Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Active Workstation Use on Workload, Task Performance, and Postural and Physiological Responses

OCCUPATIONAL APPLICATION: We assessed workload and performance when using two active workstations. Our results, consistent with earlier evidence, indicates that active workstations do not increase physical activity at the expense of reduced performance and operator workload, if these workstations are used for simple tasks that do not require great attention or fine motor control. Active workstations also allowed for more variability in posture and reduced static posture. However, reinforcement of ergonomics recommendations in terms of reducing non-neutral postures may be necessary. TECHNICAL ABSTRACT Background: Over the past 30 years, work has become more sedentary due to increased computer desk work, which has led to the development of major health consequences such as obesity and diabetes. One promising intervention for decreasing sedentariness is the incorporation of active workstations. Objective: We investigated the impact of two active workstations (standing and walking) on workload, task performance, and postural and physiological responses during standard office work tasks. Methods: Using a counterbalanced, within-subjects design, 30 subjects (aged 23.2 [3.1] years) were tested in three workstations: sitting, standing, and walking. A battery of simulated office tasks, including mousing, keyboarding, and cognition tasks, were presented in a randomized order during each trial. Subjective workload was assessed using the NASA-Task Load Index. Performance outcomes included reaction time, number of errors, and total task time. Physiological responses included percent heart rate reserve and heart rate variability. Neck, trunk, and shoulder inclination angles were analyzed to identify differences between workstations with respect to working posture. Results: Compared to sitting, standing and walking both resulted in significantly higher objective measures of workload. While use of walking workstation led to significantly decreased performance on fine motor control tasks, standing did not reduce performance and resulted in improved mousing performance. Both standing and walking allowed for more variability in posture. There was also an indication of more deviation from idle sitting posture while standing and walking compared to sitting. Conclusions: This study contributes to the guidance needed for the use of active workstations, to take advantage of the potential health benefits without sacrificing performance or substantially increasing workload. A standing workstation, properly adjusted based on user anthropometry and ergonomics recommendations, decreased sedentary time, allowed for more postural variability, and enhanced performance on some mousing and cognition tasks, while perceived workload remained consistent with levels while seated.
An Improved Deep Neural Network Algorithm for the Prediction of Limited Proteolysis in Native Protein

Protease is a proteolytic enzyme that hydrolyzes the amino acid where the cleavage only occurs at specific sites of the amino acid substrate. By discovering the nick site, the prediction on the function of proteases can be identified and enable humans to control the protein's hydrolysis by their corresponding protease. It is very contributed to controlling protein production especially viral protein. The experts may alter the production of viral protein by reducing the viral proteases to undergo proteolysis. With the rise of computational methods in this era, deep learning is becoming more famous and applied in every field of study, including the biological area. Conventional techniques such as mass spectrometry and two-dimensional gel electrophoresis are being replaced by computational methods due to time-consuming. Thus, this study improves the deep learning algorithm by proposing the Hybrid model of Random Forest + Deep Neural Network (Hybrid RF+DNN) to classify nick sites. The classification in this study is compared with the other machine learning algorithms such as Random Forest (RF), Support Vector Machine (SVM), and Deep Neural Network (DNN). The proposed method is believed to enhance the classification results in identifying the positive and negative nick sites. The RF is a feature-selector that gathers the most important feature before entering the DNN classifier. This approach reduces the data dimensionality and speeds up the execution time of the training process. The performance of the models was measured by confusion matrix, specificity, sensitivity, etc. However, the proposed method is not the best performer among the mentioned classifiers from the result. The proposed method may become the best performer as the parameter tuning is done more precisely, even after the feature selection by the RF algorithm. Thus, the proposed method with the enhancement appears to be an alternative to the researcher discovering nick site.
Distributed tracking-ADMM approach for chance-constrained energy management with stochastic wind power in smart grid

