Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining Sensory-motor Training Versus Impairment-based Training on Pain and Function in Subjects With Knee Osteoarthritis

Purpose: Osteoarthritis is a degenerative joint disease affecting synovial joints and damages joints due to stresses caused by an abnormality in any of the synovial joint tissues, including articular cartilage and subchondral bone, ligaments, menisci, periarticular muscles, peripheral nerves, and synovium. To compare the effect of sensory-motor training versus impairment-based training on pain and physical function in subjects with knee osteoarthritis. Methods: Simple random sampling was used to divide 30 subjects aged 50 and 70 years who met the inclusion and exclusion criteria into two groups (n=15). Group A received sensory-motor training, while Group B received impairment-based training. Before the treatment, the subjects walked for 10 minutes to warm up. For three weeks, each group was treated three times per week. Pre-test; post-test outcomes are noted, the visual analog scale (VAS) was used to assess pain, and the Western Ontario and McMaster Universities osteoarthritis index (WOMAC) was used to assess physical function. Results: Comparing the post-test pain (VAS) scores between groups showed that the mean±SD of posttest pain (VAS) score in the sensory-motor training group was 2.707±1.01. The mean±SD in the impairment-based training group was almost the same, at 2.29±1.13. It was statistically significant at the 5% level. Similarly, the mean±SD of the posttest function (WOMAC) score in the sensory-motor training group was 16.55±6.92. Conclusion: Sensory-motor training is superior to impairment-based training on pain and physical function in subjects with knee osteoarthritis.
Process Optimization for Development of Guar Gum-Based Biodegradable Hydrogel Film Using Response Surface Methodology

In the current study, a guar-gum-based biodegradable hydrogel film was prepared using an initiator (potassium persulfate), crosslinker (N-N methyl bis acrylamide), and plasticizer (glycerol) for packaging of fruits and vegetables. The effect of independent variables (initiator, crosslinker, and plasticizer) on the biodegradation (% wt. loss), color difference (ΔE), hardness (N), swelling index (%), and transparency (%) of the film was studied using Box–Behnken design, random surface methodology (RSM). The results showed significant effects on all the abovementioned parameters, and it was observed that the developed model was accurate, with a prediction error of only −3.19 to 2.99%. The optimized formulation for the preparation of hydrogel film was 0.15% initiator, 0.02% crosslinker, and 2.88% plasticizer exhibiting satisfactory biodegradability, color difference, hardness, swelling index, and transparency. Results showed that a guar-gum-based biodegradable hydrogel film has adequate physical, optical, and biodegradable properties and can be successfully utilized in the food packaging industry.
Quantum confinement effects across two-dimensional planes in MoS2 quantum dots

The low quantum yield (∼10−5) has restricted practical use of photoluminescence (PL) from MoS2 composed of a few layers, but the quantum confinement effects across two-dimensional planes are believed to be able to boost the PL intensity. In this work, PL from 2 to 9 nm MoS2 quantum dots (QDs) is excluded from the solvent and the absorption and PL spectra are shown to be consistent with the size distribution. PL from MoS2 QDs is also found to be sensitive to aggregation due to the size effect.
Asymptotic Behavior of Structure Function at Small Wave Numbers in Late Stage of Phase Separation : Complex Dynamics in Nonlinear Systems

The asymptotic behavior of the structure function at small wave numbers in systems undergoing phase separation is investigated. Brief reviews of the multi-time scaling and the k4-asymptotic behavior of the structure function for the Cahn-Hilliard equation are presented. Then the validity of the k 4-behavior for other systems is investigated. Numerical simulations for the spin exchange kinetic Ising model, for the Cahn-Hilliard model with the surface diffusivity only and for the simple liquid mixture are performed. It is found that the k4-behavior is consistent with these simulations.
Green, Sustainable Synthesis of γ-Fe2O3/MWCNT/Ag Nano-Composites Using the Viscum album Leaf Extract and Waste Car Tire for Removal of Sulfamethazine and Bacteria from Wastewater Streams

