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Behavior is one of the important factors reflecting the health status of dairy cows, and when dairy cows encounter health problems, they exhibit different behavioral characteristics. Therefore, identifying dairy cow behavior not only helps in assessing their physiological health and disease treatment but also improves cow welfare, which is very important for the development of animal husbandry. The method of relying on human eyes to observe the behavior of dairy cows has problems such as high labor costs, high labor intensity, and high fatigue rates. Therefore, it is necessary to explore more effective technical means to identify cow behaviors more quickly and accurately and improve the intelligence level of dairy cow farming. Automatic recognition of dairy cow behavior has become a key technology for diagnosing dairy cow diseases, improving farm economic benefits and reducing animal elimination rates. Recently, deep learning for automated dairy cow behavior identification has become a research focus. However, in complex farming environments, dairy cow behaviors are characterized by multiscale features due to large scenes and long data collection distances. Traditional behavior recognition models cannot accurately recognize similar behavior features of dairy cows, such as those with similar visual characteristics, i.e., standing and walking. The behavior recognition method based on 3D convolution solves the problem of small visual feature differences in behavior recognition. However, due to the large number of model parameters, long inference time, and simple data background, it cannot meet the demand for real-time recognition of dairy cow behaviors in complex breeding environments. To address this, we developed an effective yet lightweight model for fast and accurate dairy cow behavior feature learning from video data. We focused on four common behaviors: standing, walking, lying, and mounting. We recorded videos of dairy cow behaviors at a dairy farm containing over one hundred cows using surveillance cameras. A robust model was built using a complex background dataset. We proposed a two-pathway X3DFast model based on spatiotemporal behavior features. The X3D and fast pathways were laterally connected to integrate spatial and temporal features. The X3D pathway extracted spatial features. The fast pathway with R(2 + 1)D convolution decomposed spatiotemporal features and transferred effective spatial features to the X3D pathway. An action model further enhanced X3D spatial modeling. Experiments showed that X3DFast achieved 98.49% top-1 accuracy, outperforming similar methods in identifying the four behaviors. The method we proposed can effectively identify similar dairy cow behaviors while improving inference speed, providing technical support for subsequent dairy cow behavior recognition and daily behavior statistics. [ABSTRACT FROM AUTHOR]

In coal mining, solid backfilling technology is widely used. However, its efficiency is seriously hindered by the following two factors. Firstly, the process flow of the solid backfilling operation is more complicated in the back, and the spatiotemporal linkage (SPL) between actions of the cylinders powering each support and between hydraulic supports in the whole face lacks continuity. Secondly, the coal mining process in the front has a higher level of intelligence and technical maturity than the backfilling operation in the back, the latter permanently staying behind the former. To this end, the present study investigates the SPL of the mining and backfilling operations for single supports in the working and whole faces. The SPL of cylinder actions is analyzed for intelligent backfilling using hydraulic supports. We also investigate the SPL of the positions of each piece of key equipment involved in different steps of intelligent backfilling in the whole face. Formulas are derived for calculating the time required to complete the cyclic hydraulic support movement–discharge–filling operation for single supports and the whole face. The key factors influencing the time required to complete a hydraulic support movement–discharge–filling cycle are analyzed. On this basis, a backfilling efficiency optimization scheme is proposed. It envisages reducing the number of tampings and time gaps in actions of single supports and cylinders, increasing the number of hydraulic supports in parallel operation, and intelligent upgrading of the backfilling operation. These findings help synchronize coal mining and backfilling operations. [ABSTRACT FROM AUTHOR]

It is now well understood that HIV-positive individuals, even those under effective ART, tend to develop a spectrum of cognitive, motor, and/or mood conditions which are contemporarily referred to as HIV-associated neurocognitive disorder (HAND), and which is directly related to HIV-1 infection and HIV-1 replication in the central nervous system (CNS). As HAND is known to induce difficulties associated with attention, concentration, and memory, it is thus legitimate and pertinent to speculate upon the possibility that HIV infection may well influence human cognition and intelligence. We therefore propose herein to review the concept of intelligence, the concept of cells of intelligence, the influence of HIV on these particular cells, and the evidence pointing to differences in observed intelligence quotient (IQ) scores between HIV-positive and HIV-negative individuals. Additionally, cumulative research evidence continues to draw attention to the influence of the gut on human intelligence. Up to now, although it is known that HIV infection profoundly alters both the composition and diversity of the gut microbiota and the structural integrity of the gut, the influence of the gut on intelligence in the context of HIV infection remains poorly described. As such, we also provide herein a review of the different ways in which HIV may influence human intelligence via the gut-brain axis. Finally, we provide a discourse on perspectives related to HIV and human intelligence which may assist in generating more robust evidence with respect to this issue in future studies. Our aim is to provide insightful knowledge for the identification of novel areas of investigation, in order to reveal and explain some of the enigmas related to HIV infection. [ABSTRACT FROM AUTHOR]

Although relatively specific anatomo-electro-clinical features of temporal lobe epilepsy (TLE) with bilateral ictal involvement (bitemporal epilepsy—BTLE) have been described, differentiating between BTLE and unilateral TLE (UTLE) remains challenging. Surgery is often the treatment of choice for drug-resistant UTLE, whereas its use is more controversial in BTLE. It is currently unclear whether neuropsychological assessment can contribute to the differential diagnosis. We retrospectively reviewed the neuropsychological evaluation of 46 consecutive patients with refractory TLE. Eighteen patients were diagnosed with BTLE on the basis of ictal electro-clinical data, in particular a video EEG recording of at least one seizure simultaneously involving the two temporal lobes without the possibility of lateralizing its onset or at least two different seizures independently arising from the two temporal lobes. Twenty-eight patients were classified as UTLE. Presurgery evaluation data were used in this study. Compared with UTLE, BTLE was associated with a lower intelligence quotient (IQ) and more severe impairment in long-term memory, the latter remaining significant even after controlling for IQ. No significant differences were found between right and left UTLE. In conclusion, BTLE and UTLE are associated with relatively distinct neuropsychological profiles, further supporting their classification as different disorders within the TLE spectrum. [ABSTRACT FROM AUTHOR]

In complex citrus orchard environments, light changes, branch shading, and fruit overlapping impact citrus detection accuracy. This paper proposes the citrus detection model YOLO-DCA in complex environments based on the YOLOv7-tiny model. We used depth-separable convolution (DWConv) to replace the ordinary convolution in ELAN, which reduces the number of parameters of the model; we embedded coordinate attention (CA) into the convolution to make it a coordinate attention convolution (CAConv) to replace the ordinary convolution of the neck network convolution; and we used a dynamic detection head to replace the original detection head. We trained and evaluated the test model using a homemade citrus dataset. The model size is 4.5 MB, the number of parameters is 2.1 M, mAP is 96.98%, and the detection time of a single image is 5.9 ms, which is higher than in similar models. In the application test, it has a better detection effect on citrus in occlusion, light transformation, and motion change scenes. The model has the advantages of high detection accuracy, small model space occupation, easy application deployment, and strong robustness, which can help citrus-picking robots and improve their intelligence level. [ABSTRACT FROM AUTHOR]