This paper proposes a distributed strategy to the chance-constrained energy management for smart grid with penetration of stochastic wind power. The energy management model is constructed including chance constraints of spinning reserves for the sake of guaranteeing the maximum utilization of wind power on the basis of reliability. With the available wind power characterizing by Weibull distribution, the chance constraints can be converted into deterministic ones by the derived analytical form of inverse cumulative distribution function. Although the original problem is transformed into a typical convex optimization problem, the tight coupling of constraints presents challenges to the design of distributed strategy. As such, we formulate the problem into a compact form with each generator unit depending on individual decision variables, instead of the common form with decision vector being the collection of all local decision variables. Then, by developing a new initialization method and an adaptive weight matrix selection method, a distributed strategy based on tracking Alternating Direction Method of Multipliers (ADMM) is proposed to solve the model. The simulation results indicate that the proposed distributed strategy achieves comparable performance to the corresponding centralized scenario, and better performance than distributed consensus-based ADMM in the related literature. Moreover, the validity of the proposed distributed strategy is confirmed in one day chance-constrained energy management with stochastic wind power.
High School Graphics Experience Influencing the Self-Efficacy of First-Year Engineering Students in an Introductory Engineering Graphics Course

Today's students enter engineering colleges with different technical backgrounds and prior graphics experience. This may due to their high school of provenience, which can be technical or non-technical. The prior experience affects students’ ability in learning and hence their motivation and self-efficacy beliefs. This study intended to evaluate the role of prior high school graphics experience in first-year engineering students' self-efficacy beliefs in an introductory engineering graphics course. It also intended to evaluate the relationship between such freshmen's self-efficacy beliefs and their performance. Two assessment instruments were used in this study. The first is the eight-item Course Interest Survey (CIS) Confidence subscale, which was used to assess self-efficacy beliefs. The second is a multiple choice questionnaire designed on the course topics, which was used to assess performance. Ninety-nine students of the University of Brescia (Italy) participated in the experiment. Significant differences in self-efficacy were found between engineering freshmen from the technical high school versus engineering freshmen from the non-technical high school. A significant relationship between self-efficacy and performance was found only for engineering freshmen from the technical high school.
Dynamics of perforated higher order nanobeams subject to moving load using the nonlocal strain gradient theory

The goal of this manuscript is to develop a nonclassical size dependent model to study and analyze the dynamic behaviour of the perforated Reddy nanobeam under moving load including the length scale and microstructure effects, that not considered before. The kinematic assumption of the third order shear deformation beam theory in conjunction with modified continuum constitutive equation of nonlocal strain gradient (NLSG) elasticity are proposed to derive the equation of motion of nanobeam included size scale (nonlocal) and microstructure (strain gradient) effects. Mathematical expressions for the equivalent geometrical parameters due to the perforation process of regular squared pattern are developed. Based on the virtual work principle, the governing equations of motion of perforated Reddy nanobeams are derived. Based on Navier's approach, an analytical solution procedure is developed to obtain free and forced vibration response under moving load. The developed methodology is verified and checked with previous works. Impacts of perforation, moving load velocity, microstructure parameter and nonlocal size scale effects on the dynamic and vibration responses of perforated Reddy nanobeam structures have been investigated in a wide context. The obtained results are supportive for the design of MEMS/NEMS structures such as frequency filters, resonators, relay switches, accelerometers, and mass flow sensors, with perforation.
Effects of Stimulus Octave and Timbre on the Tuning Accuracy of Secondary School Instrumentalists

