Miracle-dz/UniFAR-FTUs huggingface dataset:
Teacher's Perspectives of Online Learning vs. Offline Leaning: A Case Study from West Java

Since the start of the COVID-19 pandemic, the education system has undergone dramatic changes. The teaching and learning process is no longer done in a usual classroom setting; instead, it involves virtual meetings and online classes. This paper intended to describe the opinions of English teachers in Geeta School National Plus, in Cirebon, West Java about the advantages and disadvantages of the online and offline settings, and the possibility of combining the two systems in their school. The research used a case study design. The participants were two English teachers in Geeta School National Plus. The data were collected in May 2021 through offline and online interviews using the Google Meet application. The data were analysed qualitatively. The results showed that the teachers agreed that online learning is the best possible solution during the COVID-19 pandemic. Yet, they also agreed that there is a wide opportunity to apply a blended-learning system in the school in accordance with the government rules. This implies that the school or the government need to provide adequate supporting facilities to ensure successful implementation of blended learning. Keywords: blended-learning, education, online, offline setting
Dermolipectomias após procedimentos bariátricos no Sistema Público de Saúde: um longo caminho a percorrer

dos procedimentos pós-bariátricos, número de cirurgias bariátricas. Métodos: coletados do registro de saúde (DATASUS) 2008 e análise dos parâmetros selecionados, com avaliação das principais técnicas de dermolipectomia pós-bariátrica, sua distribuição território nacional, seu tempo de internação, sua mortalidade, os custos para o Sistema Público, a comparação entre as dermolipectomias pós-bariátricas e a distribuição problems faced by the population, and its incidence has gradually increased in recent decades. Amid the global obesity epidemic, bariatric procedures have increased significantly and, despite the growing number of post-bariatric procedures, these are not equivalent to the number of bariatric surgeries. Methods: Data were collected from the public health registry (DATASUS) between 2008 and 2019 to analyze the selected parameters, with an assessment of the main post-bariatric dermolipectomy techniques, their distribution in the national territory, their length of stay, their mortality, costs for the Public System, the comparison between post-bariatric dermolipectomies and the distribution of bariatric procedures in the national territory. Furthermore, dermolipectomies and the distribution of plastic surgeons in Brazil were compared. Results: An increase of 164% was evidenced in the number of post-bariatric dermolipectomies during the studied period. Post-bariatric abdominal dermolipectomy was the most performed procedure, accounting for 65% of the procedures, followed by brachial (14.8%), crural (14.7%) and circumferential (4.7%) dermolipectomy. There was an inequality in the distribution of post-bariatric procedures among Brazilian macro-regions, with the Southeast Region having the highest percentage (49.8%) of dermolipectomies. Conclusions: Despite the progressive increase in post-bariatric dermolipectomies, they did not follow the number of bariatric procedures in the national territory. Therefore, there is a need for a parallel growth between both so that there is complementation in treating these patients. Then, there might be an improvement in the distribution of dermolipectomies in the national territory, allowing more patients to benefit. ABSTRACT
Early Motor Repertoire of Very Preterm Infants and Relationships with 2-Year Neurodevelopment

The Motor Optimality Score, revised (MOS-R) is an extension of the Prechtl General Movements Assessment. This study aims to determine the relationship between MOS-R and 2-year neurodevelopmental outcomes in a cohort of 169 infants born very preterm (<31 weeks’ gestational age), and to examine the predictive validity of the MOS-R at 3–4 months’ corrected age (CA) above perinatal variables associated with poor outcomes, including Prechtl fidgety movements. Development at 2 years’ CA was assessed using Bayley Scales of Infant and Toddler Development, Third edition (Bayley-III) (motor/cognitive impairment: Bayley-III ≤ 85) and Neurological, Sensory, Motor, Developmental Assessment (NSMDA) (neurosensory motor impairment: NSMDA ≥ 12). Cerebral palsy (CP) was classified at 2 years as definite or clinical. The MOS-R was related to 2-year outcomes: Bayley-III motor (BMOS-R = 1.24 95% confidence interval (0.78, 1.70)), cognitive (BMOS-R = 0.91 (0.48, 1.35)), NSMDA scores (BMOS-R = −0.34 (−0.42, −0.25)), definite CP (odds ratio [OR] 0.67 (0.53, 0.86)), clinical CP (OR 0.74 (0.66, 0.83)) for each 1-point increase in MOS-R. MOS-R ≤ 23 predicted motor (sensitivity 78% (60–91%); specificity 63% (54–72%)) and neurosensory motor impairment (sensitivity 86% (64–97%); specificity 59% (51–68%)). The MOS-R is strongly related to CP and motor and cognitive delay at 2 years and is a good predictor of motor and neurosensory motor impairment.
Multi-UAV Interception Inspired by Harris’ Hawks Cooperative Hunting Behavior

