Balance Performance Research Articles

Ultrafast Synthesis of Transition Metal Phosphides in Air via Pulsed Laser Shock.

Transition metal phosphide nanoparticles (TMP NPs) represent a promising class of nanomaterials in the field of energy; however, a universal, time-saving, energy-efficient, and scalable synthesis method is currently lacking. Here, a facile synthesis approach is first introduced using a pulsed laser shock (PLS) process mediated by metal-organic frameworks, free of any inert gas protection, enabling the synthesis of diverse TMP NPs. Additionally, through thermodynamic calculations and experimental validation, the phase selection and competition behavior between phosphorus and oxygen have been elucidated, dictated by the redox potential and electronegativity. The resulting composites exhibit a balanced performance and extended durability. When employed as electrocatalysts for overall water splitting, the as-constructed electrolyzer achieves a low cell voltage of 1.54 V at a current density of 10 mA cm-2. This laser method for phosphide synthesis provides clear guidelines and holds potential for the preparation of nanomaterials applicable in catalysis, energy storage, biosensors, and other fields.

Improved-Performance Amorphous Ga2O3 Photodetectors Fabricated by Capacitive Coupled Plasma-Assistant Magnetron Sputtering

Ga2O3 has received increasing interest for its potential in various applications relating to solar-blind photodetectors. However, attaining a balanced performance with Ga2O3-based photodetectors presents a challenge due to the intrinsic conductive mechanism of Ga2O3 films. In this work, we fabricated amorphous Ga2O3 (a-Ga2O3) metal–semiconductor–metal photodetectors through capacitive coupled plasma assisted magnetron sputtering at room temperature. Substantial enhancement in the responsivity is attained by regulating the capacitance-coupled plasma power during the deposition of a-Ga2O3. The proposed plasma energy generated by capacitive coupled plasma (CCP) effectively improved the disorder of amorphous Ga2O3 films. The results of X-ray photoelectron spectroscopy (XPS) and current-voltage tests demonstrate that the additional plasma introduced during the sputtering effectively adjust the concentration of oxygen vacancy effectively, exhibiting a trade-off effect on the performance of a-Ga2O3 photodetectors. The best overall performance of a-Ga2O3 photodetectors exhibits a high responsivity of 30.59 A/W, a low dark current of 4.18 × 10−11, and a decay time of 0.12 s. Our results demonstrate that the introduction of capacitive coupled plasma during deposition could be a potential approach for modifying the performance of photodetectors.

A multi-objective model for integrated supplier order allocation and supply chain network transportation planning decision-making

Effective supplier order allocation (SOA) and transportation planning (TP) are critical for the smooth operation of supply chains, especially in dynamic markets with evolving customer demands. While previous research has made significant strides in addressing these areas individually, studies that integrate both aspects while considering a comprehensive set of objectives are limited. This study introduces an innovative multi-objective model that concurrently addresses total operational costs, supplier defect rates, sustainability performance, and supply chain network disruption risks. The model applies an augmented max–min approach of fuzzy multiple objective linear programming (AMM-FMOLP), which enhances overall utility while ensuring balanced performance across all objectives. The inclusion of all five objectives in the model is essential for a holistic evaluation of supply chain performance. The model’s effectiveness and practicality are validated through a case study involving a computer numerical control (CNC) machine tool assembly company, under various scenarios. Additionally, sensitivity analysis reveals how adjustments in supply chain structure can further improve performance. Moreover, the execution process of this study does not require expert intervention, making it a unique data-driven decision model particularly suitable for intelligent supply chain management and decision-support systems. This approach enhances the flexibility and resilience of supply chains, enabling them to effectively respond to unforeseen events and minimize their impact on business operations, especially in volatile global markets.