To test the effects of octave and timbre on tuning accuracy, four stimuli—B-flat 4 sounded by flute, oboe, and clarinet and B-flat 2 sounded by tuba—functioned as reference pitches for high school wind players (N = 72). The two stimulus octaves combined with participants’ assigned tuning notes created soprano, tenor, and bass tuning groups. All participants tuned to each instrument. Results indicated no effect due to tuning group. There was a significant difference due to stimulus. Participants’ responses were more out of tune to the tuba stimulus than to the oboe, clarinet, and flute stimuli, which were not different from each other. There was no difference in the distribution of in-tune, sharp, and flat responses across tuning stimuli, a result that differs from the “preference for sharpness” effect in previous research. Verbal and performance responses to the tuba, oboe, and flute stimuli revealed misconceptions between participants’ perceptions of tuning difficulty and actual performance difficulty and favored the use of oboe and flute as tuning references. Most of the participants (82%) reported tuning to the tuba as the prevalent approach to mass tuning in their school bands.
Carbon Nanotube Interconnects − A Promising Solution for VLSI Circuits

ABSTRACT In nanoscale regime, the performance of traditional copper interconnects degrades substantially in terms of latency, power dissipation and induced crosstalk noise. This is due to miniaturization of electronic devices and many-fold enhancement of interconnect lengths in very large-scale integrated (VLSI) circuits. However, carbon nanotubes (CNTs) due to their unique physical properties such as high thermal conductivity, current carrying capability and mechanical strength have drawn the attention of researchers in recent times. The present paper provides comprehensive investigations in the various CNT structures for on-chip VLSI interconnect applications. Different configurations of CNT structures are studied namely single-wall CNT (SWCNT), multiwall CNT (MWCNT) and mixed-wall CNT bundle (MCB). The performance of CNT interconnects is analyzed using driver-interconnect-load system. It is investigated that the reduction in propagation delay in MCB interconnect is nearly 69%, 60%, 40% and 22% as compared to copper, SWCNT bundle, MWCNT and MWCNT bundle interconnect structures, respectively. This analysis considers an interconnect length variation from 500 to 2500 µm for 32-nm technology node. For the same dimensions the overall reduction in power dissipation in MCB interconnect is nearly 60%, 49%, 45% and 36% as compared to copper, SWCNT, MWCNT and MWCNT bundle interconnects, respectively. Furthermore, the effect of crosstalk on the interconnect structures has been examined. It is investigated that MCB has least crosstalk induced delay than all the other interconnect structures. Consequently, it is envisaged that MCB outperforms copper, SWCNT, MWCNT and MWCNT bundle interconnects and are best suited for future VLSI interconnects.
Numerical analysis of natural convection of magnetohydrodynamic flow in vertical micro-channel with rarefaction effects and radiative heat transfer

In this article, we present a comprehensive analysis of the flow and heat transfer characteristics of a fully developed incompressible, electrically conducting, and radiatively active fluid flow in micro-channel in the presence of transverse magnetic field. The Navier–Stokes and energy governing equations for magnetohydrodynamic flow, including thermal radiation and rarefaction effects, are considered to examine the wall properties (friction and heat transfer) and the flow properties (temperature and velocity). Two rarefaction effects of velocity slip and temperature jump at the wall are modeled as the product of characteristic slip/jump length and the first derivatives of velocity and temperature, respectively. Since the natural convection of magnetohydrodynamic flow in channel is resulted from the competition between deriving forces by pressure gradient, temperature gradient, and magnetic field, its flow and heat transfer characteristics should be understood systematically. First, we obtain the system parameters representing thermal radiation, buoyancy, magnetic field, temperature difference, velocity slip length, and temperature jump length through the non-dimensionalization process, and then their influences are rigorously evaluated by solving the governing equations numerically using Runge–Kutta algorithm with shooting method.
Assessing a Stochastic Fire Spread Simulator

Several wildfire simulators have been proposed in recent years. Often, such simulators have been judged to be reasonable if they are capable of predicting mean fire growth accurately. However, when the management objective is a burn probability map, this kind of assessment will be insufficient, since it does not address the uncertainties intrinsic to fire behaviour. The problem of comparing output from a stochastic fire growth simulator with real fire behaviour is difficult in general. Focussing on a single (important) aspect of the fire behaviour provides a way through this difficulty. In this paper, we propose a method to judge the appropriateness of a particular stochastic fire spread simulator by comparing the variability in the rates of spread in simulated output with the variability in the rates of spread seen in some experimental micro-scale fires. The methodology can be applied to other stochastic fire spread models and to large-scale fires.
Preventive effect of greater occipital nerve block on patients with episodic migraine: A randomized double‐blind placebo‐controlled clinical trial

