Terms Of Balance Research Articles

Comparison of a single session of tDCS on cerebellum vs. motor cortex in stroke patients: a randomized sham-controlled trial

Objective The purpose of this study was to determine whether a single session of trans-cranial direct current stimulation (tDCS) of the cerebellum and M1 has any advantages over one another or sham stimulation in terms of balance, gait and lower limb function. Methods A total of 66 patients who had experienced their first ever stroke were recruited into three groups for this double-blinded, parallel, randomized, sham-controlled trial: cerebellar stimulation group (CbSG), M1 stimulation group (MSG) and sham stimulation group (SSG). A single session of anodal tDCS with an intensity of 2 mA for a duration of 20 min was administered in addition to gait and balance training based on virtual reality using an Xbox 360 with Kinect. Balance, gait, cognition and risk of fall were assessed using outcome measures before intervention (T0), immediately after intervention (T1) and an hour after intervention (T2). Results Across group analysis of all outcome measures showed statistically non-significant results (p > .05) except for Six Minute Walk Test (p value T0 = .003, p value T1 = .025, p value T2 = .016). The training effect difference showed a significant difference in balance, gait and cognition, as well as cerebral and cerebellar stimulation, in comparison to sham stimulation (p < .05). The risk of falls remained unaffected by any stimulation (p > .05). Conclusions In addition to Xbox Kinect-based rehabilitation training, a single session of anodal tDCS to the M1 or cerebellum may be beneficial for improving lower limb function, balance and gait performance.

Telerehabilitation for Stroke: A Personalized Multi-Domain Approach in a Pilot Study.

Stroke, a leading cause of long-term disability worldwide, manifests as motor, speech language, and cognitive impairments, necessitating customized rehabilitation strategies. In this context, telerehabilitation (TR) strategies have emerged as promising solutions. In a multi-center longitudinal pilot study, we explored the effects of a multi-domain TR program, comprising physiotherapy, speech therapy, and neuropsychological treatments. In total, 84 stroke survivors (74 analyzed) received 20 tailored sessions per domain, addressing individual impairments and customized to their specific needs. Positive correlations were found between initial motor function, cognitive status, independence in activities of daily living (ADLs), and motor function improvement after TR. A lower initial health-related quality of life (HRQoL) perception hindered progress, but improved ADL independence and overall health status, and reduced depression correlated with a better QoL. Furthermore, post-treatment improvements were observed in the entire sample in terms of fine motor skills, upper-limb functionality, balance, independence, and cognitive impairment. This multi-modal approach shows promise in enhancing stroke rehabilitation and highlights the potential of TR in addressing the complex needs of stroke survivors through a comprehensive support and interdisciplinary collaboration, personalized for each individual's needs.

A novel software defect prediction approach via weighted classification based on association rule mining

Software defect prediction technology is used to assist software practitioners in effectively allocating test resources and identifying hidden defects in a timely manner. However, the prediction of defect-prone software using association rule mining algorithms is limited because of the unbalanced distribution of defect data. Furthermore, although the existing weighted association rule mining approach considers item strength, the weight calculation still relies on expert experience and lacks fine granularity. We propose a novel software defect prediction approach based on mutual information and correlation coefficient weighted class association rule mining (MCWCAR). The MCWCAR model employs a cost-sensitive strategy and generates frequent itemsets according to three mining objectives while maintaining the original item distribution: defective class rules, non-defective class rules, and feature association relationships. During the weighted frequent itemset mining process, it combines feature selection and itemset screening to determine the appropriate feature combination through mutual information weighted support. Meanwhile, the correlation coefficient is applied to accurately depict the correlation between feature items and defect classes, serving as the weight to mine class association rules. Additionally, to ensure that interestingness measures have asymmetry and effectively represent negative associations under the condition of class imbalance, the addedvalue is adopted in the filtering association rules. We conducted experiments on 27 open-source datasets and evaluated the performance differences between MCWCAR and state-of-the-art baseline classifiers. Experimental results demonstrate that the proposed algorithm significantly outperforms other baselines in terms of Balance, Gmean, MCC, and F-measure.

