Individual Strengths Research Articles

Integration of MILP and discrete-event simulation for flow shop scheduling using Benders cuts

Optimization-based scheduling in the chemical industry is highly beneficial but also highly difficult due to its combinatorial complexity. Different modeling and optimization techniques exist, each with individual strengths. We propose Benders decomposition to integrate mixed-integer linear programming (MILP) and discrete-event simulation (DES) to solve flow shop scheduling problems with makespan minimization objective. The basic idea is to generate valid Benders cuts based on sensitivity information of the DES sub problem, which can be found in the critical paths of DES solutions. For scaled literature flow shops, our approach requires at least an order of magnitude fewer iterations than a genetic algorithm and provides optimality gap information. For a real-world case study, our approach finds good solutions very quickly, making it a powerful alternative to established methods. We conclude that the Benders-DES algorithm is a promising approach to combine rigorous MILP optimization capabilities with high-fidelity DES modeling capabilities.

Pain and fatigue in adult patients with multiple osteochondromas: The Netherlands.

Multiple Osteochondromas (MO) is a rare genetic disorder characterised by the presence of numerous benign bone tumours, known as osteochondromas. Within the spectrum of debilitating symptoms associated with MO, pain is recognized as a major problem. Interestingly, our clinical observations suggest that fatigue is also a significant concern but has merely been touched upon in MO literature. This study aims to (1) assess the level of pain and fatigue in adult patients with MO; (2) compare fatigue in MO to healthy subjects and patients with Rheumatoid Arthritis (RA); (3) identify associated variables for pain and fatigue in patients with MO. In this cross-sectional study, 353 adult MO patients completed a survey with validated questionnaires on pain, fatigue and psychosocial factors. Pain and fatigue were assessed with the Numeric Rating Scale (NRS), and fatigue was also measured with the Checklist Individual Strength (CIS). Fatigue (CIS) was compared with reference scores of healthy subjects and patients with RA, using a one-sample t-test. Multiple linear regression models for pain and fatigue were developed using a-priori selected independent variables based on a theoretical framework (ICF-model). Pain was reported by 87.8% (NRS = 3.19±2.6) and fatigue by 90.4% (NRS = 4.1±2.6) of patients with MO. Fatigue scores for MO (CIS = 84.1±15.3) were significantly higher (p<0.001) compared to reference scores of healthy subjects and patients with RA. The multivariable analysis for pain provided a final regression model with six variables (R2 = 0.445, p<0.001) of which fear avoidance beliefs and fatigue had the strongest association. For the fatigue models NRS (R2 = 0.455, p<0.001) and CIS (R2 = 0.233, p<0.001), the strongest associations were found with anxiety and depression respectively. Pain and fatigue are highly prevalent in patients with MO. Fatigue is significantly higher compared to healthy subjects and patients with RA. Several variables associated with pain and fatigue have been identified that could help improve multidisciplinary treatment plans.

Visceral fat mass dynamics in a 2-year randomized STrength versus ENdurance training trial in people with obesity.

To compare the effectiveness of strength versus endurance training on reducing visceral fat in individuals with obesity. For the STrength versus ENdurance (STEN) 24-month randomized clinical trial, we assigned 239 participants with abdominal obesity to either strength or endurance training (two to three times a week, 60 min/training session) in addition to standard nutritional counselling to promote a healthy diet. Changes in abdominal visceral adipose tissue (VAT) area quantified by magnetic resonance imaging after 12 months were defined as a primary endpoint. Participants (aged 44 years, 74% women, body mass index: 37 kg/m2, mean VAT volume: 4050 cm3) had an approximately 50% retention rate and a 30% good training programme adherence at 12 months. There was no difference between strength and endurance training in VAT volume dynamics after 12 and 24 months (p = .13). Only in the good adherence group did we find a trend for reduced VAT volume in both training regimens. Independently of the exercise programme, there was a continuous trend for moderate loss of abdominal subcutaneous AT volume, body fat mass, body mass index and improved parameters of insulin sensitivity. Although parameters of physical fitness improved upon both exercise interventions, the dynamics of resting energy expenditure, glucose and lipid metabolism parameters were not different between the intervention groups and did not significantly improve during the 2-year trial (p > .05). Despite heterogeneous individual training responses, strength and endurance training neither affected VAT volume nor key secondary endpoints differently.