Multi-walled carbon nanotubes (MWCNTs) decorated with Ag nanoparticles (NPs) are bifunctional adsorbent nanomaterials with antibacterial activity. They can be magnetically recovered from wastewater in case of coupling with γ-Fe2O3. In this study, for the first time, an environmentally friendly technique was applied to prepare a nanocomposite (NC) material composed of γ-Fe2O3/MWCNT/Ag by using Bridgestone disposable tires and Viscum album leaves extract. γ-Fe2O3/MWCNTs/Ag NC was employed for the removal of sulfamethazine (SMT) from aqueous solutions. Under the optimized conditions determined via the Taguchi method, the highest SMT adsorption capacity of the γ-Fe2O3/MWCNT/Ag NC was measured to be 47.6 mg/g. The experimental data fitted well with the pseudo-second-order kinetic model and the Langmuir isotherm. The thermodynamic parameters implied that the adsorption process was endothermic. In addition to adsorption of the drug pollutant, the NC demonstrated a superior antibacterial activity against Gram-positive bacteria. The reusability test also showed that over 79% SMT can be removed using γ-Fe2O3/MWCNTs/Ag NC even after four adsorption cycles. Taken together, γ-Fe2O3/MWCNTs/Ag NC was proven to be a promising antibacterial nano-adsorbent for wastewater treatment.
Evaluation of Phytochemical, Nutritional and Antioxidant Properties of a Functional Tea Prepared from Blends of Local Spices Utazi (Gongronema latifolium), Nchanwu (Ocimum gratissium) and Tumeric (Curcuma longa)

The study assessed the phytochemical, nutritional and antioxidant properties of a functional tea made from mixture of Utazi leaf Gongronema latifolium), Nchanwu leaf (Ocimum gratissimum) and Turmeric rhizome (Curcuma longa). The three spices were individually processed by drying and mincing before combining them at different ratios that resulted to 16 samples. The samples were generated through D-optimal mixture design using statistical software (Design Expert version 12). The samples were evaluated for phytochemical, nutritional and antioxidant properties. The fresh raw materials were destalked (for the leaves), sorted, washed, withered, oxidized for 24 h, oven dried at 60oC for 30 min, cooled and milled, and packaged. Fresh turmeric rhizome were sorted, washed blanched at 90oC for 2 min, cooled, peeled, sliced, oven dried at 60oC for 30 min, cooled, milled and packaged in teabags and high density polyethylene. The alkaloids, saponin, phenol, cardiac glycoside, flavonoid, tannin, steroid and anthocyanin content ranged from 12.00-22.00, 0.42-1.15, 11.67-15.63, 0.06-0.67, 12.67-22.00, 0.56-0.89, 1.00-1.67, 46.00-54.00 mg/100g respectively. The vitamin C and E content ranged from 3.03-4.13, 0.31-0.64 mg/100g respectively. The minerals iron and zinc content of the tea samples ranged from 3.53-4.70, 0.06-0.78 ppm respectively. The sensory evaluation score of the tea infusion of the sample AB and DA were ‘liked very much’ with the rating of 8.60 and 8.20 respectively, these samples were more acceptable to the panelist. The antioxidant scavenging activity ranged from 42.00-47.00% with sample EC exhibiting the highest level of activity, and the proportion was 70g, 24.62g, 5.38g of Utazi leave, Nchanwu leave, and Turmeric rhizome.
Notes on the distribution of Dalmatinella simonae (Gastropoda: Hydrobiidae) in Croatia and the utility of barcoding in its determination

