Miracle-dz/UniFAR-FTUs huggingface dataset:
Face detection and recognition with 180 degree rotation based on principal component analysis algorithm

This paper presents a simple and fast recognition system with various facial expressions, poses, and rotation. The proposed system performed in two phases. Face detection is the first phase. The front and profile face detected cropped face area from the image by Viola-Jones algorithm and the right side face is detected from the image by taking the flip of the profile image. Principal component analysis (eigenfaces) algorithm is used in the recognition phase and depends on created database models used to be compared with test face image input to the recognition procedure. For training and testing the system, two sets of the image of the file exchange interface (FEI) database have been used to identify the person. The experimental result shows the effectiveness and robustness of the method used for the detection of the face and achieves high accuracy of 96%, which improves the recognition performance with low execution time. Furthermore, the accuracy of 35 trained images for recognition is 97.143% with average time execution which is (0.323657s). Also, the accuracy of 15 tested images for recognition is 93.315% with average time execution which is (0.3348s) which indicates a good and strong success and accuracy method for facial recognition.
Tourism and Mental Health: Foundations, Frameworks, and Futures

Tourism contributes to mental health. We could: recognize, measure, value, and market those contributions; analyze components and design products to maximize mental health benefits; and use mental health benefits in tourism industry marketing and lobbying. If we measure benefits to health-research standards, then tourism could also gain commercial opportunities within the health sector. Currently, there are widely differing bodies of evidence within different tourism subsectors, reflecting historical research emphases. Music, museums, and shopping malls have been identified as therapeutic for some. Nature tourism therapies have been tested extensively, with a higher standard of evidence. Adventure tourism has been analyzed principally from a phenomenological perspective, indicating powerful psychological effects. Many mental health therapies require continuing behavioral change. Tourism research could contribute to these therapies, since it includes detailed data on the effects of program design and guiding, and individual personalities, interests, capabilities, motivations, experiences, emotions, and satisfaction.
Impact Performance of Three-dimensional Woven Composites with Novel Binding Yarn Patterns

ABSTRACT This research offered an experimental examination of the effect of binder yarns, and 3D woven patterns on impact (Charpy and drop weight impact), and compression after impact (CAI) performance of seven (07) different kinds of 3D woven jute/green epoxy composites. Along with four (04) typical classifications of 3D woven reinforcements i.e., OLL, OTT, ALL, ATT, and three (03) novel (hybrid) 3D reinforcements i.e., H1 (OTT and ATT interlocking pattern), H2 (OTT and ALL interlocking pattern), H3 (OLL warp and weft interlocks “bidirectional”) were also developed on dobby weaving machine. OTT composite displayed the highest amount of impact strength during Charpy impact in both in-plane directions i.e., warp and weft in comparison with others due to the existence of the truly vertical binder yarns which is comparable with H1. While ALL sample exhibited the highest value of maximum load, work done, and energy absorbed during the 3 J and 6 J drop weight impact energies which is nearest comparable with hybrid 3 (H3) composite. H3 composite sample revealed the highest value of compression after impact (CAI) stress and modulus in both energy levels due to the presence of both warp and weft binder yarns in a single 3D structure.
Power modules design and optimization for medium power of MMC inverters : high insulation voltage gate driver system and 3D packaging

In this research, the author focuses on both a design optimization for a Medium Voltage Modular Multilevel Converter (MV-MMC) use as a DC/AC or AC/DC converter and gate drivers systems for IGBT modules which are used in this kind of application. For example, the MMC converters are used in Medium-Voltage Direct Current (MVDC) electrical ship power systems. For such application, according to IEEE document, the DC bus voltage can be up to 35kV. Hence, gate drivers’ systems for IGBT modules for MVDC-MMC applications are major concerns in terms of architectures and insulation voltage capabilities. Thus, this dissertation provides solutions to answer these problems. The study also includes the studies of a dielectric material which is used as insulation material. The results of experimental tests of a proposed dielectric material for different layers thicknesses to sustain different insulation voltage levels are also provided to clearly validate this study. Actually, a MMC converter composes of a number of converter cells connected in series. One cell (converter’s sub-module) is classically composed of two IGBT modules. Based on the cell topology, a challenged gate driver’s architecture for power semiconductor modules is proposed and compared to the classical one in terms of high and low galvanic insulation voltage levels’ requirements, converter’s cell size, etc.
Modelling and optimization of lead adsorption by CoFe2O4@CMC@HZSM-5 from aqueous solution using response surface methodology

