Ukrainian Catholic University

On 24 February 2022, Russia began a full-scale invasion of Ukraine. The war has dramatically impacted every area of life in Ukraine, including education. In this paper, we curate a uniquely comprehensive dataset of standardized exam outcomes used for admissions to higher education institutions in Ukraine—analogous to the Standardized Aptitude Test (SAT) in the United States—to provide strong estimates of student displacement and the first analysis of student drop-off, or decline of participation in the Ukrainian education system, following the Russian full-scale invasion. We conducted descriptive statistical analysis, which included computing and comparing means across groups of students, conditioned on geographic location, migration pattern, and demographics, coupled with data visualization. We found that, among the graduating Ukrainian high school students in 2022, approximately 36,500 (16%) were displaced, with 64% of them moving abroad, primarily to Poland, Germany, and Czechia. Most displaced students originated from the front-line war regions, and either moved abroad or migrated towards the central and western parts of Ukraine. Further, we found a 21% decline in graduating high school students taking the standardized higher education entrance exam in 2022, as compared to 2021. This drop-off from the common educational pathway consists of approximately 41,500 students. With these findings taken together, we estimate that at least 78,000—a staggering 34%—of high school seniors have been directly impacted by the Russian invasion of Ukraine. We also study the impacts on subgroups and at the intersection of socio-economic status (as measured by urban vs. rural location) and gender, and find that intersectionality exacerbates the impacts, with men from rural areas being particularly adversely impacted. We conclude this article by reflecting on several policies pursued by the Ukrainian government and its institutions, aimed at minimizing disruptions to the school year and retaining students. Our analysis has important implications for governmental organizations like the Ukrainian government and the European Union, and human rights organizations like the UN Refugee Agency and the International Organization for Migration who wish to understand the impact of the Russian invasion on the education system in Ukraine.

This study investigates the dynamic pathways of organisational resilience among Ukrainian firms operating in a war economy. Our research highlights the profound impact of armed conflicts on commerce, emphasising the need for businesses to develop resilience strategies to mitigate risks and maintain operations. Through an examination of organisational data representing the 2‐year period following Russia's full‐scale invasion of Ukraine, our findings support the presence of two resilience pathways previously described in the extant literature, ‘bounce‐back’ and ‘bounce‐beyond’ and expose two new pathways which we have labelled ‘bounce‐less’ and ‘bounce‐boom.’ Our findings reveal the complex and varying paths of organisational resilience resulting from changes in market demand and resource availability, underscoring the importance of organisational adaptability, resourcefulness and innovation. We also propose a broader definition of resilience than is currently found in the literature – one which recognises the challenges of achieving a baseline of organisational survival in a time of crisis. The article concludes with practical implications and recommendations for future research on resilience in wartime conditions.

We consider algebraic bases of symmetric and supersymmetric polynomials on Banach spaces ℓp and their applications to canonical partition functions in statistical quantum physics. The main results give representations of a given divergent grand canonical partition function as products of an analytic function and an unbounded function with respect to a parameter. Such a representation can be useful for investigations of the behavior of the grand canonical partition function and numerical computations.

Marketing—when administered responsibly, inclusively, justly, and systemically over place and time—holds extraordinary promise to unlock humanity's potential for a better world, capable of pulling millions of people from poverty, protecting our environment, and creating and sustaining peace, prosperity and well-being. This Macro Ethos is illuminated in an article shared by Macromarketing scholars with interests in scholarly contributions, which impact in ways that enhance the well-being of people, societies and the fragile biosphere we inhabit, on a large scale. Key foci include happiness and its measures; bridging divides via training for collaboration, critical thinking, and a sustainable future; marketing during wartime, with insights from Ukraine and implications for resilience, adaptation and peaceful prosperity; public marketing, Macromarketing, activism and constructive engagement; and developing more responsible, harmonic, and supportive societies in Brazil and beyond. The authors conclude with some discussion, including opportunities for further collaboration and impactful research.

