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Abstract   Intermediate quantifiers are expressions of natural language, for example “most, almost all, many, a few” using which we quantify a number of some objects in a given univer…

Abstract   Intermediate quantifiers are expressions of natural language, for example “most, almost all, many, a few” using which we quantify a number of some objects in a given universe. We have shown in [23] that all valid syllogisms with intermediate  quantifiers are a consequence of only two algebraic inequalities and one equality. The result was obtained in the formalism  of Lukasiewicz fuzzy type theory whose truth values form a linearly ordered complete MV-algebra. In this paper we will  prove that the same holds if we replace MV-algebra by a much more general IEQ-algebra (involutive EQ-algebra).   

Abstract Purpose Life satisfaction (LS) is increasingly recognized as a crucial indicator and predictor of health and well-being across the lifespan. The impact of LS may be enhanced through physical…

Abstract Purpose Life satisfaction (LS) is increasingly recognized as a crucial indicator and predictor of health and well-being across the lifespan. The impact of LS may be enhanced through physical activity (PA), although studies exploring the dynamic and bidirectional nature of the relationship are scarce. One principal goal of this project is to examine the dynamic, personalized interactions between LS and PA and exercise identity (the degree to which exercise is a fundamental aspect of one’s self-concept) in geographic areas with different air pollution loads. Method We used data from a 12-month prospective cohort study (N =1314, mean age =38.09 [12.55]; range 18-65) with four 2-week intensive measurement bursts to evaluate the bidirectional relationship between LS (assessed at the end of the day) and PA (assessed by Fitbit Charge 3 or 4 throughout the day). The sample included both active (runners; n =747, 57%) and inactive (n =567, 43%) individuals living in Moravia-Silesia and South Bohemia, geographic areas with different levels of air pollution. A dynamic Bayesian model based on an extension of the vector autoregressive model was used to estimate both lagged and contemporaneous associations between LS and PA. Results There were meaningful autoregressive effects of first order for both LS (β = 0.394) and PA (β = 0.316), and a within-person contemporaneous association between LS and PA (β = 0.087) that was also associated with temporal factors and trends (weekly and monthly seasonal variation, day in study), gender, age, and exercise identity. Conclusion This study highlights the importance of periodicity on 2 temporal scales for both PA and LS, with age and gender also playing crucial roles. The findings underscore the importance of tailored, context-aware interventions to sustain engagement and enhance well-being through PA.    

Current research evaluating the consequences of stigma towards people with mental illness is not nuanced in emphasizing the critical distinction between stigma as negative attitudes and discrimination…

Current research evaluating the consequences of stigma towards people with mental illness is not nuanced in emphasizing the critical distinction between stigma as negative attitudes and discrimination as harmful behaviours that limit access to services, employment, and social inclusion. Understanding these distinctions is essential for designing targeted, evidence-based universal, targeted and indicated interventions to improve the quality of life and well-being. This review evaluates the evidence on the consequences of stigma towards people with mental illness. Using PRISMA guidelines, we analysed 448 studies (294 quantitative, 154 qualitative) investigating stigma's negative outcomes. Findings were categorized into health, service use, psychosocial, economic, and structural impacts. Although stigma is consistently associated with adverse outcomes across life domains, evidence of a causal link between negative attitudes and poorer outcomes for individuals with mental disorders remains limited. Furthermore, there is a striking scarcity of research from low- and middle-income countries, with significant regional gaps, and studies addressing structural stigma embedded in societal institutions are particularly rare. Efforts to combat stigma must distinguish between attitudes and behaviours, focusing on reducing discrimination while enhancing public mental health literacy and access to effective interventions. Tackling these challenges requires a comprehensive, evidence-informed approach to improving mental health outcomes for all.

