Adaptation Process Research Articles

Resilience and Student Integration in Higher Education

Entering the academic environment requires students to adapt to certain changes and accept challenges related to a new learning environment. Young people bring with them significant concerns and expectations regarding the organisational climate, the specific nature of activities, learning strategies, as well as social relationships. Many of these changes encountered by students often become overwhelming, exerting a varied psychological impact. This study is part of a more extensive programme aimed at maximising adaptive strategies and optimally integrating students into higher education, while enhancing resilience across all age groups. This investigative approach provides valuable quantitative data to design and implement support programmes, counselling, mentoring, and coaching. The study aims to highlight that, in the process of integration, each student’s ability to demonstrate resilience is crucial; this resilience implies certain complex adaptive systems that are, at the same time, in constant evolution, underscoring the dynamic process of adaptability. Thus, the university must offer both individual and group counselling packages tailored to the student’s specific needs. Understanding the factors that lead to successful academic adaptation is therefore essential in establishing intervention models and strategies to provide counselling and support to all students, with particular focus on those at educational risk. Accordingly, students' resilience and capacity for integration constitute a multi-faceted process, determined and closely linked to a network of interactions between psychological and interpersonal constructs.

Turkish Immigrants’ Perceptions of the Polish Healthcare System

The experiences of migrants and refugees within the healthcare system play an important role in ensuring mutual adaptation. The questions we address focus on accessibility to healthcare, lack of trust and communication, and the social adaptation of Turkish immigrants in Poland . Turkish immigrants hold significant importance in the immigrant population of Poland, both from historical and socioeconomic-cultural perspectives. The Polish healthcare system has recently faced serious due to both the COVID-19 pandemic and pandemic and the influx of refugees. As the Turkish immigrant population expands in Poland, the importance of the position of increases, as it shapes healthcare relations among both Turkish immigrants and the general Polish population. With this research, we aim to understand the health experiences of migrants and the factors affecting these experiences, focusing on the relationship between the health system in Poland and its migrants. Our data was collected through interviews with 11 Turkish immigrants from Warsaw, Poznań, Toruń, Wrocław, and Bydgoszcz, along with participant observation in Poland. The findings point to the complex interplay of challenges and opportunities in migrants' healthcare experiences in Poland. Our data suggest that the healthcare system is one of the areas in which migrants are vulnerable in the host country, and states should focus on it to support the adaptation process.

REABILITAÇÃO E AUTOCONFIANÇA: O PAPEL DA FISIOTERAPIA NA VIDA DE AMPUTADOS DE MEMBROS INFERIORES

Physiotherapy plays a fundamental role in the rehabilitation and adaptation process of amputees. By providing physical, emotional and educational support to amputees, multidisciplinary work enables patients to recover by promoting lost functionality until they adapt to the physical and emotional transformations and are able to live fully and actively again. In addition, the physiotherapeutic approach is multifaceted and involves several techniques, including gait training, strengthening exercises, manual therapy and psychological support. These interventions are essential to help patients overcome the challenges related to the use of the prosthesis and the recovery of functionality. Thus, the main objective of this study is to analyze the importance of physiotherapy in the rehabilitation of patients using lower limb prostheses, highlighting the gains in mobility, adaptation to the prosthetic device and quality of life, emphasizing as a focus of the problem what are the impacts of physiotherapy on the rehabilitation of lower limb amputees in terms of mobility, adaptation to the prosthesis and quality of life? This study is characterized as a mixed approach (quantitative and qualitative) field research, carried out in a rehabilitation center specialized in lower limb prostheses in Brazil. This mixed approach allowed a more comprehensive analysis, combining numerical data with subjective perceptions of the participants. Thus, continuous and personalized physiotherapy monitoring based on measurements and field research reiterated the beneficial benefits of adaptation to the prosthesis in the lower limbs when considering the fit, comfort and functionality, and when taking into account the gait training and the established strengthening exercises. Transtibial and femoral amputation has represented not only a surgical intervention, but also a long readaptation treatment, that is, a milestone in the lives of affected individuals, which brings significant challenges. Rehabilitation begins in the preoperative period, progresses to the prosthesis fitting, and continues beyond these events, being crucial for the functional/emotional recovery of patients. Understanding the various stages of treatment and having a comprehensive rehabilitation plan are essential factors for promoting a new quality of life, which is possible for amputees, as demonstrated in the evaluations completed by patients portrayed in the various graphs representing responses to the questionnaires applied. The aim is therefore to carry out continuous and personalized physiotherapy monitoring to promote significant improvements in mobility, self-confidence and quality of life of amputee patients who use lower limb prostheses; and through treatment, a key factor for successful adaptation to the prosthesis, to facilitate the return to daily activities and promote greater functional independence. The research should also demonstrate improvements in the emotional well-being of patients, with a reduction in symptoms of depression and anxiety when considering the necessary psychological monitoring.