This study examined changes in public knowledge, behaviours and attitudes towards individuals with mental health disorders in Ukraine. A nationwide survey was used to gather data from Ukrainian adults; this data was then compared with data gathered by Quirke et al. (2021, Cambridge Prisms Global Mental Health, 8) to form a comparison study. In congruence with the original study, the Mental Health Knowledge Schedule, the Community Attitudes towards Mental Illness Scale and the Reported Intended Behaviour scales were used. Measures of knowledge and attitudes towards individuals with mental disorders reflected a small reduction of knowledge (r = 0.13, p < .001) and a large reduction in benevolent attitudes (r = 0.96, p < .001). Conversely, there was a large decrease in authoritarian attitudes (r = −0.50, p < .001). Measures of behaviour reflected a medium positive increase in past and present behaviour (r = 0.33, p < .001) and a small positive increase in intended future behaviour towards individuals with mental illness (r = 0.24, p < .001). These findings provide a snapshot of changes in stigma towards those with mental health disorders in Ukraine and highlighted the growing need for evidence-based anti-stigma interventions and the monitoring of their impact.

Look within. Look around. Reflect upon your connections with others who shape, and share, the spaces and places of your lived experience. For so many of us, when we look deeply and openly into our academic environments, we see and feel disconnection. In this provocation essay, we vulnerably share about our own disconnected experiences as we simultaneously invite others to critically reflect upon the conscious and unconscious ways in which we reinforce the ‘normalization of disconnection’ in our lives. Our hope is to inspire radical and intentional shifts into spaces and places within which we stand together, as a community grounded in care and solidarity, dropping stones of hope to create ripple effects of (re)connection and repair.

Background: The Continuous Traumatic Stress Response scale (CTSR) was designed to measure symptoms associated with multiple ongoing security threats in the context of Israeli-Palestinian conflict. Since 2014, Ukraine has faced armed invasion and war, with nationwide insecurity since February 2022. Objective: This study aimed to adapt the CTSR scale into Ukrainian and evaluate its psychometric properties within a Ukrainian sample during the ongoing war. Method: The Ukrainian adaptation of the CTSR followed the procedure used in creating the original instrument (Goral, A., Feder-Bubis, P., Lahad, M., Galea, S., O'Rourke, N., & Aharonson-Daniel, L. (2021). Development and validation of the Continuous Traumatic Stress Response scale (CTSR) among adults exposed to ongoing security threats. PLoS One, 16(5), e0251724). To identify a unique context-specific factor structure relevant to the Ukrainian experience, the initial 25 items were tested in a sample of 584 Ukrainians using exploratory and confirmatory factor analyses. Subsequently, the established scale structure was assessed for homogeneity, and convergent validity using measures of depression (PHQ-9), anxiety (GAD-7), perceived stress (PSS-4), resilience (BRS), and PTSD symptoms (PCL-5). Results: A three-factor, 9-item solution, representing the constructs of exhaustion, alienation, and helplessness, demonstrated the most acceptable fit among all the alternative CTSR models, including the original: χ² = 72.84, df = 24, p < .001, χ²/ (df) = 3.04, CFI = 0.94, TLI = 0.91, SRMR = 0.05, RMSEA = 0.08. Cronbach’s α for internal consistency ranged from 0.68 to 0.84 for total score, and subscales. Significant positive correlations ranging from 0.41 to 0.67 with symptom severity of depression, anxiety, perceived stress, and PTSD established the convergent validity of the Ukrainian CTSR, indicating that it measures related yet distinctive psychological phenomena of reactions to continuous traumatic stress. Conclusions: The revised Ukrainian version of the CTSR scale is a reliable and valid measure of continuous traumatic stress response, accurately reflecting its manifestation in the Ukrainian context. These findings are crucial for guiding clinical interventions and research in prolonged war environments, where understanding the nuances of ongoing trauma is essential.

Critical approaches to research on war-affected societies emphasize the necessity for a more empirically grounded approach to the production of knowledge. Presently, research on war-affected societies is undergoing a shift toward localization with a call for more "voices" with local knowledge and expertise. This research is an attempt to analyze the challenges of reliable knowledge production in war-affected societies and their circulation in academia, the policy-making community, and feeding media discourse. The research focuses on the Russian war against Ukraine since 2014 as a prism through which to examine the main challenges for localized knowledge production. We consider several aspects of knowledge production including the problems and issues of framing and wording that define the character of the conflict, challenges of research design and data collection, researchers' positioning dilemmas, participants' responses, differences between policy and academic research, and the role of the media. The purpose of this study is to engage with and attempts to advance the literature on knowledge localization. We argue that a move toward the localization of fieldwork requires a more sensitive and transdisciplinary approach to knowledge production. Based on our own experience of fieldwork during wartime, we point out possible ethical and methodological challenges and offer workable responses to them.