Abstract Objective Since the data regarding the efficacy of greater occipital in episodic migraines are rare, we aimed to examine the efficacy of greater occipital block in the prophylaxis of episodic migraines without aura and compare different injectable drug regimens. Methods In a randomized, double-blind placebo-controlled trial, adult patients suffering from episodic migraines without aura were randomized to one of the following: triamcinolone, lidocaine, triamcinolone plus lidocaine, and saline. Patients were assessed at baseline, one week, two weeks, and four weeks after the injection for severity and duration of headaches and side effects. Results Fifty-five patients completed the study. Repeated measures ANOVA indicated that the severity and duration decreased significantly after the greater occipital block (P < 0.001, P = 0.001 respectively) in all four groups. However, there was no difference between groups at any study time points (P > 0.05). In paired sample T-test, only groups 2 and 3 with lidocaine as a part of the injection showed a significant decrease in frequency compared to the baseline (P = 0.002, P = 0.019). Three patients reported side effects with a possible association with triamcinolone. Conclusion Greater occipital block with a local anesthetic significantly decreases the number of attacks in episodic migraine, whereas no injection was superior to the placebo in regards to the duration and severity of the headaches. Trial Registration Information: Iranian Registry of Clinical Trials (IRCT). Registration number: IRCT2017070334879N1. https://www.irct. ir/trial/26537.
FORECASTING USING NEURAL NETWORKS AND STOCHASTIC MODELS ON DAY OF THE WEEK EFFECT: A CASE STUDY OF KSE 100 INDEX

The main objective of this research was to determine the day of the week effect in Karachi stock exchange (KSE) 100 Index. The problems of financial market structure is analyzed and forecasted by many statistical models. For example Auto regressive integrated moving average (ARIMA) model and artificial neural network (ANN) models. In this research day of the week effect was investigated Wednesday found significant and Monday was noted not significant. 15 step ahead prediction of Wednesday was observed through ARIMA model and ANN models. The coefficient of correlation for actual and forecasted values was perceived 0.8871 by ARIMA model and 0.924 by ANN model. Power of accuracy was displayed 88.765% by ARIMA model and 97.18% by ANN model.
Evaluation of the experiences in underwater dam construction on soft soils

The present paper illustrates the outcome of the monitoring of the consolidation behavior of a soft foundation soil under a large submerged sand embankment. Measurements of settlements and excess pore water pressures showed a good agreement with predictions evaluated using the large strain consolidation theory. Soft soil improvement by means of deep mixing has been optimized. Moreover, the principles and developments of underwater geosynthetics applications are discussed.
Bunch Purity Measurement for SSRF

necessary to ensure that there are no electrons in the buckets around the timing bunch. These experiments typically require the pattern to be as exact as possible, with ideally no electrons in unwanted bucket/bunch positions: a typical ratio of 105 :1 between wanted/unwanted populations is desired this ratio often being referred to as the bunch purity [2]. However, in actual operation after the bunch is excited from the electron gun, due to acceleration errors during acceleration, part of the electrons will be captured by the RF buckets adjacent to the timing bunch, resulting in poor bunch purity; In addition, due to the effect of intra-beam scattering, there will also has a small amount of electrons in the adjacent buckets. Therefore, the users want to get more accurate bunch pattern, the purity measurement concept is born from this. Therefore, the injector and X-Y kicker magnets must be optimized to eliminate unwanted charges. At this time, the measurement of the bunch pattern provides a very important basis. Historically, a dedicated BPM was used to monitor the filling pattern at SSRF and other light sources [3-6]. Although the beam charge monitor based on the BPM provides a rough monitoring of the bunch pattern, the resolution can reach to 0.02% (average measurement), this method is far from the requirement of purity measurement. Therefore, a more precise system is needed to measure the bunch purity of the timing bunch. A bunch purity measurement system based on the photomultiplier tube and time-correlated single photon counter has been established at SSRF. This article introduces the construction of this system, the verification and optimization of system performance, and the related beam experiment results.
Activity Change-of-state Identification Using a Blackberry Smartphone