IMPLEMENTASI PERANCANGAN INTEGRASI SWOT BALANCED SCORECARD DALAM PENILAIAN KINERJA BISNIS PAKAN KELINCI PADA RABBIT BROTHERS DI KABUPATEN BANDUNG

Rabbit Brothers is one of the rabbit breeders established in 2017 located in West Java, West Bandung Regency. Rabbit Brothers rabbit feed sales in 2023 fluctuated. The tighter the competition, the company needs to determine strategies in business management to determine the company's current performance. The purpose of this study is to describe the strategy based on SWOT analysis, design a Rabbit Brothers rabbit feed strategy map based on SWOT Balanced Scorecard integration, performance measurement and performance assessment of Rabbit Brothers rabbit feed based on SWOT Balanced Scorecard integration, and improve Rabbit Brothers rabbit feed business performance based on SWOT Balanced Scorecard integration. The methods in this research are SWOT Analysis, Balanced Scorecard, Analytical Hierarchy Process Software Expert Choice, and Key Performance Indicator Lead Indicator. Rabbit Brothers rabbit feed strategy and strategy map, one of which is increasing profits, Rabbit Brothers rabbit feed performance is 93.04%, meaning that the company's performance is in a very healthy condition with the category (AAA). The performance of the four performance perspectives that are not optimal is improved on strategic initiatives, one of which is the content creation program.

RPKI Defense Capability Simulation Method Based on Container Virtualization

As the main inter-domain routing protocol in today’s internet, the Border Gateway Protocol (BGP) faces serious security risks during actual usage. Research on BGP malicious attack methods requires a realistic network environment, and evaluation methods based on physical networks often suffer from high costs and insufficient flexibility. Thus, we propose an efficient BGP simulated network deployment system based on a virtualization technology called the SOD–BGP. This system, combining cloud computing and virtualization technologies, creates a scalable, highly flexible basic network environment that allows for the automated simulation and evaluation of actual BGP prefix hijacking attack scenarios. A Resource Public Key Infrastructure (RPKI) simulation suite is introduced into the system, emulating a certificate issuance system, certificate storage, and a certificate synchronization verification mechanism, thus aligning the simulation environment with real-world usage scenarios. Finally, we propose a data collection and performance evaluation technique to evaluate BGP networks deploying RPKI under different attack scenarios and to explore the effectiveness of RPKI defense mechanisms at various deployment rates. A comparative analysis with other simulation techniques demonstrates that our approach achieves a balanced performance in terms of deployment speed, complexity, and RPKI integrity, providing a solid simulation technology foundation for large-scale BGP security defense strategies.

Image recommendation for social media marketing in maternity and baby care product industry – a machine learning approach

PurposeThe digital marketing landscape is rapidly evolving, but the integration of visual content still heavily depends on human expertise. Driven by the quest for innovative marketing strategies that resonate with family-oriented consumers, this study seeks to bridge this gap by applying machine learning to analyze visual content in the maternity and baby care product sector.Design/methodology/approachThis study incorporates a range of machine learning techniques – including open science framework feature detection, panoptic segmentation, customized instance segmentation, and face detection calculation methods – to analyze and predict the appeal of images, thereby enhancing user engagement and parent-child intimacy.FindingsThe exploration of various ML models, such as DT, LightGBM, RIPPER algorithm, and CNNs, has offered a comparative analysis that addresses a methodological gap in the existing literature, which frequently depends on isolated model evaluations. According to our quadrant analysis with respect to engagement rate and parent-child intimacy, the selection of a model for real-world applications depends on balancing performance and interpretability.Originality/valueThe proposed system offers a series of actionable recommendations designed to enhance customer engagement and foster brand loyalty. This study contributes to image design in maternity and baby care marketing and provides analytical insights for recommendation systems.

Lower extremity muscle activity during reactive balance differs between adults with chronic traumatic brain injury and controls.

Control of reactive balance is key to achieving safe independent walking and engagement in life activities. After traumatic brain injury (TBI), motor impairments and mobility challenges are persistent sequelae. To date, no studies have explored muscle activity of individuals with chronic TBI during a task that requires reactive control of balance. To investigate lower extremity muscle activity during a reactive balance test performed by adults with chronic severe TBI and matched controls. We hypothesized that abnormal activity of lower extremity muscles would be related with poorer reactive balance performance. Also, we performed an exploratory analysis for those with TBI investigating the impact of unilateral versus bilateral lower extremity involvement in the control of reactive balance. Ten adults with chronic severe TBI who were independent community ambulators and ten matched controls performed the computerized reactive balance test (Propriotest®) while lower extremity muscle activity was recorded. Electromyographic (EMG) activity was contrasted (Mann-Whitney U Test) between groups across each 10 s epoch of the 120 s test. Additionally, test scores were correlated (Spearman) with lower extremity composite EMG activity to distinguish muscle activity patterns related with reactive balance performance. Lastly, reactive balance test scores were correlated with reactive balance test scores and clinical functional measures only for the TBI group. Although the TBI group exhibited greater EMG activity across the entire test compared with the control group, significant differences were not observed. Greater composite EMG activity correlated significantly with poorer reactive balance performance across most of the 10 s windows of the test. Greater muscle activity exhibited during the reactive balance test by individuals with chronic severe TBI compared to those without disabilities, particularly at small unexpected perturbations, highlights the greater physiologic effort required to control reactive balance even after independent ambulation is achieved.