Adapting a pain coping skills training intervention for people with chronic pain receiving maintenance hemodialysis for end stage Kidney disease.

Pain Coping Skills Training (PCST) is a first-line cognitive-behavioral, non-pharmacological treatment for chronic pain and comorbid symptoms. PCST has been shown to be effective in racially and ethnically diverse cohorts across several chronic medical conditions. However, PCST has not been evaluated in those with end stage kidney disease (ESKD) receiving in-center maintenance hemodialysis. Due to the high rates of morbidity associated with ESKD, and time-intensive treatment, an adaptation of PCST was warranted to address the unique challenges experienced by people living with ESKD. Using current guidelines developed by Card and colleagues for intervention adaptation, PCST was adapted so that it could be implemented among people living with ESKD in a national multisite trial. The objective of this paper was to describe the adaption process outlined by Card and colleagues including how the team selected an effective intervention to adapt, developed a program model, identified mismatches in the original intervention and study population, and then adapted the intervention for those with ESKD treated with in-center maintenance hemodialysis. Finally, we briefly describe future directions for clinical practice and research with the adapted PCST intervention for those with ESKD.Trial registration: ClinicalTrials.gov #NCT04571619.

Impact of inter-species hybridisation on antifungal drug response in the Saccharomyces genus

BackgroundAntifungal drug resistance presents one of the major concerns for global public health, and hybridization allows the development of high fitness organisms that can better survive in restrictive conditions or in presence of antifungal agents. Hence, understanding how allelic variation can influence antifungal susceptibility in hybrid organisms is important for the development of targeted treatments. Here, we exploited recent advances in multigenerational breeding of hemiascomycete hybrids to study the impact of hybridisation on antifungal resistance and identify quantitative trait loci responsible for the phenotype.ResultsThe offspring of Saccharomyces cerevisiae x S. kudriavzevii hybrids were screened in the presence of six antifungal drugs and revealed a broad phenotypic diversity across the progeny. QTL analysis was carried out comparing alleles between pools of high and low fitness offspring, identifying hybrid-specific genetic regions involved in resistance to fluconazole, micafungin and flucytosine. We found both drug specific and pleiotropic regions, including 41 blocks containing genes not previously associated with resistance phenotypes. We identified linked genes that influence the same trait, namely a hybrid specific ‘super’ QTL, and validated, via reciprocal hemizygosity analysis, two causal genes, BCK2 and DNF1. The co-location of genes with similar phenotypic impact supports the notion of an adaption process that limits the segregation of advantageous alleles via recombination.ConclusionsThis study demonstrates the value of QTL studies to elucidate the hybrid-specific mechanisms of antifungal susceptibility. We also show that an inter-species hybrid model system in the Saccharomyces background, can help to decipher the trajectory of antifungal drug resistance in pathogenic hybrid lineages.

An ABCX model of family adjustment in adoption and permanent fostering of children with intellectual disability

Children with intellectual or developmental disabilities (IDD) represent a growing proportion of children who are adopted or in foster care. This study aims to explore family adjustment in foster and adoptive families of children with IDD using the ABCX model of family adjustment. Sixty-two families with adopted and foster children with IDD between two and 36 years old in Spain participated in the study. Parents completed a self-reported questionnaire including measures of child demands, family strengths, adjustment of expectations and family adjustment to adoption. The combination of child demands, family strengths and family expectations predicted 55% of the variance of family adjustment (R2 = .55, F (3,56) = 25.571, p < .001), with C Factor being the most relevant (b = .458, p < .001). No differences were found in the adaptation process depending on the severity of the disability, the age of placement, or the adoption versus fostering process. Significant differences were found in the adaptation process dimensions depending on the special versus ordinary process. Differences were also found in some family dimensions depending on the diagnosis of the disability or the family stage. These findings highlight the importance of previous expectations and special processes in adopting children and young people with IDD.

