes are significantly different between individuals with and without the -α3.7del, being haplotype D and genotype AD the most prevalent in patients with this deletion in homozygosity. Furthermore, multiple correspondence analysis revealed that individuals without the -α3.7del are grouped with other European populations, while samples with the -α3.7del are separated from these and found more closely related to the African population.ConclusionThis study revealed for the first time an association of the HS-40 haplotype D with the -α3.7del in the Portuguese population, and its likely African ancestry. These results may have clinical importance as in vitro analysis of haplotype D showed a decrease in its enhancer activity on α-globin gene.

Comparison between classification algorithms using a multiple correspondence analysis with python.

To analyse the data of a survey questionnaire we apply multiple correspondence analysis “MCA” as a method to help us convert data into a scatter plot, but it is difficult to study it and get good results, so we need to make a classification to facilitate the study. Among the most usable classification methods, hierarchical ascending classification and k-means. To compare them, we conducted a questionnaire on distance studies during the Corona crisis, which included the opinions of 304 university professors from most universities in Algeria; in our application, we used the Python programming language.

Clinical Manifestations of Dengue in Children and Adults in a Hyperendemic Region of Colombia.

Dengue is the most common arboviral disease in the world. Traditionally, it has affected more adults, but the incidence in children has increased in recent years. Colombia is no stranger to this change; therefore, we aimed to find the differences in signs, symptoms, and clinical, hematological, and hemogram characteristics between children under 12 years old and individuals aged 12 years and older in an endemic region of Colombia in 2020-2022. The analyses were conducted with baseline data, corresponding to a cross-sectional design. Multiple correspondence analysis was used for general, dermatological, and clinical symptom profiles. Discriminant analysis was used for laboratory profiles. Multiple correspondence analysis was applied to nominal categorical data, employing Euclidean distances to analyze age groups. Discriminant analysis was applied to a training sample and validated on a test sample. The overall agreement of the model's discrimination, sensitivity, specificity, and fit indicators was calculated. The results indicated that individuals under 12 years exhibited distinct dermatological and clinical features, including rash, pruritus, hypotension, lymphocyte count, and platelet count, compared with those aged 12 years and older. In contrast, those 12 years and older were profiled for general and clinical symptoms such as pain (back pain, retro-orbital pain, headache), dizziness, chills, hematuria, tachypnea, and elevated/high hematocrit, hemoglobin, and basophil values. These findings are crucial to understanding the high incidence in children; they also facilitate rapid understanding of the disease in clinical care settings and differentiate it from other febrile outbreaks. This will affect disease control, particularly in severe cases, and reduce mortality.

Clinical Profile of Patients with Primary Sjögren's Syndrome with Non-Identified Antinuclear Autoantibodies.

Objectives-The aim of the present study was to characterize the clinical phenotype of patients with primary Sjögren's syndrome (pSS) with non-identified antinuclear antibodies (ANA) in comparison with that of patients with pSS with negative ANA, positive typical ANA (anti-Ro/SSA and/or La/SSB) and positive atypical ANA. Methods-We conducted an observational, retrospective monocentric study at the Erasme University Hospital (Brussels, Belgium). Two hundred and thirty-three patients fulfilling the 2002 American-European Consensus Group criteria for pSS were included in this study. The patients were subdivided according to their ANA profile and demographics. The clinical and biological data of each subgroup were compared. Moreover, the relationships between these data and the ANA profiles were determined by multiple correspondence analysis. Results-In our cohort, 42 patients (18%) presented a non-identified ANA-positive profile. No statistically significant difference could be observed between non-identified ANA patients and ANA-negative patients in terms of age and/or ESSDAI score at diagnosis. There were significantly more frequent articular manifestations, positive rheumatoid factor (RF), and the use of corticosteroids in anti-Ro/SSA-positive patients compared to ANA-negative (p ≤ 0.0001) and non-identified ANA-positive patients (p ≤ 0.01). However, a significantly higher proportion of RF positivity and corticosteroid treatment was observed in non-identified ANA-positive patients compared to ANA-negative patients (p < 0.05). Conclusions-For the first time to our knowledge, our study has characterized the clinical phenotype of patients with pSS with non-identified ANA at diagnosis. The non-identified ANA-positive patients featured mostly a clinical phenotype similar to that of the ANA-negative patients. On the other hand, the non-identified ANA-positive patients were mainly distinguished from the ANA-negative patients by a greater proportion of RF positivity and the need for corticosteroid use due to articular involvement.

How Professional and Market Logics and the Conflict between Institutional Demands Affect Hospital Accreditation Compliance: A Multiple-Case Study in Brazil.

Hospital accreditation has become ubiquitous in developing countries. While research acknowledges that accreditation can enhance healthcare quality, efficiency, and safety, concerns persist regarding hospitals' management of conflicts stemming from the diverse institutional logic inherent in this process. Therefore, this study aimed to investigate how professional and market logic, alongside conflicts arising from institutional demands, affect compliance with hospital accreditation. To this end, we conducted a multiple-case study in four Brazilian hospitals employing in-depth interviews and on-site observations. The triangulation of narrative analysis and the outcomes of multiple correspondence analysis revealed that when professional logic predominates, there is a greater propensity to tailor accredited activities by segmenting the tasks between physicians and nurses with the intention of mitigating existing conflicts. Conversely, when conflicts occur over established goals between professionals and orientated marked logic executives, the accreditation process is impeded, resulting in non-compliance. Ultimately, the findings underscore the alignment between the pursuit of legitimacy and efficiency within the accreditation process. We conclude by delineating the theoretical and practical implications of scrutinizing the internal dynamics of institutional logic.

Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates

The current work aims to analyze the main themes related to artificial intelligence (AI) and sustainable development during the pandemic period. This study provides an overview of the specialized literature related to AI and sustainability from the beginning of the pandemic through 2023. The present paper analyses scientific literature emphasizing both artificial intelligence's positive and negative impacts on sustainable development objectives (SDGs). To conduct the research, we employed bibliometric analysis and text-mining techniques to identify the major themes in the literature indexed in the Web of Science and Scopus databases. Firstly, we used descriptive measures to identify the authors' impact, the article production by country, the main keywords used, and other descriptive data. We further used data reduction methods based on co-word analysis (such as multiple correspondence analysis) on authors' keywords to show patterns in the themes explored in the literature. Bibliometric analysis was supplemented by text mining using Latent Dirichlet allocation (LDA) and structural topic modeling on abstracts to provide a comprehensive view of scientific debates on AI and sustainable development. Our research has identified various themes in the literature related to AI and sustainable development. These themes include social sustainability, health-related issues, AI technologies for energy efficiency, sustainability in industry and innovation, IoT technologies for smart and sustainable cities, urban planning, technologies for education and knowledge production, and the impact of technologies on SDGs. We also found that there is a significant positivity bias in the literature when discussing the impact of AI on sustainable development. Despite acknowledging certain risks, the literature tends to focus on the potential benefits of AI across various sectors. In addition, the analysis shows a growing emphasis on energy efficiency, which is facilitated by the use of AI technologies. Our study contributes to a better understanding of current scholarly discussion trends and emerging scientific avenues regarding AI and sustainable development. It also highlights the areas where research is needed and the implications for practitioners and policymakers.

POLICE’S PSYCHO-SOCIAL PROFILE IN COLOMBIAN ACTUAL SCENES: A PERSPECTIVE FROM THE CITIZENRY/POPULATION. CASE: JURISDICTION OF PUENTE ARANDA, BOGOTÁ

Objective: The objective of this article is to analyze the Psychosocial Profile (PP) of police officers from a citizen perspective. Theoretical Framework: The PP is a tool to reveal the service that is provided daily according to effective, respectful, adaptable, communicative and assertive actions, continuous learning and leadership, among other causal competencies, which ratify an effective service that responds to the institutional mission. Method: The esearch is qualitative and quantitative, exploratory and descriptive, structured with a phenomenological design, which is based on the identification of characteristics of the PP, based on six competencies: personal, interpersonal, cognitive, institutional, community and physical. To obtain the information for the research, a population focus conformed of the inhabitants of the Town of Puente Aranda and a random sample of 384 people, was studied and interviewed. Results and Discussion: The characteristics of the PP constitute the concordance between direct and linear associations according to the categories: psychosocial profile, commitment, vocation, behavioral criteria and the profile of the leadership of the police service in relation to the citizen and the fulfillment of the institutional mission. Research Implications: This is evidenced according to the multiple correspondence analyses between the singular competencies and the community’s socio-demographic variables according to the provision of the police service. Originality/Value: The importance of optimizing the psychosocial profile of the police officer is established based on their contextualized and active social interaction, taking into account personal, interpersonal, cognitive, physical, institutional, leadership and teamwork skills to fulfill their service mission. to the citizens.

Understanding microplastic presence in different wastewater treatment processes: Removal efficiency and source identification

Municipal effluents discharged from wastewater treatment plants (WWTPs) are a considerable source of microplastics in the environment. The dynamic profiles of microplastics in treatment units in WWTPs with different treatment processes remain unclear. This study quantitatively analyzed microplastics in wastewater samples collected from different treatment units in two tertiary treatment plants with distinct processes. The influents contained an average of 15.5 ± 3.5 particles/L and 38.5 ± 2.5 particles/L in the two WWTPs with in the oxidation ditch process and the integrated fixed-film activated sludge process, respectively. Interestingly, microplastic concentrations in the influent were more influenced by the population density in the served area than sewage volume or served population equivalent. Throughout the treatment process, concentrations were reduced to 1.5 ± 0.5 particles/L and 1.0 ± 1.0 particles/L in the final effluents, representing an overall decrease of 90% and 97%, in WWTPs with the oxidation ditch process and integrated fixed-film activated sludge process, respectively. A significant proportion of the microplastics were removed during the primary treatment stage in both WWTPs, with better performance for foam, film, line-shaped and large-sized microplastics. Most microplastics were accumulated in activated sludge, indicating its key role as the primary sink in WWTPs. The multiple correspondence analysis identified laundry washing and daily necessities such as packaging and containers as the major contributors to microplastics in WWTPs. The study proposed recommendations for upgrading WWTPs, modifying designs, and implementing strategies to reduce microplastic sources, aiming to minimize the release of microplastics into the environment. These findings can shed lights on the sources of microplastics in WWTPs, and advance our understanding of the mechanisms for more effective microplastic removals in wastewater treatment technologies in future applications.