Dalmatinella simonae is a recently described species from Lake Sladinac and the river Cetina (Croatia). New findings from the rivers Cetina, Neretva and Ruda indicate a wider distribution of this species especially in comparison with its relative D. fluviatilis, known only from a short section of the river Zrmanja. Its occurrence is also probable in the river Neretva in Bosnia and Herzegovina. Barcoding analysis, using mitochondrial cytochrome oxidase subunit I (COI), confirmed the occurrence of this species in new sites, and the nearly complete lack of genetic divergence.
Deep Learning Based Gait Recognition Using Convolutional Neural Network in the COVID-19 Pandemic

Gait recognition is the behavioral biometric trait that tracks humans based on their walking motion. It has gained attention because of its non-invasive and unobtrusive behaviors and applicable to the different application area. In this paper, we target model-free gait recognition with the deep learning approach for the Muslim community in the COVID-19 pandemic. The different convolutional neural network architectures (CNN) are examined by using the spatio-temporal gait representation called Gait Energy Images (GEI). We explored both the identification and verification problems to determine the suitability of the proposed CNN frameworks. In gait recognition, the intraclass variation is larger than the inter-class variation because of the shooting view, the walking speed, the wearing condition, and so on. To tackle this challenge, the verification framework is more suitable for the 1:1 association of gait recognition. As for the verification problem, we implemented the Siamese network with the parallel CNN architecture. All the proposed methods are tested against the public gait datasets called OUISIR-LP and OUISIR-MVLP to determine the identification and verification performance in terms of recognition accuracy and error rate. Doi: 10.28991/ESJ-2022-06-05-012 Full Text: PDF
ANALISIS FORENSIK DIGITAL PADA SKYPE BERBASIS WINDOWS 10 MENGGUNAKAN FRAMEWORK ACPO

Kejahatan di dunia setiap tahunnya semakin meningkat. Hal ini di dukung dengan mudahnya masyarakat dalam mendapatkan perangkat teknologi dan akses internet yang semakin luas. Aplikasi Skype merupakan salah satu sarana yang dapat digunakan untuk melakukan kejahatan dunia maya. Hal ini dikarenakan jumlah penggunanya yang semakin meningkat. Oleh karena itu dalam menangani kejahatan di dunia maya di butuhkan metode forensik digital untuk menemukan bukti digital. Penelitian ini bertujuan membandingkan hasil analisis forensik pada aplikasi Skype berbasis windows 10 dengan metode static forensic dan framework atau kerangka kerja Association of Chief Police Officers (ACPO). Hasil yang di dapatkan adalah Autopsy berhasil mendapatkan bukti digital berupa 15 kontak person, 1 pesan teks, dan 9 file gambar dengan persentase kinerja sebesar 48%. Sedangkan tool forensik Belkasoft Evidence Center berhasil mendapatkan bukti digital 15 kontak person, 2 pesan teks dan untuk file gambar tidak dapat ditemukan dengan persentase kinerja sebesar 32%. Dari hasil tersebut dapat di simpulkan bahwan Autopsy memiliki kinerja yang lebih baik dari Belkasoft dalam menemukan bukti digital yang telah terhapus.
Statistical issues surrounding the analysis of forensic low-template DNA samples

Increased sensitivity of forensic DNA profiling over the last decade has led to increased stochasticity in the resulting profiles, causing difficulties for interpretation that were acknowledged by the Caddy Report [Caddy et al., 2008]. These difficulties were largely overcome with the adoption of statistical models allowing for dropout and dropin, but interpretation issues remain, several of which are tackled in this thesis. One such issue concerns the choice of allele frequency databases when the ethnic background of the true source of the crime scene DNA is unknown. I propose a heuristic for choosing a single database and adjusting the likelihood ratio calculations to allow for the possibility that a different database may be more appropriate. Another issue in general, and specifically for the database choice heuristic, is the choice of an appropriate value for the population genetics parameter FST to account for distant relatedness between the alleged contributor and an alternative source of the DNA. I present empirical estimates of FST in worldwide populations, relative to the continental-scale reference databases that are used for UK forensic DNA profiles. In the last few years many software packages for the evaluation of low-template DNA samples have emerged, including likeLTD originally developed by my supervisor Prof Balding but greatly improved and reprogrammed by myself as part of my PhD work. There remains little consensus on how to validate these software packages. I present a method of validation based on the use of multiple-replicate crime stain profiles. It relies on the intuition that sufficient replicates of even very noisy DNA profiling runs eventually generate the same information as a single high-quality replicate. I show that likeLTD performs well when assessed by this approach. Finally, I present a new statistical model that extends likeLTD to incorporate the peak height information in a crime scene profile. I show results based on simulation and laboratory trials verifying the good performance of the new model in improved discrimination between true and false hypotheses.
Research on controllable ozone oxidation on diamond surface