Children who experience adversities in the pre-perinatal period are at increased risk of developing impairment later in life, despite the absence of overt brain and neurological abnormalities. However, many of these children exhibit sequelae several years after a period of normal appearance. As a result, the need for reliable developmental assessments for the early detection of infants at high risk of adverse neurodevelopmental outcomes has emerged. The Griffiths Mental Developmental Scales have a promising but poorly explored prognostic ability. This longitudinal study evaluated the predictive power of the Griffiths Mental Developmental Scales at 12 and 24 months on the cognitive and neuropsychological profile at 6 years of age in a sample of 70 children with a history of prematurity or perinatal asphyxia but without brain and neurological abnormalities. We found that the Griffiths Mental Developmental Scales at 24 months had good predictive ability on the intelligence quotient at 6 years and the capacity to predict some neuropsychological performances. On the other hand, the Griffiths Mental Developmental Scale at 12 months was not associated with the performance at 6 years or 24 months. Conclusion: Data on brain development converge to indicate that the first two years of age represent a critical stage of development, particularly for children experiencing mild pre-perinatal adversities who are thought to exhibit white matter dysmaturity. For this reason, this age is crucial for identifying which children are at major risk, leaving enough time to intervene before overt deficits become apparent. Brain development in the first 2 years could explain the limited reliability of early neurodevelopmental testing. What is Known: • Pre-perinatal adversities increase the risk of developing neurodevelopmental disorders. • The predictive ability of the Griffith scale is poorly explored in low-grade conditions. What is New: • The predictive ability of the Griffith scale has been investigated in low-risk children. • A complete neuropsychological profile could offer a more accurate prediction than the intellectual quotient. [ABSTRACT FROM AUTHOR]

Aims: To investigate cortical organization in brain magnetic resonance imaging (MRI) of preterm‐born adults using percent contrast of gray‐to‐white matter signal intensities (GWPC), which is an in vivo proxy measure for cortical microstructure. Methods: Using structural MRI, we analyzed GWPC at different percentile fractions across the cortex (0%, 10%, 20%, 30%, 40%, 50%, and 60%) in a large and prospectively collected cohort of 86 very preterm‐born (<32 weeks of gestation and/or birth weight <1500 g, VP/VLBW) adults and 103 full‐term controls at 26 years of age. Cognitive performance was assessed by full‐scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale. Results: GWPC was significantly decreased in VP/VLBW adults in frontal, parietal, and temporal associative cortices, predominantly in the right hemisphere. Differences were pronounced at 20%, 30%, and 40%, hence, in middle cortical layers. GWPC was significantly increased in right paracentral lobule in VP/VLBW adults. GWPC in frontal and temporal cortices was positively correlated with birth weight, and negatively with duration of ventilation (p < 0.05). Furthermore, GWPC in right paracentral lobule was negatively correlated with IQ (p < 0.05). Conclusions: Widespread aberrant gray‐to‐white matter contrast suggests lastingly altered cortical microstructure after preterm birth, mainly in middle cortical layers, with differential effects on associative and primary cortices. [ABSTRACT FROM AUTHOR]

Objective To study the intellectual level and the factors influencing the intelligence in children aged 616 years with attention deficit hyperactivity disorder (ADHD). Methods A retrospective study was conducted on 2 861 children who were diagnosed with ADHD according to the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition between October 2014 and September 2022 at Henan Children's Hospital. The Wechsler Intelligence Scale for Children-Fourth Edition was used to assess the intellectual levels of the ADHD children. Based on intelligence quotient (IQ) scores, the intellectual levels were classified into five categories: borderline (70-79), low average (80-89), average (90-109), high average (110-119), and superior (5120). The intellectual levels among the children of different genders, grades, and parental education levels were compared. Results Among the 2 861 ADHD children, 569 (19.89%) were classified as borderline, 846 (29.57%) as low average, 1 304 (45.58%) as average, 111 (3.88%) as high average, and 31 (1.08%) as superior. The boys had lower scores in working memory, processing speed, and overall IQ than the girls (P<0.05). There were significant differences in perceptual reasoning, working memory, processing speed, and overall IQ scores among different grade groups (P<0.05). The scores in language comprehension, perceptual reasoning, working memory, processing speed, and overall IQ were found to be associated with parental education level in ADHD children (P<0.05). Conclusions The proportion of ADHD children with low average and borderline intellectual levels is relatively high. The IQ level of ADHD children is influenced by gender, grade level and parental education level. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper was to investigate the relationships among the intellectual ability of artificial intelligence (AI), cognitive emotional processes and the positive and negative reactions of human members. The authors also examined the moderating role of AI status in teams. Design/methodology/approach: The authors designed an experiment and recruited 120 subjects who were randomly distributed into one of three groups classified by the upper, middle and lower organization levels of AI in the team. The findings in this study were derived from subjects' self-reports and their performance in the experiment. Findings: Regardless of the position held by AI, human members believed that its intelligence level is positively correlated with dependence behavior. However, when the AI and human members are at the same level, the higher the intelligence of AI, the more likely it is that its direct interaction with team members will lead to conflicts. Research limitations/implications: This paper only focuses on human–AI harmony in transactional work in hybrid teams in enterprises. As AI applications permeate, it should be considered whether the findings can be extended to a broader range of AI usage scenarios. Practical implications: These results are helpful for understanding how to improve team performance in light of the fact that team members have introduced AI into their enterprises in large quantities. Originality/value: This study contributes to the literature on how the intelligence level of AI affects the positive and negative behaviors of human members in hybrid teams. The study also innovatively introduces "status" into hybrid organizations. [ABSTRACT FROM AUTHOR]

