Adaptive Research Articles

Harmonizing two measures of adaptive functioning using computational approaches: prediction of vineland adaptive behavior scales II (VABS-II) from the adaptive behavior assessment system II (ABAS-II) scores

BackgroundVery large sample sizes are often needed to capture heterogeneity in autism, necessitating data sharing across multiple studies with diverse assessment instruments. In these cases, data harmonization can be a critical tool for deriving a single dataset for analysis. This can be done through computational approaches that enable the conversion of scores across various instruments. To this end, our study examined the use of analytical approaches for mapping scores on two measures of adaptive functioning, namely predicting the scores on the vineland adaptive behavior scales II (VABS) from the scores on the adaptive behavior assessment system II (ABAS).MethodsData from the province of Ontario neurodevelopmental disorders network were used. The dataset included scores VABS and the ABAS for 720 participants (autism n = 547, 433 male, age: 11.31 ± 3.63 years; neurotypical n = 173, 95 male, age: 12.53 ± 4.05 years). Six regression approaches (ordinary least squares (OLS) linear regression, ridge regression, ElasticNet, LASSO, AdaBoost, random forest) were used to predict VABS total scores from the ABAS scores, demographic variables (age, sex), and phenotypic measures (diagnosis; core and co-occurring features; IQ; internalizing and externalizing symptoms).ResultsThe VABS scores were significantly higher than the ABAS scores in the autism group, but not the neurotypical group (median difference: 8, 95% CI = (7,9)). The difference was negatively associated with age (beta = -1.2 ± 0.12, t = -10.6, p < 0.0001). All estimators demonstrated similar performance, with no statistically significant differences in mean absolute error (MAE) values across estimators (MAE range: 4.96–6.91). The highest contributing features to the prediction model were ABAS composite score, diagnosis, and age.LimitationsThis study has several strengths, including the large sample. We did not examine the conversion of domain scores across the two measures of adaptive functioning and suggest this as a future area of investigation.ConclusionOverall, our results supported the feasibility of harmonization. Our results suggest that a linear regression model trained on the ABAS composite score, the ABAS raw domain scores, and age, sex, and diagnosis would provide an acceptable trade-off between accuracy, parsimony, and data collection and processing complexity.

AI-Driven Energy Efficiency Optimizations in mHealth Applications: A Comprehensive Review on User Behavior Prediction and System Performance

Recently, mHealth applications have gained immense popularity, revolutionizing healthcare management for chronic diseases and fitness tracking. However, continuous data processing and transmission increase the strain on battery life. This study examines AI and machine learning-based techniques to reduce energy consumption in mHealth applications without compromising functionality. Adaptive sampling, task scheduling, and predictive user behavior modeling were implemented, significantly reducing power consumption and extending battery life. Challenges such as data privacy and model generalization in deploying these AI technologies are also addressed, along with future research and broader adoption.

A numerical simulation research on fish adaption behavior based on deep reinforcement learning and fluid–structure coupling: The refuge–predation behaviors of intelligent fish under varying environmental pressure

The study of fish swimming behavior and locomotion mechanisms holds substantial scientific and engineering significance. With the rapid progression of artificial intelligence, the integration of artificial intelligence with high-precision numerical simulation methods presents a novel and highly efficient tool for investigating fish behavior. In this paper, we proposed a fish perception model that more closely reflects natural logic. By introducing the individual vision and partially visibility model, a physics-based visual system that mirrored the sensory capabilities of live fish was developed. Furthermore, through the construction of a flow vision using conventional neural networks, we enhanced the intelligent fish's ability to detect unsteady hydrodynamic parameters via numerical lateral line. The validity of the new model was demonstrated through experiments, which the intelligent fish hunts complex moving targets in unsteady flow. Finally, we applied the model to study the refuge/predation behaviors of coral reef fish under varying unsteady flow pressures. The results indicated that swimming capabilities significantly impact fish survival strategies in high flow velocity, highly unsteady hydrodynamic environments, shaping distinct evolutionary decision-making traits. These insights may help to understand the niche competition mechanisms of fish in different flow conditions.

