Adaptive Function Research Articles

Trajectories of Perceived Parental Psychological Control and the Longitudinal Associations with Chinese Adolescents' School Adjustment across High School Years.

Past research supports the detrimental effects of parental psychological control on adolescent school adjustment in both emotional and academic domains. However, how psychological control changes during adolescence, and how such developmental course is related to adolescent psychological well-being and academic functioning are unclear. The direction of effects between parenting and child behaviors is also inconclusive. This 3-year longitudinal study addressed these research gaps by using five waves of survey data on 710 Chinese adolescents of high school ages (Mean age at T1 = 15.54 years, SD = 0.45, 50% males). Using latent growth curve models and latent class growth analysis, the majority of adolescents (about 63%) reported gradual increases of parental psychological control in the first 2 years of high school but a slight decline afterwards, while the other 37% perceived low and stable levels. Results from parallel latent growth modeling suggested that trajectories of psychological control were positively related to developmental trends of internalizing problems (i.e., depression and anxiety) and maladaptive academic functioning, but negatively associated with the trajectory of adaptive academic functioning, as indexed by intercept-intercept and slope-slope associations. The random-intercept cross-lagged models further revealed that psychological control was predictive of adolescent anxiety and lower adaptive academic functioning, and bidirectionally associated with maladaptive academic-related beliefs and behaviors at the within-person level. Taken together, these findings highlight the crucial role of parental psychological control on adolescent school adjustment in the Chinese cultural context and support the reciprocal model of parent-child interactions.

Clinical, genetic, and cognitive correlates of seizure occurrences in Phelan-McDermid syndrome

BackgroundPhelan-McDermid syndrome (PMS) is a genetic neurodevelopmental disorder caused by SHANK3 haploinsufficiency and is associated with an increased risk for seizures. Previous literature indicates that around one third of individuals with PMS also have epilepsy or seizures, with a wide range of types and ages of onset. Investigating the impact of seizures on intellectual and adaptive functioning for PMS is a primary concern for caregivers and is important to understanding the natural history of this syndrome.MethodsWe report on results from 98 individuals enrolled in a prospective, longitudinal study. We detailed seizure frequency, type, and age of onset, and we analyzed seizure occurrence with best estimate IQ, adaptive functioning, clinical features, and genotype. We conducted multiple linear regression analyses to assess the relationship between the presence of seizures and the Vineland Adaptive Behavior Scale, Second Edition (VABS-II) Adaptive Behavior Composite score and the best estimate full-scale IQ. We also performed Chi-square tests to explore associations between seizure prevalence and genetic groupings. Finally, we performed Chi-square tests and t-tests to explore the relationship between seizures and demographic features, features that manifest in infancy, and medical features.ResultsSeizures were present in 41% of the cohort, and age of onset was widely variable. The presence of seizures was associated with significantly lower adaptive and intellectual functioning. Genotype–phenotype analyses were discrepant, with no differences in seizure prevalence across genetic classes, but with more genes included in deletions of participants with 22q13 deletions and seizures compared to those with 22q13 deletions and no seizures. No clinical associations were found between the presence of seizures and sex, history of pre- or neonatal complications, early infancy, or medical features. In this cohort, generalized seizures were associated with developmental regression, which is a top concern for PMS caregivers.ConclusionsThese results begin to eludicate correlates of seizures in individuals with PMS and highlight the importance of early seizure management. Importantly, presence of seizures was associated with adaptive and cognitive functioning. A larger cohort might be able to identify additional associations with medical features. Genetic findings suggest an increased capability to realize genotype–phenotype relationships when deletion size is taken into account.

A three-years follow-up of extra intensive support for individuals with intellectual disability and severe challenging behaviour in the Netherlands

Adults with Intellectual Disability who show severe challenging behaviour need intensive individual support. If intensive support proves to be insufficient, extra intensive support can be provided in the Netherlands, which is characterized by more time for individual care. The present study evaluates the impact of extra intensive support over time. Client characteristics of adults receiving intensive support (IS, N=70) or extra intensive support (IS+, N=35) are compared and the impact of provided support on challenging behaviour (Developmental Behaviour Checklist-Adults), adaptive behaviour (Vineland II), and Quality of Life (San Martin Scale) is evaluated over a three years period. Compared to adults receiving intensive support, those receiving extra intensive support initially showed higher intensity of challenging behaviour, higher number of mental health diagnoses and stronger focus on goals to reduce challenging behaviour. Over time, intensity of challenging behaviour decreased in adults receiving extra intensive support, although Quality of Life and adaptive functioning did not improve. Results show that the indications for receiving extra intensive support are clear and that the extra support is effective over time. It is concluded that extra individual support is serving those who need this support.

