Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of dry needling in the treatment of neck pain and disability associated with myofascial trigger points

Objective: The aim of this study is to evaluate the effectiveness of dry needling (DN) with fast-in and fast-out technique for myofascial trigger points (MTrPs) in the upper trapezius muscle associated with neck pain. Patients and Methods: Patients aged 18-70 years, who have had neck pain at least one active MTrP in the upper trapezius muscle treated with DN, were included in the study. Pain and disability were assessed with Numeric Rating Scale (NRS) and Neck Disability Index (NDI) before treatment (T0), after first session (T1) and after last session (T2). Number of MTrPs where DN was performed and the number of DN sessions were recorded. Patients were evaluated based on the minimal clinically important change (MCIC) scores for NRS and NDI. Results: A total of 76 patients (Female: 67, Male: 9) were included in the study. Median number of DN sessions was 3 and median of MTrPs that DN performed was 4. Both NRS and NDI showed significant improvement at T1 and T2. More than 90% of patients had MCIC at T1 and T2. Conclusion: Dry needling with fast-in and fast-out technique is effective for pain and disability management in patients with neck pain due to MTrPs.
From observation to simulation

The description of globular protein structures as an ensemble of contiguous closed loops or tightened end fragments reveals fold elements crucial for the formation of stable structures and for navigating the very process of protein folding. These are the ends of the loops, which are spatially close to each other but are situated apart in the polypeptide chain by 25–30 residues. They also correlate with the locations of highly conserved hydrophobic residues (referred to as topohydrophobic), in a structural alignment of the members of a protein family. This study analysed these positions in 111 representatives of different protein folds, and then carried out dynamic Monte Carlo simulations of the first steps of the folding process, aimed at predicting the origins of the assembling folds. The simulations demonstrated that there is an obvious trend for certain sets of residues, named mostly interacting residues ,t o be buried at the early stages of the folding process. Location of these residues at the loop ends and correlation with topohydrophobic positions are demonstrated, thereby giving a route to simulations of the protein folding process.
Improvements for NLP Models by Considering Language Differences

Aspect extraction has been playing a critical role in opinion mining of product reviews. Most of the existing works tackling various Natural Language Processing tasks focus on English corpus and barely talked about the effect of language differences when apply the algorithm to other languages. Based on a previous aspect extraction neural model and its application to text data in Chinese, this paper analyzed possible reasons and proposed plausible approaches to address the importance of handling language differences in Natural Language Processing tasks. By bringing the importance of adaptiveness of language models to attention, future NLP research work might produce more robust and comprehensive work regardless of the impact of language differences.
Advanced Structural Materials for Gas-Cooled Fast Reactors—A Review

This review summarizes the development of the Gas-Cooled Fast Reactor (GFR) concept from the early 1970s until now, focusing specifically on structural materials and advanced fuel cladding materials. Materials for future nuclear energy systems must operate under more extreme conditions than those in the current Gen II or Gen III systems. These conditions include higher temperatures, a higher displacement per atom, and more corrosive environments. This paper reviews previous GFR concepts in light of several promising candidate materials for the GFR system. It also reviews the recent development of nuclear power and its use in the peaceful exploration of space. The final section focuses on the development and testing of new advanced materials such as SiCf/SiC composites and high entropy alloys (HEA) for the construction and development of GFRs.
Explaining the rural-urban learning achievements gap in Ethiopian primary education: a re-centered influence function decomposition using Young Lives data

ABSTRACT The rural-urban learning achievements gap is a persistent issue to be addressed from a different approach. This study employed re-centered influence function decomposition with Young Lives data to estimate the rural-urban education production function and decompose the rural-urban learning achievements gap in Ethiopia. Results revealed that the rural-urban education production function is different across achievements distributions. Moreover, most of the rural-urban learning achievements gap is explained by student background characteristics. Unmeasured characteristics explain much of the proportion of the gap but the importance of that proportion varies across the distribution. Policy implications of the findings were discussed.
Pose Estimation for Ground Robots: On Manifold Representation, Integration, Reparameterization, and Optimization

In this article, we focus on pose estimation dedicated to nonholonomic ground robots with low-cost sensors, by probabilistically fusing measurements from wheel odometers and an exteroceptive sensor. For ground robots, wheel odometers are widely used in pose estimation tasks, especially in applications in planar scenes. However, since wheel odometer only provides two-dimensional (2D) motion measurements, it is extremely challenging to use that for accurate full 6-D pose (3-D position and 3-D orientation) estimation. Traditional methods for 6-D pose estimation with wheel odometers either approximate motion profiles at the cost of accuracy reduction, or rely on other sensors, e.g., inertial measurement unit, to provide complementary measurements. By contrast, we propose a novel motion-manifold-based method for pose estimation of ground robots, which enables to utilize wheel odometers for high-precision 6-D pose estimation. Specifically, the proposed method, first, formulates the motion manifold of ground robots by a parametric representation, second, performs manifold-based 6-D integration with wheel odometer measurements only, and third, reparameterizes manifold representation periodically for error reduction. To demonstrate the effectiveness and applicability of the proposed algorithmic module, we integrate that into a sliding-window pose estimator by using measurements from wheel odometers and a monocular camera. Extensive simulated and real-world experiments are conducted for evaluation, and the proposed algorithm is shown to outperform competing the state-of-the-art algorithms by a significant margin in pose estimation accuracy, especially when deployed in complex, large-scale real-world environments.
The Impact of Social Media on Academic Performance of Students at Universities in Amhara Regional State