INCEPT: A Framework for Duplicate Posts Classification with Combined Text Representations

Dealing with many of the problems related to the quality of textual content online involves identifying similar content. Algorithmic solutions for duplicate content classification typically rely on text vector representation, which maps textual information into a set of features. Ideally, this representation would capture all aspects of the underlying text, including length, word frequencies, syntax, and semantics. While recent advancements in text representation have led to improved performance, a comprehensive approach that explicitly incorporates all text features has not yet been proposed. In this study, we present the INCEPT framework that utilizes multiple representation methods to detect duplicate text pairs, taking advantage of their individual strengths. The core of our approach involves using a stacking ensemble of pairwise vector distance measurements that are computed from multiple text representation methods. A stacking classifier then utilizes these distance scores as input and learns to identify duplicate posts. We assess the proposed framework’s effectiveness in identifying duplicate posts in an online Question and Answer platform. By combining several text representation methods, INCEPT performs well in the duplicate posts classification task. Our experiments demonstrate that specific framework configurations outperform the accuracy scores obtained from individual text representation methods. Therefore, we also infer that no single text representation method can independently capture a text’s features.

What Are the Lived Experiences of Strengths in Autistic Individuals? A Systematic Review and Thematic Synthesis

What Are the Lived Experiences of Strengths in Autistic Individuals? A Systematic Review and Thematic Synthesis

Immediate effects of Kinesio Taping ® on respiratory parameters in healthy individuals

BackgroundKinesio taping® (KT) could facilitate respiratory muscle contraction, improving breathing. Therefore, this study aimed to analyze the immediate effects of KT application on thoracoabdominal mobility, vital capacity, and respiratory muscle strength of healthy young individuals. MethodsThis clinical trial included 19 healthy individuals, measuring their maximum inspiratory and expiratory pressure, vital capacity, and thoracoabdominal mobility using cirtometry. Participants were evaluated, and KT was applied below the xiphoid process; then, they were reassessed 15 min after the application. ResultsThe thoracoabdominal mobility did not significantly change the axillar (84.2 ± 6.6 cm vs 83.6 ± 6.1 cm; p = 0.116), xiphoid process (74.2 ± 8.8 cm vs 74.2 ± 8.63 cm; p = 0.805), and umbilical (73.7 ± 8.1 cm vs 74.2 ± 8.35 cm; p = 0.344) circumferences. Additionally, the vital capacity (3.8 ± 1.0 L vs 3.5 ± 1.3 L; p = 0.097), the maximal inspiratory pressure (−85.3 ± 31.7 cmH2O vs −79.5 ± 34.7 cmH2O; p = 0.265), and maximal expiratory pressure (63.9 ± 31.8 cmH2O vs 59.5 ± 36.1 cmH2O; p = 0.277) were not significantly different. ConclusionsKT showed no immediate effect on thoracoabdominal mobility, vital capacity, and respiratory muscle strength of healthy young adults. Future studies should investigate the effects of KT applied for a longer time (i.e., long-term effects). Furthermore, individuals with respiratory diseases could be evaluated, especially those presenting dysfunction in the rib cage morphology.

Neuropsychological functioning after COVID-19: minor differences between individuals with and without persistent complaints after SARS-CoV-2 infection

Objective: It is unclear how self-reported severe fatigue and difficulty concentrating after SARS-CoV-2 infection relate to objective neuropsychological functioning. The study aimed to compare neuropsychological functioning between individuals with and without these persistent subjective complaints. Method: Individuals with and without persistent severe fatigue (Checklist Individual Strength (CIS) fatigue ≥ 35) and difficulty concentrating (CIS concentration ≥ 18) at least 3 months after SARS-CoV-2 infection were included. Neuropsychological assessment was performed on overall cognitive functioning, attention, processing speed, executive functioning, memory, visuo-construction, and language (18 tests). T-scores −1.5 SD below population normative data (T ≤ 35) were classified as “impaired”. Results: 230 participants were included in the study, of whom 22 were excluded from the analysis due to invalid performance. Of the participants included in the analysis, 111 reported persistent complaints of severe fatigue and difficulty concentrating and 97 did not. Median age was 54 years, 59% (n = 126) were female, and participants were assessed a median of 23 months after first infection (IQR: 16–28). With bivariate logistic regression, individuals with persistent complaints had an increased likelihood of slower information processing speed performance on the Stroop word reading (OR = 2.45, 95%CI = 1.02–5.84) compared to those without persistent complaints. Demographic or clinical covariates (e.g. hospitalization) did not influence this association. With linear regression techniques, persistent complaints were associated with lower t-scores on the D2 CP, TMT B, and TMT B|A. There were no differences in performance on the other neuropsychological tests. Conclusions: Individuals with subjective severe fatigue and difficulty concentrating after COVID-19 do not typically demonstrate cognitive impairment on extensive neuropsychological testing.