This paper presents an approach to intercept adversarial unmanned aerial vehicle (UAV) by using Harris’ hawks (Parabuteo unicinctus) cooperative hunting behavior. A simplified UAV guidance model is introduced to reduce mathematical complexity, but still capture the important behavior of these unmanned aircrafts. A mixed guidance law suited to the Harris’ hawks natural hunting style at high-speed is adopted for the leader UAV to intercept target UAV with good maneuverability and horizontal turning escape tactic. The follower UAVs use Markov decision process to help the leader UAV rounded up their targets. The "flush-and-ambush" strategy and "relay attack" strategy of Harris’ hawks used in cooperative hunting are introduced for multiple UAVs interception in order to increase the probability of success. Simulation results demonstrate availability and effectiveness of the interception approach.
Study on fusion diagnosis techniques of wear faults in synthesized monitoring of aero-engine

Although spectrometric oil analysis(SOA) is a widely applied technique for wear condition monitoring of lubricating system,this single monitoring technique is difficult to accurately predict some damages or failures in oil wetted system including bearing fatigues of aero-engine.In this paper,two techniques including SOA and auto debris classifier were applied to synthetically monitor a certain aero-engine,the Dempster-Shafer(D-S) evidence theory was used to implement fusion diagnosis,and an engine oil monitoring expert system was developed to carry out fusion diagnosis.Finally,some examples were analyzed;the results indicate that synthesized monitoring and fusion diagnosis is an important approach to increase the reliability for forecasting failures of aero-engine.
Mathematical Model Insights into EEG Origin under Transcranial Direct Current Stimulation (tDCS) in the Context of Psychosis

Schizophrenia is a psychotic disease that develops progressively over years with a transition from prodromal to psychotic state associated with a disruption in brain activity. Transcranial Direct Current Stimulation (tDCS), known to alleviate pharmaco-resistant symptoms in patients suffering from schizophrenia, promises to prevent such a psychotic transition. To understand better how tDCS affects brain activity, we propose a neural cortico-thalamo-cortical (CTC) circuit model involving the Ascending Reticular Arousal System (ARAS) that permits to describe major impact features of tDCS, such as excitability for short-duration stimulation and electroencephalography (EEG) power modulation for long-duration stimulation. To this end, the mathematical model relates stimulus duration and Long-Term Plasticity (LTP) effect, in addition to describing the temporal LTP decay after stimulus offset. This new relation promises to optimize future stimulation protocols. Moreover, we reproduce successfully EEG-power modulation under tDCS in a ketamine-induced psychosis model and confirm the N-methyl-d-aspartate (NMDA) receptor hypofunction hypothesis in the etiopathophysiology of schizophrenia. The model description points to an important role of the ARAS and the δ-rhythm synchronicity in CTC circuit in early-stage psychosis.
A Three – Dimensional Finite Element Analysis of Polyetheretherketone PEEK in Dental Implant Prosthesis: A Novel Implant System

This current numerical investigation aim to evaluate the benefits of substituting Titanium with CRF- PEEK for better stress distribution in implant- bone interface. 3D models of a dental implant for the first mandibular molar were constructed using the computed tomography (CT) scan. Four distinct models using a combination of titanium, carbon reinforced polyetheretherketone (CRF- PEEK), and zirconia for implant /abutment materials were studied. A three- dimensional finite element simulation was used to evaluate the stress distribution at the implant – bone interface under a compressive axial load of magnitude 120 N. A spherical indenter was used to simulate occlusal load. Mesh independent study was converged for a very large number of elements. Finite element analysis showed: 1) there was no significant difference in the distribution pattern of stress at the implant – bone interface in the different material models studied, 2) the stress values for all prosthetic implant parts were well below the yield strength, 3) a larger deformation of PEEK implant versus titanium. The substitution of titanium with PEEK for the implant does not provide any better stress distribution and may lead to problems from the deformation of the implant.
Prognostic value of neutrophil to lymphocyte ratio in acute gall stone and alcoholic pancreatitis