Abstract In recent years, there have been more and more researches on the surface modification of diamonds, however, the exact types and quantities of oxygen-related species on diamond surfaces and the method to control the condition parameters to obtain as many oxygen-containing groups as possible have been rarely studied so far. Therefore, in this work, we focused on these questions. And we find out that ozone oxidation would not affect the overall crystal structure and morphology of diamonds. Besides, changing oxidation time and ozone concentration would significantly influence the density of hydroxyl groups, which is manifested as a change of oxygen content. In order to make the hydroxyl density on diamond surface reach a high level (3.12 × 1014 units/cm2), so that diamonds can be better combined with the resin matrix, the ozone oxidation time should be 15 min, and the ozone concentration should be 115 g•m−3. And under these conditions, the thermal conductivity of diamond and polysiloxane composites can reach 8.02 W/mK.
Improvement of Integrated Watershed Management in Indonesia for Mitigation and Adaptation to Climate Change: A Review

Climate change is a major challenge for Indonesia due to its impact on food, water, energy sustainability, and environmental health. Almost all Indonesian regions are exposed to floods, landslides, soil erosion, drought, and heavy rains. In response to these challenges, the Government of Indonesia has determined integrated watershed management (IWM) to be one of the key programs to reduce greenhouse gas (GHG) emissions, as stated in the updated Indonesian nationally determined contribution (NDC). This paper intends to review Indonesia′s efforts in mitigating and adapting to climate change through an IWM approach, and its attempts to realize a decent life and environment for all communities. Improvement of the IWM can be conducted by strengthening the synergy between the responsible institutions for watershed management and the responsible institutions for handling mitigation and adaptation of climate change impacts. In addition, it is important to prioritize coordination, participation, and collaboration not only at the national government level but also at the international level, since numerous problems may exist in the transboundary between countries, and finding solutions should involve planning, implementation, monitoring, and evaluation. Implementing the micro watershed model (MWM), supported by culture, local wisdom, and traditional knowledge in communities, can be used to improve the current IWM.
A Novel Hybrid Method to Predict PM2.5 Concentration Based on the SWT-QPSO-LSTM Hybrid Model

PM2.5 concentration is an important indicator to measure air quality. Its value is affected by meteorological factors and air pollutants, so it has the characteristics of nonlinearity, irregularity, and uncertainty. To accurately predict PM2.5 concentration, this paper proposes a hybrid prediction system based on the Synchrosqueezing Wavelet Transform (SWT) method, Quantum Particle Swarm Optimization (QPSO) algorithm, and Long Short-Term Memory (LSTM) model. First, the original data are denoised by the SWT method and taken as the input of the prediction model. Then, the main parameters of the LSTM model are optimized by global search based on the QPSO algorithm, which solves the problems of slow convergence and local extremum of traditional parameter training algorithms. Finally, the PM2.5 daily concentration data of Chengdu, Shijiazhuang, Shenyang, and Wuhan are predicted by the proposed SWT-QPSO-LSTM model, and the prediction results are compared with those of single prediction models and hybrid prediction models. The experimental results show that the proposed model achieves higher prediction precision and lower prediction error than other models.
Penalty Virtual Element Method for the 3D Incompressible Flow on Polyhedron Mesh