The knowledge of the effects of organophosphate flame retardants on children's neurodevelopment is limited. The purpose of the present research is to evaluate the association between exposure to organophosphate flame retardants and children's neurodevelopment in two European cohorts involved in the Human Biomonitoring Initiative Aligned Studies. The participants were school-aged children belonging to the Odense Child Cohort (Denmark) and the PCB cohort (Slovakia). In each cohort, the children's neurodevelopment was assessed through the Full-Scale Intelligence Quotient score of the Wechsler Intelligence Scale for Children, using two different editions. The children's urine samples, collected at one point in time, were analyzed for several metabolites of organophosphate flame retardants. The association between neurodevelopment and each organophosphate flame retardant metabolite was explored by applying separate multiple linear regressions based on the approach of MM-estimation in each cohort. In the Danish cohort, the mean ± standard deviation for the neurodevelopment score was 98 ± 12; the geometric mean (95% confidence interval (95% CI)) of bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) standardized by creatinine (crt) was 0.52 µg/g crt (95% CI = 0.49; 0.60), while that of diphenyl phosphate (DPHP) standardized by crt was 1.44 µg/g crt (95% CI = 1.31; 1.58). The neurodevelopment score showed a small, negative, statistically imprecise trend with BDCIPP standardized by crt (β = −1.30; 95%CI = −2.72; 0.11; p-value = 0.07) and no clear association with DPHP standardized by crt (β = −0.98; 95%CI = −2.96; 0.99; p-value = 0.33). The neurodevelopment score showed a negative trend with BDCIPP (β = −1.42; 95% CI = −2.70; −0.06; p-value = 0.04) and no clear association with DPHP (β = −1.09; 95% CI = −2.87; 0.68; p-value = 0.23). In the Slovakian cohort, the mean ± standard deviation for the neurodevelopment score was 81 ± 15; the geometric mean of BDCIPP standardized by crt was 0.18 µg/g crt (95% CI = 0.16; 0.20), while that of DPHP standardized by crt was 2.24 µg/g crt (95% CI = 2.00; 3.52). The association of the neurodevelopment score with BDCIPP standardized by crt was −0.49 (95%CI = −1.85; 0.87; p-value = 0.48), and with DPHP standardized by crt it was −0.35 (95%CI = −1.90; 1.20; p-value = 0.66). No clear associations were observed between the neurodevelopment score and BDCIPP/DPHP concentrations that were not standardized by crt. No clear associations were observed with bis(1-chloro-2-propyl) phosphate (BCIPP) in either cohort, due to the low detection frequency of this compound. In conclusion, this study provides only limited evidence of an inverse association between neurodevelopment and exposure to BDCIPP and DPHP. The timing of exposure and effect modification of other organophosphate flame retardant metabolites and other substances should be the subject of further investigations that address this scientific hypothesis. [ABSTRACT FROM AUTHOR]

The Coronavirus (2019) explosion has put every economic region at risk. Educators are not an exception. The terrible result of lockdown in every area of the world, including India, has led to the protracted closure of schools and institutions, leaving education in shambles. The process of teaching and learning became online. The current research study identifies the multiple factors affecting online education and analyses the issues school educators face while teaching. A structured questionnaire was administered to 118 school teachers serving on boards and government schools across the Bengaluru North area, Karnataka. Results of the study indicate that teachers are using various appropriate methods in delivering online teaching. The study helps educational institutions and policymakers understand multiple problems with the teaching community in teaching virtually, thereby finding feasible options to make the inevitable online teaching system more effective. [ABSTRACT FROM AUTHOR]

The trend of digital information transformation has become a topic of interest. Many data are threatening; thus, protecting such data from attackers is considered an essential process. Recently, a new methodology for data concealing has been suggested by researchers called coverless steganography. Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image. This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems. The system uses the secret message to generate the stego image in the form of one of the Intelligence Quotient (IQ) games, themaze. Firstly, a full grid is generatedwith several specific rows and columns determined fromthe number of bits of the secretmessage. Then, these bits are fed to the full grid to formthemaze game stego image. Finally, the generatedmaze game stego image is sent to the recipient. The experimental results, using the Bit Error Rate (BER), were conducted, and confirmed the strength of this system represented by a high capacity, perfect performance, robustness, and stronger hiding system compared with existing coverless steganography systems. [ABSTRACT FROM AUTHOR]

Excessive fluoride (F) intake during infancy and early childhood causes some irreparable structural and functional changes in memory, learning and intellectual deficits. The aim of this study was risk assessment of F in drinking water and correlation with children's Intelligence Quotient in rurals of Bushehr province. This cross-sectional study was conducted among 8-12-years-old school children of 12 rurals (30 points) in Bushehr province, Iran on 140 children. The F levels were determined by using UV-Vis Shimadzu (UV-1601, PC) spectrophotometer. Children's intelligence was measured using the Raven's Standard Progressive Matrices. Data was statistically analyzed using the ANOVA test and Pearson correlation by Statistical Analysis Software (SPSS v. 23). The mean concentration of F was ranged from 0.55 to 8.63 mg/l. Most of the children's who were assessed were in categories D and E of Raven's Test. There are a negative and significant correlation between the IQ and F concentration level in drinking water (r= - 0.279, p-value= 0.002). But, no significant correlation observed between the IQ and sex of children's (r= -0.084, p-value= 0.361). Results supports that children exposed to F are at risk for impaired development of intelligence. For the benefit and health of future generations, immediate and basic attention needs to be focused on this significant public health problem. [ABSTRACT FROM AUTHOR]

With the increasing level of precision and intelligence in the aquaculture, real-time mastery of the growth status of aquaculture individuals has become an important means to improve aquaculture efficiency and save resources and the environment. Therefore, accurate individual recognition of underwater fish has become one of the key technologies for precision aquaculture. In order to cope with the impact of the complex underwater environment on the recognition accuracy, this paper proposes a coarse and fine-grained features learning method for individual fish recognition. The method consists of a coarse-grained feature learning network and two fine-grained feature learning networks. The trunk of the network is responsible for learning coarse-grained features of the fish, the first branch learns fine-grained features of fish from head, body, and tail, and the second branch learns fine-grained features of fish from upper and lower fins. we supplemented different levels of noise and attack to the training set of fine-grained features and enriched the grayscale variation to cope with the complexity and variability of the underwater environment. The simulation experimental results show that the method achieves more than 96.7% in key indicators such as Rank-1 and Rank-5, and also performs well in other fish recognition tasks with certain generalization. [ABSTRACT FROM AUTHOR]

We investigate the notion that basic visual information is acting as a building block for more complex cognitive processes in humans. Specifically, we measured individual visual orientation discrimination thresholds to report significant correlations against the total standardised intelligence quotient (IQ), verbal-IQ and non-verbal IQ scores evaluated using the Wechsler Abbreviated Scale of Intelligence Second Edition (WASI-II) test battery comprising Verbal Reasoning, Block Design, Similarities and Matrix Reasoning subtests (N = 92). A multiple linear regression analysis showed that participants' performance in our visual discrimination task, could be explained only by individual scores in Verbal Reasoning which quantifies the ability to comprehend and describe words and Matrix Reasoning, which evaluates general visual processing skills including abstract and spatial perception. Our results demonstrate that low-level visual abilities and high-level cognitive processes are more tightly interwoven together than previously thought and this result could pave the way for further research on how cognition can be defined by basic sensory processes. [ABSTRACT FROM AUTHOR]

The design of the front face of a truck can directly affect the user's sensory evaluation of the vehicle. Therefore, based on Kansei Engineering theory and deep learning technology, this paper proposes an intelligent design method for the rapid generation of truck front face modeling solutions driven by user images. First, through Kansei Engineering's relevant experimental methods and scientific data analysis process, the emotional image of the truck's front face is deeply excavated and positioned, and the corresponding relationship between the characteristics of the truck's front face and the user's emotional image cognition is explored. Then, we used the generative confrontation network to integrate the user's emotional image of the front face of the truck into the intelligent and rapid generation process of the new design scheme of the front face of the truck. Finally, the physiological data of the Electroencephalogram (EEG) experiment are used to evaluate the degree of objective matching between the generated modeling design scheme and the expected image. The purpose of this research is to improve the efficiency, reliability, and intelligence level of truck front face design, and to achieve a more personalized, precise, and high-quality design. This helps to improve the conformity of the modeling design scheme under specific image semantics. [ABSTRACT FROM AUTHOR]