Features of Correlation of Defense Mechanisms and Intelligence in Adolescence and Adulthood

Keywords. Intelligence, defense mechanisms, intellectualization, regression, compensation. The current stage of society’s development is characterized by rapid changes of a social, public, political, economic, cultural and other nature. The personality has to constantly adapt to changes and new demands are placed on the manifestations of its adaptability and personality traits. Human intelligence plays an important role in the adaptation process. Since the psychological defense mechanisms of the personality are one of the most important factors in the formation of the personal structure, the problems of evaluating their effectiveness and activity levels are relevant today. The article presents the indicators of intelligence development in two age groups of personality development and the frequency of applicability of various psychological defense mechanisms, as well as the characteristics of the correlation between intelligence and psychological defense mechanisms of teenagers and young people. The purpose of our research was to study the characteristics of the correlation between defense mechanisms and intelligence at different stages of personality development. By the comparative analysis of the received data, it becomes clear that only the intellectualization defense mechanism is positively correlated with intelligence among teenagers, and compensation and intellectualization are positively correlated with intelligence among young people, and a negative correlation with regression was recorded.

ARTIFICIAL INTELLIGENCE-BASED AUDIT SOFTWARE: TODAY'S REALITIES AND FUTURE VISION

In today's era of big data, traditional audit methods may not always be sufficient to address the complex risks faced by businesses. At this point, AI-supported audit software (AIAS) emerges as a promising solution to overcome these challenges. This study aims to comprehensively examine the current state and future potential of AIAS, analyzing the opportunities and challenges arising from the integration of these technologies into audit processes. To achieve this, we investigate the use cases of AIAS across various audit types and sectors, assessing the benefits they offer and the challenges they present. Additionally, by analyzing the global and local pioneers of AIAS, we identify the factors driving the development of these technologies and uncover future trends. This compilation-based study reveals that AIAS has the potential to make audit processes more efficient, effective, and reliable. However, it also emphasizes the need for careful consideration of issues such as data privacy, algorithmic bias, and ethical implications. This study underscores the importance of collaboration among auditors, businesses, and regulators to fully harness the potential of AIAS while minimizing potential risks. It advocates investing in a continuous learning and adaptation process. Future research should delve deeper into the impact of AIAS across different sectors and develop recommendations to fully capitalize on the potential of these technologies.

ADAPTIVE CONTROL SYSTEM FOR A FLUIDIZED BED DRYER

The advantages and disadvantages of numerous interconnected adaptive drying process control systems have been analyzed. An adaptive system for the process has been developed that enables the calculation of hydrodynamics and seed moisture content in a fluidized bed. This system is based on the separation of reactive zones, taking into account the fluidized bed and dynamic models of the drying process within the fluidized bed.

Application of Extreme Machine Learning for Smart Agricultural Robots to Reduce Manoeuvering Adaptability Errors

The agricultural robots limit complicated manoeuvring jobs, reducing the need for human intervention. Automation and control of these robots are performed by observing and practising the crop type, regulations, and external weather conditions. This article proposes and discusses a Manoeuvering Adaptable Task Processing Model (MATPM). This model is designed to improve the adaptability and precision of agricultural robots coinciding with farming and climatic conditions. For this purpose, extreme machine learning is employed to learn, align, and respond to external conditions to improve precise manoeuvring. The external impacting features and their adaptability to the crop and climatic conditions are valued using the learning process. In this process, maximum adaptability is considered to improve precision agriculture. The tasks are then classified based on adaptability and executed sequentially. If an unpredictable impacting factor hinders a task, then the adaptability is paused from training and it improves the chances of training by using different completed and paused tasks from the previous manoeuvring processes. Therefore, precision in smart farming and robot system adaptability is ensured with fewer adaptability errors. From the comparative assessment, the proposed model improves adaptability by 8.71 % and precision by 11.44 %, with 8.96 % less adaptability error for various tasks/ day.