Chronic occupational stress is associated with a pronounced decline in emotional and cognitive functioning. Studies on neural mechanisms indicate significant changes in brain activity and changed patterns of event-related potentials in burnout subjects. This study presents an analysis of brain functional connectivity in a resting state, thus providing a deeper understanding of the mechanisms accompanying burnout syndrome. The sample consists of 49 burnout employees and 49 controls, matched by age, gender and occupation (Mage = 36.15, SD = 8.10; 59 women, 39 men). Continuous dense-array EEG data were collected from a 256-channel EEG system. The difference in functional connectivity between burnout and control subjects was tested in the eyes-closed (EC) and eyes-open (EO) conditions using the resting-state paradigm. The results indicate significant differences in brain activity between the burnout and the control groups. The resting-state network of the burnout group is characterized by decreased functional connectivity in frontal and midline areas in the alpha3 sub-band (11–13 Hz) in an eyes-open condition. The most significant effect of decreased connectivity was observed in the right frontal brain area. For the first time, these analyses point to distinctive aspects of functional connectivity within the alpha3 sub-band in burnout syndrome. These findings provide insights into the neurobiological underpinnings of burnout syndrome and its associations with changed resting-state networks. The data on neural characteristics in burnout subjects may help to understand the mechanisms of decline in cognitive function and emotion regulation and to search for adequate methods of treatment.

Introduction The full-scale Russian war has caused Ukrainian female refugees to experience many stressful events which may have an adverse impact on their mental health. Understanding the prevalence and determinants associated with anxiety is essential for psychosocial support. The study aimed: to evaluate the psychometric validity of the Ukrainian version of the Beck Anxiety Inventory (BAI) among Ukrainian female refugees in the Czech Republic, to determine the prevalence of anxiety, and to identify key determinants for anxiety in this population. Methods Anxiety was measured by BAI, which was validated by applying confirmatory factor analysis. Linear regressions were run to understand associations between social, physical and mental health determinants and anxiety, adjusted by socio-demographics. Results The BAI had a high level of internal consistency. External consistency was confirmed through: structural validity via CFA, indicating that a four-factor model, including cognitive, autonomic, neuromotor, and panic factors, were the most appropriate for the Ukrainian version of BAI; and convergent validity, shown by significant correlations between the total scores of the BAI and coping strategies, perceived stress, depression as well as self-reported physical and mental health. The study revealed that more than half of the participants had moderate to concerning symptoms of anxiety. The analysis indicated that poor perceived health, ineffective coping strategies, high perceived stress, and hampered daily activities due to health issues, are significant predictors of increased anxiety. Conversely, positive or stable social relations with relatives, neighbors, and locals, and the absence of discrimination, were shown to be crucial in reducing anxiety levels.

Indoor positioning systems have become increasingly popular due to the growing demand for location-based services in various domains. While effective outdoors, traditional Global Positioning System (GPS) technologies are often unsuitable for indoor environments due to their reliance on satellite signals, which are severely attenuated or obstructed indoors. This limitation underscores the need for alternative indoor localization solutions. Bluetooth Low Energy (BLE) has emerged as a favorable solution for indoor localization, thanks to its widespread deployment in smartphones and other consumer devices, providing a low-cost and energy-efficient option. However, BLE-based localization is frequently challenged by signal interference and multipath effects, which degrade the system’s accuracy. This work presents a novel approach that fuses BLE and Inertial Measurement Unit (IMU) data to address these limitations and enhance indoor positioning accuracy. Our approach employs a Multi-Carrier Phase Difference method for precise BLE-based distance estimation, which is subsequently combined with IMU data through a particle filter framework. The IMU data are processed using the Madgwick filter and a step-detection model to capture motion dynamics accurately. The fusion model demonstrates substantial improvements in localization accuracy, with experimental results showing up to a 25% reduction in measurement errors, especially in challenging and complex indoor environments.