Effect of Detraining on Muscle Strength, Functional Capacity, Mental Health, and Body Composition in Individuals with Spinal Cord Injury.

Spinal cord injury (SCI) is a condition that significantly affects the quality of life (QoL) of individuals, causing motor, physiological, social, and psychological impairments. Physical exercise plays a crucial role in maintaining the health and functional capacity of these individuals, helping to minimize the negative impacts of SCI. The aim of this study was to evaluate the effect of detraining (DT) (reduction or cessation of physical exercise) during the pandemic on five individuals with thoracic SCI. We assessed muscle strength using strength tests, functional capacity using a functional agility test, mental health using anxiety and depression inventories, and body composition using dual-energy X-ray absorptiometry (DEXA). The results after 33 months of DT showed significant losses in functional agility and MS, as well as a worsening in symptoms of anxiety and depression. It was observed that total body mass and fat mass (FM) exhibited varied behaviors among the individuals. Similarly, the results for lean body mass were heterogeneous, with one participant showing significant deterioration. It is concluded that DT caused by the pandemic worsened the physical and mental condition of individuals with SCI, highlighting the importance of continuous exercise for this population and underscoring the need for individual assessments to fully understand the impacts of DT.

A Multi-Agent Approach for the Optimized Operation of Modular Electrolysis Plants

In response to the energy transition to renewable resources, green hydrogen production via electrolysis is gaining momentum. Modular electrolysis plants provide a flexible and scalable solution to meet rising hydrogen demand and adapt to renewable energy fluctuations. However, optimizing their operation poses challenges, especially when dealing with heterogeneous electrolyzer modules. In this work, a combination of decentralized Multi-Agent Systems and the Module Type Package concept is presented that enhances the cost-optimized operation of modular electrolysis plants. This approach synergizes the individual strengths of Multi-Agent Systems in handling complex operational dynamics with the efficiency of the Module Type Package for integration and control capabilities. By integrating these technologies, the approach addresses the heterogeneity of electrolyzer modules and increases the adaptability, scalability, and operational flexibility of electrolysis plants. The approach was validated through a case study, demonstrating its effectiveness in achieving cost-optimized load scheduling, dynamic response to demand–supply fluctuations, and resilience against electrolyzer module malfunctions. In summary, the presented approach offers a comprehensive solution for the effective coordination and optimization of modular electrolysis plants.

Rhythm and music for promoting sensorimotor organization in autism: broader implications for outcomes.

Emerging research suggests that music and rhythm-based interventions offer promising avenues for facilitating functional outcomes for autistic individuals. Evidence suggests that many individuals with ASD have music processing and production abilities similar to those of neurotypical peers. These individual strengths in music processing and production may be used within music therapy with a competence-based treatment approach. We provide an updated perspective of how music and rhythm-based interventions promote sensory and motor regulation, and how rhythm and music may then impact motor, social, and communicative skills. We discuss how music can engage and motivate individuals, and can be used intentionally to promote skill acquisition through both structured and flexible therapeutic applications. Overall, we illustrate the potential of music and rhythm as valuable tools in addressing skill development in individuals on the autism spectrum.

Ultrasound-guided gluteal nerves electrical stimulation to enhance strength and power in individuals with chronic knee pain: a randomized controlled pilot trial.