Real-time Detection of Abnormal Financial Transactions Using Generative Adversarial Networks: An Enterprise Application

This paper presents a novel real-time financial fraud detection framework utilizing Generative Adversarial Networks (GANs) for enterprise applications. The proposed system addresses critical challenges in fraud detection, including class imbalance, real-time processing requirements, and enterprise scalability. Implementing a sophisticated multi-layered architecture, the system integrates advanced preprocessing techniques with an optimized GAN model explicitly designed for fraud pattern recognition. The framework incorporates parallel processing capabilities and adaptive batch processing mechanisms to maintain high throughput while ensuring sub-second latency. The experimental evaluation uses a subset of the European Credit Card Transaction dataset, comprising 50,000 transactions with a balanced representation achieved through strategic sampling and SMOTE technique. The proposed model achieves 97.8% accuracy, 96.5% precision, and 95.8% recall, demonstrating competitive performance compared to traditional machine learning approaches. Real-time performance analysis shows consistent sub-100ms latency while maintaining robust performance under varying load conditions. The system demonstrates linear scalability up to 32 nodes, with high availability and failover capabilities. The comprehensive assessment validates the framework's effectiveness in enterprise environments, providing practical solutions for financial institutions facing evolving fraud challenges. This research contributes to the advancement of financial security technology through the innovative application of adversarial learning in fraud detection.

Adaptive dissemination process in weighted hypergraphs

Adaptive dissemination process in weighted hypergraphs

A Prismatic-Layer Advancing-Front Approach to Anisotropic Metric-Based Curved Mesh Generation

We present a strategy for generating curved, high-order, hybrid meshes that consist of a combination of prismatic layers close to the body and unstructured elements in the rest of the domain. Such curved meshes are required for high-order discretizations, but they are difficult to generate and adapt, in particular when anisotropic elements are desired next to curved geometries. To address the problem of possible inversions in this region, the proposed strategy grows prismatic, anisotropic layers of elements close to the geometry, using a metric to dictate the element sizing and starting with a metric-conforming surface mesh. The curvature of the elements attenuates as the layers grow, and the prismatic regions end once linear faces are possible. A linear unstructured mesh fills the remaining portion of the domain, and it is generated using a simple, metric-based advancing-front algorithm. The strategy is implemented in an adaptive solution process by using an existing mesh as a scaffold for metric evaluation. Results are presented for two-dimensional problems in an output-based adaptive setting. Comparisons with global remeshing show similar performance in output convergence, mesh quality, and aspect-ratio distributions and improved robustness and efficiency due to lack of a separate mesh curving step.

Lexical ways of designating the Internet in modern Russian: semantics, pragmatics, spelling

The article focuses on the words that designate the Internet and its segments and discusses such problems as the process of assimilation of lexeme "интернет" in contemporary Russian language and its spelling variants, the reasons and mechanisms of appearance of its synonyms. Formal and cognitive adaptation of the anglicisms "internet", "web", "net" and stylistic peculiarities of word-formative and semantic derivatives that appeared on the base of Russian language are also discussed. Particular attention is paid to the tendency for some English-language stems to become affixoids in contemporary Russian. Modern explanatory dictionaries and corpus data were used as sources of linguistic information about the functioning of investigated lexemes ([https://ruscorpora.ru/], [http://www.webcorpora.ru]), data obtained by search by keywords was also analyzed. Descriptive method was used in the research. Identified designations of the Internet, as well as its segments, are analyzed in terms of their origin and semantics. Their stylistic features are also explained. The research’s scientific novelty lies in identifying for the first time a variety of lexemes designating the Internet and its segments. The article considers the process of adaptation of lexical units denoting the concept of "Internet", as well as the peculiarities of their functioning in contemporary Russian language. The reasons for the emergence of synonymic designations of the word "Internet" and their peculiarities are analysed. A number of studied nominations ("глубокий", "черный" vs. "поверхностный", "белый интернет") are not listed in modern explanatory dictionaries. The conducted analysis allowed us to draw the following conclusion: synonyms of the lexeme "интернет" that appeared in Russian language, on the one hand reflect the denotative significance of the realia called "Internet", its role in modern society, and on the other hand the synonyms demonstrated significant word-formation and cognitive potential of contemporary Russian language.

