Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Course and Causes: A Case Study on Navigating the Transition from Manual to Biometric-Fingerprint Attendance at a Sri Lankan State-owned Enterprises

Employee resistance to change at State-Owned Enterprises (SOEs) is a visible phenomenon in both local and global contexts. Though it’s an expanding and significant area, it’s also heavily understudied, depicting both literature and empirical gaps in the said scope. Under a qualitative approach, a case study strategy has been used to explore change and employee resistance in the Healthway General Hospital (HGH). In the light of the context, this study emphasizes the reasons behind employee resistance to changes, opportunities, and recommendations for improving change implementation in the SOE set. This paper recommends establishing a comprehensive employee union, actively involving employee unions’ inputs in strategy formulation, and for the Sri Lankan government to intervene in establishing a separate human resources department in HGH hospital. These key findings will contribute to expanding literature while strengthening the understanding of the researchers and practitioners in the scope of change management in SOEs.
Burnout among Health Care Workers during COVID-19: An Applied Study at King Abdulaziz Hospital in Al Ahsa

The objective of this study was to measure burnout prevalence among health care workers at KAH during the COVID-19 pandemic. The method applied in this study was a descriptive quantitative approach. We collected the data via self-assisted online survey utilizing the Copenhagen Burnout Inventory (CBI), a reliable instrument to measure burnout by investigating its three subdomains: personal, work-related and client-related. The results came out from this study were that: 244 HCWs completed the questionnaire. The mean of total burnout, personal burnout, work-related burnout, and client-related burnout score was 55.89 (SD 19.8), 64.8 (SD 22.16), 57.6 (SD 21.05) and 45.18 (SD 24.54), respectively. Factors that contributed to the increased levels of burnout included: younger age, female gender, the nursing profession, fewer years of experience, extended working hours per shift, fewer off days per month, fewer hours of sleep per night, increased workload, prolonged contact with COVID-19 cases, frequent change in regular job duties and the higher perceived psychological impact of the pandemic. The study concluded that healthcare workers at KAH experienced high rates of personal burnout and work-related burnout during the COVID-19 pandemic. Therefore, institutional intervention to address burnout was deemed necessary.
Design and Performance Analysis of a Dynamic Magnetic Resonance Imaging-Compatible Device for Triangular Fibrocartilage Complex Injury Diagnosis

Pain and injury of the triangular fibrocartilage complex (TFCC) due to overuse or trauma are commonly diagnosed through static MRI scanning, while TFCC is always involved in radial and ulnar deviation of the wrist. To the best of our knowledge, a dynamic MRI diagnostic method and auxiliary tool have not been applied or fully developed in the literature. As such, this study presents the design and evaluation of a dynamic magnetic resonance imaging (MRI) auxiliary tool for TFCC injury diagnosis. First, 3D scanning and Python are used to measure and fit the radial and ulnar deviation trajectories of healthy participants and patients. 3D printing is then used to manufacture the auxiliary tool for dynamic MRI, and dynamic MRI diagnosis is then conducted to explore the clinical effect. The radial and ulnar deviation trajectory is presented as an asymmetric curve without an obvious circular centre, and the results indicate that the designed auxiliary device meets the requirements of the ulnar and radial movements of the human wrist. According to the MRI contrast test results, the image quality score of patients wearing the auxiliary device is higher than for those without. Such devices could assist clinicians in the diagnosis of TFCC damage, and our method could not only serve as the reference standard for clinical noninvasive diagnosis but also help in understanding the disease and improving the accuracy of TFCC diagnosis.
Evaluation of residue variability in a conformation‐specific context and during evolutionary sequence reconstruction narrows drug resistance selection in Abl1 tyrosine kinase