Assessing Commercial Sugarcane Irrigators’ Intentions to Adapt Water-Use Behaviour in Response to Climate Variability in South Africa

The scarcity of water resources in South Africa remains a considerable challenge for water users. This study evaluated the impact of climate variability on the adaptive water-use behaviour of sugarcane producers by identifying the factors influencing their adaptation decisions. A survey, the Theory of Planned Behaviour (TPB), and structural equation modelling (SEM) were used to achieve this objective. The study involved 54 sugarcane producers from the Impala Irrigation Scheme, selected through random sampling. Socio-economic profiles revealed a largely male, older demographic with varied education levels and farm characteristics. Results indicated that attitude (β = 0.349, p &lt; 0.1) and subjective norms (β = 0.281, p &lt; 0.05) significantly influenced farmers’ intentions to adapt, while perceived behavioural control had no significant effect (β = 0.051, p &gt; 0.1). These findings suggest that improving farmers’ attitudes and strengthening social support systems can enhance their intentions to adopt adaptive strategies. However, the model’s explanatory power (R² = 0.276) suggests that other unexamined factors may also influence farmers’ adaptive intentions, highlighting the need for further research. Overall, our findings suggest that interventions targeting attitudes, social support, and resource access can improve adaptive behaviours.

Innovative Work Behavior in Response to Technology Readiness: The Role of Career Adaptability in the Ghanaian Public Sector

Background: In an era where technological advancements are reshaping the global workforce, understanding the dynamics of technology adoption within the public sector becomes paramount. This study examines how employees in the Ghanaian public sector respond to technology readiness (TR) in terms of their career adaptability (CA) and innovative work behavior (IWB). The uniqueness of this research lies in its empirical investigation of how TR’s motivational and inhibitory dimensions influence CA and, subsequently, IWB, within a context marked by rapid digital transformation. This study is essential due to the key role of Ghana’s public sector employees in national development, especially with ongoing digitization. It fills a research gap by assessing how these employees’ psychological readiness for technology affects their careers and innovation. Method: The study used a cross-sectional survey design and collected data from 484 public sector employees and their supervisors. Partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses. Results: Findings reveal that optimism, insecurity, and discomfort — components of TR — exert a significant influence on CA, which in turn fosters IWB. Interestingly, innovativeness did not predict CA, suggesting a nuanced interplay between TR dimensions and adaptability. Implications: By elucidating the factors that drive CA and IWB in response to TR, this study offers valuable insights for policymakers and organizational leaders seeking to enhance employee adaptability and innovation amidst technological changes. It underscores the importance of nurturing an optimistic and secure technological environment to cultivate a resilient and forward-thinking public sector workforce. Originality/Value: This study pioneers the exploration of TR’s impact on CA and IWB, utilizing the career construction model of adaptation as a theoretical lens. The findings provide actionable strategies for bolstering the public sector’s technological and innovative capacity, informed by the empirical evidence from the surveyed sample.

Reaching out or going it alone? How birth order shapes networking behavior and entrepreneurial action in the face of obstacles

Whether individuals grew up as first-born or later-born siblings in their families can influence their behavior well into adulthood. This study examines the impact of birth order on networking behavior and entrepreneurial action, integrating birth order theory with psychological threat response theories. It suggests that first-born and later-born entrepreneurs inherently differ in their social responses to the uncertainties and threats of entrepreneurship, which affects how intensively they engage in networking behavior and entrepreneurial action. Three empirical studies involving over 900 entrepreneurs were conducted using between-family analysis. The results indicate that later-borns, overall, exhibit more adaptive behavior than first-borns when navigating the challenges of entrepreneurship: Especially when facing severe threatening obstacles, later-born entrepreneurs tend to intensify their efforts to build, seek, and use external networks, which enables them to engage in more entrepreneurial action. This study offers new insights into the relationship between birth order and entrepreneurship, enhancing our understanding of why some individuals may respond more adaptively to threats, network more intensively, and exploit opportunities more actively than others.