In this paper, a penalty virtual element method (VEM) on polyhedral mesh for solving the 3D incompressible flow is proposed and analyzed. The remarkable feature of VEM is that it does not require an explicit computation of the trial and test space, thereby bypassing the obstacle of standard finite element discretizations on arbitrary mesh. The velocity and pressure are approximated by the practical significative lowest equal-order virtual element space pair (Xh,Qh) which does not satisfy the discrete inf-sup condition. Combined with the penalty method, the error estimation is proved rigorously. Numerical results on the 3D polygonal mesh illustrate the theoretical results and effectiveness of the proposed method.
Motor Imagery Analysis from Extensive EEG Data Representations Using Convolutional Neural Networks

Motor imagery is a complex mental task that represents muscular movement without the execution of muscular action, involving cognitive processes of motor planning and sensorimotor proprioception of the body. Since the mental task has similar behavior to that of the motor execution process, it can be used to create rehabilitation routines for patients with some motor skill impairment. However, due to the nature of this mental task, its execution is complicated. Hence, the classification of these signals in scenarios such as brain–computer interface systems tends to have a poor performance. In this work, we study in depth different forms of data representation of motor imagery EEG signals for distinct CNN-based models as well as novel EEG data representations including spectrograms and multidimensional raw data. With the aid of transfer learning, we achieve results up to 93% accuracy, exceeding the current state of the art. However, although these results are strong, they entail the use of high computational resources to generate the samples, since they are based on spectrograms. Thus, we searched further for alternative forms of EEG representations, based on 1D, 2D, and 3D variations of the raw data, leading to promising results for motor imagery classification that still exceed the state of the art. Hence, in this work, we focus on exploring alternative methods to process and improve the classification of motor imagery features with few preprocessing techniques.
Specific Features of Operation of Distributed Generation Facilities Based on Gas Reciprocating Units in Internal Power Systems of Industrial Entities

The creation of a decentralized low-carbon energy infrastructure is the main trend in the development of the electric power industry in many countries. Distributed generation facilities (DGs) based on gas reciprocating units (GRUs) are often built by industrial entities for the efficient utilization of secondary energy resources in order to minimize the environmental impact. Modern GRUs have some advantages, but they have design features that should be factored in when connecting them to the internal power systems of industrial entities. Incorrect consideration of possible operating conditions of GRU in their design can lead to their damage, excessive shutdowns, and disruptions in power supply to essential power consumers with significant damage and losses from undersupply of their products. Excessive shutdowns of GRUs are often caused by a non-selective choice of settings for relay protection devices or by load surges that exceed the allowable ones. With high availability factors, GRUs are disconnected five to eight times more often compared to large gas turbine and steam turbine power units. The large total power consumed by electric motors, as part of the load of an industrial entity, determines the nature and parameters of electromechanical transient processes during emergency disturbances. The presented analysis of issues facing real DG facilities relies on the acts of investigation into the causes of accidents. Calculations have shown that the action of the “Load Agreement Module” in the GRU excitation controller can provoke the occurrence of a voltage avalanche in the internal power system with a complete shutdown of the load. The paper presents recommendations on the choice of control algorithms and voltage settings for the GRU excitation controller. Technical solutions are given to prevent damage and excessive shutdowns of GRU in various operating conditions of the system, and to help ensure a reliable power supply to power consumers. The change in approaches to the design of DG facilities is substantiated in the light of their significant differences from other electric power facilities.
Experiences and social impact in the application of requirements engineering in the development of an intelligent platform

Rural Community Tourism (RCT) is an activity that contributes to the economic, social and sustainable development of a country in rural areas. In this research, the goal is to develop an intelligent platform (IP) to meet the needs of different participants in RCT. It presents the experience of focusing on requirements engineering, going through different iterations where a SWOT analysis was performed, while using extreme programming, complying with ISO 25010[9], etc. The accurate identification of requirements is essential for the implementation and usability of the platform to have a social impact on the direct participants.