Linear codes are the most important family of codes in cryptography and coding theory. Some codes only have a few weights and are widely used in many areas, such as authentication codes, secret sharing schemes and strongly regular graphs. By setting p≡1(mod4), we constructed an infinite family of linear codes using two distinct weakly regular unbalanced (and balanced) plateaued functions with index (p-1)/2. Their weight distributions were completely determined by applying exponential sums and Walsh transform. As a result, most of our constructed codes have a few nonzero weights and are minimal.

This paper describes control methods to improve electric vehicle performance in terms of handling, stability and cornering by adjusting the weight distribution and implementing control systems (e.g., wheel slip control, and yaw rate control). The vehicle is first simulated using the bicycle model to capture the dynamics. Then, a study on the effect of weight distribution on the driving behavior is conducted. The study is performed for three different weight configurations. Moreover, a yaw rate controller and a wheel slip controller are designed and implemented to improve the vehicle\'s performance for cornering and longitudinal motion under the different loading conditions. The simulation through the bicycle model is compared to the experiments conducted on a rear-wheel driven radio-controlled (RC) electric vehicle. The paper shows how the wheel slip controller contributes to the stabilization of the vehicle, how the yaw rate controller reduces understeering, and how the location of the center of gravity (CoG) affects steering behavior. Lastly, an analysis of the combination of control systems for each weight transfer is conducted to determine the configuration with the highest performance regarding acceleration time, braking distance, and steering behavior.

BACKGROUND: Modern radiotherapeutic techniques, such as intensity-modulated radiation therapy or stereotactic body radiotherapy, require high-dose delivery precision. However, the precise localization of tumors during patient respiration remains a challenge. Therefore, it is essential to investigate effective methods for monitoring respiration to minimize potential complications. Despite several systems currently in clinical use, there are drawbacks, including the complexity of the setup, the discomfort to the patient, and the high cost.
OBJECTIVE: This study investigated the feasibility of using a novel pressure sensor array (PSA) as a tool to monitor respiration during radiotherapy treatments. The PSA was positioned between the treatment couch and the back of the patient lying on it and was intended to overcome some limitations of current methods. The main objectives included assessing the PSA\'s capability in monitoring respiratory behavior and to investigate prospective applications that extend beyond respiratory monitoring.
METHODS: A PSA with 31 pressure-sensing elements was used in 12 volunteers. The participants were instructed to breathe naturally while lying on a couch without any audio or visual guidance. The performance of the PSA was compared to that of a camera-based respiratory monitoring system (RPM, Varian, USA), which served as a reference. Several metrics, including pressure distribution, weight sensitivity, and correlations between PSA and RPM signals, were analyzed. The PSA\'s capacity to provide information on potential applications related to patient stability was also investigated.
RESULTS: The linear relationship between the weight applied to the PSA and its output was demonstrated in this study, confirming its sensitivity to pressure changes. A comparison of PSA and RPM curves revealed a high correlation coefficient of 0.9391 on average, indicating consistent respiratory cycles. The PSA also effectively measured the weight distribution at the volunteer\'s back in real-time, which allows for monitoring the patient\'s movements during the radiotherapy.
CONCLUSIONS: PSA is a promising candidate for effective respiratory monitoring during radiotherapy treatments. Its performance is comparable to the established RPM system, and its additional capabilities suggest its multifaceted utility. This paper shows the potential use of PSA for patient monitoring in radiotherapy and suggests possibilities for further research, including performance comparisons with other existing systems and real-patient applications with respiratory training.