The influence mechanism of relational capital on adaptive behaviors of Chinese expatriates in Latin America

Purpose In line with the theory of planned behavior, this study aims to examine the mediating effect of cultural identity and role identity between relational capital and adaptive behavior, and the moderating effect of willingness to learn. Design/methodology/approach Data were collected from 241 Chinese expatriates in Latin America through a two-wave survey. Findings The findings indicate that expatriates’ perceived relational capital can promote adaptive behaviors by enhancing their cultural identity and role identity. Willingness to learn positively moderates the indirect effects of relational capital on adaptive behaviors through cultural identity and role identity. For expatriates with a high willingness to learn, the impact of relational capital on their adaptive behaviors through cultural identity and role identity is stronger. Originality/value This study extends empirical research on expatriate adaptation. Organizations should promote the accumulation of expatriates’ relational capital while they are working abroad. Meanwhile, willingness to learn should be considered as a criterion when selecting expatriates.

Family experiences with supplemental social security income and legal guardianship for autistic adults: A mixed-methods study

BackgroundFamily interactions with the Supplemental Social Security Income (SSI) program and the decision to pursue legal guardianship are poorly understood in services research for autistic adults. MethodsWe conducted a mixed-methods study and incorporated quantitative survey data from 122 autistic adults in an existing longitudinal cohort with qualitative interviews with 12 autistic adults and/or legal guardians. We explored sociodemographic, developmental, and behavioral features associated with the likelihood of having SSI and a legal guardian at 25 years old. Spoken interviews were transcribed verbatim, and interviews were analyzed using a rapid qualitative analytic approach. ResultsThere were quantitative differences in whether families were able to obtain SSI and guardianship based on intelligence quotient (IQ) scores, adaptive behavior, and autistic characteristics, but not by race, ethnicity, or maternal education. Qualitative data analysis revealed six themes that highlighted the challenges associated with obtaining and maintaining SSI, along with the complex, nuanced decisions associated with legal guardianship. Families noted many challenges in navigating these procedures and some potential benefits for each unique circumstance. ConclusionsThese findings offer new perspectives on experiences associated with pursuing SSI benefits and legal guardianship for autistic adults, including similarities and key differences in these procedures. Findings also provide suggestions for future research to improve coordination and supports for families throughout adulthood.

Understanding the Dynamism of Leadership Behavior, Style and Traits.

This study explores the dynamics of leadership by analyzing three key models- Stogdill (1974), Derue et al. (2011), and Gutterman (2023). These models provide complementary perspectives on leadership traits, behaviors, and emotional intelligence. Universal attributes like self-confidence and persistence intersect with adaptive behaviors and relational skills, emphasizing leadership's multidimensional nature. Emotional intelligence is highlighted as vital for addressing modern organizational challenges. Through a comparative analysis, this study synthesizes theoretical and practical insights, identifying overlaps and distinctions. The findings offer a comprehensive understanding of leadership and a foundation for future research in diverse organizational contexts.

Developmental and Functional Outcomes Amongst Culturally and Linguistically Diverse Autistic Children.

Children typically learn by attending to other people. Autism traits may impact access to social stimuli fundamental to early learning, increasing children's likelihood of a learning disability. Recent reports have highlighted that Autistic children from minority backgrounds have a higher likelihood of co-occurring intellectual disability. This study aimed to firstly confirm that early autism traits are concurrently and prospectively associated with lower developmental quotients, and secondly to examine the developmental and functional gains in Culturally and Linguistically Diverse (CALD) and non-CALD Autistic children following one year of Group-based Early Start Denver Model (G-ESDM). Secondary data on 114 non-CALD and 91 CALD Autistic preschoolers receiving the G-ESDM was utilised to address the study aims. Children were administered the Autism Diagnostic Observation Schedule (ADOS) at entry into the service. The Mullen Scales of Early Learning and the Vineland Adaptive Behaviour Scales-II were administered at both entry (Time 1) and 12 months later (Time 2). While no concurrent associations were found between autism traits and Developmental Quotient (DQ), significant associations were found prospectively with ADOS scores at Time 1 and DQ at Time 2, holding for both groups after controlling for DQ at Time 1. Autistic children made significant gains in cognition and functional behaviour following one year of early therapy, with no differences between the two groups. The results indicate that young Autistic children make significant gains in early development and add to the sparse research on the developmental and functional outcomes of Autistic children from CALD communities.