Background: Acute pancreatitis (AP) is associated with increased mortality. Many scoring systems have been used to predict the severity of acute pancreatitis but they are either time consuming or done after 48 hours of admission. The aim of the study was to evaluate the prognostic value of Neutrophil to lymphocyte ratio (NLR) in acute gall stone and alcoholic pancreatitis.Methods: 240 patients with acute pancreatitis were prospectively enrolled from December 2017 to December 2019 from the department of general surgery and gastroenterology at St. John’s Medical College, Bangalore. NLR obtained at admission were compared with other known prognostic scoring systems.Results: A total of 240 patients were studied with an etiology of gall stone (N=131) and alcohol (N=109). NLR (17.6±18.3 vs 8.7±8.4, p<0.001) were significantly high in gall stone pancreatitis group whereas high NLR were not related to severe AP in alcoholic AP. For gall stone pancreatitis group NLR demonstrated a predictive value and not in alcoholic AP.Conclusions: NLR can be used as a predictor of severity of acute pancreatitis, at the time of initial diagnosis. Our study demonstrated that NLR can predict the severity in gall stone pancreatitis.
Machine-learning-based high-speed lensless large-field holographic projection using double-sampling Fresnel diffraction method

Machine learning can effectively accelerate the runtime of a computer-generated hologram. However, the angular spectrum method and single fast Fresnel transform-based machine learning acceleration algorithms are still limited in the field-of-view angle of projection. In this paper, we propose an efficient method for the fast generation of large field-of-view holograms combining stochastic gradient descent (SGD), neural networks, and double-sampling Fresnel diffraction (DSFD). Compared with the traditional Gerchberg – Saxton (GS) algorithm, the DSFD-SGD algorithm has better reconstruction quality. Our neural network can be automatically trained in an unsupervised manner with a training set of target images without labels, and its combination with the DSFD can improve the optimization speed significantly. The proposed DSFD-Net method can generate 2000-resolution holograms in 0.05 s. The feasibility of the proposed method is demonstrated with simulations and experiments.
Peptides Regulating Proliferative Activity and Inflammatory Pathways in the Monocyte/Macrophage THP-1 Cell Line

This study evaluates the effects of five different peptides, the Epitalon® tetrapeptide, the Vilon® dipeptide, the Thymogen® dipeptide, the Thymalin® peptide complex, and the Chonluten® tripeptide, as regulators of inflammatory and proliferative processes in the human monocytic THP-1, which is a human leukemia monocytic cell line capable of differentiating into macrophages by PMA in vitro. These peptides (Khavinson Peptides®), characterized by Prof. Khavinson from 1973 onwards, were initially isolated from animal tissues and found to be organ specific. We tested the capacity of the five peptides to influence cell cultures in vitro by incubating THP-1 cells with peptides at certain concentrations known for being effective on recipient cells in culture. We found that all five peptides can modulate key proliferative patterns, increasing tyrosine phosphorylation of mitogen-activated cytoplasmic kinases. In addition, the Chonluten tripeptide, derived from bronchial epithelial cells, inhibited in vitro tumor necrosis factor (TNF) production of monocytes exposed to pro-inflammatory bacterial lipopolysaccharide (LPS). The low TNF release by monocytes is linked to a documented mechanism of TNF tolerance, promoting attenuation of inflammatory action. Therefore, all peptides inhibited the expression of TNF and pro-inflammatory IL-6 cytokine stimulated by LPS on terminally differentiated THP-1 cells. Lastly, by incubating the THP1 cells, treated with the peptides, on a layer of activated endothelial cells (HUVECs activated by LPS), we observed a reduction in cell adhesion, a typical pro-inflammatory mechanism. Overall, the results suggest that the Khavinson Peptides® cooperate as natural inducers of TNF tolerance in monocyte, and act on macrophages as anti-inflammatory molecules during inflammatory and microbial-mediated activity.
Fusion in Cryptocurrency Price Prediction: A Decade Survey on Recent Advancements, Architecture, and Potential Future Directions