The post-communist WHO European region, often called Central and Eastern Europe (CEE), includes 28 countries with over 770 million people. Mental health systems remain shaped by the communist legacy o…

The post-communist WHO European region, often called Central and Eastern Europe (CEE), includes 28 countries with over 770 million people. Mental health systems remain shaped by the communist legacy of centralized institutions, a narrow biomedical focus, and neglect of social and psychological dimensions. Chronic underfunding persists, further strained by shrinking civic space in some countries and the war in Ukraine. Substantial progress has been made in the past decade, with modernization and rights-based approaches gaining ground. Yet reforms face entrenched barriers: underinvestment disproportionate to the burden; pervasive stigma, weak advocacy, and limited involvement of people with lived experience; dominance of institutional care over prevention, promotion, and community services; reliance on donor-driven projects that falter once funding ends; and human resource problems. Governance is often unstable, with low prioritization, clientelism, and personal biases undermining reforms. Research and data remain scarce, leaving systems unevaluated and vulnerable to reversal. Poor decision-making compounds these barriers: systemic missteps, driven by limited expertise, weak evidence, and personal biases, prevent resources from achieving the best possible outcomes. To move forward, CEE must integrate health, social, and education systems, secure sustainable crisis services, strengthen professional skills, involve people with lived experience, expand public mental health expertise, and, above all, commit greater and more transparent investment, closer to western European levels, if resilient and effective systems are to be built.

Abstract This study examines the stressor-response process in physical activity among 226 participants across four countries. We analyzed their step count collected via activity monitors before and a…

Abstract This study examines the stressor-response process in physical activity among 226 participants across four countries. We analyzed their step count collected via activity monitors before and after a significant stressor: the COVID-19 lockdown. Results showed that a ‘local dynamic complexity’ metric significantly predicts the rate of recovery to pre-COVID levels of physical activity. These findings provide new opportunities for just-in-time interventions to support physical activity recovery after disruptive stressors. Data availability The data used in the analysis are available at https://osf.io/gsmhk/. Code availability The R scripts used for the analysis are available at https://osf.io/gsmhk/.

Annotation This methodical material provides a comprehensive framework for the computation and interpretation of walking and running spatiotemporal parameters derived from consumer-grade wea…

Annotation This methodical material provides a comprehensive framework for the computation and interpretation of walking and running spatiotemporal parameters derived from consumer-grade wearable technology data (Fitbit Charge 3,4 wristbands) supplemented by the walking and running biomechanical data from the 4HAIE study. The document outlines a methodological approach for sequencing, analysis, and computation of combined data from inertial and optical sensors, focusing on extracting running/walking metrics such as stride length, covered distance, and pace. Particular attention is paid to algorithmic preprocessing, noise filtering, signal segmentation, and validation strategies relative to gold-standard biomechanical and Global Position System data.

Abstract Background: Dyslipidemia and distorted fatty acid (FA) metabolism are frequent biochemical abnormalities associated with anorexia nervosa (AN). Gut microbiota is supposed to play an important…

Abstract Background: Dyslipidemia and distorted fatty acid (FA) metabolism are frequent biochemical abnormalities associated with anorexia nervosa (AN). Gut microbiota is supposed to play an important role in the etiopathogenesis of AN. Apart from the digestive function of bile acids (BAs), these compounds have multiple metabolic functions due to the activation of specific receptors. Objective/aims: The aims of the study were to investigate biochemical measures, including plasma lipids (lipoproteins, respectively), fatty acid (FA) patterns, and the profile of plasma Bas, in AN patients and healthy controls (CON). Methods: Plasma phospholipid FA and BAs profiles were analyzed in 39 women with a restrictive type of AN (AN-R; median age 17 years) and in 35 CON women (median age 20 years). Results: Compared to CON, AN had an increased concentration of HDL-C, increased content of palmitic acid, and decreased proportion of linoleic acid. Moreover, AN had a drop in the level of the sum of PUFAn-6 and increased delta 9 desaturase activity for stearic acid. In AN, we found decreased levels of plasma tauroursodeoxycholic acid (TUDCA). In AN, concentrations of 22:5n-6, 16:0, 20:3n-6 and fat mass index were predic-tors of HDL-C levels (R2 = 0.43). Conclusions: Patients with AN-R had an increased concentration of HDL-C, decreased levels of total PUFA n-6, and increased activity of D9D for stearic acid. Furthermore, AN exerted decreased levels of TUDCA. Therefore, a decreased level of TUDCA could potentially serve as a marker of AN.