A modified magnetic nano-biocomposite based on zeolite (CoFe 2 O 4 @CMC@HZSM-5) was syn- thesized and characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, field-emission scanning electron microscopy, vibrating sample magnetometer, and Brunauer– Emmett–Teller tests. CoFe O was applied as an adsorbent for the efficient removal of Pb(II). Then, the applicability of the nano-biocomposite adsorbent was investigated for the lead removal. To determine the relationship between effective parameters on lead adsorption, the response surface methodology was applied. Maximum removal efficiency by CoFe 2 O 4 @CMC@ HZSM-5 under optimal conditions with a contact time of 300 min, pH = 5, Pb(II) concentration of 400 mg/L, and 0.4 g of the adsorbent (reactor volume = 200 mL) was 96% for synthetic and 75% for real samples, respectively. The adsorption of Pb(II) by CoFe 2 O 4 @CMC@HZSM-5 followed the Langmuir isotherm and pseudo-second-order kinetic models. According to the negative Δ H ° values, the adsorption of Pb(II) onto CoFe 2 O 4 @CMC@HZSM-5 was exothermic and thermodynamics studies indicated that was not possible and spontaneous in nature. The magnetic nano-biocompos-ite adsorbent had good reusability and attained a high removal efficiency of 91% for Pb(II) after six consecutive adsorption cycles, thus can be recommended as a coefficient adsorbent for the removal of Pb(II) from contaminated water.
The Investigation of Mobile Virtual Reality Application Instructional Content in Geography Education: Academic Achievement, Presence, and Student Interaction

Abstract In this study, we created an interactive Virtual Reality (VR) instructional application for geography education. The sample consisted of 9th grade students as 20 students in the control group and 20 students in the experimental group. Expository Instruction Methods, one of the traditional teaching methods, were applied to the control group, and the teacher on the slide explained the “Shape and Movements of the Earth” as the subject. The students in the experimental group used the VR-based interactive teaching environment we designed for the same subject under the supervision of a teacher. We explored the relationship between students’ level of presence and their academic achievement and received students’ opinions. The students’ academic scores in the experimental group were higher with a statistically significant difference than the control group, and we found that the motivation was higher in the experimental group. The research aims to show the effect of using VR interactive teaching materials in geography education, specifically for “Shape and Movements of the Earth”.
A Software-Circuit-Device Co-Optimization Framework for Neuromorphic Inference Circuits

Neuromorphic circuits, which usually use analog computation for vector-matrix multiplication (VMM) in neural networks (NN), are promising machine learning accelerators with much lower latency and power consumption than digital ones. Analog computation is expected to have a more efficient design space than digital computation since the signals are not digitized. Therefore, it is very suitable for Internet-of-Thing (IoT) applications that require ultra-low power consumption at a low cost. For IoT applications, sometimes it is also desirable to eliminate the digital circuits (such as adders, registers, shifters, multiplexers, and Analog-to-Digital Converters) between the VMM arrays to further reduce the power consumption. However, the optimization of a purely analog circuit is more difficult and requires full SPICE circuit simulations. In this paper, we present a software-circuit-device co-optimization framework using a python wrapper for automatic full circuit SPICE simulation and analysis for neuromorphic circuits. This framework allows users to experiment with how the NN design (software) affects the performance of the hardware neuromorphic circuits. It takes Verilog-A or SPICE models from calibrations or PDK in various technologies and emerging memories (such as ReRAM) without further calibration (unlike using behavior models). We show that the simulation time is reasonable even with hundreds of thousands of synapses under limited computation resources. Using ReRAM and a 45nm generic technology as an example, the effects of feedback network and OpAmp design, software ML architecture, and input data accuracy on the inference accuracy are studied.
The Dark Side of Leadership: The Impact of Despotic Leadership on Job Performance and Vigor with the Moderating Role of Islamic Work Ethics