Neuropsychological Profile of 25 Brazilian Patients with 22q11.2 Deletion Syndrome: Effects of Clinical and Socioeconomic Variables

The 22q11.2 deletion syndrome (22q11.2DS) is associated with a heterogeneous neurocognitive phenotype, which includes psychiatric disorders. However, few studies have investigated the influence of socioeconomic variables on intellectual variability. The aim of this study was to investigate the cognitive profile of 25 patients, aged 7 to 32 years, with a typical ≈3 Mb 22q11.2 deletion, considering intellectual, adaptive, and neuropsychological functioning. Univariate linear regression analysis explored the influence of socioeconomic variables on intellectual quotient (IQ) and global adaptive behavior. Associations with relevant clinical conditions such as seizures, recurrent infections, and heart diseases were also considered. Results showed IQ scores ranging from 42 to 104. Communication, executive functions, attention, and visuoconstructive skills were the most impaired in the sample. The study found effects of access to quality education, family socioeconomic status (SES), and caregiver education level on IQ. Conversely, age at diagnosis and language delay were associated with outcomes in adaptive behavior. This characterization may be useful for better understanding the influence of social-environmental factors on the development of patients with 22q11.2 deletion syndrome, as well as for intervention processes aimed at improving their quality of life.

A bivariational, stable, and convergent hierarchy for time-dependent coupled cluster with adaptive basis sets.

We propose a new formulation of time-dependent coupled cluster with adaptive basis functions and division of the one-particle space into active and secondary subspaces. The formalism is fully bivariational in the sense of a real-valued time-dependent bivariational principle and converges to the complete-active-space solution, a property that is obtained by the use of biorthogonal basis functions. A key and distinguishing feature of the theory is that the active bra and ket functions span the same space by construction. This ensures numerical stability and is achieved by employing a split unitary/non-unitary basis set transformation: the unitary part changes the active space itself, while the non-unitary part transforms the active basis. The formulation covers vibrational as well as electron dynamics. Detailed equations of motion are derived and implemented in the context of vibrational dynamics, and the numerical behavior is studied and compared to related methods.

Machine learning‐based wind‐induced response analysis in rectangular building models with limbs

SummaryThis study investigates the impact of different positions of two limbs on the structural response of a rectangular building model to wind forces. The building's geometry assumes Z and + shapes based on specific limb configurations. Computational fluid dynamics (CFD) simulations are performed to quantify wind‐induced pressures, resulting in wind force coefficients. These coefficients are used to develop predictive machine learning models through Gene Expression Programming, Group Method of Data Handling‐combinatorial (GMDH‐Combi), Model Tree, and Artificial Neural Network (ANN) techniques. The ANN analysis explores various combinations of training algorithms, adaptation functions, activation functions, and performance functions to enhance model accuracy. Among these, the Levenberg–Marquardt (LM) with gradient descent with momentum (GDM) adaptation function and sigmoid activation function exhibit superior performance with high R‐squared values. These predictive models are then employed for a comprehensive comparative assessment of the maximum wind force coefficient (CF, max) concerning different limb positions and angles of attack (AOA). For CF, max vs Limb position, variations of limb position are examined for most critical cases of AOA. Similarly, the study of CF, max vs AOA involves an exhaustive investigation into the variation of AOA for the building with the worst limb position. The analysis reveals that changes in AOA have a more pronounced effect on CF, max compared to alterations in limb position. Interestingly, within the AOA range of 1.5 to 2.5, the CF, max consistently reaches a minimum across all models. However, the relationship between CF, max and the critical structural parameter ‘S' (representing limb position) remains less conclusive for the most significant AOAs.

Strong convergence of adaptive time-stepping schemes for the stochastic Allen–Cahn equation

Abstract It is known from Beccari et al. (2019) that the standard explicit Euler-type scheme (such as the exponential Euler and the linear-implicit Euler schemes) with a uniform timestep, though computationally efficient, may diverge for the stochastic Allen–Cahn equation. To overcome the divergence, this paper proposes and analyzes adaptive time-stepping schemes, which adapt the timestep at each iteration to control numerical solutions from instability. The a priori estimates in $\mathscr{C}(\mathscr{O})$-norm and $\dot{H}^{\beta }(\mathscr{O})$-norm of numerical solutions are established provided the adaptive timestep function is suitably bounded, which plays a key role in the convergence analysis. We show that the adaptive time-stepping schemes converge strongly with order $\frac{\beta }{2}$ in time and $\frac{\beta }{d}$ in space with $d$ ($d=1,2,3$) being the dimension and $\beta \in (0,2]$. Numerical experiments show that the adaptive time-stepping schemes are simple to implement and at a lower computational cost than a scheme with the uniform timestep.