A wearable mobility monitoring system (WMMS) could be a valuable device for rehabilitation decision-making. A proof-of-concept system is developed that uses the BlackBerry 9550 as a self-contained WMMS platform. An integrated tri-axial accelerometer, GPS, and timing data are processed to identify the mobility change-of-state (CoS) between standing, walking, sitting, lying, stair climbing, going up or down a ramp, riding an elevator, and riding in a car. Following feature extraction from the sensor data, a decision tree is used to distinguish the CoS. In the complete system, real-time CoS identification on the smartphone will trigger video capture for improved mobility context analysis. Preliminary evaluation involved collecting three trials from one subject while he completed a continuous circuit that incorporated all target mobility tasks. The average sensitivity is 89.7 % and the specificity is 99.5 % for walking-related activities. The sensitivity is 72.2 % for stair navigation and 33.3% for ramp recognition, since accelerations for a ramp gait are similar to those for a walking gait. These results provide insight into algorithms and features that can be used to recognize CoS in real-time.
Forecasting of Travel Time for Public Transport Vehicles Based on the Kalman Filtering Algorithm

Through analysis on the running characteristics of the public transport vehicles,and then using Kalman filtering algorithm establish the prediction model for the travel time of the public transport vehicles. The result of using this model to predict the travel time in the future based on the detected traffic volume shows that this model has high accuracy,and the method can effectively improve the effect of operation on dynamic dispatching for public transport vehicles and the utilization of the traffic resource. So,the method has much vale to application.
Recent Transposition of an LTR-Retrotransposon in the Gene Coding for S Receptor Kinase is Responsible for a Novel Self-Compatible Phenotype of Radish (Raphanus Sativus L.)

Self-incompatibility (SI) responses of radish (Raphanus sativus L.) are determined by two tightly linked genes encoding an S receptor kinase (SRK) and an S-locus cysteine-rich protein/S locus protein 11 (SCR/SP11), respectively. A radish showing an almost self-compatible (SC) phenotype was identified in this study. Inheritance patterns showed that this SC phenotype was dominant over an SI phenotype. In addition, this SC phenotype co-segregated with an S haplotype in an F2 population. This SC radish contained an RsS-26 haplotype in which duplicate SRK-like genes were previously identified. Full-length sequences of two SRK-like genes of 18,133-bp and 6,200-bp in length were obtained from radish with the RsS-26 haplotype (designated as RsSRK-26-1 and RsSRK-26-2, respectively). Duplicate SCR/SP11-like genes were also identified in the radish with the RsS-26 haplotype. Phylogenetic analyses indicated that both duplicate SRK-like and SCR/SP11-like genes were closely related to other known SRK and SCR/SP11 genes, respectively. No critical mutation was found in the coding region of SRK-like or SCR/SP11-like gene. However, a 4,146-bp intact LTR-retrotransposon was identified in the third intron of RsSRK-26-1 of the SC radish. Interestingly, this LTR-retrotransposon was not detected in three other breeding lines containing the same RsS-26 haplotype. Except for this LTR-retrotransposon, only two single nucleotide polymorphisms (SNPs) were identified in intronic regions between normal and mutant RsSRK-26-1 alleles. While normal transcription was observed for radish showing RsSRK-26-1 and SI phenotypes in these three breeding lines, no transcript of RsSRK-26-1 was detected in the SC radish, suggesting that recent transposition of an LTR-retrotransposon in the RsSRK-26-1 gene might be responsible for the SC phenotype of radish.