Dual Motor Power Sharing Control for Electric Vehicles With Battery Power Management

Induction motor powertrains are emerging as a cost-effective option for high-power electric vehicles (EVs). A differential four-wheel drive (D4WD) EV based on two open end winding induction motor (OEWIM) propulsion is presented in this paper. Each OEWIM is driven by two 2-level voltage source inverters (VSI) with two isolated battery packs as the source. The proposed drive control algorithm integrates the uniform state-of-charge (SoC) distribution and fault-tolerant operation. A two-stage look-up table (LUT) based direct torque control (DTC) scheme is proposed to balance the SoC of batteries by selecting the suitable redundant VSI voltage vectors. The proposed LUT-DTC scheme is less sensitive to variations in motor parameters and provides excellent steady-state and transient performance. The results show the superiority of the proposed controller in terms of battery SoC balancing. The performance of the EV drive with the proposed LUT-DTC is validated by both simulation and laboratory experiments for the FTP75 and HFET driving cycles under different operating modes under normal and fault conditions. The dual motor driven D4WD with the proposed LUT-DTC is found to achieve 89.2% efficiency.

Scale-Up Investigation of a Pilot and Industrial Scale Semi-Autogenous Mill Using a Particle Scale Model

A particle scale model based on a full two-way coupling of the Discrete Element Method (DEM) and Smoothed Particle Hydrodynamics (SPHs) methods is applied to SAG mills. Motion and collisions of resolved coarser particles within an SAG mill are performed by the DEM component. Fine particles in the feed combine with the water to form a slurry, which is represented by the SPH component of the model. Slurry rheology is controlled by solid loading and fine particle size distribution for each volume of slurry. Transport, dispersion, and grinding of the slurry phase particle size distribution are predicted by solving additional coupled advection–diffusion equations in the SPH component of the model. Grinding of the finer particles in the slurry due to collisions and shear of the coarser particles (rocks and grinding media) is achieved via the inclusion of population balance terms in these equations for each SPH particle. This allows prediction of the transport of both coarser and finer material within the grinding and pulp chambers of an SAG mill, including the discharge performance of the mill. This particle-scale model is used to investigate the relative performance (throughput, product size distribution, resident particle size distribution, net power draw, wear) for an SAG mill at a pilot scale and a 36 ft industrial scale. The 36′ SAG mill considered is a geometrically scaled-up version of the 1.8 m Hardinge pilot scale mill but with a longer belly length, reflecting current SAG mill design preferences. The belly lifters are scaled to a lesser degree with a larger number of lifters used (but still many fewer liners than would typically be used in a large SAG mill based on conventional liner selection rules). The model shows that despite reasonable qualitative similarities, many aspects of the charge structure, slurry transport, coarse particle and slurry discharge through the grates, and the collision energy spectra vary in important ways. This demonstrates that a near purely geometric scale-up of an SAG mill is not sufficient to produce a comparable performance at the two physical mill scales.

Experimental analysis of dust composition impact on Photovoltaic panel Performance: A case study

Solar Photovoltaic systems are greatly influenced by meteorological conditions of the surrounding area, dust is the most influencing one. Dust deposition on the surface of photovoltaic (PV) panel hinder the penetration of solar radiation to PV cells and eventually reduce the power production of PV system. To overcome dust-based power losses, frequent cleaning is required depending on geographical location, PV integration scheme and size of the PV power plant. In this manuscript, consequences of dust deposition on photovoltaic systems such as drop in radiation and output power operating are studied, and the optimal time interval for cleaning is determined. Airborne dust particles were collected for a month for morphological and meteorological characterization. The average mass concentrations of the sample are 187.63 μgm-3, showcasing an irregular distribution of dust particles having unlike shapes and sizes. In this study, the influence of dust deposition is quantified using temperature and insolation for clean and dirty PV panels. The overall performance of the PV system is studied based on a comparison of quantified and recorded data. Lastly, different cleaning methodologies are studied to procure the best ones. Power losses were brought down to 7% when PV panels were cleaned fortnightly, which is the most feasible interval in terms of balance between cleaning cost and energy wasted due to soiling.