Diseases with readily available therapies may eventually prevail against the specific treatment by the acquisition of resistance. The constitutively active Abl1 tyrosine kinase known to cause chronic myeloid leukemia is an example, where patients may experience relapse after small inhibitor drug treatment. Mutations in the Abl1 tyrosine kinase domain (Abl1‐KD) are a critical source of resistance and their emergence depends on the conformational states that have been observed experimentally: the inactive state, the active state, and the intermediate inactive state that resembles Src kinase. Understanding how resistant positions and amino acid identities are determined by selection pressure during drug treatment is necessary to improve future drug development or treatment decisions. We carry out in silico site‐saturation mutagenesis over the Abl1‐KD structure in a conformational context to evaluate the in situ and conformational stability energy upon mutation. Out of the 11 studied resistant positions, we determined that 7 of the resistant mutations favored the active conformation of Abl1‐KD with respect to the inactive state. When, instead, the sequence optimization was modeled simultaneously at resistant positions, we recovered five known resistant mutations in the active conformation. These results suggested that the Abl1 resistance mechanism targeted substitutions that favored the active conformation. Further sequence variability, explored by ancestral reconstruction in Abl1‐KD, showed that neutral genetic drift, with respect to amino acid variability, was specifically diminished in the resistant positions. Since resistant mutations are susceptible to chance with a certain probability of fixation, combining methodologies outlined here may narrow and limit the available sequence space for resistance to emerge, resulting in more robust therapeutic treatments over time.
A Professional Inquiry: Supporting Teacher Implementation of the Incredible Years for Teachers Programme through Group Leader Teacher Visits

The Incredible Years for Teachers programme (IYT) is an evidence-based classroom behaviour management programme which, since 2011, has been offered to teachers who are teaching students aged 3 - 8 years, in New Zealand primary schools and kindergartens. The IYT course has been designed so it can be flexibly implemented to meet the needs of course participantswhile still maintaining course fidelity. A critical component to individualising the IYT programme is between workshop and group leader teacher visits. This professional inquiry set out to identify how IYT group leaders, as part of teacher visits, can effectivelysupport teachers to implement the IYT programme in their classes. Teachers’ perceptions of group leader actions that support them to implement the IYT programme in their classes were gathered using an online questionnaire. The main finding of this inquiry is a collaborative and differentiated approach based upon a coaching model should be utilised throughout all phases of the teacher visit. Findings from this inquiry suggest this could be best achieved through basing the group leader and teacher visit on the ‘Teaching as Inquiry’ cycle, as this is consistent with research about sustaining effective teacher learning.
Miniaturized substrate integrated waveguide filter using fractal open complementary split‐ring resonators

A miniaturized substrate integrated waveguide (SIW) bandpass filter using fractal open complementary split‐ring resonators (FOCSRRs) unit‐cell is proposed. The proposed structure is realized by etching the proposed FOCSRR unit‐cells on the top metal surface of the SIW structure. The working principle of the proposed filter is based on the evanescent‐mode propagation. The proposed FOCSRRs behave as an electric dipoles in condition of the appropriate stimulation, which are able to generate a forward‐wave passband region below the cutoff frequency of the waveguide structure. Since, the electrical size of the proposed FOCSRRs unit‐cell is larger than the conventional OCSRRs unit‐cell; therefore, the FOCSRR unit‐cell is a good candidate to miniaturize the SIW structure. The proposed filter represents high selectivity and compact size because of the utilization of the sub‐wavelength resonators. The introduced filter is simulated by a 3D electromagnetic simulator. In order to validate the ability of the proposed topology in size reduction, 1‐ and 2‐stage of the proposed filters have been fabricated based on the standard printed circuit board process. The measured S‐parameters of the fabricated filters are in a good agreement with the simulated ones. The proposed SIW filters have many advantages in term of compact size, low insertion loss, high return loss, easy fabrication and integration with other circuits. It is the first time that the FOCSRR unit‐cells were combined with the SIW structure for miniaturization of this structure. Furthermore, a wide upper‐stopband with the attenuation >20 dB in the range of 3–8 GHz is achieved. The results show that, a miniaturization factor about 75.5% has been obtained.
Study on the partial discharge recognition for special-shaped voltage method