Generalizovaná úzkostná porucha (GAD) se vyznačuje chronickými a nadměrnými obavami v různých aspektech každodenního života, včetně osobních a p…

Generalizovaná úzkostná porucha (GAD) se vyznačuje chronickými a nadměrnými obavami v různých aspektech každodenního života, včetně osobních a pracovních povinností, zdraví či mezilidských vztahů. Diagnostická kritéria procházejí mírnou úpravou při přechodu Mezinárodní klasifikace nemocí z verze 10 (MKN-10) na novou verzi, MKN-11. V našem článku se podíváme na změny v nové klasifikaci nemocí, která by se měla stát diagnostickým vodítkem v nadcházejících letech. Cílem tohoto článku je podrobněji prozkoumat charakteristiky generalizované úzkostné poruchy, její diagnostické výzvy a aktuální postupy v léčbě, včetně nejmodernějších přístupů. Léčba GAD obvykle zahrnuje farmakoterapii, psychoterapii nebo jejich kombinaci. Častými komplikacemi úspěšné léčby jsou vedlejší účinky léků nebo nedostatečná odpověď na léčbu až rezistence. Nadějí pro pacienty může být využití moderních technologií v léčbě generalizované úzkostné poruchy, jakými je například virtuální realita, kterou využíváme v našem centru Výzkumu virtuální reality v duševním zdraví a neurovědách v Národním ústavu duševního zdraví při léčbě úzkostných poruch, a to včetně GAD.   Generalized Anxiety Disorder (GAD) is characterized by chronic and excessive worries across various aspects of daily life, including personal and work-related responsibilities, health, and interpersonal relationships. The diagnostic criteria undergo a slight modification with the transition from the 10th edition of the International classification of diseases (ICD-10) to the new version, ICD-11. This article examines the changes in the new classification, which is expected to become the diagnostic guideline in the coming years. The aim of this article is to explore in detail the characteristics of generalized anxiety disorder, its diagnostic challenges, and current treatment approaches, including the most modern techniques. GAD treatment typically involves pharmacotherapy, psychotherapy, or a combination of both. Common complications in the successful treatment of GAD include side effects of medications or insufficient response to treatment, including resistance. A promising approach for patients may be the use of modern technologies in the treatment of generalized anxiety disorder, such as virtual reality used at our Virtual reality research center for mental health and neurosciences at the National institute of mental health in the treatment of anxiety disorders, including GAD.

Abstract Aristotle's Square also known as Square of Opposition, is a mathematical diagram dating back to Greek philosophy and exhibiting the connection between four logical propositions in a…

Abstract Aristotle's Square also known as Square of Opposition, is a mathematical diagram dating back to Greek philosophy and exhibiting the connection between four logical propositions in a simple graphical form. Fuzzy Relational Concept Analysis (FRCA) is a technique for extracting special clusters called fuzzy concepts from a Fuzzy Relational Context Family (FRCF), which is a dataset organized as multiple fuzzy object-attribute and object-object relations. The primary FRCA tools to obtain information from data are special fuzzy quantifiers viewed as interpretations in a model of formulas of the formal theory of the intermediate generalized quantifiers. This work focuses on the issue of generating a collection of fuzzy concepts from a certain FRCF, by choosing one of four particular FRCA quantifiers: the positive universal quantifier 𝒮1, the negative universal quantifier 𝒮−1, the positive existential quantifier 𝒮∃, and the negative existential quantifier 𝒮−∃. Certainly, the selection of the quantifier is crucial in the FRCA procedure since it affects the final concept classification: diverse fuzzy concepts arise from varying quantifiers. As the initial objective, this article introduces the logical relations involving 𝒮1,𝒮−1, 𝒮∃, and 𝒮−∃, in order to arrange them in a graded version of the Aristotelian square. The second goal of this study is to examine the connections among fuzzy concepts produced by distinct quantifiers in {𝒮1,𝒮−1,𝒮∃,𝒮−∃}. Therefore, our findings provide a twofold contribution to the advancement of Aristotle's square. Indeed, they reveal a novel interpretation of the square of opposition within the framework of Fuzzy Relational Concept Analysis, emphasizing its potential as a valuable tool for the analysis of data.