Cryptographic forms of money are distributed peer-to-peer (P2P) computerized exchange mediums, where the exchanges or records are secured through a protected hash set of secure hash algorithm-256 (SHA-256) and message digest 5 (MD5) calculations. Since their initiation, the prices seem highly volatile and came to their amazing cutoff points during the COVID-19 pandemic. This factor makes them a popular choice for investors with an aim to get higher returns over a short span of time. The colossal high points and low points in digital forms of money costs have drawn in analysts from the scholarly community as well as ventures to foresee their costs. A few machines and deep learning algorithms like gated recurrent unit (GRU), long short-term memory (LSTM), autoregressive integrated moving average with explanatory variable (ARIMAX), and a lot more have been utilized to exactly predict and investigate the elements influencing cryptocurrency prices. The current literature is totally centered around the forecast of digital money costs disregarding its reliance on other cryptographic forms of money. However, Dash coin is an individual cryptocurrency, but it is derived from Bitcoin and Litecoin. The change in Bitcoin and Litecoin prices affects the Dash coin price. Motivated from these, we present a cryptocurrency price prediction framework in this paper. It acknowledges different cryptographic forms of money (which are subject to one another) as information and yields higher accuracy. To illustrate this concept, we have considered a price prediction of Dash coin through the past days’ prices of Dash, Litecoin, and Bitcoin as they have hierarchical dependency among them at the protocol level. We can portray the outcomes that the proposed scheme predicts the prices with low misfortune and high precision. The model can be applied to different digital money cost expectations.
Study on the Adsorption Characteristics of Mo-Doped Graphene on the Decomposition Products of SF6 Substitute Gas Based on First-Principle Calculations

C4F7N, C5F10O, etc., as new environmental-friendly alternative gases decompose under partial discharge and produce a series of products such as CO, CF4, C2F6, C3F8, CF3CN, C2F5CN, and COF2. Based on the first-principles calculation method of density functional theory (DFT), the adsorption characteristics of intrinsic state graphene and Mo-doped graphene adsorbing SF6 and its substitute gas decomposition products are calculated and analyzed. By comparing the adsorption energy, adsorption distance, density of state, Mulliken charge population, charge transfer amount, and molecular orbital energy for adsorbing different decomposition gases, it can be seen that the system structure is the most stable when Mo is doped at the T site of the graphene surface. The adsorption of Mo-doped graphene on gas molecules is significantly stronger than that of intrinsic graphene, and the order of adsorption is: SO2F2 > H2S > SO2 > CF4. The adsorption of H2S gas molecules by intrinsic state and Mo-doped graphene is n-type adsorption, while the adsorption of SO2F2, CF4, and SO2 gas molecules is p-type adsorption. Mo-doped graphene can be used as a detection device for SO2F2 gas resistance sensors.
A Randomized Clinical Trial on Therapeutic Effects of Myrtus communis L. Cream on Chronic Skin Lesions and Quality of Life of Sulfur Mustard-exposed Veterans

: Sulfur mustard is one of received Eucerin cream (placebo group) twice in a day for one month. Then, We assessed the chronic skin problems and itching-related parameters (such as the itching time, severity, distribution, frequency, and calculated itching score), duration of sleep, number of waking up at night, and quality of life in the both groups. Our analysis of data revealed that application of myrtle cream effectively decreased skin problems including; itching and burning sensation. Additionally, myrtle markedly decreased skin lesion symptoms such as excoriation in the case group as compared with before treatment. Noticeably, myrtle cream significantly improved quality of life of the patients in the case group. The present study provides more in-depth information regarding the protective role of myrtle on the sulfur mustard-induces skin complication. Also, myrtle effectively improved quality of life of the sulfur mustard-exposed veterans.
APPRENTICE: Towards a Cobot Helper in Assembly Lines