The aryl hydrocarbon receptor (AHR) repressor limits expression of antimicrobial genes but not AHR-dependent genes in intestinal eosinophils.

Intestinal eosinophils express the aryl hydrocarbon receptor (AHR), an environmental sensor and ligand-activated transcription factor that responds to dietary or environmental ligands. AHR regulates tissue adaptation, survival, adhesion, and immune functions in intestinal eosinophils. The AHR repressor (AHRR) is itself induced by AHR and believed to limit AHR activity in a negative feedback loop. We analysed gene expression in intestinal eosinophils from WT and AHRR-KO mice and found that AHRR did not suppress most AHR-dependent genes. Instead, AHRR limited the expression of a distinct small set of genes involved in the innate immune response. These included S100 proteins, antimicrobial proteins and alpha-defensins. Using bone marrow-derived eosinophils we found that AHRR-KO eosinophils released more reactive oxygen species upon stimulation. This work shows that the paradigm of AHRR as a repressor of AHR transcriptional activity does not apply to intestinal eosinophils. Rather, AHRR limits the expression of innate immune response and antimicrobial genes, possibly to maintain an anti-inflammatory phenotype in eosinophils when exposed to microbial signals in the intestinal environment.

Quantised adaptive consensus control of heterogeneous nonlinear multi-agent systems under external disturbance

This paper is primarily devoted to the distributed consensus tracking control for heterogeneous nonlinear multi-agent systems (MASs) with a directed communication topology. Taking the considered heterogeneous nonlinear MASs own unknown nonlinear term and quantised input signals, the adaptive radial basis function neural networks (RBFNNs)-based approximator is utilised to tackle these interesting challenges. Next, considering the boundness of disturbances, the upper bound of time-varying disturbance is utilised in the controller design. Then, a distributed dynamic compensator is developed to complete coordination task, which only requires to exchange output information via the communication network. In addition, the compensator transforms the adaptive output consensus problem into asymptotic tracking problem, without needing extra stability conditions. Finally, by means of the Lyapunov stability theory, the satisfying result of the consensus error converging to zero asymptotically can be obtained. Through simulations, the effectiveness of the developed protocol is illustrated.

Childhood maltreatment exposure is differentially associated with transdiagnostic perinatal depression symptoms

History of childhood maltreatment (CM) is common and robustly associated with prenatal and postpartum (perinatal) depression. Given perinatal depression symptom heterogeneity, a transdiagnostic approach to measurement could enhance understanding of patterns between CM and perinatal depression. MethodsIn two independently collected samples of women receiving care at perinatal psychiatry clinics (n = 523 and n = 134), we categorized longitudinal symptoms of perinatal depression, anxiety, stress, and sleep into transdiagnostic factors derived from the Research Domain Criteria and depression literatures. We split the perinatal period into four time points. We conducted a latent profile analysis of transdiagnostic factors in each period. We then used self-reported history of CM (total exposure and subtypes of abuse and neglect) to predict class membership. ResultsA three-class solution best fit our data. In relation to positive adaptive functioning, one class had relatively more positive symptoms (high adaptive), one class had average values (middle adaptive), and one class had fewer adaptive symptoms (low adaptive). More total CM and specific subtypes associated with threat/abuse increased an individual's likelihood of being in the Low Adaptive class in both samples (ORs: 0.90–0.97, p < .05). LimitationsGeneralizability of our results was curtailed by 1) limited racial/ethnic diversity and 2) missing data. ConclusionsOur results support taking a person-centered approach to characterize the relationship between perinatal depression and childhood maltreatment. Given evidence that increased exposure to childhood maltreatment is associated with worse overall symptoms, providers should consider incorporating preventative, transdiagnostic interventions for perinatal distress in individuals with a history of childhood maltreatment.

