Specific Movements Research Articles

A tale of three betrayals: news framing of women who enable abusive men

ABSTRACT This study identified the dominant frames in the news coverage of three lawyers – Lisa Bloom, Susan Estrich, and Tina Tchen – who have repeatedly self-identified as feminists and yet have sided with accused harassers and abusers in trying to smear the names of the women sharing their stories. In our analysis of how journalists constructed meaning around this apparent contradiction, we found four dominant news frames: Traitors, Gears in Factories of Complicity, Sellouts, and Blemished Justice Warriors. These frames showed that journalists’ meaning making mostly aligned with research about the significant role played by many women in enabling the patriarchy for personal gain, despite their actions’ consequences for other women. Our analysis also shows that what referred to as ‘the successful institutionalization of the women’s movement’ (p. 152) in news coverage has since evolved into a broader news institutionalization of women’s rights and social justice beyond any specific movement or source. Despite this evidence of progress, we argue that what is missing across the journalistic framing of the analyzed cases is an emphasis on structural and socioeconomic conditions that continue to encourage many women to seek short-term gain at the expense of other women’s suffering.

Addressing Data Absenteeism and Technology Chauvinism in the Use of Gamified Wearable Gloves Among Older Adults: Moderated Usability Study.

Digital health technologies have the potential to improve health outcomes for older adults, especially for those recovering from stroke. However, there are challenges to developing these technologies, such as data absenteeism (where older adults' views are often underrepresented in research and development) and technology chauvinism (the belief that sophisticated technology alone is the panacea to addressing health problems), which hinder their effectiveness. In this study, we aimed to address these challenges by developing a wearable glove integrated with culturally relevant exergames to motivate older adults to exercise and, for those recovering from stroke, to adhere to rehabilitation. We conducted a moderated usability study with 19 older adults, of which 11 (58%) had a history of stroke. Our participants engaged in a 30-minute gameplay session with the wearable glove integrated with exergames, followed by a quantitative survey and an in-depth interview. We used descriptive analysis to compare responses to the System Usability Scale between those who had a history of stroke and those who did not. In addition, we analyzed the qualitative interviews using a bottom-up thematic analysis to identify key themes related to the motivations and barriers regarding the use of wearable gloves for rehabilitation and exercise. Our study generated several key insights. First, making the exergames exciting and challenging could improve exercise and rehabilitation motivation, but it could also have a boomerang effect, where participants may become demotivated if the games were very challenging. Second, the comfort and ease of use of the wearable gloves were important for older adults, regardless of their stroke history. Third, for older adults with a history of stroke, the functionality and purpose of the wearable glove were important in helping them with specific exercise movements. Our findings highlight the importance of providing contextual support for the effective use of digital technologies, particularly for older adults recovering from stroke. In addition to technology and usability factors, other contextual factors such as gamification and social support (from occupational therapists or caregivers) should be considered to provide a comprehensive approach to addressing health problems. To overcome data absenteeism and technology chauvinism, it is important to develop digital health technologies that are tailored to the needs of underserved communities. Our study provides valuable insights for the development of digital health technologies that can motivate older adults recovering from stroke to exercise and adhere to rehabilitation.

Facial expressions to identify post-stroke: A pilot study

Background and Objective:Timely stroke treatment can limit brain damage and improve outcomes, which depends on early recognition of the symptoms. However, stroke cases are often missed by the first respondent paramedics. One of the earliest external symptoms of stroke is based on facial expressions. Methods:We propose a computerized analysis of facial expressions using action units to distinguish between Post-Stroke and healthy people. Action units enable analysis of subtle and specific facial movements and are interpretable to the facial expressions. The RGB videos from the Toronto Neuroface Dataset, which were recorded during standard orofacial examinations of 14 people with post-stroke (PS) and 11 healthy controls (HC) were used in this study. Action units were computed using XGBoost which was trained using HC, and classified using regression analysis for each of the nine facial expressions. The analysis was performed without manual intervention. Results:The results were evaluated using leave-one-our validation. The accuracy was 82% for Kiss and Spread, with the best sensitivity of 91% in the differentiation of PS and HC. The features corresponding to mouth muscles were most suitable. Conclusions:This pilot study has shown that our method can detect PS based on two simple facial expressions. However, this needs to be tested in real-world conditions, with people of different ethnicities and smartphone use. The method has the potential for a computerized assessment of the videos for use by the first respondents using a smartphone to perform screening tests, which can facilitate the timely start of the treatment.