Trophic Interactions of Callinectes sapidus (Blue Crab) in Vendicari Nature Reserve (Central Mediterranean, Ionian Sea) and First Record of Penaeus aztecus (Brown Shrimp)

Invasive alien species pose severe threats to global biodiversity, ecosystem functions, and socio-economic values, particularly in coastal and marine ecosystems. This study aimed to investigate the trophic interactions between alien species and native fauna in a Mediterranean coastal ecosystem. Notably, our research focused on the presence and ecological roles of the invasive Atlantic blue crab (Callinectes sapidus) and the brown shrimp (Penaeus aztecus) within the Vendicari Nature Reserve (VNR), a protected area on the southeastern coast of Sicily, Italy. Field observations, specimen collection, and interviews with local fishermen were conducted to assess the presence, distribution, and feeding habits of these species. The results revealed significant temporal shifts in the diet of C. sapidus, with a clear decrease in predation on the alien Penaeus aztecus (first observed in the VNR) over the study months. The presence of C. sapidus in the fishing area around the reserve has been detected for many years, while P. aztecus appears to have recently colonized the area. Additionally, photographic evidence documented the predation of C. sapidus by Octopus vulgaris, highlighting a potential adaptive feeding behavior by the common octopus in response to the abundance of this invasive crab. The integration of scientific research, local ecological knowledge, and community participation is essential for mitigating the impacts of biological invasions and preserving the biodiversity and ecological integrity of natural ecosystems.

Rank-Related Differences in Dogs’ Behaviours in Frustrating Situations

Dogs are strongly dependent on humans, not only for sustenance, but they also form asymmetrical bonds with us where they rely on assistance from the human partner in the case of difficult situations. At the same time, cohabiting dogs form hierarchies, and their rank strongly influences their behaviour in various social interactions. In this study, we investigated whether high- and low-ranking dogs would behave differently in non-social and social contexts where a formerly available reward suddenly becomes inaccessible. We hypothesised that dominant and subordinate dogs would show different levels of human dependence; thus, they will show different levels and different signs of frustration depending on the social nature of the context, where the reward was locked either in a closed cage or withheld in the hand of the experimenter. The results showed that while the holistic rank (‘dominant’ vs. ‘subordinate’) of the dogs did not show a significant association with their reactions to frustrating situations, the rank components (‘agonistic’ and ‘leadership’ ranks) were better predictors of the dogs’ behaviour. In the non-social context, the highly resource-oriented ‘agonistic-dominant’ dogs were more persistent with their attempts of getting to the reward. However, in the social context, the dogs with high ‘leadership scores’ behaved more demandingly with the non-complying experimenter. This study provides a first-time indication that the various aspects of dominance in dogs can affect their adaptive reward-oriented behaviours differently, depending on the potentially available human assistance.

"What Can We Do?": A Psychological Perspective on (Mal)Adaptive Coping Strategies and Barriers to Coping in an Area of Severe Climate Vulnerability in Bangladesh.

As the mental well-being of billions of people is at risk due to the impacts of climate change, more research is required to better understand the psychological implications of climate vulnerability. This research aims to describe the coping strategies of a climate change affected population and the consequences of adaptation behavior. We conducted 60 qualitative in-depth interviews to elicit the lived experiences of climate-vulnerable men and women in Bhola, Bangladesh. Interviews were analyzed following the tenets of Grounded Theory. Identified coping strategies included "resignation" or "help-seeking" as well as barriers to coping, such as limited "efficacy," limited "time," or "stigma," which constrained participants - especially women - in their coping behavior. Our results indicate that certain barriers can lead people to pursue more easily accessible coping strategies, some of which can be interpreted as maladaptive. It is therefore recommended to lift barriers to coping through community-led interventions, such as platforms for sharing problems and knowledge regarding coping strategies.

Multi-Modal and Adaptive Robot Control through Hierarchical Quadratic Programming