Background: The biomechanical outcomes of intra-articular calcaneal fracture treatment have not been fully explored. The purpose of this study was to analyze pedobarographic assessments of balance and body weight distribution over the lower limbs in patients following calcaneal fracture treatment with the Ilizarov method and to compare the results with those of a control group. Materials and Methods: The data for our retrospective study came from cases of intra-articular calcaneal fractures treated with the Polish modification of the Ilizarov method in the period between 2021 and 2022. The experimental group (21 patients; 7 women, 14 men) included Sanders classification calcaneal fractures type 2 (n = 3), type 3 (n = 5), and type 4 (n = 13). The control group comprised 21 sex-matched healthy volunteers, with no significant differences from the experimental group in terms of age or BMI. The examination included an assessment of balance and weight distribution over the lower limbs. The device used was a FreeMED MAXI pedobarographic platform (SensorMedica). Results: The mean displacement of the center of gravity in the experimental group was significantly higher at 1307.31 mm than in the control group (896.34 mm; p = 0.038). The mean area of the center of gravity was not significantly different between the groups. An analysis of weight distribution over the operated and uninjured limb in the experimental group and the non-dominant and dominant limb, respectively, in the control group revealed no significant differences. We observed no significant differences in the percentage of weight distribution over the lower limbs between the operated limb in the experimental group and the non-dominant limb in the control group, or between the uninjured limb in the experimental group and the dominant limb in the control group. Conclusions: The use of the Ilizarov method in calcaneal fracture treatment helps normalize the percentage weight distribution in the lower limbs, with the results comparable with those obtained in the healthy control group. The mean displacement of the center of gravity was worse in the experimental group than in controls; whereas the mean area of the center of gravity was comparable between the two groups. Treatment of calcaneal fractures with the Ilizarov method does not help achieve completely normal static parameters of lower-limb biomechanics. Patients treated for calcaneal fractures with the Ilizarov method require longer and more intense rehabilitation and follow-up.

Estimation of body mass from skeletal metrics can reveal important insights into the paleobiology of archeological or fossil remains. The standard approach constructs predictive equations from postcrania, but studies have questioned the reliability of traditional measures. Here, we examine several skeletal features to assess their accuracy in predicting body mass.
Antemortem mass measurements were compared with common skeletal dimensions from the same animals postmortem, using 115 rhesus macaques (male: n = 43; female: n = 72). Individuals were divided into training (n = 58) and test samples (n = 57) to build and assess Ordinary Least Squares or multivariate regressions by residual sum of squares (RSS) and AIC weights. A leave-one-out approach was implemented to formulate the best fit multivariate models, which were compared against a univariate and a previously published catarrhine body-mass estimation model.
Femur circumference represented the best univariate model. The best model overall was composed of four variables (femur, tibia and fibula circumference and humerus length). By RSS and AICw, models built from rhesus macaque data (RSS = 26.91, AIC = -20.66) better predicted body mass than did the catarrhine model (RSS = 65.47, AIC = 20.24).
Body mass in rhesus macaques is best predicted by a 4-variable equation composed of humerus length and hind limb midshaft circumferences. Comparison of models built from the macaque versus the catarrhine data highlight the importance of taxonomic specificity in predicting body mass. This paper provides a valuable dataset of combined somatic and skeletal data in a primate, which can be used to build body mass equations for fragmentary fossil evidence.

This paper describes an automated method and device to conduct the Chair Stand Tests of the Fullerton Functional Test Battery. The Fullerton Functional Test is a suite of physical tests designed to assess the physical fitness of older adults. The Chair Stand Tests, which include the Five Times Sit-to-Stand Test (5xSST) and the 30 Second Sit-to-Stand Test (30CST), are the standard for measuring lower-body strength in older adults. However, these tests are performed manually, which can be labor-intensive and prone to error. We developed a sensor-integrated chair that automatically captures the dynamic weight and distribution on the chair. The collected time series weight-sensor data is automatically uploaded for immediate determination of the sit-to-stand timing and counts, as well as providing a record for future comparison of lower-body strength progression. The automatic test administration can provide significant labor savings for medical personnel and deliver much more accurate data. Data from 10 patients showed good agreement between the manually collected and sensor-collected 30CST data (M = 0.5, SD = 1.58, 95% CI = 1.13). Additional data processing will be able to yield measurements of fatigue and balance and evaluate the mechanisms of failed standing attempts.