Enhancing patient safety through integrated sensor technology and machine learning for bed-based patient movement detection in inpatient care

The occurrence of inpatient falls and new-onset seizures are common complications during hospital stays, posing risks to patient safety and potentially leading to prolonged hospital stays and further complications. Given the constraints on medical staff’s ability to provide constant monitoring due to their workload, the implementation of a sensor device equipped with machine learning capabilities to recognize and prevent these events becomes imperative. This study utilized data acquired through the Movella Xsens sensor, which detects real-time motions and 3D movements, in conjunction with the PyCaret machine-learning algorithm. Adult-sized and infant-sized mannequins were used to assess the algorithm’s ability in predicting specific movements associated with breathing, seizures, rolling to the right side, rolling to the left side, rolling off the bed from the left, and rolling off the bed from the right. The study achieved an overall 89% accuracy rate in detecting each specific movement using the combination of PyCaret and Xsens sensors. The application of PyCaret alongside Xsens sensors demonstrates promising results in accurately detecting movements, thereby mitigating falls and post-seizure complications in an inpatient setting, consequently improving patient safety. Further exploration of this technology holds the potential to revolutionize healthcare delivery by incorporating it into a trigger alert system capable of promptly warning medical staff of urgent situations through real-time capture and analysis of potentially harmful motions.

Effect of material composition and thickness of orthodontic aligners on the transmission and distribution of forces: an in vitro study.

To investigate the effects of material type and thickness on force generation and distribution by aligners. Sixty aligners were divided into six groups (n = 10): one group with a thickness of 0.89mm using Zendura Viva (Multi-layer), four groups with a thickness of 0.75mm using Zendura FLX (Multi-layer), CA Pro (Multi-layer), Zendura (Single-layer), and Duran (Single-layer) sheets, and one group with a thickness of 0.50mm using Duran sheets. Force measurements were conducted using Fuji® pressure-sensitive films. The lowest force values, both active and passive, were recorded for the multi-layered sheets: CA Pro (83.1N, 50.5N), Zendura FLX (88.9N, 60.7N), and Zendura Viva (92.5N, 68.5N). Conversely, the highest values were recorded for the single-layered sheets: Duran (131.9N, 71.8N) and Zendura (149.7N, 89.8N). The highest force was recorded at the middle third of the aligner, followed by the incisal third, and then the cervical third. The net force between the incisal and cervical thirds (FI-FC) showed insignificant difference across different materials. However, when comparing the incisal and middle thirds, the net force (FI-FM) was higher with single-layered materials. Both overall force and net force (FI-FM) were significantly higher with 0.75mm compared to those with a thickness of 0.50mm. Multi-layered aligner materials exert lower forces compared to their single-layered counterparts. Additionally, increased thickness in aligners results in enhanced retention and greater force generation. For effective bodily tooth movement, thicker and single-layered rigid materials are preferred. This research provides valuable insights into the biomechanics of orthodontic aligners, which could have significant clinical implications for orthodontists. Orthodontists might use this information to more effectively tailor aligner treatments, considering the specific tooth movement required for each individual patient. In light of these findings, an exchangeable protocol for aligner treatment is suggested, which however needs to be proven clinically. This protocol proposes alternating between multi-layered and single-layered materials within the same treatment phase. This strategy is suggested to optimize treatment outcomes, particularly when planning for a bodily tooth movement.

Objective estimation of m-CTSIB balance test scores using wearable sensors and machine learning.