Existing research on automatic river network classification methods has difficulty scientifically quantifying and determining feature threshold settings and evaluating weights when calculating multi-indicator features of the local and overall structures of river reaches. In order to further improve the accuracy of river network classification and evaluate the feature weight, this paper proposes an automatic grading method for river networks based on ensemble learning in CatBoost. First, the graded river network based on expert knowledge is taken as the case; with the support of the existing case results, a total of eight features from the semantic, geometric, and topological aspects of the river network were selected for calculation. Second, the classification model, obtained through learning and training, was used to calculate the classification results of the main stream and tributaries of the river reach to be classified. Furthermore, the main stream river reaches were connected, and the main stream rivers at different levels were hierarchized to achieve river network classification. Finally, the Shapley Additive explanation (SHAP) framework for interpreting machine learning models was introduced to test the influence of feature terms on the classification results from the global and local aspects, so as to improve the interpretability and transparency of the model. Performance evaluation can determine the advantages and disadvantages of the classifier, improve the classification effect and practicability of the classifier, and improve the accuracy and reliability of river network classification. The experiment demonstrates that the proposed method achieves expert-level imitation and has higher accuracy for identifying the main stream and tributaries of river networks. Compared with other classification algorithms, the accuracy was improved by 0.85–5.94%, the precision was improved by 1.82–9.84%, and the F1_Score was improved by 0.8–5.74%. In this paper, CatBoost is used for river network classification for the first time, and SHAP is used to explain the influence of characteristics, which improves the accuracy of river network classification and enhances the interpretability of the classification method. By constructing a reasonable hierarchy, a better grading effect can be achieved, and the intelligence level of automatic grading of river networks can be further improved. [ABSTRACT FROM AUTHOR]

Plane-wave imaging (PWI) is a high-frame-rate imaging technique that sacrifices image quality. Deep learning can potentially enhance plane-wave image quality, but processing complex in-phase and quadrature (IQ) data and suppressing incoherent signals pose challenges. To address these challenges, we present a complex transformer network (CTN) that integrates complex convolution and complex self-attention (CSA) modules. The CTN operates in a four-step process: delaying complex IQ data from a 0° single-angle plane wave for each pixel as CTN input data; extracting reconstruction features with a complex convolution layer; suppressing irrelevant features derived from incoherent signals with two CSA modules; and forming output images with another complex convolution layer. The training labels are generated by minimum variance (MV). Simulation, phantom and in vivo experiments revealed that CTN produced comparable- or even higher-quality images than MV, but with much shorter computation time. Evaluation metrics included contrast ratio, contrast-to-noise ratio, generalized contrast-to-noise ratio and lateral and axial full width at half-maximum and were –11.59 dB, 1.16, 0.68, 278 μm and 329 μm for simulation, respectively, and 9.87 dB, 0.96, 0.62, 357 μm and 305 μm for the phantom experiment, respectively. In vivo experiments further indicated that CTN could significantly improve details that were previously vague or even invisible in DAS and MV images. And after being accelerated by GPU, the CTN runtime (76.03 ms) was comparable to that of delay-and-sum (DAS, 61.24 ms). The proposed CTN significantly improved the image contrast, resolution and some unclear details by the MV beamformer, making it an efficient tool for high-frame-rate imaging. [ABSTRACT FROM AUTHOR]

Aim: Using a visual psychophysical paradigm, we sought to assess motion and form coherence thresholds as indices of dorsal and ventral visual stream processing respectively, in individuals with cerebral visual impairment (CVI). We also explored potential associations between psychophysical assessments and brain lesion severity in CVI. Method: Twenty individuals previously diagnosed with CVI (mean age = 17 years 11 months [SD 5 years 10 months]; mean Verbal IQ = 86.42 [SD 35.85]) and 30 individuals with neurotypical development (mean age = 20 years 1 month [SD 3 years 8 months]; mean Verbal IQ = 110.05 [SD 19.34]) participated in the study. In this two‐group comparison, cross‐sectional study design, global motion, and form pattern coherence thresholds were assessed using a computerized, generalizable, self‐administrable, and response‐adaptive psychophysical paradigm called FInD (Foraging Interactive D‐prime). Results: Consistent with dorsal stream dysfunction, mean global motion (but not form) coherence thresholds were significantly higher in individuals with CVI compared to controls. No statistically significant association was found between coherence thresholds and lesion severity. Interpretation: These results suggest that the objective assessment of motion and form coherence threshold sensitivities using this psychophysical paradigm may be useful in helping to characterize perceptual deficits and the complex clinical profile of CVI. What this paper adds: In participants with cerebral visual impairment (CVI), motion (but not form) coherence thresholds were significantly higher compared to controls.These psychophysical results support the notion of dorsal stream dysfunction in CVI. [ABSTRACT FROM AUTHOR]

An increasing number of neuropsychologists are evaluating children with congenital heart disease (CHD). When conceptualizing results, the provider must consider medical risks such as abnormal neuroimaging and comorbidities, along with social risks such as socioeconomic status. The aim of the current study was to examine the influence of parent income and education on IQ and achievement across race groups in adolescents with CHD, while also accounting for medical risk (e.g., gestational age, number of ventricles, neuroimaging). This is a single-center cross-sectional study, including 92 children ages 12–19 years (median 14.9 years; 59% male; 71% White; 29% Black) with high risk CHD (i.e., cardiac surgery <12 months) who were referred for a neuropsychological evaluation. Retrospective data were retrieved from a larger clinical registry. Patients completed an intellectual assessment (WISC-V; WAIS-IV; WASI-II), Word Reading and Math Calculation tests. Parents completed questionnaires assessing the family environment [income, parent education]. Results revealed significant differences in IQ when comparing children who were Black versus White (11.4 point IQ difference); however, around 70% of this variance was explained by parent income and education. Medical variables accounted for 12% of the variance in IQ. For academics, parent income and education accounted for 91.5% and 78.8% of the variance in race group differences for reading and math, respectively. Medical risk and sex explained 11.7% and 14.7% of the variance in reading and math, respectively. Findings suggest that sociodemographic factors should be weighed heavily during the neuropsychological evaluation, including prioritizing risk, making recommendations, and facilitating referrals. [ABSTRACT FROM AUTHOR]