Purpose: This study examines the interactive effects of despotic leadership and Islamic work ethic (IWE) on the job outcomes of employees, that is, job performance and vigor. Methodology: Using a time lag design, we collected data from 201 regular faculty members of a medium-sized private university in Pakistan. Findings: The analysis revealed that despotic leadership relates significantly to the employee job performance but not vigor. IWE showed a significant effect on vigor, but not on job performance. In addition, the results also confirmed that IWE moderates the relationship between despotic leadership and vigor but not for job performance. Significance: This study added value to the body of knowledge by examining the moderating role of IWE between despotic leadership, vigor, and job performance. Limitations: Limitations and future directions for research have also been discussed. Practical Implications: Employees who work under the supervision of despotic leaders must be given proper training to minimize the fear of such leaders. The findings of the study also provide some important possibilities for the part of IWE in increasing the positive energies (i.e. vigor) at work.
Computational Design of Nanobody Binding to Cortisol to Improve Their Binding Affinity Using Molecular Docking and Molecular Dynamics Simulations

Currently, nanobody binding cortisol has been deposited in the database. Unfortunately, the affinity is still in micromolar order. Substituting hydrophobic residues in the binding pocket and utilizing CDR2 and CDR3 is the strategy to improve the affinity. A single and double substitution at positions 53 and 101 have been introduced to the nanobody structure through molecular modeling. The affinity toward cortisol was evaluated using molecular docking to get the binding pose. The highest binding energy pose was used as the initial coordinate to analyze further using 100 ns molecular dynamics simulations. The binding affinities calculated by MMGBSA showed that MT3, MT5, and MT6 have better binding affinity than WT. In contrast, the ligand movement through MD simulations reveals that MT1, MT3, and MT5 are relatively stable. Hence, docking and MD simulations showed that MT3 is the best mutant than others. This mutant is substituting the threonine to isoleucine at position 53. New hydrophobic interactions occurred and caused the increase of binding. Eventually, this study provides valuable structural information to improve the binding affinity of nanobody binding cortisol for further development of this molecule to antibody-based biosensor design.
Revised Correlation for Accurate Estimation of CO2-Brine Interfacial Tension at Reservoir Conditions

A recently reported correlation of CO2–brine interfacial tension (IFT) for the full range of reservoir pressure, temperature, and formation water salinity necessary to evaluate CO2 sequestration in hydrocarbon reservoirs has been revised and simplified. The new CO2–brine correlation predicts CO2–brine IFT normalized by water surface tension from temperature, CO2-water density difference normalized by the density difference between water and it's vapor(function of pressure and temperature), and the valence-weighted molality of the cations. The correlation was derived from a database that covers 1298 CO2–brine IFT data including 484 for pure water. The revised CO2–brine IFT correlation accurately predicts available data for pure CO2–pure water IFT data with an average absolute relative error (AARE) of 2.4% and standard deviation (SD) of 3.1%. Similarly, for CO2–brine IFT correlation achieves an AARE of 2.4% and a SD of 3.5%. We also examine simple methods for predicting the interfacial tension between water and mixtures of CO2 and other gases. We find that while under ideal conditions the mole-fraction weighted average is a viable approximation to the mixture interfacial tension, it typically overstates IFT in many situations. We propose a minor generalization of Kashefi's (2012) method which has better qualitative behavior and improves predictions with an AARE of approximately 5%.
Improving minimum rate predictors algorithm for compression of volumetric medical images