There is less research on partial discharge (PD) detection under special-shaped wave voltage and corresponding pattern recognition of insulation defects in the current literature. A special-shaped wave voltage method is proposed that is non-destructive testing characteristics, which can be applied to the PD detection of insulation defects. This paper investigates pattern recognition of insulation defects for the special-shaped wave voltage method. First, we analyzed the principle of PD pattern recognition, the PD pattern structure, feature extraction and classifier selection. Subsequently, by using the inherent pattern classification and noise suppression capabilities of the BP neural network, the extracted feature vectors are studied. Finally, the accuracy rate of pattern recognition of PD types of each defect is emphatically compared and analyzed. This study has shown that the pattern recognition algorithm of the BP neural network can be applied to the PD pattern recognition under special-shaped wave voltage of insulation defects, and the accuracy rate of pattern recognition under optimal special-shaped wave voltage is higher than under power frequency AC voltage. Therefore, the PD pattern recognition under special-shaped wave voltage has practical application value.
An Approach to Participatory Business Process Modeling: BPMN Model Generation Using Constraint Programming and Graph Composition

Designing business process models plays a vital role in business process management. The acquisition of such models may consume up to 60% of the project time. This time can be shortened using methods for the automatic or semi-automatic generation of process models. In this paper, we present a user-friendly method of business process composition. It uses a set of predefined constraints to generate a synthetic log of the process based on a simplified, unordered specification, which describes activities to be performed. Such a log can be used to generate a correct BPMN model. To achieve this, we propose the use of one of the existing process discovery algorithms or executing the activity graph-based composition algorithm, which generates the process model directly from the input log file. The proposed approach allows process participants to take part in process modeling. Moreover, it can be a support for business analysts or process designers in visualizing the workflow without the necessity to design the model explicitly in a graphical editor. The BPMN diagram is generated as an interchangeable XML file, which allows its further modification and adjustment. The included comparative analysis shows that our method is capable of generating process models characterized by high flow complexity and can support BPMN constructs, which are sufficient for about 70% of business cases.
Robust adaptive control Lyapunov‐barrier function for non‐collocated control and safety of underactuated robotic systems

Quadratic program‐based control Lyapunov‐control barrier function (QP‐CLBF) is a recently developed control scheme that balances stability and safety in an optimal fashion. However, direct application of such controllers to uncertain nonlinear systems with model uncertainties and disturbances could potentially degrade the performance of closed‐loop systems and violate/restrict safety‐critical constraints. This article presents a novel robust QP‐based adaptive approach for non‐collocated control of a class of underactuated robotic systems with a semi‐strict‐feedback form through which exponential disturbance‐to‐error (eDE) stability of all system solutions is ensured. We begin by developing a backstepping design technique based on which a neural network‐based adaptive control is designed to approximate unknown nonlinear functions. To compensate for uncanceled uncertainties, including modeling approximation error, chained error effects between coordinates, and disturbances, virtual inputs are designed whose gains are evolved by projection‐based adaptation mechanisms. To construct a three‐term control law, including feedforward, adaptive, and optimal terms, a QP optimization problem is synthesized to compute a family of optimal stabilizing signals while encoding time‐varying robust CLF (TVRCLF) and CBF (TVRCBF), and control bounds as constraints. In contrast with existing QP‐CLBF, our control technique with the proposed TVRCLF and TVRCBF significantly improves control objectives and strictly guarantees safety by automatically compensating for unknown uncertainties without the need for knowing their bounds a priori. The eDE stability of all system errors is proven using Lyapunov stability arguments for both collocated and non‐collocated coordinates. Simulations and comparisons to a baseline QP‐CLBF‐based feedback linearization (QP‐CLBF/FL) on a single‐link flexible‐joint robot verify the benefits of the proposed control approach.
Approximation of surface wave velocity in smart composite structure using Wentzel–Kramers–Brillouin method