Purpose: Sickle cell disease (SCD) is a multisystemic disease that results in diverse clinical manifestations in the form of acute and chronic complications. This study aims to assess the academic achievements of patients with SCD.Methods and Materials: A cross-sectional study was a study conducted among adult patients with SCD from the eastern province of Saudi Arabia, where SCD is more widespread than in other regions.Results: A total of ninety patients with SCD, whose median age was 32.33 ± 11.84, were retrospectively evaluated. Of the total number, 32 (35.5%) did not obtain a secondary higher education certificate, and five (3.3%) were illiterate. Sixty-three (70%) of the patients were female, indicating no significant association between gender and education level (p-value > 0.05). The patients' mean annual hospitalizations and emergency visits totaling 4.7 and 8.43, respectively, were not significantly associated with education (p-value > 0.05). Throughout the patients' lives, mean blood transfusions and ICU admissions occurred 6.29 and 2.75 times, respectively, which were not significantly associated with education level (p-value > 0.05). However, education was inversely proportional to a history of splenectomy and cholecystectomy (p < 0.05). Laboratory parameters (hemoglobin level, WBC, platelets, and hemoglobin F) showed no significant associations with education level (p-value > 0.05). Patients with sickle-thalassemia exhibited a trend of being better-educated than those without the diseases, but the difference did not reach statistical significance (p-value > 0.05). A linear regression analysis revealed no significant associations among clinical and laboratory parameters.Conclusion: SCD is a multisystemic disease that impacts socioeconomic status, learning ability, and academic achievements. More research is needed to identify factors that predict poor performance. Additionally, intelligence quotient (IQ) and cognitive assessment should be incorporated into early screening programs for SCD in order to implement preventive measures and a thorough investigation of underlying causes. [ABSTRACT FROM AUTHOR]

A decline in intellectual functioning (intelligence quotient [IQ]) is often observed following more severe forms of traumatic brain injury (TBI) and is a useful index for long-term outcome. Identifying brain correlates of IQ can serve to inform developmental trajectories of behavior in this population. Using magnetic resonance imaging (MRI), we examined the relationship between intellectual abilities and patterns of cortical thickness in children with a history of TBI or with orthopedic injury (OI) in the chronic phase of injury recovery. Participants were 47 children with OI and 58 children with TBI, with TBI severity ranging from complicated-mild to severe. Ages ranged from 8 to 14 years old, with an average age of 10.47 years, and an injury-to-test range of ∼1–5 years. The groups did not differ in age or sex. The intellectual ability estimate (full-scale [FS]IQ-2) was derived from a two-form (Vocabulary and Matrix Reasoning subtests) Wechsler Abbreviated Scale of Intelligence (WASI). MRI data were processed using the FreeSurfer toolkit and harmonized across data collection sites using neuroComBat procedures, while holding demographic features (i.e., sex, socioeconomic status [SES]), TBI status, and FSIQ-2 constant. Separate general linear models per group (TBI and OI) and a single interaction model with all participants were conducted with all significant results withstanding correction for multiple comparisons via permutation testing. Intellectual ability was higher (p < 0.001) in the OI group (FSIQ-2 = 110.81) than in the TBI group (FSIQ-2 = 99.81). In children with OI, bi-hemispheric regions, including the right pre-central gyrus and precuneus and bilateral inferior temporal and left occipital areas were related to IQ, such that higher IQ was associated with thicker cortex in these regions. In contrast, only cortical thickness in the right pre-central gyrus and bilateral cuneus positively related to IQ in children with TBI. Significant interaction effects were found in the bilateral temporal, parietal, and occipital lobes and left frontal regions, indicating that the relationship between IQ and cortical thickness differed between groups in these regions. Changes in cortical associations with IQ after TBI may reflect direct injury effects and/or adaptation in cortical structure and intellectual functioning, particularly in the bilateral posterior parietal and inferior temporal regions. This suggests that the substrates of intellectual ability are particularly susceptible to acquired injury in the integrative association cortex. Longitudinal work is needed to account for normal developmental changes and to investigate how cortical thickness and intellectual functioning and their association change over time following TBI. Improved understanding of how TBI-related cortical thickness alterations relate to cognitive outcome could lead to improved predictions of outcome following brain injury. [ABSTRACT FROM AUTHOR]

Against the background of the war in Ukraine, the COVID-19 pandemic has waned from public consciousness as the threat of the virus to health is outweighed by safety concerns during the war. Pandemic restrictions in the European region are being lifted despite low vaccination rates in Central and Eastern European countries and a lack of effective containment strategies. However, Central and Eastern European countries are influenced most by the flow of refugees from neighboring Ukraine where a triple health crisis occurs: an overloaded health system, an ongoing COVID-19 pandemic, and the war. The aim: to review the progress regarding viral surveillance technologies that use genomics, digital, and informational tools, to find the gap in the literature and formulate policy recommendations for continuing surveillance in the context of permacrisis. Unstructured search was conducted through scientific (PubMed and Google Scholar databases) and grey literature using the keywords. The paper highlights aspects of war-related problems of infectious diseases control in Europe, new challenges in healthcare connected with COVID-19 pandemic and war in Ukraine and provides discussion on the role of innovative surveillance systems in tackling infection outbreaks (with COVID-19 pandemic as an example). The paper overviews perspectives of the implementation of the discussed measures. Future COVID-19 outbreaks and new variants are possible. Complex adaptive system models, new tools, and the next level of health and digital intelligence are needed to provide timely and valuable insights. Combining lessons learned from the COVID-19 pandemic, the threat of war, and the need for continuous outbreaks surveillance, new public health and digital intelligence tools must be designed and implemented at regional, European, and global levels. [ABSTRACT FROM AUTHOR]

This study investigated if the association between childhood maltreatment and cognition among psychosis patients and community controls was partially accounted for by genetic liability for psychosis. Patients with first-episode psychosis (N = 755) and unaffected controls (N = 1219) from the EU-GEI study were assessed for childhood maltreatment, intelligence quotient (IQ), family history of psychosis (FH), and polygenic risk score for schizophrenia (SZ-PRS). Controlling for FH and SZ-PRS did not attenuate the association between childhood maltreatment and IQ in cases or controls. Findings suggest that these expressions of genetic liability cannot account for the lower levels of cognition found among adults maltreated in childhood. [ABSTRACT FROM AUTHOR]

The aim of our study is to examine the predictive levels between pre-service teachers' intelligence domains and Biophilia levels in the theory of multiple intelligences. A quantitative approach has been adopted in the study and the model of the research is the relational screening model. The study group of this research consists of 574 (390 female, 184 male) pre-service teachers. The sampling method of our research is the convenient sampling method. The data collection tools of the research were "The Scale for Determining the Levels of Biophilia for Pre-service Teachers" developed by Sefali and Ozay Kose (2022) and the "Multiple Intelligence Inventory" developed by Ozden (2003). The study determined that Biophilia Levels 1, 2, and 4 are significant predictors of verbal intelligence domain. It was determined that Biophilia Level 1 and Biophilia Level 3 are significant predictors of Logical intelligence. It was determined that Biophilia Level 1 and Biophilia Level 4 are significant predictors of the visual intelligence domain. Biophilia Level 1 is a positive significant predictor of the musical intelligence domain; Biophilia Level 3 is a negative considerable predictor of ID. In addition, it was determined that Biophilia Level 2 has approximate significance in predicting ID. Biophilia Level 1 and Biophilia Level 2 were determined as significant predictors of the bodily intelligence domain. Only Biophilia Level 2 was determined as a significant predictor of the social intelligence domain. Biophilia Level 1 and Biophilia Level 2 were determined as significant predictors of the intrinsic intelligence domain. Biophilia Level 1, Biophilia Level 2, and Biophilia Level 3 were determined as significant predictors of the nature intelligence domain. Based on the findings obtained in our study, it can be said that different levels of Biophilia are predicted according to intelligence domains. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Test & Measurement Technology is the property of Publishing Center of North University of China and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To report the characteristics associated with response to methylphenidate (MPH) in children and adolescents with ADHD. Methods: Studies reporting potentials predictors of response to MPH were searched in Medline and Embase from January 1998 to March 2022. Narrative synthesis was performed. Results: Fifty-seven reports of 46 studies totaling 6,656 ADHD patients were included. No association appears between response to MPH and age, gender, MPH dosage, ADHD subtype, comorbidities nor socioeconomic status when considering a specific patient. No conclusion could be drawn about body weight, ADHD severity, intelligence quotient, and parental symptoms of depression or ADHD. Conclusions: None of these potential predictors have proven their usefulness to predict response to MPH on an individual basis in clinical practice. In research, potential predictors should be measured, their association with response to MPH assessed, in order to control for confounding variables when modeling response to MPH. [ABSTRACT FROM AUTHOR]