Various pathophysiological contexts can be accompanied by weakness, arthrogenic muscle inhibition, and even disability. In this scenario, peripheral nerve stimulation has been studied not only for pain management but also for the improvement of neuromuscular parameters. For this purpose, the use of Transcutaneous Electrical Nerve Stimulation (TENS) has typically been investigated, but recently, the use of ultrasound-guided percutaneous peripheral nerve stimulation (pPNS) has gained popularity. In this regard, electrical stimulation has a predisposition to activate Type II muscle fibers and has been shown to be capable of generating short-term potentiation by increasing calcium sensitivity. However, the evidence of pPNS applied in humans investigating such variables is rather limited. This pilot study aimed to assess the feasibility of the methodology and explore the potential of pPNS in enhancing hip extension performance in individuals suffering from knee pain, comparing it with TENS. Twelve participants were divided into pPNS and TENS groups, undergoing pre- and post-intervention assessments of peak concentric power (W), strength (N), execution speed (m/s), and one-repetition maximum (1RM) (kg) estimation. For pPNS, two needles were positioned adjacent to the superior and inferior gluteal nerves under ultrasound guidance. For TENS, electrodes were positioned between the posterosuperior iliac spine and the ischial tuberosity, and halfway between the posterosuperior iliac spine and the greater trochanter. The interventions consisted of 10 stimulations of 10 s at a frequency of 10 Hz with a pulse width of 240 μs, with rest intervals of 10 s between stimulations. Peripheral nerve stimulation significantly improved concentric power at 30% (p = 0.03) and 50% (p = 0.03) of 1RM, surpassing TENS, which showed minimal changes. No significant strength differences were observed post-intervention in either group. This work presents evidence where pPNS applied to the gluteal nerves results in an enhanced performance of hip extension at submaximal loads. However, this improvement does not seem to be reflected in short-term changes in the estimation of the 1RM by the force-velocity profile.

Physical Simulation for Studying the Effect of Thermal Cycles Peak Temperature on Intermetallic Formation at Triclad Joints Interface

Aluminum/steel structural transition joints (STJs) are extensively used in the shipbuilding industry. This is because they offer the advantage of effectively combining these two materials, leading to substantial weight savings while maximizing their individual strengths. The research target is to evaluate the metallurgical properties of explosion‐welded Triclad aluminum/steel STJs under different peak temperature thermal cycles. Herein, the Gleeble physical simulator to apply thermal cycles on Triclad specimens with appropriate geometry is exploited. The results highlight that the peak temperature significantly affects the extension, thickness, and chemical composition of the intermetallic layer at the Fe/Al interface. An increase in peak temperature results in an increase in both the extension and thickness of the intermetalliclayer. The increase in peak temperature leads also to the formation of intermetallic compounds with a higher percentage of aluminum.

The effect of perceived social support on fatigue in mothers having twin infants: the mediating role of sleep quality

ABSTRACT The aim of this study is to investigate the mediating role of sleep quality in the relationship between multidimensional perceived social support and fatigue among mothers of twin infants. One hundred and six (106) twin mothers participated in this cross-sectional study, who completed the Descriptive Information Form, Multidimensional Scale of Perceived Social Support, Pittsburgh Sleep Quality Index, and Checklist Individual Strength. The scale score averages of the mothers in the study are as follows: social support, 61.41 ± 23.86; fatigue, 77.64 ± 28.68; and sleep quality, 8.26 ± 2.38. According to the path model, perceived social support has a negative effect on poor sleep quality (p = .001, Beta = −0.411), and poor sleep quality has a positive effect on fatigue (p = .001, Beta = 0.335). Sleep quality also mediates the effect of multidimensional perceived social support on mothers’ fatigue levels (p = .001, Beta = −0.138). The study results suggest that the perceived social support and fatigue levels of twin mothers are moderate, while their sleep quality is poor. Therefore, mothers of twin infants may benefit from increased social support to alleviate fatigue and enhance sleep quality.