Numerical analysis of multipurpose shell-tube-heat exchanger withal stylized geometry at different baffle gaps and various flow rates

The effects of changing 90 mm and 110 mm plate spacings and FR factor of 0.9 kg/h, 1.3 kg/h, 1.7 kg/h, 1.9 kg/h on the total heat transfer performance and PD in the new design HX were examined. The results obtained by taking into account the change in plate spacing and FR factor of 0.9 kg/h, 1.3 kg/h, 1.7 kg/h and 1.9 kg/h, as well as variable factors, were transferred to the study and displayed in figures. In the study, firstly, the results of HCO obtained by changing FR and range were monitored. In the analysis, the interval values were 90 mm and 110 mm and the changes in the FR values of 0.9 kg/h, 1.3 kg/h, 1.7 kg/h and 1.9 kg/h increased in direct proportion. The smallest value of the heat transfer rate was obtained at 110 mm plate spacing and 0.9 kg/h FR. In addition, if the plate spacing was 90 mm, the smallest HCO was obtained at 0.9 kg/h. The largest HCO was obtained when the plate spacing was 90 mm and FR was 1.9 kg/h. In the second part of the study, the results of PD obtained by changing FR and gap were monitored. In the analysis, the interval values were 90 mm and 110 mm and the changes in FR values of 0.9 kg/h, 1.3 kg/h, 1.7 kg/h and 1.9 kg/h increased in direct proportion. The smallest value of PD level was obtained at 90 mm plate spacing and 0.9 kg/h FR. In addition, if the plate spacing was 110 mm, the smallest heat transfer coefficient was obtained at 0.9 kg/h. The largest PD value was obtained when the plate spacing was 110 mm and FR was 1.9 kg/h. In the last part of the study, the results obtained by changing FR and range of the HTPD value were monitored. In the analysis, the interval values were 90 mm and 110 mm, and the changes in FR values of 0.9 kg/h, 1.3 kg/h, 1.7 kg/h and 1.9 kg/h decreased in direct proportion. The smallest value of the HTPD level was obtained at 110 mm plate spacing and 1.9 kg/h FR. In addition, if the plate spacing was 90 mm, the smallest HTPD value was obtained at 1.9 kg/h. The highest HTPD value was obtained when the plate spacing was 90 mm and FR was 0.9 kg/h. Therefore, choosing a system with a 90 mm plate spacing and a FR of 0.9 kg/h will be more efficient in terms of thermohydraulic performance and pressure balancing. As a result, it was concluded that if the plate spacing was selected as 90 mm, a 15 % improvement could be achieved compared to the system design with a 110 mm plate spacing. As a new, it is thought that it will contribute to the literature in future studies, as the thermal performance, pressure drop and heat transfer coefficient results obtained at new flow rate values and compartment spacing values are obtained for the first time in a new STH designed in different dimensions than the literature.