We use administrative and survey-based micro data to study the relationship between cognitive abilities (IQ), the formation of inflation expectations, and the consumption plans of a representative male population. High-IQ men display 50 |$\%$| lower forecast errors for inflation than other men. High-IQ men, but not others, have consistent inflation expectations and perceptions over time. In terms of choice, only high-IQ men increase their consumption propensity when expecting higher inflation as the consumer Euler equation prescribes. Education levels, income, other expectations, and socio-economic status, although important, do not explain the variation in expectations and choice by IQ. Recent modelling attempts to incorporate boundedly rational agents into macro models do not fully capture all the facts we document. We discuss which dimensions of expectations formation and choice are important for heterogeneous-agents models of household consumption and for the transmission of fiscal and monetary policy. [ABSTRACT FROM AUTHOR]

Social behaviors in animals such as bees, ants, and birds have shown high levels of intelligence from a multi-agent system perspective. They present viable solutions to real-world problems, particularly in navigating constrained environments with simple robotic platforms. Among these behaviors is swarm flocking, which has been extensively studied for this purpose. Flocking algorithms have been developed from basic behavioral rules, which often require parameter tuning for specific applications. However, the lack of a general formulation for tuning has made these strategies difficult to implement in various real conditions, and even to replicate laboratory behaviors. In this paper, we propose a flocking scheme for small autonomous robots that can self-learn in dynamic environments, derived from a deep reinforcement learning process. Our approach achieves flocking independently of population size and environmental characteristics, with minimal external intervention. Our multi-agent system model considers each agent’s action as a linear function dynamically adjusting the motion according to interactions with other agents and the environment. Our strategy is an important contribution toward real-world flocking implementation. We demonstrate that our approach allows for autonomous flocking in the system without requiring specific parameter tuning, making it ideal for applications where there [ABSTRACT FROM AUTHOR]

Background: Phenylketonuria (PKU) is a rare inborn error of metabolism affecting the catabolism of phenylalanine (Phe). To date, findings regarding health-related quality of life (HRQoL) in adults with early-treated classical PKU are discrepant. Moreover, little is known about metabolic, demographic, and cognitive factors associated with HRQoL. Hence, we aimed to investigate HRQoL and its association with demographic, metabolic, and cognitive characteristics in a large European sample of adults with early-treated classical PKU. Results: This cross-sectional study included 124 adults with early-treated classical PKU from Hungary, Italy, Spain, Switzerland, and Turkey. All participants prospectively completed the PKU quality of life questionnaire (PKU-QoL), a questionnaire specifically designed to evaluate the impact of PKU and its treatment on HRQoL in individuals with PKU. In addition, information about Phe levels (concurrent and past year), demographic (age and sex), and cognitive variables (intelligence quotient, IQ) were collected. Most domains revealed little or no impact of PKU on HRQoL and more than three-quarters of the patients rated their health status as good, very good, or excellent. Nevertheless, some areas of concern for patients were identified. Patients were worried about the guilt that they experience if they do not adhere to the dietary protein restriction and they were most concerned about high Phe levels during pregnancy. Further, tiredness was the most affected symptom, and the supplements' taste was considered a main issue for individuals with PKU. The overall impact of PKU on HRQoL was higher in women (U = 1315.5, p =.012) and in adults with a lower IQ (rs = − 0.448, p =.005). The overall impact of dietary protein restriction was higher in adults with higher concurrent Phe levels (rs = 0.272, p =.007) and higher Phe levels during the past year (rs = 0.280, p =.009). Conclusion: The impact of PKU on most domains assessed in the PKU-QoL was considered to be low. These results likely reflect the successful implementation of the newborn screening resulting in the prevention of severe adverse long-term outcomes. However, a particular clinical focus should be given to patients with lower IQ, higher Phe levels, and women, as these variables were associated with a lower HRQoL. [ABSTRACT FROM AUTHOR]

As a consequence of the application advanced maintenance practices, the theoretical probability of failures occurring is relatively low. However, observations of low levels of market intelligence and maintenance management have been reported. This comprehensive study investigates the determinants of maintenance practices in companies utilising hydraulic machinery, drawing on empirical evidence from a longitudinal questionnaire-based survey across the West-Balkan countries. This research identifies critical predictors of technical and sustainable maintenance performance metrics by employing the CA-AHC (Correspondence Analysis with Agglomerative Hierarchical Clustering) method combined with non-parametric machine learning models. Key findings highlight the significant roles of the number of maintenance personnel employed; equipment size, determined on the basis of nominal power consumption; machinery age; and maintenance activities associated with fluid cleanliness in influencing hydraulic machine maintenance outcomes. These insights challenge current perceptions and introduce novel considerations with respect to aspects such as equipment size, maintenance skills and activities with the aim of preserving peak performance. However, the study acknowledges the variability resulting from differing operational conditions, and calls for further research for broader validation. As large-scale heterogeneous datasets are becoming mainstream, this research underscores the importance of using multidimensional data analysis techniques to better understand operational outcomes. [ABSTRACT FROM AUTHOR]

Fault diagnosis is an essential process for the health maintenance of rotating machinery. With the development of AI technology, many deep learning-based methods have been applied to fault diagnosis to enhance the intelligence level of equipment maintenance. Such methods normally need a large amount of labeled data for model training. However, label acquisition is a difficult task that requires extensive human labor. To address these issues, a fault diagnosis method based on feature extraction via an unsupervised graph neural network is proposed in this paper. In the proposed method, the K-nearest neighbor approach is adopted to construct a fault graph from the collected signals, thereby providing extra relationship information for fine feature mining. Then, the GraphSAGE model is trained on the constructed graph in an unsupervised way, that is, it does not need labeled data, to extract features of each signal sample. Based on the extracted features, some traditional classifiers are adopted to identify the fault types. The proposed model is evaluated on a rolling bearing dataset provided by the University of Paderborn and a motor rotor dataset collected by a constructed motor rotor system. Compared with some traditional deep learning-based fault diagnosis methods, the proposed model can achieve more accurate diagnoses even when there are only a few labeled samples. [ABSTRACT FROM AUTHOR]