Accurate balance assessment is important in healthcare for identifying and managing conditions affecting stability and coordination. It plays a key role in preventing falls, understanding movement disorders, and designing appropriate therapeutic interventions across various age groups and medical conditions. However, traditional balance assessment methods often suffer from subjectivity, lack of comprehensive balance assessments and remote assessment capabilities, and reliance on specialized equipment and expert analysis. In response to these challenges, our study introduces an innovative approach for estimating scores on the Modified Clinical Test of Sensory Interaction on Balance (m-CTSIB). Utilizing wearable sensors and advanced machine learning algorithms, we offer an objective, accessible, and efficient method for balance assessment. We collected comprehensive movement data from 34 participants under four different sensory conditions using an array of inertial measurement unit (IMU) sensors coupled with a specialized system to evaluate ground truth m-CTSIB balance scores for our analysis. This data was then preprocessed, and an extensive array of features was extracted for analysis. To estimate the m-CTSIB scores, we applied Multiple Linear Regression (MLR), Support Vector Regression (SVR), and XGBOOST algorithms. Our subject-wise Leave-One-Out and 5-Fold cross-validation analysis demonstrated high accuracy and a strong correlation with ground truth balance scores, validating the effectiveness and reliability of our approach. Key insights were gained regarding the significance of specific movements, feature selection, and sensor placement in balance estimation. Notably, the XGBOOST model, utilizing the lumbar sensor data, achieved outstanding results in both methods, with Leave-One-Out cross-validation showing a correlation of 0.96 and a Mean Absolute Error (MAE) of 0.23 and 5-fold cross-validation showing comparable results with a correlation of 0.92 and an MAE of 0.23, confirming the model's consistent performance. This finding underlines the potential of our method to revolutionize balance assessment practices, particularly in settings where traditional methods are impractical or inaccessible.

Compliance and Kinetostatics of a Novel 2PRS-2PSS Compliant Parallel Micromanipulator: Modeling and Analysis.

A novel 2PRS-2PSS (P represents the prismatic pair, R represents the revolute hinge, S represents the spherical hinge) compliant parallel micromanipulator with two translational DOFs and two rotational DOFs is presented, and its compliance model and kinetostatic model are sequentially developed and analyzed. Initially, an analytical model used to describe the compliance of this micromanipulator was developed using the compliance matrix method (CMM). Through a comparison with finite element analysis, the accuracy of this analytical model is confirmed, and the influence of various dimensional and structural parameters on the compliance behavior is investigated. Subsequently, the micromanipulator is treated as an equivalent spring system, allowing for the derivation of its governing equation based on the established compliance model. From this equation, a kinetostatic model relating input forces to output displacements is derived. Validation of this model is performed by comparing analytical results with finite element simulations under specific motion trajectories, revealing a maximum relative error of 6.18%. This close agreement verifies the accuracy of the kinetostatic model. Finally, the impact of the parameters of the flexure hinge on the mapping matrix is examined to offer insights into minimizing undesired displacements, providing valuable guidance for optimizing the micromanipulator's performance.

The relationship between manual ability, dystonia and choreoathetosis severity and upper limb movement patterns during reaching and grasping in children and young adults with dyskinetic cerebral palsy

IntroductionImpaired upper limb movements are a key feature in dyskinetic cerebral palsy (CP). However, information on how specific movement patterns relate to manual ability, performance and underlying movement disorders is lacking. Insight in these associations may contribute to targeted upper limb management in dyskinetic CP. This study aimed to explore associations between deviant upper limb movement patterns and (1) manual ability, (2) severity of dystonia/choreoathetosis, and (3) movement time/trajectory deviation during reaching and grasping. Participants/methodsParticipants underwent three-dimensional upper limb analysis during reaching forwards (RF), reaching sideways (RS) and reach-and-grasp vertical (RGV) as well as clinical assessment. Canonical correlation and regression analysis with statistical parametric mapping were used to explore associations between clinical/performance parameters and movement patterns (mean and variability). ResultsThirty individuals with dyskinetic CP participated (mean age 16±5 y; 20 girls). Lower manual ability was related to higher variability in wrist flexion/extension during RF and RS early in the reaching cycle (p < 0.05). Higher dystonia severity was associated with higher mean wrist flexion (40–82 % of the reaching cycle; p = 0.004) and higher variability in wrist flexion/extension (31–75 %; p < 0.001) and deviation (2–14 %; p = 0.007/60–73 %; p = 0.006) during RF. Choreoathetosis severity was associated with higher elbow pro/supination variability (12–19 %; p = 0.009) during RGV. Trajectory deviation was associated with wrist and elbow movement variability (p < 0.05). ConclusionCurrent novel analysis of upper limb movement patterns and respective timings allows to detect joint angles and periods in the movement cycle wherein associations with clinical parameters occur. These associations are not present at each joint level, nor during the full movement cycle. This knowledge should be considered for individualized treatment strategies.