Effect of some chemical and natural preservative solutions on vase life, water relations and some chemical composition of Dianthus caryophyllus L. cut flowers

To investigate the effect of some pulsing and holding solutions on the quality of carnation cv. Turbo cut flowers, a laboratory experiment was conducted in the Agricultural Research Center and Cairo University, Egypt during 2020 and 2021 seasons. In this regard distilled water, silver thiosulfate (STS) at 0.4 ppm + sucrose 10% (PS1) and AgNO3 at 10.0 ppm + sucrose 10% (PS2) were employed as a pulsing solution for 15 min while distilled water, sucrose 4% (HS1), boric acid (BoA) at 200 ppm + sucrose 4% (HS2), 8-hydroxyquinoline sulfate (8-HQS) at 300 ppm + sucrose 4% (HS3), Amino-oxyacetic acid (AOA) at 250 ppm + sucrose 4% (HS4), 8-HQS + AOA + sucrose 4% (HS5), BoA + 8-HQS + sucrose 4% (HS6), BoA + AOA + sucrose 4% (HS7), BoA + 8-HQS + AOA + sucrose 4% (HS8), rosemary extract at 25% + sucrose 2% (HS9) and thyme extract at 25% + sucrose 2% (HS10) were used as holding solutions. Regarding pulsing solutions, PS2 and PS1 exhibited a positive effect on all studied traits, while the mastery was to HS8 concerning the effect of holding solutions. Pulsing cut carnations in a solution containing PS2 followed by holding in HS8 resulted in the highest values in terms of vase life, water balance, chlorophyll a, carotenoids and total sugars, while the highest water uptake and loss and chlorophyll b were obtained by pulsing in PS1 followed by holding in HS8. It is recommended to pulse carnation cv. Turbo cut flowers in AgNO3 at 10.0 ppm + sucrose 10% solution for 15 min followed by holding in BoA + 8-HQS + AOA + sucrose 4% for getting the longest vase life, enhancing water uptake and maintaining water balance. Additionally, this preservative solution effectively reduces chlorophyll degradation and preserves the content of carbohydrates throughout the postharvest period.

Almost balancers, almost cobalancers, almost Lucas-balancers and almost Lucas-cobalancers

In this work, the general terms of almost balancers, almost cobalancers, almost Lucas-balancers and almost Lucas-cobalancers of first and second type are determined in terms of balancing and Lucas-balancing numbers. Later some relations on all almost balancing numbers and all almost balancers are obtained. Further the general terms of all balancing numbers, Pell numbers and Pell–Lucas number are determined in terms of almost balancers, almost Lucas-balancers, almost cobalancers and almost Lucas-cobalancers of first and second type.

TransROTA: A code for solving collisionality-extended Braginskii's closure formalism for toroidally-rotating plasmas with nonlinear successive overrelaxation