Dual-task paradigms can provide insights on the structures and mechanisms underlying information processing and hold diagnostic, prognostic, and rehabilitative value for populations with cognitive deficits such as in individuals with intellectual disability (ID). In this paradigm, two tasks are performed separately (single-task context) and concurrently (dual-task context). The change in performance from single- to dual-task context represents dual-task interference. Findings from dual-task studies have been largely inconsistent on whether individuals with ID present with dual-task-specific deficits. The current review aimed to map the published literature on dual-task methods and pattern of dual-task interference in individuals with ID. A scoping review based on Arksey and O'Malley's five-stage methodological framework was performed. Seventeen electronic databases and registries were searched to identify relevant studies, including gray literature. Charted data from included studies were analyzed quantitatively and qualitatively. PRISMA guidelines informed the reporting of this review. Twenty-two studies involving 1,102 participants (656 with ID and 446 without ID) met the review's inclusion criteria. Participants in the included studies were heterogeneous in sex, age (range 3-59 years), etiology and ID severity. Included studies characterized their ID-sample in different ways, most commonly using intelligence quotient (IQ) scores. Other measures of intellectual function (e.g., mental age, ID severity, verbal and/or visuospatial ability scores) were also used, either solely or in combination with IQ. Methods of dual-task testing varied across studies, particularly in relation to dual-task combinations, equation of single-task performance between groups, measurement and reporting of dualtask performance for each single-task, and task priority instructions. Thematic content of the included studies were: (1) structural interference to dual-tasking; (2) etiology-based differences in dual-tasking; (3) gait and balance dual-task performance; (4) testing executive function using dual-task paradigms; and (5) training effect on dual-task performance. Although the evidence consistently supported the intact dual-tasking ability of individuals with ID, the pattern of dual-task interference was inconsistent. Likewise, the evidence was inconclusive regarding dual-task deficit specific to individuals with ID because of heterogeneity in dual-task study designs among included studies. [ABSTRACT FROM AUTHOR]

Choroid plexus carcinomas (CPC) are rare aggressive tumours that primarily affect very young children. Treatment for CPC typically involves a combination of surgery, chemotherapy, and radiation therapy. Whilst considered necessary for a cure, these therapies have significant neurocognitive consequences for patients, negatively impacting cognitive function including memory, attention, executive functioning, and full-scale intelligence quotients (FSIQ). These challenges significantly impact the quality of life and ultimately socioeconomic parameters such as the level of educational attainment, marital status, and socioeconomic status. This review looks at the tumour- and treatment-related causes of neurocognitive damage in CPC patients and the progress made in finding strategies to reduce these. Opportunities to mitigate the neurodevelopmental consequences of surgery, chemotherapy, and radiation therapy are explored in the context of CPC treatment. Evaluation of the pathological and biological mechanisms of injury has identified innovative approaches to neurocognitive protection and neurorehabilitation, which aim to limit the neurocognitive damage. This review aims to highlight multiple approaches physicians can use when treating young children with CPC, to focus on neurocognitive outcomes as a measure of success. [ABSTRACT FROM AUTHOR]

Children with ADHD show poor motor control. The aim of the present study was to test whether children with ADHD improved their motor performances (oculomotor as well as posture) after a short visuopostural training period. Two groups (G1 trained and G2 non-trained), each comprising 15 children with ADHD matched in IQ (intelligence quotient), sex, and age, participated in the study. Eye movements and postural sway were measured before (T1) and after (T2) 10 min of visuopostural training for the trained group and after 10 min of resting for the non-trained group. Training consisted of a visual search task performed while the child was standing on an unstable platform. At T1, oculomotor and postural abilities were statistically similar for both groups of children with ADHD (trained and non-trained). At T2, significant improvements in both oculomotor and postural capabilities were observed for the trained group but not for the non-trained group. These findings suggest that a short visuopostural training period could help children with ADHD to learn how to focus their visual attention in order to improve motor performance. Visuopostural training could allow a better integration of sensory inputs via central mechanisms, leading to improvement in both oculomotor and postural control. Further studies on a larger number of children with ADHD will be needed to confirm these findings and explore the eventual possible persistence of the training effect. [ABSTRACT FROM AUTHOR]

After completing the technical integration of beneficiation equipment, processes, automation, and IT, the Sanshandao gold mine has significantly improved the reliability of its beneficiation equipment and processes, and achieved a higher level of intelligence in gold beneficiation through the upgrades in data acquisition platforms, intelligent operation of the beneficiation plant, and VR beneficocetoon plant. The mine has achieved stable and optimized production processes, leading to reduced manpower and increased efficiency. This has resulted in improved technical indicators and economic benefits, establishing it as one of the world’s advanced gold beneficiation plants. [ABSTRACT FROM AUTHOR]

Background: Bipolar disorder (BD) and cannabis use are each associated with neurocognitive deficits in adolescents. However, little is known regarding the association of neurocognition with cannabis use among adolescents with BD. Therefore, we examined this topic in a sample of adolescents with BD and healthy control (HC) adolescents. Methods: Participants included 121 adolescents (n = 32 with BD and lifetime cannabis use (BDCB+), n = 31 with BD and no lifetime cannabis use (BDCB−), n = 58 HC with no lifetime cannabis use), aged 14–20 years. Five neurocognitive subtests of the computerized CANTAB battery were assessed. Groups were compared using an analysis of covariance (ANCOVA) covarying for age, sex, and intelligence quotient. Results: The three groups differed significantly on tests of visuospatial working memory (F = 4.41, p = 0.014, η p 2 = 0. 07) and sustained attention (F = 5.15, p = 0.007, η p 2 = 0. 08). Post hoc analyses revealed working memory scores were significantly worse in BDCB+ versus HC (p = 0.04, d = 0.59), and sustained attention was significantly worse in BDCB− versus HC (p = 0.006, d = 0.70). Conclusion: These preliminary findings suggest that cannabis use among adolescents with BD is associated with working memory deficits. Future studies in larger samples are warranted to evaluate causation versus predisposition to cannabis use, and to evaluate duration, quantity, and potency of cannabis on neurocognition among adolescents with BD. [ABSTRACT FROM AUTHOR]

The current study sought to examine the predictive value of early learning rate on 1-year outcome measures for autism severity, adaptive behaviour, and intelligence quotient (IQ), as well as the predictive value of intake scores on early learning rate, for children with autism spectrum disorder in an early intensive behavioural intervention program. Using archived data, participants were assigned to one of two groups based on their early learning rate, either the Rapid Learners group or the Less Rapid Learners group, and descriptive analyses were assessed for outcome measures. Results indicated that scores were significantly different between groups at Year 1 for scores on adaptive behaviour and autism severity. As well, a simple linear regression was used to assess the predictability of early learning rate on Year 1 outcome measures and the predictability of Intake scores on early learning rate for the total sample. Results indicated that early learning rate only significantly predicted adaptive behaviour and autism severity scores at Year 1 and only adaptive behaviour Intake scores significantly predicted early learning rate. As a limitation of this study was the use of archived data, future researchers should consider acquiring current skills databases from service providers to better evaluate the variety of skills being taught to each child. [ABSTRACT FROM AUTHOR]