A multi‐objective optimization model for RSU deployment in intelligent expressways based on traffic adaptability

AbstractThe intelligent expressway exemplifies a prominent application of intelligent transportation systems. Roadside units (RSUs), strategically deployed alongside roadways, serve as pivotal infrastructure in facilitating interactions within intelligent expressways. A well‐planned RSU deployment strategy is crucial for enhancing service quality, it necessitates balancing performance improvements with significant financial costs due to the limited transmission range and high deployment expenses of RSUs. To tackle these challenges, an adaptive approach for RSU deployment is proposed, which takes into account economic feasibility, service requirements, and dynamic traffic demands. A traffic adaptability‐based RSU deployment (TARD) model, which integrates factors such as deployment cost, the effectiveness of information coverage, road network topology, and traffic flow characteristics have been devised. The TARD aims to minimize deployment expenses while maximizing the benefits of information coverage and alignment with road traffic demands. The Non‐dominated Sorting Genetic Algorithm II (NSGA‐II) is employed to solve this optimization model. To validate its efficacy, simulations are conducted on the G2 expressway in Shandong Province, China, demonstrating the superior performance of the TARD compared to three other deployment strategies. Ablation experiments further underscore the critical role of tunnel deployments and comprehensive coverage along long sections in bolstering network connectivity and elevating service quality.

325 Longitudinal retrospective study of performance and biomarkers of energy balance and gastrointestinal functionality in unweaned calves subjected to transport or entire commercialization at arrival

Abstract Data from 347 unweaned male dairy beef calves enrolled in 3 studies from 2021 to 2023 were used to evaluate the impact of transport or entire commercialization (marketing and transport) on performance recovery [average daily gain (ADG) and concentrate intake (CI)] and biomarkers of energy balance [non-esterified fatty acids (NEFA), beta-hydroxybutyrate (BHB), and glucose] and gastrointestinal functionality [gut permeability (Cr-EDTA) and enterocyte mass (citrulline)] at farm arrival. Calves were distributed in 3 treatments according to the different managements subjected in the previous studies: calves from a sole dairy farm that were not fasted neither transported (CTR), calves from a sole dairy farm that were transported and fasted for 19 h (TRA), and multi-origin calves commercially marketed and transported for 9 h (COM). On arrival at the rearing farm (d 0), calves were allocated individually, and body weight (BW) was recorded. Calves were fed milk replacer twice daily, and they had ad libitum access to concentrate and water. Concentrate (CI) and milk replacer intake were recorded daily, and BW and the biomarkers of energy balance and gut dysfunction were obtained on d 0 (arrival), 1, 2, and 7. Data were analyzed with mixed models. An interaction (P < 0.01) between treatment and time was observed for CI. On d 0 CTR and TRA had similar CI, while COM had the least CI. On d 1, all treatments decreased CI except CTR. While TRA recovered CI to CTR levels, COM had 50% less CI compared with the other calves on d 7. The COM calves had the least (P < 0.01) ADG compared with CTR and TRA calves. On d 0, COM calves had greater (P < 0.01) concentrations of NEFA and BHB compared with TRA and CTR, and TRA greater (P < 0.01) than CTR calves. The COM calves did not recover NEFA and BHB basal concentrations by d 7 as observed in TRA calves. Concentration of Cr-EDTA was greater on d 0 for TRA calves compared with CTR and COM calves, however concentration of Cr-EDTA was greater during the first 7 d in COM calves compared with CTR and TRA calves. Finally, citrulline concentration was less in COM calves compared with CTR and TRA calves independently of the sampling day. The entire commercialization process, marketing and transportation, of unweaned dairy beef calves impairs intake recovery and growth, and these results are aligned with negative energy balance and comprised gastrointestinal functionality at farm arrival.

Sensor-Based Balance Training with Exergaming Feedback in Subjects with Chronic Stroke: A Pilot Randomized Controlled Trial.