TransROTA (Transport analysis based on ROTAtions) is a code that solves the axisymmetric version of Stacey-Sigmar extended plasma rotation model based on a collisionality-extended Braginskii's closure formalism with realistic d-shaped flux surface geometry in toroidally-confined plasmas [Nucl. Fusion 53 (2013) 043,011]. The Stacey-Sigmar model is unique in rotation and transport calculations by retaining all the terms in the angular momentum balance and by considering the first-order poloidal asymmetries in density, velocity, and electrostatic potential, for a higher accuracy in rotation calculations. TransROTA code evolves out of an earlier two-ion code GTROTA [Comp. Phys. Comm. 184 (2013) 2571–2587] and is developed for more practical studies on rotation and transport of up to five ion species (including deuterium and carbon). The main practical application is focused on intrinsic rotation studies. TransROTA requires a well-calibrated radial velocity profile of carbon impurity as one of the 21 required inputs. Once provided, TransROTA stably converges its nonlinear iterations with locally-optimized Successive Overrelaxation (SOR) scheme only, which is a remarkable improvement from GTROTA. This stable convergence is achieved by both modified application of the model equations and improvement in the numerical method. The new numerical scheme successfully removes the numerical instability issues commonly observed in GTROTA to make TransROTA not only to robustly converge the solutions but also to be faster and user-friendly. Program SummaryProgram title: A_TransROTA2023aCPC Library link to program files: https://doi.org/10.17632/3hnht4j94k.1Licensing provisions: CCO 1.0Programming language: Matlab2023aSupplementary material: Quick Test Run guide, User's Manual, and input preparation templates (available in the provided package)Journal Reference of previous version: C. Bae, W.M. Stacey, and T.D. Morley, GTROTA: A code for the solution of the coupled nonlinear extended neoclassical rotation equations in tokamak plasmas using successive over-relaxation and simulated annealing. Computer Physics Communications, 2013. 184(11): p. 2571-2587.Does the new version supersede the previous version?: YesReasons for the new version: Velocity and transport calculations of previous two-ion model of GTROTA extended to five ions with a robust convergence. Faster and user-friendly code. Upgraded for intrinsic (or spontaneous) rotation and impurity transport studies.Summary of revisions: TransROTA can calculate the velocities and transport parameters of up to five ion species in tokamaks. The numerical iterations are much more stable than GTROTA code and robustly find converged solutions. Two practical extensions are also added for the studies of intrinsic rotation and for the investigation of relative torque contributions of residual stress and neoclassical toroidal viscosity torques.Nature of problem: Rotation velocities of toroidally-confined plasmas and consequent plasma transport properties are calculated from a coupled set of nonlinear equations based on Stacey-Sigmar plasma rotation theory with collisionality-extended Braginskii's closure formalism. The consequent coupled set of equations in orthogonal toroidal coordinates (radial, poloidal, and toroidal) are extremely nonlinear in nature, thus its numerical iterations can easily grow unstable. Its numerical model has many inherent sources of singularities in their system coefficients. There is a need to remodel the formalism so that the resultant model is more resilient against such singularity effects.Solution method: The final numerical model solved by TransROTA has been reformulated to yield a more robust convergence with less singularity effects. The key to this success is based on the lessons learned from GTROTA code that all iterations of the unknown variables approach their solutions at vastly-different rates. Thus, while keeping a similar functional decomposition of the entire system of unknowns, application of locally-optimized SOR relaxation schemes to each functional subsystem can allow the nonlinear iterations of all the functional subsystems to approach their solutions at a synchronized rate for a successful convergence of the entire system.Additional comments including restrictions and unusual features: The theoretical model and the code are not developed for a good accuracy in the plasma edge region where the normalized radial radius is beyond 0.80. TransROTA is designed to use TRANSP code to prepare many of its required inputs although any tools can be used. TransROTA provides two MS Excel input templates for user-friendly preparation of all inputs. The provided templates are specifically customized for EAST tokamak coordinates and their positive directions. Refer to User's Manual on how to customize the positive coordinate directions for other tokamaks.

The role of fresh water in driving ice shelf crevassing, rifting and calving

Meltwater is widely implicated in the disintegration of ice shelves and the lower density of fresh meltwater relative to salty seawater can reconcile observations and models of ice shelf rifting. Advanced numerical models predict that a seawater-filled basal crevasse will break through a shelf to form a rift only where extensional stresses equal those at the seaward shelf edge. However, rifts open in ice shelf interiors where resistance to flow at the sides and base of the ice shelf, or buttressing, is estimated to significantly reduce extensional stresses compared to those at the shelf edge. The stress in a shelf is often quantified in terms of a buttressing number and rifts are seen to open in areas where the estimated buttressing number is between 0.2 and 0.3. Numerical models assuming fresh meltwater-filled basal crevasses predict rift opening for buttressing numbers up to about 0.2. Published estimates indicate that about a quarter of the area of the Antarctic ice shelves are characterized by buttressing numbers less than 0.2. The present results indicate that those areas are directly vulnerable to rifting in the presence of abundant meltwater and that calving of those areas could drive further rifting. The numerical results suggest that rifting can be understood in terms of a horizontal force balance, justifying derivation of a simple analytic relation between the density of water infilling a rift and the maximum buttressing number allowing rifting. This analytic relation should hold for any spacing of crevasses or any vertical variations in ice rheology. Enforcing a horizontal force balance also allows derivation of an analytic relation between the heights of closely spaced ice shelf crevasses and buttressing numbers.