Effects of Structured Physical Activity on Motor Fitness in Preschool Children.

The aim was to investigate the impact of a specific structured movement activities (SMA) program compared to free play activity (FRP) on the strength, speed, agility, coordination, and balance of motor fitness (MF) in 6-year-old boys and girls. A total of 53 children (24 boys, 29 girls) were randomly allocated to either the SMA group or the FRP group. Both group activities were administered three times a week over a 6-month period. MF variables were assessed before (pre-) and after (post-) using tests: the flamingo balance (FLA), the standing long jump (SLJ), plate tapping (PTT), the obstacle course backwards (OCB), and the shuttle run 4 × 5 m (SRT). At the post-test, the SMA program resulted in significant (p < 0.05) improvements in OCB, PTT, SLJ, and SRT tasks. For FRP, a noteworthy improvement was observed only in OCB (ES = 0.45, p < 0.05). An ANCOVA revealed a significant group × time interaction (F = 21.71-52.41, η2 = 0.258-0.512, p < 0.01) for OCB, PTT, and SRT, favoring SMA over FRP. The present findings suggest that SMA may be more effective than FRP when aiming to develop motor coordination, agility, and speed of movement in children.

Dynamic anthropomorphic thorax phantom for quality assurance of motion management in radiotherapy

Background and purposeMotion management techniques are important to spare the healthy tissue adequately. However, they are complex and need dedicated quality assurance. The aim of this study was to create a dynamic phantom designed for quality assurance and to replicate a patient’s size, anatomy, and tissue density. Materials and methodsA computed tomography (CT) scan of a cancer patient was used to create molds for the lungs, heart, ribs, and vertebral column via additive manufacturing. A pump system and software were developed to simulate respiratory dynamics. The extent of respiratory motion was quantified using a 4DCT scan. End-to-end tests were conducted to evaluate two motion management techniques for lung stereotactic body radiotherapy (SBRT). ResultsThe chest wall moved between 4 mm and 13 mm anteriorly and 2 mm to 7 mm laterally during the breathing. The diaphragm exhibited superior-inferior movement ranging from 5 mm to 16 mm in the left lung and 10 mm to 36 mm in the right lung. The left lung tumor displaced ± 7 mm superior-inferiorly and anterior-posteriorly. The CT numbers were for lung: −716 ± 108 HU (phantom) and −713 ± 70 HU (patient); bone: 460 ± 20 HU (phantom) and 458 ± 206 HU (patient); soft tissue: 92 ± 9 HU (phantom) and 60 ± 25 HU (patient). The end-to-end testing showed an excellent agreement between the measured and the calculated dose for ion chamber and film dosimetry. ConclusionsThe phantom is recommended for quality assurance, evaluating the institution’s specific planning and motion management strategies either through end-to-end testing or as an external audit phantom.

Energy conversion in pole vaulting using finite element analysis

The article examines pole vaulting as a demanding track and field discipline, where athletes use a flexible pole to clear a high bar. The study explores the research challeng-es associated with this discipline, including the impact of pole material, the physical capabilities of the vaulter, and the vaulting technique on performance. The paper pre-sents a new Finite Element Analysis in ANSYS, focusing on energy conversion in the pole-vaulter interaction. Simulation results highlight the influence of pole stiffness and length for jump height, as well as the impact of synchronization between pole and pole positions on performance. Finally, the article highlights that pole vault performance is intrinsically linked to the pole vaulter's specific movement and ability to optimize interac-tion with the pole. This deeper understanding can help improve individual performance in this demanding athletics discipline.

Pediatric Performance-Based Outcome Measures for Upper Extremity Function: A Scoping Review and Linking to the International Classification of Functioning, Disability, and Health.