Noise recognition of moving parts in a sealed cavity based on the fusion of recognition results and high-dimensional mapping

The detection and identification of noise from moving parts inside a sealed cavity is crucial for ensuring the reliability of sealed equipment. However, traditional noise recognition methods struggle to meet the stringent demands for high detection accuracy. Inspired by the idea of ensemble learning, this paper proposes a noise recognition method that combines recognition results with high-dimensional mapping to enhance the recognition of noise. Firstly, a built noise identification experimental system is used to collect signals. Then, features are filtered and extracted based on acoustic emission principles and signal properties. Ultimately, a new fusion method is devised incorporating recognition results as new features into the original dataset and designing multiple layers of single algorithms based on their individual strengths to enhance the feature extraction capabilities of the algorithm. In the first layer of the fusion algorithm, CatBoost learns from the original dataset and incorporates its recognition results into the dataset. XGBoost then trains on the new dataset as the training set. Finally, the sparse output matrix generated by XGBoost is input into a logistic regression (LR) algorithm for training and prediction. The proposed method is verified by experiments on datasets and the results show that the accuracy of this method is higher than that of a single recogniser. It also performs better than current mature stacking fusion methods and mapping-based fusion methods. This fusion approach is of great significance for improving noise recognition accuracy and for innovating fusion methods.

A Case Report of Alcoholic Hepatitis with Megaloblastic Anemia Treated with Korean Medicine

Objectives: This study aimed to report a case of alcoholic hepatitis with megaloblastic anemia that improved with Korean medicine treatment.Methods: A 27-year-old woman with alcoholic hepatitis and megaloblastic anemia was treated with herbal medicine, acupuncture, and moxibustion. The responses before and after treatment were evaluated using blood tests, ultrasound imaging, the Checklist Individual Strength (CIS), and the numerical rating scale (NRS).Results: Post-treatment, blood tests showed improved liver function test, lipid test, and anemia work-up. Ultrasound imaging showed improvement in the superoinferior diameter of right lobe, from 13.02 to 11.09, and the fatty liver improved. The CIS score decreased from 107 to 55. Fatigue diminished from NRS 10 to NRS 3, and dizziness dropped from NRS 5 to NRS 1. The abdominal distension slightly decreased, from NRS 7 to NRS 5.Conclusion: Korean medicine treatment might be effective for treating alcoholic hepatitis with megaloblastic anemia.

Penerapan Teori Harapan Victor Vroom dalam Meningkatkan Motivasi Kerja Karyawan

Motivation is a complex process that influences an individual's strength, direction and persistence in achieving goals. This article explores the application of Victor Vroom's Expectancy Theory to increase employee work motivation in various sectors. Vroom's theory emphasizes the importance of individual beliefs about the relationship between effort, performance, and results in driving motivation. Using content analysis techniques, this research identifies themes and patterns from literature related to work motivation. The application of Vroom's motivation principles in the context of the public sector, education, and business shows that understanding expectations and desired outcomes can improve individual motivation and performance. For example, the implementation of financial incentives such as Performance Allowances (TPP) in the Wajo Regency Government and project-based learning models in education have shown positive results in increasing motivation. In addition, good governance practices that emphasize transparency and accountability are also in line with Vroom's principles. Organizations that align motivation strategies with employee expectations can achieve increased engagement, reduce dissatisfaction, and create a culture of continuous improvement. In conclusion, understanding and applying Vroom's Expectancy Theory can help organizations create a work environment that supports and significantly improves individual performance

Future Innovation Unleashed for Sustainability in Longitudinal Research in Micro- and Small-Sized Enterprises

The research reveals how micro- and small-sized enterprises can unleash future innovation to pursue sustainability. This empirical participatory action research is conducted from 2018 to 2022 in 18 multi-case micro- and small-sized enterprises. The findings reveal that these enterprises pursue sustainability through instrumental, moral and intrinsic value creation in combination. Despite the experienced uncertainty and resource limitations of the participating enterprises, they can pursue future innovation to create value for customers and society addressing, respectively, UN SDGs No. 3, 8, 9, 11, 12 and 17. None of the hitherto noted entrepreneurial literature branches can alone support micro- and small-sized enterprises to pursue future innovation. However, the literature branches illustrate individual useful strengths. Furthermore, they illustrate limitations for value creation. The illustrated useful strengths and the accompanying limitations call for context-dependent use in micro- and small- sized enterprises through the integration of the relevant specific extant literature branches to support their innovation aims, respectively, utilising opportunities, their own and others’ heterogeneous behaviours and reorganising resources to unleash future sustainable innovation in an action learning approach. Further collaborative participatory action research is needed to support and enable the practical implication potential for value creation in micro- and small-sized enterprises.