Efficient Difficulty Level Balancing in Match-3 Puzzle Games: A Comparative Study of Proximal Policy Optimization and Soft Actor-Critic Algorithms

Match-3 puzzle games have garnered significant popularity across all age groups due to their simplicity, non-violent nature, and concise gameplay. However, the development of captivating and well-balanced stages in match-3 puzzle games remains a challenging task for game developers. This study aims to identify the optimal algorithm for reinforcement learning to streamline the level balancing verification process in match-3 games by comparison with Soft Actor-Critic (SAC) and Proximal Policy Optimization (PPO) algorithms. By training the agent with these two algorithms, the paper investigated which approach yields more efficient and effective difficulty level balancing test results. After the comparative analysis of cumulative rewards and entropy, the findings illustrate that the SAC algorithm is the optimal choice for creating an efficient agent capable of handling difficulty level balancing for stages in a match-3 puzzle game. This is because the superior learning performance and higher stability demonstrated by the SAC algorithm are more important in terms of stage difficulty balancing in match-3 gameplay. This study expects to contribute to the development of improved level balancing techniques in match-3 puzzle games besides enhancing the overall gaming experience for players.

Deep Reinforcement Learning-based scheduling for optimizing system load and response time in edge and fog computing environments

Edge/fog computing, as a distributed computing paradigm, satisfies the low-latency requirements of ever-increasing number of IoT applications and has become the mainstream computing paradigm behind IoT applications. However, because large number of IoT applications require execution on the edge/fog resources, the servers may be overloaded. Hence, it may disrupt the edge/fog servers and also negatively affect IoT applications’ response time. Moreover, many IoT applications are composed of dependent components incurring extra constraints for their execution. Besides, edge/fog computing environments and IoT applications are inherently dynamic and stochastic. Thus, efficient and adaptive scheduling of IoT applications in heterogeneous edge/fog computing environments is of paramount importance. However, limited computational resources on edge/fog servers imposes an extra burden for applying optimal but computationally demanding techniques. To overcome these challenges, we propose a Deep Reinforcement Learning-based IoT application Scheduling algorithm, called DRLIS to adaptively and efficiently optimize the response time of heterogeneous IoT applications and balance the load of the edge/fog servers. We implemented DRLIS as a practical scheduler in the FogBus2 function-as-a-service framework for creating an edge–fog–cloud integrated serverless computing environment. Results obtained from extensive experiments show that DRLIS significantly reduces the execution cost of IoT applications by up to 55%, 37%, and 50% in terms of load balancing, response time, and weighted cost, respectively, compared with metaheuristic algorithms and other reinforcement learning techniques.

A novel sampling approach for prediction of post-earthquake damage to buildings

Predicting damage to buildings using field-based samples is important for crisis management after an earthquake. Because building damage in seismic regions is spatially correlated, neighboring samples will contain similar information. However, if they are treated as independent observations, the total sample set will not provide sufficient information. To prevent this, sample locations must be dispersed throughout the region and the spatial correlation of observations must be taken into account. The current study proposes a two-stage sampling approach to select well-dispersed samples of small size containing substantial information. The sample locations have been chosen using the Halton iterative partitioning method and individual buildings were randomly selected for each location. The selected sample buildings were employed in a kriging regression model to predict the damage ratio. Multiple factors were used in the model as predictor variables to increase the prediction accuracy. The proposed sampling approach was compared to other sampling methods in terms of spatial balance and prediction error using both simulated and real datasets from the 2017 Sarpol-e Zahab earthquake in Iran. The proposed approach provided better results than the other approaches. Although some factors affected the building damage in the actual data, a combination of fault strike angles and seismic intensity measures provided more accurate predictions than other combinations.

A comparative study on the overlapping effects of clinically applicable therapeutic interventions in patients with central nervous system damage.