Medical imaging technologies are experiencing a growth in terms of usage and image resolution, namely in diagnostics systems that require a large set of images, like CT or MRI. Furthermore, legal restrictions impose that these scans must be archived for several years. These facts led to the increase of storage costs in medical image databases and institutions. Thus, a demand for more efficient compression tools, used for archiving and communication, is arising. Currently, the DICOM standard, that makes recommendations for medical communications and imaging compression, recommends lossless encoders such as JPEG, RLE, JPEG-LS and JPEG2000. However, none of these encoders include inter-slice prediction in their algorithms. This dissertation presents the research work on medical image compression, using the MRP encoder. MRP is one of the most efficient lossless image compression algorithm. Several processing techniques are proposed to adapt the input medical images to the encoder characteristics. Two of these techniques, namely changing the alignment of slices for compression and a pixel-wise difference predictor, increased the compression efficiency of MRP, by up to 27.9%. Inter-slice prediction support was also added to MRP, using uni and bi-directional techniques. Also, the pixel-wise difference predictor was added to the algorithm. Overall, the compression efficiency of MRP was improved by 46.1%. Thus, these techniques allow for compression ratio savings of 57.1%, compared to DICOM encoders, and 33.2%, compared to HEVC RExt Random Access. This makes MRP the most efficient of the encoders under study.
Characterization of Microfragmented Adipose Tissue Architecture, Mesenchymal Stromal Cell Content and Release of Paracrine Mediators

The use of microfragmented adipose tissue (µFAT) for the treatment of musculoskeletal disorders, especially osteoarthritis (OA), is gaining popularity, following positive results reported in recent case series and clinical trials. Although these outcomes were postulated to rely on paracrine signals, to date, a thorough fingerprint of released molecules is largely missing. The purpose of this study was to first characterize both structure and cell content of unprocessed lipoaspirate (LA) and µFAT, and further identify and frame the array of signaling factors in the context of OA disease, by means of high throughput qRT-PCR for extracellular-vesicle (EV) embedded miRNAs and proteomics for tissue and secreted factors. Cell count showed reduction of blood cells in µFAT, confirmed by histological and flow cytometry analyses, that also showed a conserved presence of structural, endothelial and stromal components and pericytes. In the secretome, 376 and 381 EV-miRNAs in LA and µFAT, respectively, were identified. In particular, most abundant and µFAT upregulated EV-miRNAs were mainly recapitulating those already reported as ASC-EVs-specific, with crucial roles in cartilage protection and M2 macrophage polarization, while only a scarce presence of those related to blood cells emerged. Furthermore, secretome proteomic analysis revealed reduction in µFAT of acute phase factors driving OA progression. Taken together, these results suggest that processing of LA into µFAT allows for removal of blood elements and maintenance of tissue structure and stromal cell populations, and possibly the increase of OA-protective molecular features. Thus, microfragmentation represents a safe and efficient method for the application of adipose tissue properties in the frame of musculoskeletal disorders.
The Effects of Theory-Based Educational Intervention and WhatsApp Follow-up on Papanicolaou Smear Uptake Among Postnatal Women in Malaysia: Randomized Controlled Trial