As one of the leading causes of disability in the world, stroke can determine a reduction of balance performance with a negative impact on daily activity and social life. In this study, we aimed to evaluate the effects of sensor-based balance training with exergaming feedback on balance skills in chronic stroke patients. 21 individuals (11F, 57.14 ± 13.82 years) with a single event of ischemic stroke were randomly assigned to the sensor-based balance training group (SB-group) or the usual care balance training group (UC-group). Both groups received 10 add-on sessions with exergaming feedback (SB-group) or conventional training (UC-group). Clinical and instrumental evaluation was performed before (t0), after (t1), and after one month (t2) from intervention. Participation level was assessed using the Pittsburgh Rehabilitation Participation Scale at the end of each session. The SB-group showed an improvement in postural stability (p = 0.02) when compared to the UC-group. In the evaluation of motivational level, the score was statistically higher in the SB-group with respect to the UC-group (p < 0.01). Except for the improvement in postural stability, no difference was recorded in clinical score, suggesting a comparable gain in both groups. However, patients undergoing sensor-based training exhibited a higher participation score, ultimately indicating the use of this training to improve the adherence to rehabilitation settings, especially in patients with lower compliance.

Adaptive integral terminal sliding mode control of unmanned bicycle via ELM and barrier function

Abstract In this paper, an unmanned bicycle (UB) with a reaction wheel is designed, and a second-order mathematical model with uncertainty is established. In order to achieve excellent balancing performance of the UB system, an adaptive controller is designed, which is composed of nominal feedback control, compensating control using extreme learning machine observer and reaching control via integral terminal sliding mode (ITSM) and barrier function (BF)-based adaptive law. Owing to the features of BF-based ITSM (BFITSM), not only any uncertainty or disturbance upper bound is not needed any longer but also the finite-time convergence of the closed-loop system can be ensured with a predefined error bound. Moreover, the BF-based control gain can be adaptively adjusted according to the update of the lumped uncertainty such that the overestimation is removed. The stability analysis of the closed-loop system is given according to Lyapunov theory. Comparable experimental results on an actual UB are carried out to validate the superior balancing performance of the proposed controller.

Effect of magnesium doping on NiO hole injection layer in quantum dot light-emitting diodes

Abstract This study reports on the fabrication of quantum dot light-emitting diodes (QLEDs) with an ITO/Ni1−x Mg x O/SAM/TFB/QDs/ZnMgO/Al structure and investigates the effects of various Mg doping concentrations in NiO on device performance. By doping Mg into the inorganic hole-injection layer NiO (Ni1−x Mg x O), we improved the band alignment with the hole-injection layer through band tuning, which enhanced charge balance. Optimal Mg doping ratios, particularly a Ni0.9Mg0.1O composition, have demonstrated superior device functionality, underscoring the need for fine-tuned doping levels. Further enhancements were achieved through surface treatments of Ni0.9Mg0.1O with UV-Ozone (UVO) and thermal annealing (TA) of the ZnMgO electron transport layer. Consequently, by optimizing Mg-doped NiO in QLED devices, we achieved a maximum external quantum efficiency of 8.38 %, a brightness of 66,677 cd/m2, and a current efficiency of 35.31 cd/A, indicating improved performance. The integration of Mg-doped NiO into the QLED structure resulted in a device with superior charge balance and overall performance, which is a promising direction for future QLED display technologies.

Optimal dispatch of unbalanced distribution networks with phase-changing soft open points based on safe reinforcement learning

Distributed energy resources and uneven load allocation cause the three-phase unbalance in distribution networks, which may harm the health of power equipment and increase the operational costs. There is emerging opportunity to dispatch soft open points to improve the operation performance of active distribution network. This paper proposes an optimal dispatch strategy to improve the network balancing performance, where a new type of phase-changing soft open point is installed. First, a new type of phase-changing soft open point with full-phase changing ability is introduced to balance the three-phase power flow. Then, the optimization model is formulated for phase-changing soft open points dispatching to minimize the total cost of distribution network. Furthermore, the model is formed as a constrained Markov decision process and efficiently solved by the augmented Lagrangian-based safe deep reinforcement learning algorithm featuring the soft actor-critic method. Finally, numerical simulations are conducted to validate the effectiveness, accuracy, and efficiency of the proposed method.