This study was conducted to investigate the effects of anti-gravity treadmill (AGT) training, which provides visual feedback and Biorescue training on proprioception, muscle strength, balance, and gait, in stroke patients. A total of 45 people diagnosed with post-stroke were included as study subjects; they were randomized to an AGT training group provided with visual feedback (Group A), a Biorescue training group provided with visual feedback (Group B), and an AGT/Biorescue group that subsequently received AGT training and Biorescue training (Group C). A muscle strength-measuring device was used to evaluate muscle strength. Timed Up and Go and Bug Balance Scale assessment sheets were used to evaluate balance ability. Dartfish software was used to evaluate gait ability. The results of the study showed that Groups A and C had a significant increase in muscle strength compared with Group B; in terms of balance and gait abilities, Group C showed a significant increase in balance ability and gait speed and a significant change in knee joint angle compared with Groups A and B. In conclusion, this study suggests that including a method that applies multiple therapeutic interventions is desirable in the rehabilitation of stroke patients to improve their independence.

Towards Early Dark Energy in string theory

Early Dark Energy (EDE) is a prominent model to resolve the Hubble tension, which employs a dynamical axion with a periodic potential. In this work, we take first steps towards the embedding of this model into stable compactifications of string theory. First, we provide a pedagogical review of the EDE scenario and its main challenges. Second, we construct a simple supergravity toy model using only minimal ingredients. Already at this level, we can understand the origin of the harmonics of the EDE scalar potential in terms of a delicate balance of the leading terms from separate non-perturbative effects. Third and final, we embed the model into a KKLT-type compactification, with the EDE scalar field realized by a two-form axion. We find that a successful embedding, with all moduli stabilized, requires restrictive assumptions, which are lacking at present a known string theory implementation mechanism, both on the Pfaffians and on the exponents of the non-perturbative terms responsible for the EDE dynamics. We point out that such non-generic conditions reflect well known challenges of the EDE model and further investigation might guide us towards a conclusive resolution. An alternative viewpoint suggests that rather than serving as the foundation for a string theory embedding, these conditions might instead indicate that EDE is, in fact, incompatible with string theory, at least in the realizations we study here. Further investigation will be needed to ascertain the status of EDE in string theory.

Evaluation of patients' post-operative results operated for hip fracture with computerized dynamic posturography: Proximal femoral nailing versus hip arthroplasty.

Proximal femoral nailing (PFN) and hip arthroplasty (HA) are the two most often utilized surgical procedures for treating hip fractures in older patients. The post-operative postural balance and functional outcomes of patients may be significantly influenced by the technical distinctions between PFN and HA. This will influence the surgeon's preferred course of therapy. To examine the functional outcomes of patients treated with PFN and HA following a hip fracture, this study used computerized dynamic posturography (CDP). The aim of that study was to evaluate how the two treatment modalities affected patients' post-operative balance, postural stability, and functional rehabilitation. A total of 26 patients who underwent proximal femoral surgery (15 patients PFN [58%] and 11 patients HA [42%]) due to hip fractures were evaluated at least 12 months postoperatively. They were tested by direct radiographs, hip joint examinations, Harris hip score (HHS), and CDP. Twelve (46%) of 26 patients were male and 14 (54%) were female. The mean age of the participants in the study was 67.9±14.2 years. The mean follow-up period was 24 (12-44) months. The average Harris score of PFN group was 79.3 (46.8-100) points and HA group was 83.7 (61.9-99.9) points. There was no significant difference between the groups in terms of Harris Score (P=0.54). The average of the mixed value of the balance results obtained with CDP (the Composite score) for PFN group was 70.5 (56-79) points, and for HA group was 71.9 (56-83) points. There was no significant difference between the groups in terms of the Composite Score (P=0.47). Accordingly, 12 (80%) of the patients who underwent PFN had good results and 3 (20%) of them had bad results. Eight (72.7%) of those who underwent HA had good results and 3 (27.3%) had bad results. There was no statistically significant difference (P=0.66). Comparing the composite score for balance results and HHS results for rehabilitation with the data of the patients who underwent PFN and HA, there was no statistically significant difference between these two techniques in terms of postural stabil-ity and balance as a result of CDP examination.