Background. Performance-based outcome measures (PBOMs) are objective measures that assess physical capacity or performance in specific tasks or movements. Purpose. 1) to identify which PBOMs are most frequently reported to evaluate upper extremity (UE) function in pediatric rehabilitation 2) to determine the link between constructs of the ICF and meaningful concepts extracted from each identified PBOM. Methods. Pediatric UE PBOMs were searched in four databases. The selection of outcome measures included an initial title and abstract screening, followed by full-text review of the articles to be included based on identified selection criteria. Two reviewers were appointed to link the meaningful concepts identified in the outcome measures independently and a third reviewer was consulted in case of ambiguity to make a final decision. Findings. After the initial screening, 1786 full-text articles were reviewed, 1191 met the inclusion criteria, in which 77 outcome measures were identified and 32 were included in the linking process. From the included 32 outcome measures, 538 items were extracted and linked to the ICF. The most commonly cited measures included Assisting Hand Assessment, Jebsen-Taylor Hand Function Test, Melbourne Assessment of Unilateral Upper Limb. The Activity and Participation domain represented 364 codes followed by the Body Functions domain domain which represented 174 codes. Implications. A majority of the outcome measures identified were linked with the Mobility, Fine Hand Use of the ICF. Therefore, when selecting a PBOM, careful considerations need to be made regarding which concept of health is to be assessed.

Multimodal Autonomous Locomotion of Liquid Crystal Elastomer Soft Robot.

Self-oscillation phenomena observed in nature serve as extraordinary inspiration for designing synthetic autonomous moving systems. Converting self-oscillation into designable self-sustained locomotion can lead to a new generation of soft robots that require minimal/no external control. However, such locomotion is typically constrained to a single mode dictated by the constant surrounding environment. In this study, a liquid crystal elastomer (LCE) robot capable of achieving self-sustained multimodal locomotion, with the specific motion mode being controlled via substrate adhesion or remote light stimulation is presented. Specifically, the LCE is mechanically trained to undergo repeated snapping actions to ensure its self-sustained rolling motion in a constant gradient thermal field atop a hotplate. By further fine-tuning the substrate adhesion, the LCE robot exhibits reversible transitions between rolling and jumping modes. In addition, the rolling motion can be manipulated in real time through light stimulation to perform other diverse motions including turning, decelerating, stopping, backing up, and steering around complex obstacles. The principle of introducing an on-demand gate control offers a new venue for designing future autonomous soft robots.

Inter- and intraobserver agreement of antenatal cardiotocography assessments by maternity care professionals: A prospective study.

In the Netherlands, antenatal cardiotocography (aCTG) to assess fetal well-being is performed in obstetrician-led care. An innovative initiative was started to evaluate whether aCTG for specific indications-reduced fetal movements, external cephalic version, or postdate pregnancy-is feasible in non-obstetrician-led care settings by independent primary care midwives. Quality assessment is essential when reorganizing and shifting tasks and responsibilities. Therefore, we aimed to assess the inter- and intraobserver agreement for aCTG assessments between and within four professional groups involved in Dutch maternity care regarding the overall classification and assessment of the various components of aCTG. This was a prospective study among 47 Dutch primary care midwives, hospital-based midwives, residents, and obstetricians. Ten aCTG traces were assessed twice at a 1 month interval. To ensure a representative sample, we used two different sets of 10 aCTG traces each. We calculated the degree of agreement using the proportions of agreement. The proportions of agreement for interobserver agreement on the classification of aCTG between and within the four professional groups varied from 0.82 to 0.94. The proportions of agreement for each professional group were slightly higher for intraobserver (0.86-0.94) than for interobserver agreement. For the various aCTG components, the proportions of agreement for interobserver agreement varied from 0.64 (presence of contractions) to 0.98 (baseline heart frequency). The proportion of agreement levels between and within the maternity care professionals in the classification of aCTG traces among healthy women were comparable. This means that these professional groups are equally well able to classify aCTGs in healthy pregnant women.