PM1.0 removal enhancement in cooperated electric-ionic field by negative air ions carbon fiber electrode

The study focuses on improving the removal efficiency of submicron particles using negative air ions (NAIs), which are challenging to remove. To enhance this efficiency, cascaded carbon fiber tubular (CFT) chargers were designed to boost particle charging. Through experiments and numerical simulations, the chargers’ enhancement mechanisms, cooperation effects, and overall performance were evaluated. The optimal configuration for the CFT charger was identified as a gap distance (d = 2.0 r0) and grounded electrode length (L0 = 4πr03) that ensures high collection efficiency (96.7 % for 0.5 μm particles at 4 m/s) and ultra-low ozone generation (7.25 ppb). The study found that while the average electric field strength (E¯) and ion density significantly influence charging, an unusual improvement in collection efficiency was observed the charger with d = 2.0 r0 at u = 3 m/s, likely due to the potential predominance of the maximum electric field strength (Emax) at relative higher velocity. Besides, the CFT charger demonstrated balanced performance compared to other reported works, although higher relative humidity (80 ± 5 % RH) inhibits removal efficiency, which can be mitigated by reducing gas velocity.

Effectiveness of Technological Interventions for Older Adults With Parkinson Disease: Systematic Review.

Among the older population, Parkinson disease (PD) stands out as a leading contributor to disability. Clinically, the foremost objectives in managing PD involve proactively delaying and preventing disability. Understanding the pivotal role of gait and balance in daily functionality holds substantial clinical significance, signaling imminent disability and prompting a reevaluation of management approaches. A key priority lies in identifying novel and effective interventions for symptoms that substantially contribute to disability. This paper presents a systematic review that critically examines the existing body of literature on the use of technology in the rehabilitation of older patients with PD. By synthesizing current evidence, we aim to provide insights into the state of the field, identify gaps in knowledge, and offer recommendations for future research and clinical practice. A systematic review of the literature was conducted in September 2023 analyzing manuscripts and papers of the last 5 years from the PubMed, Scopus, Embase, Web of Science, and CINAHL databases following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 14 papers were included. The inclusion criteria are as follows: (1) randomized controlled trial, (2) PD in people aged 65 years and older, and (3) use of technology in the rehabilitation training in the older population. A large portion of effective interventions relies on the incorporation of technology, particularly through virtual reality exergames. This technology appears to have effects not only on the cognitive aspect but also on the physical domain. The analysis of the results clearly indicates that, in terms of gait and balance performance, the technological intervention outperforms the traditional approach, irrespective of the specific technology employed. This systematic review seeks to shed light on the evolving landscape of technology-assisted rehabilitation for older individuals with PD. As we delve into the available evidence, we will assess the extent to which technology can serve as a valuable adjunct to conventional therapy, offering new avenues for optimized care and improved outcomes in this growing patient demographic. As we sift through the existing evidence, our goal is to evaluate the potential of technology as a valuable supplement to traditional therapy, presenting fresh opportunities for enhanced care and better outcomes in this expanding patient demographic.

Applicability Of Balanced Scorecard In Private And Public Hospitals: A Comperative Analysis

ABSTRACT Hospitals carrying on their activities within a dynamic and open systematic, have reached their today's competitive, modern place as a result of development in not only medical and health sciences but also in many different sciences. For that reason, hospitals, like every institution, business, had to use modern management applications which is open ended for outer change and development as a critical success factor. Achieving long term sustainable successes for businesses depends on measuring skill of harmony degree of their internal and external environment with current strategies. Balanced Scorecard (BSC), which is a strategical management tool prepared for this target and direction and also expressed as balanced scorecard, performance measurement and balanced score sheet in our language, also considered to have benefits in today's providing health service. In this article, hospitals and changing management concept, strategical management, balanced scorecard revealing as strategical management tool, its use, aspects and a survey work done by managers related to factors effecting its success to applicability in health foundations, and more specifically in private and public hospitals together with investigation results and advices oriented to results takes place.

Postural control depends on early visual experience.