Understanding Students’ Perceptions of Identity in Digital Connectivism Learning Environments

Connectivist learning theory has been widely discussed with higher-order thinking skills and critical reflection in online learning environments. Yet it is unclear how students negotiate their own identity within an academic collective learning context. To gain insights into the interrelations of learner identity, i.e. construction of learner position in one's own learning community, this study examines the manner in which the identity of a writer is negotiated intra-community of writer (how do they represent themselves while learning from others in writing tasks). A qualitative case study, involving interviews and observations in Oman higher education, was conducted with 56 Omani college students after engaging in online and face-to-face research course. Analysis of results of this study indicates a degree of success in terms of students navigating their digital, individual and group academic learner identities. However, some tensions are seen in terms of balance of participation in group work and difficulties of harnessing the benefits in mixed-ability groups of writers. More research which builds on the successes and looks for ways to address the challenges from a range of perspectives is recommended.

Multi Objective Salp Swarm based Energy Efficient Routing Protocol for Heterogeneous Wireless Networks

Routing is a persistent concern in wireless sensor networks (WSNs), as getting data from sources to destinations can be a tricky task. Challenges include safeguarding the data being transferred, ensuring network longevity, and preserving energy in harsh environmental conditions. Consequently, this study delves into the suitability of using multi-objective swarm optimization to route heterogeneous WSNs in the hope of mitigating these issues while boosting the speed and accuracy of data transmission. In order to achieve better performance in terms of load balancing and reducing energy expenditure, the MOSSA-BA algorithm was developed. This algorithm combines the Multi-Objective Salp Swarm Algorithm (MOSSA) with the exploiting strategy of the artificial bee colony (BA) in the neighbourhood of Salps. Inspired by the SEP and EDEEC protocols, the integrated solutions of MOSSA-BA were used to route two and three levels of heterogeneous networks. The embedded solutions provided outstanding performance in regards to FND, HND, LND, percentage of remaining energy, and the number of packages delivered to the base station. Compared to SEP, EDEEC, and other competitors based on MOSSA and a modified multi-objective particle swarm optimization (MOPSO), the MOSSA-BA-based protocols demonstrated energy-saving percentages of more than 34% in medium-sized areas of interest and over 22% in large-sized areas of detection.

Root chemistry and microbe interactions contribute to metal(loid) tolerance of an aromatic plant – Vetiver grass

Aromatic plants, such as vetiver grass (Chrysopogon zizanioides), possess strong abilities to resist environmental stresses. However, whether such abilities stem from the interaction between specific chemical characteristics and the associated microbes in roots and rhizosphere remains unclear. We conducted pot experiments to analyze stress-tolerant parameters, organic compounds, and bacterial communities in roots and rhizosphere of vetiver under typical metal(loid) stress [cadmium (Cd), arsenic (As), or Cd + As] over time. The results showed that the vetiver displayed limited toxic symptoms in terms of oxidative stress-antioxidant balance and chlorophyll content. The root low-molecular-weight organic acids (LMWOAs), fatty acids, and sterols were highly sensitive to growth stage (increased from the 4-month to the 8-month stage), and less sensitive to metal(loid) stress. The sugar contents in the rhizosphere soils also notably increased over time. Such endo and rhizosphere chemical changes strongly correlated with and enriched the functional bacteria including Streptomyces, which can resist stress and promote plant growth. The compound-bacteria interaction highly depended on growth stage. Vetiver demonstrated a progressive adaptation to stresses through metabolite modulation and cellular defense reinforcement. Our study evidenced that vetiver shapes the interaction between organic compounds and bacterial community in the root-soil interface and provides notable stress-resistant functions.