Do Humans and Convolutional Neural Networks Attend to Similar Areas during Scene Classification: Effects of Task and Image Type

Deep neural networks are powerful image classifiers but do they attend to similar image areas as humans? While previous studies have investigated how this similarity is shaped by technological factors, little is known about the role of factors that affect human attention. Therefore, we investigated the interactive effects of task and image characteristics. We varied the intentionality of the tasks used to elicit human attention maps (i.e., spontaneous gaze, gaze-pointing, manual area selection). Moreover, we varied the type of image to be categorized (i.e., singular objects, indoor scenes consisting of object arrangements, landscapes without distinct objects). The human attention maps generated in this way were compared to the attention maps of a convolutional neural network (CNN) as revealed by a method of explainable artificial intelligence (Grad-CAM). The influence of human tasks strongly depended on image type: for objects, human manual selection produced attention maps that were most similar to CNN, while the specific eye movement task had little impact. For indoor scenes, spontaneous gaze produced the least similarity, while for landscapes, similarity was equally low across all human tasks. Our results highlight the importance of taking human factors into account when comparing the attention of humans and CNN.

Physical Demands of Walking Football in Patients With Cardiovascular Risk Factors and Diseases.

To compare the exercise intensity of walking football (WF) with walking (WA) and to describe specific movement characteristics of WF. Cross-sectional study. Sports facilities Saarland University, Germany. Eighteen patients with cardiovascular risk factors CVRFs and diseases (13 men and 5 women, age: 69 ± 10 years). Patients completed a WF match and WA session of 2 x 10 min each. Video analysis was used to characterize movements during WF. Rate of perceived exertion (RPE, Borg Scale 6-20), % maximum heart rate (HR max ), musculoskeletal pain on a visual analog scale (VAS, 1-100 mm) before and up to 72 hours after exercise, and movement patterns during WF. The mean RPE during WF (12.1 ± 2.7) and WA (11.9 ± 3.0) did not differ ( P = 0.63). The mean HR during WF (79 ± 12% of HR max ) was higher than during WA (71% ± 11%; P < 0.01). The HR variability coefficient of variation during WF (10.3% ± 5.8%) and WA (7.1 ± 5.5%) did not differ ( P = 0.13). There was no influence of exercise mode (WF vs WA) on musculoskeletal pain perception ( P = 0.96 for interaction). Injury-inciting activities such as lunges (median: 0.5 [interquartile range (IQR) 0-1.3]) and goal kicks (median: 4 [IQR: 1.8-5.3]) occurred rarely during WF. Walking football might represent an alternative to WA for health prevention programs in patients with CVRF and diseases as it is characterized by a manageable cardiocirculatory strain, moderate RPE, low pain induction, and a low number of injury-inciting activities.

Investigation of Graphene Platelet-Based Dry Lubricating Film Formation in Tribological Contacts

Dry lubricants used in highly loaded rolling bearings are in the focus of current research. In previous studies, graphene platelets applied as dry lubricants on the surfaces of angular contact ball bearings demonstrated superior properties. These specific bearings, experiencing both rolling and spinning motion, create more severe conditions for dry lubricants. To gain deeper insights into the lubrication effects, micro-tribological studies were carried out on the respective film formation and running behavior effects. In the tests, a fixed steel ball slid against an oscillating counterpart under a defined load. During the measurements, the applied load and tangential forces on the ball were recorded to calculate the friction. Comparative investigations included nano-graphite particles and fullerene as dry lubricants, in addition to graphene platelets of various staple thicknesses. To increase the adhesion of the films to the surfaces, a pre-rolling process was implemented. Afterwards, the friction on the compressed films was measured. The results indicate that the pre-rolling process effectively reduces the friction of the system. After testing, the surfaces underwent analysis using laser scanning microscopy to assess the formed films, wear, and material transfer. It has been demonstrated that the pre-rolling process leads to the formation of a very thin compacted film with surface protective properties. With the ball as a counterpart, the graphene platelets generate a transfer film on the contacting surface.