—In this paper, we describe a vision of human-robot collaboration on assembly lines, where a collaborative robotic manipulator, a.k. a. cobot, operates as a work-mate for the worker. Speciﬁcally, the cobot, referred to as the “apprentice” since it lacks the ability to replace the worker, can only aid the worker by observing his status during the assembly process, and handing over (and stowing away when done) the tools and the parts. Towards this end, we ﬁrst describe the vision, and outline the challenges involved in developing an “apprentice” cobot and share the current state of the work done.
Institutional Investors and Firm Market Performance: A Comparative Analysis in a Selected Financial Market

:-This study focused on investigating institutional ownership's impacts on financial sector firms' market performance. The research involved data selected from 12 financial sector companies in the US market. The data was gathered from official government websites and some database sites. This study finding release that institutional ownership structure had an important and significant effect on the selected companies' market performance. The aim is to discover the importance of institutional ownership structure on firms' ownership profile.
APPLICATION OF ERGONOMIC WORK ANALYSIS IN AUTOMOTIVE INDUSTRY PROCESSES USING COMPUTATIONAL INTELLIGENCE FOR DECISION MAKING

Ergonomics have proved to be increasingly important for industrial processes around the world. The evolution of machinery and equipment has caused several disorders in occupational health at work. Therefore, it is extremely important to make a comprehensive reading of the workstations and ergonomic analysis tools. The objective of the article is to make an application of the technological resources of fuzzy logic in the results found in the Ergonomic Analysis of Work (AET) in seven jobs in the automotive industry of the Industrial Pole of Manaus (PIM). The methodology applied is based on the application of ergonomic tools using Suzanne Rodgers`method and on the mathematical models characterized by Fuzzy Inference for decision making on various disorders that occur with the health of the employee. The results found in the ergonomic tool ‘’Suzanne Rodgers’’ applied to the movement of upper and lower limbs and other observations in the productive sectors, with the application of Fuzzy Logic, it was shown that the linguistic variables by colors, the legend that shows the classification of ergonomic risks through run. Therefore, they serve to make a comparison and discuss the importance of ergonomic processes for the benefit of the worker in the automotive industry for decision-making.
Galerkin Residual Correction for Fourth Order BVP

This article uses residual correction procedure for improving the Galerkin approximate solutions to higher order boundary value problem (BVP). The residual function of a differential equation is found from the approximate solution of a BVP and setting it as nonhomogeneous term we get the error differential equation. We exploit Bernstein and Bernoulli polynomials as basis functions to solve the two differential equations, namely, original and its error equations, by Galerkin technique subject to the corresponding boundary conditions. Linear and nonlinear problems of fourth order BVPs are considered to verify the proposed method. The resulting numerical solutions are compared with the analytic solutions as well as the results of other approaches those have been reported in the literature. This method is also applied to sixth order BVPs. The comparison reveals that the current procedure is more accurate.
An improved heuristic algorithm for the maximum benefit Chinese postman problem

The maximum benefit Chinese postman problem (MBCPP) is a practical generalization of the Chinese postman problem. A distinctive feature of MBCPP is that the postman can traverse each edge arbitrary times and obtains a benefit for each traversal of an edge, which depends on the number of times that the edge has been traversed. (Pearn and Wang, Omega 31 (2003) 269–273) discussed MBCPP under the assumption that the benefits of each edge is a non-increasing function of the number of traversals. They showed that MBCPP under this assumption is NP-hard, and proposed a heuristic algorithm which applies the minimum spanning tree and the minimal-cost 𝑇 -join algorithms. (Corber´an, Plana, Rodr´ıguez-Ch´ıa and Sanchis, Math. Program. 141 (2013) 21–48) presented an integer programming formulation and a branch-and-cut algorithm for MBCPP without the assumption on the benefits. This is based on the idea of integrating the benefits of each edge into two benefits, each representing that the edge is traversed an odd or even number of times. In this paper, by applying the idea of Corber´an et al. , we improve the heuristic algorithm of Pearn and Wang. Our algorithm applies to the general case with no assumption on the benefits, and can perform better even if the benefits are non-increasing. We then analyze the efficiency of our heuristic algorithm in theory and in practice, and prove that it finds the optimal solution when the benefits satisfy a certain property.