Trends in the Development of Mass Media in the Context of Modern Chinese Political Ideology

Mass media have historically played a crucial role in shaping societal values and advancing political ideologies. This study aims to identify the distinctive features of the ideological functions and political characteristics of Chinese media at various stages of their development. The object of the study is Chinese media as an instrument of state power and a mechanism of ideological influence. The subject of the study is the evolution of the ideological functions of Chinese mass media throughout different stages of their development. The research employs historical, comparative, systemic, and functional analysis. The novelty of the study lies in its comprehensive examination of the transformation of Chinese media through the lens of their political functions and ideological objectives. The study emphasizes that Chinese media play a pivotal role in promoting party ideals, ensuring political stability, and shaping international discourse. The key findings of the research are as follows: 1. The dynamic process of adaptation by Chinese media to changes in social and political conditions is evident. 2. The critical role of media in fostering public consensus and legitimizing governmental authority is highlighted. A notable contribution of the author is the systematic classification of the stages in the evolution of Chinese media—from complete politicization to more subtle forms of political activity, and eventually to re-politicization in the modern era. The study illustrates the uniqueness of China’s media system, which blends national and international objectives, thereby strengthening political order domestically and advancing the nation’s interests on the global stage. This research is valuable for scholars and political scientists studying the history of communication, the use of media to achieve political goals, agenda-setting, and political propaganda.

Translation, Evaluation and Validation of the Adult Strabismus -20 (AS-20) Questionnaire in Swedish.

To translate and validate the Adult Strabismus 20 (AS-20) questionnaire, a health-related quality of life questionnaire specifically devised for patients with strabismus. The AS-20 was translated in accordance with the principles of good practice for the translation and cultural adaptation process for patient-related outcomes (PRO) according to the methodology recommended by the International Society for Pharmacoeconomics and Outcome Research (ISPOR). The translation, evaluation, and validation were performed in several steps. The study used both qualitative and quantitative methods and engaged 31 final-year orthoptic students in workshops, as well as 19 experts (experienced clinical orthoptists), 17 laymen (members of the public), and 17 patients from national eye clinics. The final translated questionnaire was tested for reliability and validity in 68 adults with strabismus by internal consistency using Cronbach´s alpha and content and construct validity using the Rasch analysis. The Swedish AS-20 showed a high level of internal consistency. Cronbach´s alpha was 0.95 for the psychosocial subscale and 0.92 for the functional subscale. However, the Rasch analysis indicated that both items and responses should be condensed to achieve content and construct validity. The thorough translation and evaluation process resulted in a validated AS-20 questionnaire for use in the Swedish language, and shows reliability as an instrument to measure health-related quality of life (HRQoL) in adults with strabismus in a clinical setting.

RNA modifications in plant adaptation to abiotic stresses.

Epitranscriptomic chemical modifications of RNAs have emerged as potent regulatory mechanisms in the plant stress adaptation process. Currently, over 170 distinct chemical modifications have been identified in mRNAs, tRNAs, rRNAs, microRNAs (miRNAs), and long-noncoding RNAs (lncRNAs). The genetic and molecular studies have identified the genes responsible for adding and removing chemical modifications on RNA molecules, known as "writers" and "erasers," respectively. Among the identified chemical modifications in mRNAs, N6-methyladenosine (m6A) is the most prevalent modification in eukaryotic mRNAs. Recent studies have identified m6A writers and erasers across different plant species, including Arabidopsis (Arabidopsis thaliana), rice (Oryza sativa), cotton (Gossypium hirsutum), and tomato (Solanum lycopersicum). Accumulating discoveries have improved our understanding of the functions of RNA modifications in plant stress responses. This review highlights the latest developments in RNA modification research, emphasizing the biological and cellular roles of diverse chemical modifications in mRNAs, tRNAs, rRNAs, miRNAs, and lncRNAs in the plant response to environmental and hormonal signals. Moreover, we propose and discuss the critical questions and future challenges in enhancing our understanding of the cellular and mechanistic roles of RNA modifications in plant stress responses. Integrating molecular insights regarding the regulatory roles of RNA modifications in stress responses with novel genome- and RNA-editing technologies will facilitate the breeding of stress-tolerant crops via precise engineering of RNA modifications.