In mathematical physics, the Wentzel–Kramers–Brillouin approximation or Wentzel–Kramers–Brillouin method is a technique for finding approximate solutions to linear differential equations with spatially varying coefficients. An attempt has been made to approximate the velocity of surface seismic wave in a piezo-composite structure. In particular, this article studies the dispersion behaviour of Love-type seismic waves in functionally graded piezoelectric material layer bonded between initially stressed piezoelectric layer and pre-stressed piezoelectric half-space. In functionally graded piezoelectric material stratum, theoretical derivations are obtained by the Wentzel–Kramers–Brillouin method where variations in material gradient are taken exponentially. In the upper layer and lower half-space, the displacement components are obtained by employing separation of variables method. Dispersion equations are obtained for both electrically open and short cases. Numerical example and graphical manifestation have been provided to illustrate the effect of influencing parameters on the phase velocity of considered surface wave. Obtained relation has been deduced to some existing results, as particular case of this study. Variation in cut-off frequency and group velocity against the wave number are shown graphically. This study provides a theoretical basis and practical utilization for the development and construction of surface acoustics wave devices.
Machine Learning Methods to Analyze Injury Severity of Drivers from Different Age and Gender Groups

Access to non-biased and accurate models capable of predicting driver injury severity of collision events is vital for determining what safety measures should be implemented at intersections. Inadequate models can underestimate the potential for collision events to result in driver fatalities or injuries, which can lead to improperly assessing the safety criteria of an intersection. This study investigates how injury severity differs between drivers of various ages and gender groups using cost-sensitive data-mining models. Previous research efforts have used machine learning methods for predicting injury severity; however, these studies did not consider the consequences (cost) of incorrect predictions. This paper addresses this shortfall by considering the monetary cost of incorrect injury severity predictions when developing C4.5, instance-based (IB), and random forest (RF) machine-learning models. One model of each method was developed for four distinct cohorts of drivers (i.e., younger males, younger females, older males, and older females). Each model considered a selection of driver, vehicular, road/traffic, environmental, and crash parameters for determining if they significantly influenced driver injury severity. A five-year period of two-vehicle crash data collected at signalized intersections in the metropolitan area of Miami, Florida was used in the models. Results indicated that cost-sensitive learning classifiers were superior to regular classifiers at accurately predicting injuries and fatalities of crashes. Among cost-sensitive models, RF outperformed C4.5 and IB models in predicting driver injury severity for four groups of drivers. The models displayed substantial differences in injury severity determinants across the age/gender cohorts.
Short-Term High-Intensity Circuit Training Does Not Modify Resting Heart Rate Variability in Adults during the COVID-19 Confinement

Background/Objective: The quarantine caused by the COVID-19 pandemic increased sedentary behavior, psychological stress, and sleep disturbances in the population favoring the installation of alterations in the cardiovascular system. In this sense, physical exercise has widely been suggested as an efficient treatment to improve health. The current study determined the impact of short-term high-intensity circuit training (HICT) on resting heart rate variability (HRV) in adults. Methods: Nine healthy participants (age: 31.9 ± 4.4 yr.) performed 36 HICT sessions (3 times per day; 3 days per week) and four participants (age: 29.5 ± 1.7 yr.) were assigned to a control group. The HICT consisted of 12 min of whole-body exercises performed during a workout. Twenty-four hours before and after the exercise program, HRV parameters were recorded. Results: The heart rate exercise during the last session trended to be lower when compared with the first HICT session (p = 0.07, d = 0.39, 95% CI = −13.50, 0.72). The interval training did not modify the HRV time (Mean NN, SDNN, RMSSD, NN50, pNN50) and frequency (LF, HF, LF/HF ratio, total power) domain parameters. Conclusion: Thirty-six HICT sessions did not provide enough stimuli to modify the resting HRV in adults during social isolation elicited by the COVID-19 pandemic. However, the data suggested that exercise protocol did not induce cardio-vagal adaptations.
A New Learning Control System for Basketball Free Throws Based on Real Time Video Image Processing and Biofeedback