The present study investigated the role of early visual experience in the development of postural control (balance) and locomotion (gait). In a cross-sectional design, balance and gait were assessed in 59 participants (ages 7-43 years) with a history of (a) transient congenital blindness, (b) transient late-onset blindness, (c) permanent congenitally blindness, or (d) permanent late-onset blindness, as well as in normally sighted controls. Cataract-reversal participants who experienced a transient phase of blindness and gained sight through cataract removal surgery showed worse balance performance compared with sighted controls even when tested with eyes closed. Individuals with reversed congenital cataracts performed worse than individuals with reversed developmental (late emerging) cataracts. Balance performance in congenitally cataract-reversal participants when tested with eyes closed was not significantly different from that in permanently blind participants. In contrast, their gait parameters did not differ significantly from those of sighted controls. The present findings highlight both the need for visual calibration of proprioceptive and vestibular systems and the crossmodal adaptability of locomotor functions.

Sentiment Analysis Techniques: A Comparative Study of Logistic Regression, Random Forest, and Naive Bayes on General English and Nigerian Texts

This research investigates sentiment analysis on two distinct datasets: a general English dataset and a Nigerian dataset (Gangs of Lagos movie review), using three machine learning algorithms: Logistic Regression, Random Forest, and Naive Bayes with python programming language and its libraries. The study aims to evaluate and compare the performance of these models across different linguistic and cultural contexts. Results indicate that Logistic Regression consistently outperforms the other models, achieving the highest accuracy and balanced performance across sentiment classes. Random Forest provides comparable results but struggles with positive sentiment detection in the Nigerian dataset. Naive Bayes shows the lowest overall accuracy, with significant challenges in recall for certain sentiment classes. These findings highlight the importance of model selection and tuning tailored to specific datasets for effective sentiment analysis.

Predictors of Chronic Dizziness in Acute Unilateral Vestibulopathy: A Longitudinal Prospective Cohort Study.

Chronic dizziness after acute unilateral vestibulopathy (AUVP) causes significant social and economic burdens. This study aims to identify predictors of chronic dizziness. Prospective, longitudinal cohort study. ENT departments from secondary and tertiary hospitals. Participants meeting the Barany Society's diagnostic criteria for AUVP were included. Evaluations occurred within 0 to 21 days (T1), and at 4 (T2) and 10 weeks (T3) postonset. The primary outcome measure was the Dizziness Handicap Inventory (DHI) at 6 months, with a score >30 indicating chronic dizziness. Five clusters of predictors were assessed at T1-3: central vestibular compensation, visual dependence, movement exposure, psychological factors, and balance performance. Separate linear regression models for T1, T2, and T3 were constructed to explain the variability in the 6-month DHI score. Receiver operating characteristics analyses were conducted to predict chronic dizziness. From June 2021 to January 2024, 103 participants (55.2 ± 16.6 years old, 49 women) were included. The regression models explained the variability in the 6-month DHI score by 33.0% at T1, 47.6% at T2, and 64.0% at T3 (P < .001), including psychological factors (T1, T2, T3), visual dependence (T2, T3), and static balance performance (T3). Cutoff values for the Vestibular Activities Avoidance Instrument (23/54), Visual Vertigo Analog Scale (33.5/100), and Hospital Anxiety and Depression Scale-Anxiety (7.5/21) at 10 weeks postonset predicted chronic dizziness. Higher psychological burden, increased visual dependence, and poorer static balance performance were associated with chronic dizziness. Cutoff values were determined to identify individuals with AUVP at risk for chronic dizziness.

Effects of visual and auditory cognitive tasks on postural balance in adolescents with intellectual disability: A comparative analysis of trained versus non-trained individuals

This study aimed to investigate the influence of visual and auditory cognitive tasks on postural balance in adolescents with intellectual disabilities (ID). Participants included two groups: a trained group (n = 11) with experience in athletic activities and a sedentary group (n = 14). The experiment used a comparative cross-sectional design, with data collection involving single-task (ST) and Visual dual-task (VDT), and auditory dual-task (ADT) conditions in both firm and foam surface conditions. Cognitive tests included the Working Memory Test (WMT) and the Selective Attention Test (SAT). Results revealed that the trained group demonstrated significantly superior balance performance (p < 0.05). During the SAT, VDT conditions had lower center of pressure (CoP) values than ADT conditions in the sedentary group (p < 0.01), this result was observed in the training group only in the WMT, suggesting greater postural instability during ADT. These findings highlight the complex relationship between cognitive function and motor control in adolescents with ID, highlighting the potential benefits of regular physical activity interventions to improve postural balance abilities in this population.