This paper proposes a novel Hierarchical Quadratic Programming (HQP)-based framework that enables multi-tasking control under multiple Human-Robot Interaction (HRI) scenarios. The proposed controllers’ formulations are inspired by real-world contact-rich scenarios, which currently constitute one of the main limitations in terms of widespread practical deployment. Indeed, HRI can occur through different modalities, based on human’s needs. The objective is to create a unique framework for various types of possible interactions, avoiding the necessity of switching between different control architectures, which requires dealing with discontinuities. To achieve this, we firstly propose a HQP-based hybrid Cartesian/joint space impedance control formulation. Based on the robot’s dynamics, this controller enables an adaptive compliance behaviour, while achieving hierarchical motion control. This is validated through a series of experiments that show the accuracy of trajectory tracking, which remains in the order of 10mm during fast motions thanks to the addition of the robot dynamics. Besides, the hybrid compliance behaviour allows to deviate from such accuracy when an interaction is present. We then consider the case in which the human needs to move the robot directly, by proposing a hybrid admittance/impedance controller, that is again based on a HQP formulation and provides inherent softening when conflicting tasks are present, or in close-to-limit and near-singular configurationsa. This is validated through several experiments in which the human easily moves the robot in the workspace via direct physical interaction. Next, we formulate an additional hierarchy that enables force control and allows to maintain a specific interaction force at the end effector. We then extend this to simultaneous force and trajectory tracking. Overall, we obtain a multi-purpose HQP-based control framework, that seamlessly switchwes between interaction modes, enabling multiple hierarchical behaviours, and covering a wide spectrum of interaction types, essential for synergistic HRI.

Extreme Weather, agricultural insurance and farmer's climate adaptation technologies adoption in China

We explore how farmers adjust their climate adaptation behaviors and participation in agricultural insurance in response to extreme weather events. A random effects model is constructed to clarify the relationships between extreme weather events, agricultural insurance and climate adaptation technologies (CAT). Using survey data from 622 farmers in China, Probit models and instrumental variable analysis show that extreme weather events significantly increase farmers' adoption of CAT and their participation in agricultural insurance. Furthermore, agricultural insurance significantly promotes farmers' adoption of CAT. Agricultural insurance influences the adoption of CAT through both substitutive and complementary effects, the complementary effects are more pronounced. Therefore, we recommended the continued promotion of CAT and agricultural insurance to strengthen farmers' resilience to extreme weather events.

Study on Impact Mechanisms of Resident Adaptability in Old Communities Based on Complex Adaptive System Theory: Theoretical Construction and Empirical Analysis of Xuzhou City Center

Confronted with both internal environmental degradation and external economic transformation, the internal environment of old residential communities has become increasingly complex. Enhancing resident adaptability is crucial for communities to address multiple urban crises and align with community development and evolution. Complex Adaptive System (CAS) theory provides an excellent analytical framework for this study, emphasizing that the adaptability of agents contributes to system complexity. The complex adaptability issues faced by old residential communities essentially involve mismatches among resident adaptive capacities, pathways, and objectives amid changing environmental and socioeconomic conditions. This study focuses on residents of 15 old residential communities in the central urban area of Xuzhou. Utilizing CAS theory, a structural equation model is constructed to explore the mechanisms influencing resident adaptability. The results indicate that the following: ① The perceived built environment and social environment have significant positive impacts on resident adaptability. ② Mediation analysis reveals that the perceived built environment plays a positive mediating role in the relationship between the objective built environment and resident adaptability, as well as between the social environment and resident adaptability. The objective built environment also serves as a positive mediator when the social environment affects resident adaptability. ③ Among the control variables examined, income, family structure, and housing tenure significantly impact resident adaptability. This study not only deepens the theoretical understanding of adaptability issues in old residential communities, providing a more nuanced perspective for understanding residents’ adaptive behaviors in complex environments, but also offers specific strategic recommendations for community renewal and enhancing resident adaptability, thus holding significant theoretical and practical value.

Optimizing Microgrid Performance: Integrating Unscented Transformation and Enhanced Cheetah Optimization for Renewable Energy Management

The increased integration of renewable energy sources (RESs), such as photovoltaic and wind turbine systems, in microgrids poses significant challenges due to fluctuating weather conditions and load demands. To address these challenges, this study introduces an innovative approach that combines Unscented Transformation (UT) with the Enhanced Cheetah Optimization Algorithm (ECOA) for optimal microgrid management. UT, a robust statistical technique, models nonlinear uncertainties effectively by leveraging sigma points, facilitating accurate decision-making despite variable renewable generation and load conditions. The ECOA, inspired by the adaptive hunting behaviors of cheetahs, is enhanced with stochastic leaps, adaptive chase mechanisms, and cooperative strategies to prevent premature convergence, enabling improved exploration and optimization for unbalanced three-phase distribution networks. This integrated UT-ECOA approach enables simultaneous optimization of continuous and discrete decision variables in the microgrid, efficiently handling uncertainty within RESs and load demands. Results demonstrate that the proposed model significantly improves microgrid performance, achieving a 10% reduction in voltage deviation, a 10.63% decrease in power losses, and an 83.32% reduction in operational costs, especially when demand response (DR) is implemented. These findings validate the model’s efficacy in enhancing microgrid reliability and efficiency, positioning it as a viable solution for optimized performance under uncertain renewable inputs.