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and neuropsychiatric symptoms resulting from the loss of dopamine-producing neurons in the substantia nigra pars compacta (SNc). Dopamine transporter scan (DATSCAN), based on single-photon emission computed tomography (SPECT), is commonly used to evaluate the loss of dopaminergic neurons in the striatum. This study aims to identify a biomarker from DATSCAN images and develop a machine learning (ML) algorithm for PD diagnosis. Using 13 DATSCAN-derived parameters and patient handedness from 1309 individuals in the Parkinson’s Progression Markers Initiative (PPMI) database, we trained an AdaBoost classifier, achieving an accuracy of 98.88% and an area under the receiver operating characteristic (ROC) curve of 99.81%. To ensure interpretability, we applied the local interpretable model-agnostic explainer (LIME), identifying contralateral putamen SBR as the most predictive feature for distinguishing PD from healthy controls. By focusing on a single biomarker, our approach simplifies PD diagnosis, integrates seamlessly into clinical workflows, and provides interpretable, actionable insights. Although DATSCAN has limitations in detecting early-stage PD, our study demonstrates the potential of ML to enhance diagnostic precision, contributing to improved clinical decision-making and patient outcomes.

Objective. Complex biological systems have evolved to control movement dynamics despite noisy and unpredictable inputs and processing delays that necessitate forward predictions. The staple example in vertebrates is the locomotor control emerging from interactions between multiple systems—from passive dynamics of inverted pendulum governing body motion to coupled neural oscillators that integrate predictive forward and sensory feedback signals. These neural dynamic computations are expressed in the rhythmogenic spinal network known as the central pattern generator (CPG). While a system of ordinary differential equations constituting a rate model can accurately reproduce flexor-extensor modulation patterns aligned with experimental data from cats, the equivalent computations performed by thousands of neurons in vertebrates or even in silicon are poorly understood. Approach. We developed a locomotor CPG model expressed as a spiking neural network (SNN) to test how damage affects the distributed computations of a well-defined neural circuit with known dynamics. The SNN-CPG model accurately recreated the input–output relationship of the rate model, describing the modulation of gait phase characteristics. Main Results. The degradation of distributed computation within elements of the SNN-CPG model was further analyzed with progressive simulated lesions. Circuits trained to express flexor or extensor function, with otherwise identical structural organization, were differently affected by lesions mimicking results in experimental observations. The increasing external drive was shown to overcome structural damage and restore function after progressive lesions. Significance. These model results provide theoretical insights into the network dynamics of locomotor control and introduce the concept of degraded computations with applications for restorative technologies.

This chapter provides an overview of the changes in the bilateral trade relations between the European Union (EU) and Ukraine since the start of the full-scale Russian aggression against Ukraine in February 2022. It describes new trade barriers that have arisen due to the war and legal responses undertaken by Ukraine and the EU and its member states to further implement the EU-Ukraine Association Agreement (AA), specifically its trade part, namely the Deep and Comprehensive Free Trade Area (DCFTA). This chapter argues that the full-scale war has led to deeper trade liberalisation between EU and Ukraine, however, trade concessions are temporary and with many caveats. Finally, the author suggests potential legal instruments that could shape the bilateral trade relations between the EU and Ukraine and facilitate further trade liberalisation while contributing to the recovery of Ukraine.

Since 2014, the Association Agreement (AA) between Ukraine and the EU has been a fundamental framework for implementing political, socio-economic, and institutional reforms, including in the education sector. The inception of Russian military aggression in 2014, marked by the annexation of Crimea and the Donbas and followed by a full-scale war, has caused a devastating impact on Ukraine’s education system. Through a comprehensive analysis, this research probes the extent to which Ukraine’s higher education system has demonstrated resilience during the war triggered by Russia’s aggression. The study contends that Ukraine’s commitment to align with the European Higher Education Area (EHEA) and the Bologna process, as outlined in the AA, significantly contributed to fortifying the Ukrainian higher education system’s resilience and formed the core of its transformative capabilities amidst armed conflict. Through a multi-dimensional analysis, the chapter aims to provide insights into the complex interplay between war, resilience, EU support measures, and higher education reform, with implications for Ukraine's post-war recovery efforts and its path towards potential EU accession through its further integration into the European Education Area (EEA).