Feature fusion Vision Transformers using MLP-Mixer for enhanced deepfake detection

Deepfake technology, utilizing deep learning and computer vision, presents significant security threats by generating highly realistic synthetic media, such as images and videos. In this paper, we propose a feature fusion-based method for deepfake detection, harnessing the capabilities of three Vision Transformer (ViT) architectures: Dual Attention Vision Transformers (DaViT), Inception Transformer (iFormer), and Group Propagation Vision Transformer (GPViT). The proposed feature fusion method integrates the local–global contextual understanding of DaViT, the frequency spectrum broadening of iFormer, and the high-resolution feature retention of GPViT to provide a comprehensive analysis of visual data, crucial for detecting subtle manipulations typical in deepfakes. An MLP-Mixer (Multi-Layer Perceptron-Mixer) model is proposed for the feature fusion process for effective feature integration, enhancing the detection capabilities while preserving the individual strengths of each ViT model. The performance of the proposed method is evaluated using standard datasets, namely FaceForensics++ and Celeb-DF, demonstrating its robustness and generalizability across various scenarios. For the four manipulation techniques in the FaceForensics++ dataset, namely DeepFakes (DF), Face2Face (F2F), FaceSwap (FS), and NeuralTextures (NT), the proposed method achieves area under the curve (AUC) of 99.75%, 97.04%, 98.78%, and 87.49% respectively, Moreover, it demonstrates an AUC of 99.84% on the Celeb-DF dataset. The performance of the proposed model has been evaluated against many state-of-the-art methods to ensure its robustness and generalization capabilities.

Bullying and Cyberbullying in School: Rapid Review on the Roles of Gratitude, Forgiveness, and Self-Regulation.

This study aims to assist decision-making in anti-bullying interventions by highlighting the importance of positive factors such as gratitude, forgiveness, and self-regulation in mitigating the negative impacts of bullying/cyberbullying. The objective was to examine and synthesize available evidence on the impact of gratitude, forgiveness, and self-regulation practices in the school context regarding bullying/cyberbullying phenomena. Three databases were consulted (Web of Science, Scopus, and Scielo), and the results include 14 articles. The three character strengths were associated with psychological well-being, life and school satisfaction, improved mental health, increased likelihood of engaging in pro-social behavior, and reduced involvement in bullying/cyberbullying situations. These strengths have the potential to enhance overall well-being and decrease risk behaviors, leading to more positive outcomes in experiences of violence. These results underscore the importance of considering students' individual strengths and the possible interventions to promote healthy school environments.

Two-Year Results of a Five-Year Personalized Integrative Obesity Coaching Program (IBO) Based upon a Systems Health Perspective and an Evolutionary Longitudinal Study Approach.

This study presents the outcomes of a 5-year personalized integrative coaching program for adults with obesity (body mass index BMI ≥ 30 kg/m2), based upon a systems health perspective, during the first 2 years. This longitudinal study, which had an evolutionary design, included all adults who enrolled in the program. Health-related quality of life (HRQoL) was measured with the Short Form-36 (SF-36), and physical outcomes included weight, waist circumference, aerobic capacity, lipid profile, and HbA1c. Subsequently, participants completed questionnaires (e.g., the Symptom Checlist-90 (SCL-90) and the Checklist Individual Strength (CIS)). Seventy-nine adults with a mean BMI of 39.5 kg/m2 (SD 5.3) were included. Forty-four participants completed 2 years in the program. Compared to baseline, there were significant improvements in the SF-36 subscales 'physical functioning' (MD 9.9 points, 95% CI: 2.1-17.5, p = 0.013) and 'general health perceptions' (MD 9.3 points, 95% CI 2.9-15.7, p = 0.006). Furthermore, significant improvements in physical outcomes and psychosocial questionnaires (e.g., weight loss (MD 3.5 kg, 95% CI: 1.2-5.7, p = 0.003), waist circumference (MD 5.1 cm, 95% CI: 2.4-7.8, p < 0.001), and CIS fatigue (MD 6.8, 95% CI: 3.1-10.5, p = 0.001) were observed. This study highlights the importance of a systems health perspective supporting the development of a personalized integrative coaching program for adults with obesity in a 'real-world' setting.