A Critical Analysis of Supported Employment for Young Adults with Autism Spectrum Disorder (ASD): The Employment Status Quo of Young Adults with ASD in Guangzhou

Autism Spectrum Disorder (ASD) is characterized by challenges in social communication and the presence of repetitive and stereotyped behaviors. Due to impediments in typical communication channels and deficits in adaptive behaviors, young adults with ASD are among the most difficult groups to integrate into society and the workforce. To better integrate young adults with ASD into society and enhance their job skills, this paper analyzes the status quo of the employment of young adults with ASD in Guangzhou. It identifies issues faced in employment and societal integration, proposes solutions for supported employment to improve their social adaptability, and aims to alleviate the employment challenges faced by young adults with ASD.

A Scoping Review of Motor and Language Measurement Tools Used in Early Childhood Research

Early childhood is a critical period characterized by rapid development of motor and language skills. Reliably assessing motor and language development in early childhood is difficult, and there is a lack of agreement on measurement tool use. This scoping review aims to identify measurement tools used to examine motor and language skills in infants and young children (0–5 years) when the relationship between these two domains is studied. A scoping review of existing literature on motor and communication skills was conducted across studies measuring gross and/or fine motor and language development in children aged 0–5 years. Systematic searches were conducted in six online databases using carefully selected keywords and search parameters. The resulting corpus of existing literature was reviewed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses. Sixty motor and 99 language measurement tools were found. The most used measurement tools for motor and language skills were the Bayley Scales of Infant and Toddlers Development, Ages and Stages Questionnaire, Mullen Scales of Early Learning, MacArthur–Bates Communicative Development Inventories, Vineland Adaptive Behavior Scales, and Gross Motor Function Classification System. Of these, the measurements used to address language skills did not include reference to all language aspects, particularly lacking were emphasis on skills associated with phonology, morphology, and pragmatics with more focused attention on the semantic language component. This study refines existing knowledge about commonly used early childhood measurement tools. This may help to inform research and encourage consistent measurement use across studies as well as in clinical practice to improve reliable comparisons across outcomes and use measurement tools with diagnostic purpose. Further, a broader inclusion of discrete language components within measurement tools is warranted to better determine the rich, nuanced relationship between early motor and language skills.

Apathy and Functional Status in Early-Stage Huntington's Disease.

Apathy is common in Huntington's disease (HD) and difficult to treat. Multiple recent calls have been made to increase understanding of apathy across the spectrum of HD severity. Functional status is an important outcome in HD trials; however, no consensus currently exists regarding the impact of apathy on functional status in HD. The authors aimed to identify correlates of apathy and effects on functional status in a primarily early-stage HD sample. This study included secondary analyses of data from a study of neuropsychiatric symptoms in a clinical HD sample. Spearman correlation analyses were used to assess the relationships between apathy (with the Frontal Systems Behavior Scale-Apathy [FrSBe-Apathy] subscore), clinical variables, and patient-reported outcomes. To assess the association of apathy with functional status, two multiple regression analyses were performed, with a different functional status measure (Adult Functional Adaptive Behavior [AFAB] scale or Total Functional Capacity [TFC] scale) as the dependent variable in each analysis. Statistically significant correlates of apathy included the Quality of Life in Neurological Disorders (Neuro-QoL) Satisfaction With Social Roles and Activities and Neuro-QoL Positive Affect and Well-Being scores (N=70 patients). Univariate correlation analyses also revealed statistically significant associations of FrSBe-Apathy scores with both functional status measures. In the multiple regression analyses, apathy significantly contributed to variability in functional status as measured by both the AFAB (N=49 patients) and TFC (N=56 patients) scales. These results underscore the need to address apathy as a target for improving functional status, social satisfaction, and well-being in HD, even for individuals with early-stage HD.