A Missense Variant in HACE1 Is Associated with Intellectual Disability, Epilepsy, Spasticity, and Psychomotor Impairment in a Pakistani Kindred

Intellectual disability (ID), which affects around 2% to 3% of the population, accounts for 0.63% of the overall prevalence of neurodevelopmental disorders (NDD). ID is characterized by limitations in a person’s intellectual and adaptive functioning, and is caused by pathogenic variants in more than 1000 genes. Here, we report a rare missense variant (c.350T&gt;C; p.(Leu117Ser)) in HACE1 segregating with NDD syndrome with clinical features including ID, epilepsy, spasticity, global developmental delay, and psychomotor impairment in two siblings of a consanguineous Pakistani kindred. HACE1 encodes a HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), which is involved in protein ubiquitination, localization, and cell division. HACE1 is also predicted to interact with several proteins that have been previously implicated in the ID phenotype in humans. The p.(Leu117Ser) variant replaces an evolutionarily conserved residue of HACE1 and is predicted to be deleterious by various in silico algorithms. Previously, eleven protein truncating variants of HACE1 have been reported in individuals with NDD. However, to our knowledge, p.(Leu117Ser) is the second missense variant in HACE1 found in an individual with NDD.

Highlight of 2023: Unlocking the therapeutic potential of natural killer cells-advances in adaptive functions, cellular engineering and immunotherapy.

Natural killer (NK) cells possess potent cytotoxicity against infected and cancerous cells and hold promise in the development of new immunotherapies. This article for the Highlights of 2023 Series focuses on current advances in NK cell biology in cancerous and infectious settings and highlights opportunities for therapeutic interventions, including engineered NK cell therapies and advancements in feeder cell technologies.

The eTHINK Study: Cognitive and Behavioral Outcomes in Children with Hemophilia

ObjectiveTo assess cognitive, behavioral, and adaptive functions in children and young adults with hemophilia treated according to contemporary standards of care. Study designeTHINK was a US-based, prospective, cross-sectional, observational study (September 2018 through October 2019). Males (aged 1-21 years) with hemophilia A or B of any severity, with or without inhibitors, were eligible. Participants underwent neurological examinations and age-appropriate neuropsychological assessments, including standardized tests/ratings scales of early development, cognition, emotional/behavioral adjustment, and adaptive skills. Results551 males with hemophilia A (n=433) or B (n=101) were enrolled. Performance on cognitive tests was largely comparable with that of age-matched US population norms, although participants in certain age groups (4-5 and 10-21 years) performed worse on measures of attention and processing speed. Furthermore, adolescents and young adults and those with comorbid attention-deficit/hyperactivity disorder (ADHD; n=64) reported more adaptive and executive function problems in daily life. Incidence of ADHD in adolescents (21%) was higher than expected in the general population. ConclusionsIn general, males with hemophilia demonstrated age-appropriate intellectual, behavioral, and adaptive development. However, specific patient/age groups showed poorer attention performance and concerns for executive and adaptive development. This study established a normative data set for monitoring neurodevelopment in individuals with hemophilia and highlights the importance of screening and intervention for challenges with cognitive and adaptive skills in this population.

Automatic 2D/3D spine registration based on two-step transformer with semantic attention and adaptive multi-dimensional loss function

An essential technique for spine surgery guidance is the registration of intraoperative 2D X-ray with preoperative 3D CT, which enables the correlation of real-time imaging with surgical planning. Previous deep-learning-based methods generally need to convert 3D CT into a 2D projection for further registration, resulting in the loss of spatial information and failing to satisfy the clinical requirements of a large adaptation range and high precision. In this paper, a novel transformer-based two-step registration network is proposed to directly regress the transformation parameters without dimension reduction of the 3D CT. The spine information is extracted by reconstruction and segmentation modules and is further used in the registration network that utilizes both the original images and the spine features. Meanwhile, an adaptive multi-dimensional loss function containing both parameter-domain loss and graph-domain loss is designed to be more consistent with the registration mechanism. Both improvements expand the range of acceptable deformations and increase registration accuracy. We demonstrate the validity and generalizability of the proposed method by achieving state-of-the-art performance on both synthesized and clinical data with an average mTRE of 0.96 mm and 2.32 mm. Further, the high registration performance over a large deformation reflects the robustness of the methods in complex scenarios. The proposed methods enhance the tremendous potential of deep learning in spinal surgery navigation.

Adaptive Membership Functions and F-Transform

Adaptive Membership Functions and F-Transform

A Laplace operator-based active contour model with improved image edge detection performance

Active contour model (ACM) is an important branch in the field of image segmentation, since it adapts to different image types and scenes. However, traditional ACMs rely on local image information, which makes them sensitive to initial contours and time-consuming. In this paper, a Laplace operator based ACM (LOACM) with improved image edge detection performance is proposed. LOACM combines the global pre-fitting function which is constructed by using the image's second-order gradient information with the adaptive boundary indicator function to build a hybrid model. Its compact code size allows it to be executed on a wide range of edge devices. To substantiate the segmentation capability of the LOACM model, the BSD500 dataset was utilized for experimentation. The results indicate that LOACM exhibits excellent performance, with average IOU and DSC scores of 0.861 and 0.924 respectively. Additionally, it consistently handles processes within an average time of less than 0.3s, significantly less than that of comparative models, providing compelling evidence of LOACM's exceptional efficiency and precision.