Despite the reported lack of structural alterations in the amygdala of individuals with attention deficit/hyperactivity disorder (ADHD) in previous meta‐analyses, subsequent observational studies produced conflicting results. Through incorporating the updated data from observational studies on structural features of the amygdala in ADHD, the primary goal of this study was to examine the anatomical differences in amygdala between subjects with ADHD and their neurotypical controls. Using the appropriate keyword strings, we searched the PubMed, Embase, and Web of Science databases for English articles from inception to February 2022. Eligibility criteria included observational studies comparing the structure of the amygdala between ADHD subjects and their comparators using magnetic resonance imaging (MRI). Subgroup analyses were conducted focusing on the amygdala side, as well as the use of different scanners and approach to segmentation. The effects of other continuous variables, such as age, intelligence quotient, and male percentage, on amygdala size were also investigated. Of the 5703 participants in 16 eligible studies, 2928 were diagnosed with ADHD. Compared with neurotypical controls, subjects with ADHD had a smaller amygdala surface area (particularly in the left hemisphere) but without a significant difference in volume between the two groups. Subgroup analysis of MRI scanners and different approaches to segmentation showed no statistically significant difference. There was no significant correlation between continuous variables and amygdala size. Our results showed consistent surface morphological alterations of the amygdala, in particular on the left side, in subjects with ADHD. However, the preliminary findings based on the limited data available for analysis warrant future studies for verification. This meta‐analytic review finds a difference in amygdala size between individuals with attention‐deficit/hyperactivity disorder (ADHD) and neurotypical controls, by using different image analyses. Although volumetric image analysis revealed no significant differences in amygdala anatomy, we used its surface area to identify the structural alterations, particularly on the left side, in ADHD, shedding light on psychotherapy designed to improve their emotion dysregulation. [ABSTRACT FROM AUTHOR]

The current review summarizes the literature on the impact of derived relational responding (DRR) technology on raising intelligence scores. We conducted a systematic review of peer-reviewed studies in PsycINFO, ERIC, and Web of Science between 1985 and 2021. Fourteen publications involving 15 experiments were identified. For studies meeting inclusion criteria, information was extracted on participant characteristics, design, settings, assessments conducted, intervention protocol and trained relations, mean intelligence quotient (IQ) scores before and after training, and outcomes. We assessed risk of bias using a revised Cochrane risk-of-bias tool for randomized trials (RoB2), the Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-I), and the What Works Clearinghouse (WWC). Overall, the results suggest that interventions using DRR procedures improve intelligence scores regardless of initial participant ability, diagnosis, or age level. Furthermore, eight of the reviewed studies used the Strengthening Mental Abilities with Relational Training (SMART), whereas two studies implemented the Promoting the Emergence of Advanced Knowledge (PEAK) protocol. Additional training procedures were identified, for example, multiple-exemplar training, fluency training, and relational flexibility training. The quality assessment showed high risk for seven randomized controlled trials, and low to moderate risk for five nonrandomized trials. Three studies used a type of single case design; one study meets standards according to the WWC protocol. The limitations and future directions are discussed. [ABSTRACT FROM AUTHOR]

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A test-Accelerator as Coherent Terahertz Source (t-ACTS) has been under development at Tohoku University, in which an intense coherent terahertz radiation is generated from the short electron bunches. Velocity bunching scheme in a traveling wave accelerating structure is employed to generate the short electron bunches. The in-phase and quadrature (IQ) modulator and demodulator were installed to the low-level RF systems of t-ACTS linac to control and measure the amplitude and phase of RF power. The amplitude and phase of the RF power applied to an RF electron gun cavities and the accelerating structure are controlled to produce the electron bunches with a uniform and small momentum spread suitable for the velocity bunching. By installing the feed-forward control system using IQ modulators for the beam conditioning, we have successfully generated flat RF pulses and improved beam quality, including the energy spectrum of the beam. The details of feed-forward control system of the amplitude and phase using the IQ modulator and the beam experiments are presented in this paper. [ABSTRACT FROM AUTHOR]

Communicating effectively by gaining productive skills in a classroom setting is one of the critical goals of learning the English language. The current study was conducted to explore the correlation of EFL learners' level of academic intelligence with their productive skills. The study tries to find an answer to what is the correlation between EFL learners’ academic intelligence and level of production skills. The study population represents EFL students at the departments of English language of the Iraqi Colleges of Education for the academic year (2022-2023). The sample includes 310 EFL students selected from the 3rd year of the Department of English of the College of Education, Ibn-Rushd for Human Sciences/University of Baghdad, College of Education/ University of Diyala, and College of Education/University of Tikrit. The current study has two instruments, the academic intelligence test consists of two dimensions (the operational and the content), while the second instrument used is the test of productive skills, which is composed of two skills; speaking skill consists of six standards (grammar, vocabulary, comprehension, fluency, pronunciation, interaction), and writing skill consists of five criteria (content, organization, grammar, vocabulary, writing technique). The results obtained reveal that there are positive significant correlations between EFL learners' and productive skills. Concerning the productive skills tested in this study, EFL learners succeed in using speaking and writing skills, which constitute a large amount of human communication. Moreover, academic intelligence abilities can help EFL learners develop the skills and strategies necessary for academic success and professional development. [ABSTRACT FROM AUTHOR]

This study aims to develop an original financial intelligence quotient (FIQ) measurement conceptual model, including guidelines for adequately handling personal finances in four developed areas to serve as benchmarks of financial intelligence. Four hypotheses were raised, one of them consists of four parts. Methods used: a questionnaire to determine how well a person’s financial decisions comply with financial behaviour guidelines, Cronbach’s Alpha coefficient to determine the internal consistency of the scales used in the questionnaire, Spearman correlation coefficient to determine the linear dependence between the variables, a linear regression model was developed to substantiate the hypothesis, the MannWhitney-Wilcoxon rank-sum criterion, the KolmogorovSmirnov test to choose the data distribution according to the normal distribution, descriptive statistics, the Kruskal-Wallis test to support the hypothesis. The results show that an individual’s FIQ influences financial decision-making in essential areas of personal finance management and varies due to education but is not dependent on gender and age. Research limitations: The study focuses only on FI and its impact on the economic well-being of Lithuanian students; the study uses oneyear data; data sets for different age groups were not the same size; and the data was not distributed in groups according to the normal distribution. [ABSTRACT FROM AUTHOR]

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Copyright of Revista Iberoamericana de Ciencias de la Actividad Física y el Deporte is the property of Revista Iberoamericana de Ciencias de la Actividad Física y el Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Dilemas Contemporáneos: Educación, Política y Valores is the property of Dilemas Contemporaneos: Educacion, Politica y Valores and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)