Deep Reinforcement Learning and Enhanced Optimization for Real-Time Energy Management in Wireless Sensor Networks

Constraints are a major issue in radio-based communication in Wireless Sensor Networks, where each sensor node has a limited amount of power. Conventional clustering and optimization methods have been inappropriate for dynamic conditions which lead to timely energy drainage and reduce the network lifetime. In this research, the novel Deep Reinforcement Learning-Enhanced Hybrid African Vulture and Aquila Optimizer has been proposed that optimizes the dynamic clustering and energy-based parameters in real time. The proposed model is designed for optimizing the Wireless Sensor Networks, by including Deep Reinforcement Learning to adjust the dynamic formation of the base of the cluster on real-time data which leads to efficient energy utilization among all the sensor nodes. It combines the best properties of the Aquila and African Vulture Optimizer to optimize the network lifetime and energy consumption. The network lifetime, which is one of the most crucial characteristics, is optimized by using the global search algorithm of African Vulture Optimiser. In contrast, it is optimized by the localized search of Aquila optimizer to reduce energy consumption. The presented novel African Vulture and Aquila model outperforms the existing methods used convention-based optimization methods. It shows a 20% improvement in energy efficiency and faster convergence with better robustness while keeping the network scalability. The proposed approach is perfectly suited for the scalable WSNs which are mainly used in the environment such as smart cities and IoT systems where a timely adaptation process is inevitable.

Genomic and virulent characterization of a duck-associated Salmonella serovar Potsdam from China

Salmonella, a common zoonotic pathogen, is a significant concern for public health, particularly when it contaminates animal-borne products. The potential for Salmonella to infect duck embryos and disrupt their normal development not only causes substantial economic losses for the industry but also poses a severe threat to public health. However, there is a lack of understanding about the prevalence of Salmonella in duck embryos and their potential public health implications. Our study aims to fill this gap by providing genomic features of the antimicrobial resistance and virulence potential of Salmonella isolates from dead duck embryos using whole-genome sequencing and in silico toolkits. We also sought to assess the virulent characterization of the major serovar isolates by experimental infection of chicken and duck embryos. Our investigation of 195 duck embryo eggs led to the isolation of 40 (20.51%) Salmonella strains, with Salmonella serovar Potsdam being the most prevalent serovar. Most isolates were resistant to streptomycin (57.3%) and nalidixic acid (50%). Notably, our findings demonstrated that S. Potsdam exhibited a preference for ducks over chickens, suggesting potential host specificity. Additionally, global phylogenomic analysis, incorporating 180 global genomes, revealed a predominant association of S. Potsdam with ducks, supporting an adaptive process specific to the waterfowl. This study determined Salmonella serovars and antimicrobial resistance profiles in dead duck embryos, revealing a rare Salmonella serovar Potsdam with a potential for duck adaption.

Cognitive Models for Machine Theory of Mind

AbstractSome of the required characteristics for a true machine theory of mind (MToM) include the ability to (1) reproduce the full diversity of human thought and behavior, (2) develop a personalized model of an individual with very limited data, and (3) provide an explanation for behavioral predictions grounded in the cognitive processes of the individual. We propose that a certain class of cognitive models provide an approach that is well suited to meeting those requirements. Being grounded in a mechanistic framework like a cognitive architecture such as ACT‐R naturally fulfills the third requirement by mapping behavior to cognitive mechanisms. Exploiting a modeling paradigm such as instance‐based learning accounts for the first requirement by reflecting variations in individual experience into a diversity of behavior. Mechanisms such as knowledge tracing and model tracing allow a specific run of the cognitive model to be aligned with a given individual behavior trace, fulfilling the second requirement. We illustrate these principles with a cognitive model of decision‐making in a search and rescue task in the Minecraft simulation environment. We demonstrate that cognitive models personalized to individual human players can provide the MToM capability to optimize artificial intelligence agents by diagnosing the underlying causes of observed human behavior, projecting the future effects of potential interventions, and managing the adaptive process of shaping human behavior. Examples of the inputs provided by such analytic cognitive agents include predictions of cognitive load, probability of error, estimates of player self‐efficacy, and trust calibration. Finally, we discuss implications for future research and applications to collective human–machine intelligence.