Comparison of injury risk indicators in amateur female rugby players from different countries

Background: Most specific rugby movements require an efficient stretch-shortening cycle (SSC). Reactive strength index (RSI) and leg stiffness have been considered a reliable measure of SSC capability and an indicator of ACL injury risk. The aim of this study was to assess and compare absolute leg stiffness (ALS) and RSI in amateur female rugby players from different countries.Methods: Players of three female rugby teams participated in the study: the female Czech team, the junior female Czech team, and the female university English team. Twenty repetitions of the submaximal bilateral hopping test were used for the calculation of ALS. RSI was obtained from 5 repetitions of the maximum hop test. Results: The values of the basic statistics were as follows: the female Czech team (median, mean SD): ALS, 25.3 kNm–1, 25.4 3.6 kNm–1; RSI, 0.53, 0.60 0.24; the junior female Czech team (median, mean SD): ALS, 22.7 kNm–1, 23.1 4.6 kNm–1; RSI, 0.37, 0.42 0.19, and the female university English team (median, mean SD): ALS, 22.7 kNm–1, 24.0 3.5 kNm–1; RSI, 0.61, 0.59 0.20. Only a between-group comparison of RSI of the female Czech team and the junior female Czech team (p = 0.04, r = 0.37, medium effect) showed significant differences. Conclusion: No significant differences between groups were found, except for Czech teams of different ages in RSI. The lower values of ALS and RSI compared to other studies can potentially be associated with a higher risk of ACL injury.

Decision Support System Driven by Thermo-Complexity: Scenario Analysis and Data Visualization

The present modelling aims to construct a computational information representation system useful for decision support system (DSS) solutions in the realization of intelligent systems or complex systems analysis solutions. Starting from an n-dimensional space (with n ≥ 7) represented by problem variables (referred to as CSF—Critical Success Factors), a dimensional embedding procedure is used to transition to a two-dimensional space. In the two-dimensional space, thanks to new lattice motion algorithms, the decision support system can determine the optimal solution with a lower computational cost based on the decision-maker’s preferences. Finally, thanks to an algorithm that takes into account the hierarchical order of importance of the seven CSFs as per the expert’s liking or according to his optimization logics, a return is made to the n-dimensional space and the final solution in the original space. As we will see, the starting and ending states in the n-dimensional space (referred to as micro-states) when projected into the two-dimensional space generate states (referred to as macro-states) which are degenerate. In other words, the correspondence between micro-states and macro-states is not one-to-one, as multiple micro-states correspond to one macro-state. Therefore, in relation to the decision-maker’s preferences, it will be the responsibility of the decision support system to provide the decision-maker with the micro-state of interest in the n-dimensional space (dimensional emergence procedure), starting from the obtained optimal macro-state. This result can be achieved starting from a flat chain of sensors capable of measuring/emulating certain specific parameters of interest. As we will see, it emerges that by considering random–exhaustive rolling value paths in order to track and potentially intervene to rebalance a dynamic system representing the state of stress/sensing of a system of interest, we are using the most general and, therefore, complex hypotheses of ergodic theory. In this work, we will focus on the representation of information in n-dimensional and two-dimensional spaces, as well as construct evaluation scenarios. We will also show the results of the decision support system in some cases of specific interest, thanks to a specific lattice motion algorithm of the realized decision-making environment.

3D Printing Bio‐Inspired Micro Soft Robot with Programming Magnetic Elastic Composites

AbstractBio‐inspired micro soft robots mimic biologically specific body structures and movement mechanisms by utilizing bionic principles. Because of its soft body, it can adapt to complex external environments. However, the existing polymer material system is single and the fabrication process is limited. How to further reduce soft robot size has become a key issue. In this work, a Programming Magnetic Elastic Composites (PMEC) is proposed for 3D printing to manufacture micro soft robots. The PMEC has the advantage of changing the direction of the internal magnetic field in response to changes in the external magnetic field. A Microsoft robot is designed and fabricated using PMEC inspired by an inchworm. Numerical simulations are also used to study the effect of soft robot size parameters on local stresses and optimize the structure. The results show that the microscale soft robot can crawl with a load of 2 times its weight at a speed of 6.67 mm s−1, crawl on slopes from 0° to 90°, and crawl over obstacles with a maximum height of 7 mm. In addition, active adaptation of soft robots to complex tunnel models based on external stimuli is achieved by magnetic field control.