Shooting free throws plays an important role in basketball. The major problem in performing a correct free throw seems to be inappropriate training. Training is performed offline and it is often not that persistent. The aim of this paper is to consciously modify and control the free throw using biofeedback. Elbow and shoulder dynamics are calculated by an image processing technique equipped with a video image acquisition system. The proposed setup in this paper, named learning control system, is able to quantify and provide feedback of the above parameters in real time as audio signals. Therefore, it yielded to performing a correct learning and conscious control of shooting. Experimental results showed improvements in the free throw shooting style including shot pocket and locked position. The mean values of elbow and shoulder angles were controlled approximately on 89o and 26o, for shot pocket and also these angles were tuned approximately on 180o and 47o respectively for the locked position (closed to the desired pattern of the free throw based on valid FIBA references). Not only the mean values enhanced but also the standard deviations of these angles decreased meaningfully, which shows shooting style convergence and uniformity. Also, in training conditions, the average percentage of making successful free throws increased from about 64% to even 87% after using this setup and in competition conditions the average percentage of successful free throws enhanced about 20%, although using the learning control system may not be the only reason for these outcomes. The proposed system is easy to use, inexpensive, portable and real time applicable.
Uji Coba Metode A/B Testing dalam Proses Desain (Objek Eksperimen: Visual Tampilan Permainan Digital Acaraki)

Metode A/B testing merupakan sebuah metode evaluasi desain yang kerap digunakan, khususnya dalam perancangan untuk medium digital, seperti pada website ataupun aplikasi digital. Penulis ingin melihat lebih jauh apakah hasil evaluasi dari A/B testing koheren dan selaras dengan desain yang dihasilkan secara iteratif dengan pertimbangan-pertimbangan teoritis. Dalam penelitian ini, penulis menggunakan obyek eksperimen dari perancangan permainan digital Acaraki: The Java Herbalist, yang merupakan permainan boardgame berbentuk fisik. Salah satu pertimbangan teoritis yang digunakan dalam perancangan adalah affordance. Dalam Iterasi desain yang dihasilkan, disiapkan dua opsi berbeda untuk keperluan A/B testing, yang kemudian diujikan kepada 64 responden. Dari sepuluh eksperimen yang dilakukan, 60% desain akhir sesuai dengan hasil A/B testing. Dari penelitian ini, penulis melihat bahwa metode A/B testing merupakan sebuah metode evaluasi yang sesuai untuk menguji karya desain, namun prakteknya perlu memperhatikan faktor-faktor seperti waktu dan juga kriteria dari responden yang berpartisipasi dalam A/B testing.
Signal Priority Request Delay Modeling and Mitigation for Emergency Vehicles in Connected Vehicle Environment

Connected vehicle-based signal priority control is widely regarded as an advanced method for improving travel efficiency of an emergency vehicle when passing through intersections. However, the vehicle-to-everything (V2X) communication delay is a critical factor affecting the performance of signal request and has rarely been considered in existing studies. This paper conducted a comprehensive delay analysis of the preemption signal request and its influence on practical preemption control for the emergency vehicle. First of all, a general end-to-end delay decomposition model is formulated to analyze significant delay uncertainties from different sources. Then, a compensated distance strategy is adopted for cooperative preemption control to ensure the reliability of preemption control and minimize impacts on performance caused by communication delay. Based on the analysis of field data and numerical results, the proposed model is able to reveal characteristics of communication delay for multimodal traffic signal control with priority. The proposed communication delay compensation strategy shows clear benefits in improving the performance of signal preemption control priority for an emergency vehicle at intersections and therefore has potential to enhance V2X applications in a connected vehicle environment.