Linear codes with a few weights have been extensively studied due to their wide applications in secret sharing schemes, strongly regular graphs, association schemes, and authentication codes. In this paper, we choose the defining sets from two distinct weakly regular plateaued balanced functions, based on a generic construction of linear codes. Then we construct a family of linear codes with at most five nonzero weights. Their minimality is also examined and the result shows that our codes are helpful in secret sharing schemes.

Calculating and predicting drug-target interactions (DTIs) is a crucial step in the field of novel drug discovery. Nowadays, many models have improved the prediction performance of DTIs by fusing heterogeneous information, such as drug chemical structure and target protein sequence and so on. However, in the process of fusion, how to allocate the weight of heterogeneous information reasonably is a huge challenge. In this paper, we propose a model based on Q-learning algorithm and Neighborhood Regularized Logistic Matrix Factorization (QLNRLMF) to predict DTIs. First, we obtain three different drug-drug similarity matrices and three different target-target similarity matrices by using different similarity calculation methods based on heterogeneous data, including drug chemical structure, target protein sequence and drug-target interactions. Then, we initialize a set of weights for the drug-drug similarity matrices and target-target similarity matrices respectively, and optimize them through Q-learning algorithm. When the optimal weights are obtained, a new drug-drug similarity matrix and a new drug-drug similarity matrix are obtained by linear combination. Finally, the drug target interaction matrix, the new drug-drug similarity matrices and the target-target similarity matrices are used as inputs to the Neighborhood Regularized Logistic Matrix Factorization (NRLMF) model for DTIs. Compared with the existing six methods of NetLapRLS, BLM-NII, WNN-GIP, KBMF2K, CMF, and NRLMF, our proposed method has achieved better effect in the four benchmark datasets, including enzymes(E), nuclear receptors (NR), ion channels (IC) and G protein coupled receptors (GPCR).

The efficiency of heavy metal in biofilm reactors depends on absorption process parameters, and those relationships are complicated. This study explores artificial neural networks (ANNs) feasibility to correlate the biofilm reactor process parameters with absorption efficiency. The heavy metal removal and turbidity were modeled as a function of five process parameters, namely pH, temperature(°C), feed flux(ml/min), substrate flow(ml/min), and hydraulic retention time(h). We developed a standalone ANN software for predicting and analyzing the absorption process in handling industrial wastewater. The model was tested extensively to confirm that the predictions are reasonable in the context of the absorption kinetics principles. The model predictions showed that the temperature and pH values are the most influential parameters affecting absorption efficiency and turbidity.

The purpose of this study was to analyse in detail body weight squat (BWS)\' fatigue effect on the range of motions (ROM) of the hip, knee, ankle and ground reaction forces (GRF). Twenty male recreational athletes (24.0 ± 3.1 years, 178.85 ± 7.12 cm and 78.7 ± 11.45 kg) participated in this study. BWS were performed on four load cell platforms until the participants failed to continue. Participants performed 73 ± 27 repetitions and the duration to complete of the repetitions was 140.72 ± 62.28 s during the BWS exercise. The forefoot and hindfoot of the feet were on two load cells, thus, there were two under each foot. All of the data collected was divided into three sections for analysis (24 ± 9 repetitions for each). In terms of GRF of the fore feet and hind feet, significant differences and medium to large effect size were found between each section (p = 0.006~0.040, ES = 0.693~0.492). No significant differences were found between right and left leg in all sections. Significant differences were found in the ROM of the hip between the sections of first-third (p = 0.044, ES = 0.482) and second-third (p = 0.034, ES = 0.510), the ROM of the knee first-third (p = 0.014, ES = 0.602) and second-third (p = 0.005, ES = 0.701) and for the ROM of the ankle first-second (p = 0.045, ES = 0.479). As a result, end-of-exercise fatigue caused an increase in the ROM of the hip, knee and ankle. Thus, it is observed that fatigue induced increased ROM, also increases the GRF towards the forefeet.