Adaptive HEVC video steganograhpy based on PU partition modes

High EfficiencyVideoCoding (HEVC) −based steganography has gained attention as a prominent research focus. Especially, block structure based HEVC video steganography has received increasing attention due to commendable performance. However, current block structure- based steganography algorithms confront with challenges such as reduced coding efficiency and limited capacity. To avoid these problems, an adaptive video steganography algorithm based on Prediction Unit (PU) partition mode in I-frames is proposed. This is done through the analysis of the block division process and the visual distortion resulting from the modification of the PU partition mode in HEVC. The PU block structure is utilized as steganographic covers, and the Rate Distortion Optimization (RDO) technique is introduced to establish an adaptive distortion function for Syndrome-trellis code (STC). Further comparison is performed between the proposed method and the state-of-the-art steganography algorithms, confirming its advantages in embedding capacity, compression efficiency, visual quality, and resistance to video steganalysis.

Bending analysis of quasicrystal plates using adaptive radial basis function method

A novel mesh-free kernel method is presented for solving function interpolation problems and partial differential equations (PDEs). Despite the simplicity and accuracy of the radial basis function (RBF) method, two main difficulties have been identified: the selection of the scale or shape parameter and the ill-conditioning issue. To address these challenges, an effective condition number (ECN) strategy is proposed for the scale parameter selection, utilizing the ill-conditioning issue to minimize errors. The study demonstrates that this method performs exceptionally well with severely ill-conditioned matrices, making it suitable challenging engineering problems. However, when the problem is severely ill-conditioned, an accurate and efficient method for determining the minimal singular values used in the ECN formulation is required. To tackle this, we utilize an efficient algorithm called minsv, which specifically computes the minimal singular value. The significance of accurately computing the smallest singular value is demonstrated through two interpolation examples, involving non-smooth and smooth test functions with various RBFs and data points. Furthermore, the RBF method is applied to solve a quasicrystal problem, which presents a challenging engineering problem with four unknown parameters, and excellent results are obtained. Finally, we illustrate that using MATLAB’s svd function can potentially produce completely incorrect minimal singular values.

Developmental Profile in Children Aged 3–6 Years: Down Syndrome vs. Autism Spectrum Disorder

This research aims to compare the developmental profiles of children with autism spectrum disorder (ASD) and children with Down Syndrome (DS) between the ages of 3 and 6 years. The study examines whether these developmental disorders share common developmental milestones or exhibit distinctive characteristics. A total of 43 children, 23 with DS and 20 with ASD, participated in the study. Cognitive and language skills were assessed using standardized tools, including the Battelle Developmental Inventory, Reynell Developmental Language Scales III, and NEPSY-II battery. The results indicated that children with ASD outperformed children with DS in the areas of fine motor skills, gross motor skills, and communication. Additionally, children with ASD demonstrated higher scores in language comprehension and expressive language, compared to children with DS. Significant correlations were found between motor skills and communication abilities. Neuropsychological evaluations revealed significant differences between the two groups in various tasks, such as the comprehension of instructions, body part naming and identification, and recognition of emotions. These findings contribute to our understanding of the similarities and differences between ASD and DS, shedding light on the dissociation between cognition and language and its impact on adaptive functioning in these populations.

한국 저교육 노인에게 적용 가능한 개념화 능력 평가 도구의 개발 및 타당화

In this study, we developed a proverb test as a measure for assessing higher-order cognitive functions in Korean older adults and explored its psychometric properties. Specifically, we aimed to investigate the applicability of the proverb test as a measure for conceptualization ability within the context of predominantly low-educated elderly population in South Korea. Twenty items were selected, taking into consideration familiarity, abstract thinking requirement, and item adequacy. The test included both open-ended and closed questions to ensure an applicability of the test among low-educated older adults. The results indicated satisfactory internal consistency for both versions of the test. Furthermore, the test demonstrated a high correlation with measures assessing higher-order thinking while exhibiting a relatively lower correlation with measures for memory and attention, thus confirming its convergent and discriminant validity. Also, significant associations were observed between the test scores and measure of daily living functions, suggesting that proverb test scores may be useful in predicting overall adaptive functioning. Additionally, literate and illiterate group showed significant differences in proverb test scores. These findings suggest that the proverb test can adequately be applied as a measure of conceptualization ability in the Korean older adults.