Background Despite the availability and accessibility of free Papanicolaou (Pap) smear as a screening tool for cervical cancer, the uptake of Pap smear in Malaysia has not changed in the last 15 years. Previous studies have shown that the high uptake of Pap smear reduces the mortality rate of patients with cervical cancer. The low uptake of Pap smear is multifactorial, and the problem could be minimized through the use of mobile technologies. Nevertheless, most intervention studies focused on individual factors, while other important aspects such as mobile technologies, especially WhatsApp, have not been investigated yet. Objective This study aims to determine the effects of a theory-based educational intervention and WhatsApp follow-up (Pap smear uptake [PSU] intervention) in improving PSU among postnatal women in Seremban, Negeri Sembilan, Malaysia. Methods A 2-arm, parallel single-blind cluster randomized controlled trial was conducted among postpartum women from the Seremban district. Twelve health clinics were randomly assigned to the intervention and control groups. At baseline, both groups received a self-administered questionnaire. The intervention group received standard care and PSU intervention delivered by a researcher. This 2-stage intervention module was developed based on Social Cognitive Theory, where the first stage was conducted face-to-face and the second stage included a WhatsApp follow-up. The control group received standard care. Participants were observed immediately and at 4, 8, and 12 weeks after the intervention. The primary endpoint was PSU, whereas the secondary endpoints were knowledge, attitude, and self-efficacy scores for Pap smear screening self-assessed using a Google Forms questionnaire. A generalized mixed model was used to determine the effectiveness of the intervention. All data were analyzed using IBM SPSS (version 25), and P value of . 05 was considered statistically significant. Results We analyzed 401 women, of whom 76 (response rate: 325/401, 81%) had withdrawn because of the COVID-19 pandemic, with a total of 162 respondents in the intervention group and 163 respondents in the control group. The proportion of Pap smears at the 12-week follow-up was 67.9% (110/162) in the intervention group versus 39.8% (65/163) in the control group (P<.001). Significant differences between the intervention and control groups were found for Pap smear use (F4,1178; P<.001), knowledge scores (F4,1172=14.946; P<.001), attitude scores (F4,1172=24.417; P<.001), and self-efficacy scores (F1,1172=10.432; P<.001). Conclusions This study demonstrated that the PSU intervention is effective in increasing the uptake of Pap smear among postnatal women in Seremban district, Malaysia. This intervention module can be tested in other populations of women. Trial Registration Thai Clinical Trials Registry TCTR20200205001; https://www.thaiclinicaltrials. org/show/TCTR20200205001
Nebivolol Hydrochloride Loaded Nanostructured Lipid Carriers as Transdermal Delivery System: Part 1: Preparation, Characterization and In Vitro Evaluation

Nebivolol hydrochloride (NEB) is a 3rd generation highly selective β1-blocker with antihypertensive properties, the elimination half-life is about 10 hrs and the oral bioavailability is about 12%. The study was aimed to develop nanostructured lipid carriers (NLC) for transdermal delivery of NEB. The study involves two separate parts, part 1 (current) involves preparation and characterization of NEB loaded NLCs (NEB-NLCs). Part 2 of the study, NEB-NLCs based gel was formulated using gelling agent carbapol 934 as transdermal delivery system using rat skin. Part 2 of the study will be presented separately in the forthcoming issue. The current investigation describes the effect of type and concentration of different solid lipids, liquid lipids, and surfactant/co-surfactant on the characteristics of NLC such as particle size, polydispersity index, zeta potential, drug entrapment efficiency, and drug release profile. Transmission electron microscopy, scanning electron microscope and atomic force microscope revealed nearly spherical shape NLC with negligible effect of liquid lipid (oleic acid) content on the particle morphology. The differential scanning calorimetry demonstrated depression in the melting point and crystallinity index of the NLCs with increasing the amount of liquid lipid. The in vitro drug release studies demonstrated that 93% of the drug was released over 24hrs. The NEB-NLCs possessed a biphasic release pattern characterized by a rapid initial release followed by a sustained release.
HapticProxy: Providing Positional Vibrotactile Feedback on a Physical Proxy for Virtual-Real Interaction in Augmented Reality

Abstract Consistent visual and haptic feedback is an important way to improve the user experience when interacting with virtual objects. However, the perception provided in Augmented Reality (AR) mainly comes from visual cues and amorphous tactile feedback. This work explores how to simulate positional vibrotactile feedback (PVF) with multiple vibration motors when colliding with virtual objects in AR. By attaching spatially distributed vibration motors on a physical haptic proxy, users can obtain an augmented collision experience with positional vibration sensations from the contact point with virtual objects. We first developed a prototype system and conducted a user study to optimize the design parameters. Then we investigated the effect of PVF on user performance and experience in a virtual and real object alignment task in the AR environment. We found that this approach could significantly reduce the alignment offset between virtual and physical objects with tolerable task completion time increments. With the PVF cue, participants obtained a more comprehensive perception of the offset direction, more useful information, and a more authentic AR experience.