Even if social media usage has become a common trend among university students in Ethiopia, only scant information is available about the pattern of usage and its relationship with the academic performance in this segment of the population. Therefore, the aim of this study is to assess impact of social media on academic performance of students at Universities in Amhara Regional State. For the purpose of the present investigation a descriptive cross-sectional design with quantitative data collection method was used. Multistage sampling technique was also used to select the study participants by stratified into academic unit and year of study. Data were collected by structured questionnaire. Descriptive and Inferential statistics like percentage, mean, t test, and Analysis of variance (Anova) were calculated. The study discovered that the use of social media had affected academic performance of students negatively. The findings show that there is a correlation between the students’ academic performance and their usage of social networks. Keywords : social media, academic performance, university student DOI: 10.7176/NMMC/95-02 Publication date: January 31 st 2021
Kocharethi, The Araya Woman - A Tale of Convergence and Dependence of Nature and Culture

Viewed dichotomous in regards to the relationship between humans and their environment - ‘Nature’ and ‘Culture’ are the two anthropological categories that even today are understood as poles apart. What’s seen to be belonging to Nature is not approved as the result of human intervention and vice-versa. However, in deference to this view, this paper seeks to elucidate how ‘Nature’ and ‘Culture’ are not contrastive in their Nature but rather converge in many ways, through Narayan’s seminal work “Kocharethi: the Araya Women”, translated from Malayalam by Catherine Thankamma. A work that is a mouthpiece of the life, the ways and practices of the Malayarayars, who abide in the Western Ghats of Kerala. Therefore, keeping a cultural and environmental perspective, the paper employs a thematic and discourse analysis of the seminal work that brings forth the convergence and dependence of Nature and Culture.
Some properties of the classification algorithms using ensemble kernels

In this paper, we study the properties of the KCCE algorithm (Kernel-based Classification with Cluster Ensemble) proposed in our previous publication. Different strategies for choosing the ensemble weights are investigated from the point of view of their influence on the quality and speed of the algorithm. We perform numerical experiments with the algorithm on real datasets from the UCI repository under conditions of artificially added noise at different levels.
Population Increases of Large Birds in North America Pose Challenges for Aviation Safety

There is a strong correlation between bird mass and the likelihood of aircraft damage during a bird–aircraft collision. Thus, the U.S. Federal Aviation Administration (FAA) has established airworthiness standards related to bird mass for engines, airframes, and windshields. Most standards use large (1.8 kg) and medium (1.1 kg) birds as benchmarks (the empennage and certain large turbofan engines use a 3.6-kg bird). There are 20 large (≥1.8 kg) and 16 medium (1.1–1.7 kg) bird species in North America with ≥20 strikes reported for civil aircraft (FAA National Wildlife Strike Database), 1990 to 2018. I analyzed the population changes of these 36 species from 1990 to 2018 in relation to flocking behavior. For the 20 large species, the combined population had a net gain of 27.8 million birds (129% increase). For the 16 medium species, the combined population had a net gain of 6.7 million birds (20% increase). Notably, all 9 species with body mass ≥3.6 kg indicated population increases. In agreement with the increased numbers of birds, the number of strikes involving large and medium birds showed significant (P < 0.01) positive trends from 1990 to 2020 as did strikes involving multiple birds. The threat to aviation safety from large and medium birds, especially flocking species, was much higher in 2018 than in 1990. Although progress is being made to mitigate the risk by management programs to keep large and medium birds away from airport properties, these actions do little to mitigate the threat during climb and approach phases of flight. Enhanced airworthiness standards for aircraft components, bird-detecting radar to provide real-time warnings, and aircraft lighting schemes to improve visibility of aircraft to birds are priority areas of research and development to mitigate these off-airport threats to aviation safety.
Utilizing Sentence Embedding for Dangerous Permissions Detection in Android Apps' Privacy Policies

Privacy policies analysis relies on understanding sentences meaning in order to identify sentences of interest to privacy related applications. In this paper, the authors investigate the strengths and limitations of sentence embeddings to detect dangerous permissions in Android apps privacy policies. Sent2Vec sentence embedding model was utilized and trained on 130,000 Android apps privacy policies. The terminology extracted by the sentence embedding model was then compared with the gold standard on a dataset of 564 privacy policies. This work seeks to provide answers to researchers and developers interested in extracting privacy related information from privacy policies using sentence embedding models. In addition, it may help regulators interested in deploying sentence embedding models to check for privacy policies' compliance with the government regulations and to identify points of inconsistencies or violations.
Mobile Application to Practice Fractions through Games for Primary School Children

This paper presents a mobile application that supports the learning process of mathematics for fifth grade students, which specifically focuses on the practice of fractions through a series of different games, such as determining if a fraction is less, greater or equals to another fraction; distributing a pizza in fractions; weighing fractions of watermelons; making equivalent fractions; among others. A comparative analysis of existing mobile applications is provided, which is based on some relevant features, such as the types of operations included, the game modes supported, the interactivity of games, the support for two players in the games, the orientation of the games to fractions, the cost of use, the possibility to drag and drop elements in the games of the mobile application, the orientation to fifth grade students, among others. Given that information and communication technologies and ludic are two elements that can provide benefits when incorporated into the teaching and learning processes, this paper also examines different studies that review the impact of mobile devices for designing effective learning experiences in the field of mathematics, the difference between traditional teaching training and the use of electronic devices, and the use of ludic as a component that could benefit the teaching and learning processes through games or entertainment activities.
Analysis of Screening Tools for Drought Tolerance in Chickpea (Cicer arietinum L.) Genotypes

Background: Chickpea is the third most significant food legume worldwide. While deeper rooting can increase water extraction, as it has been hypothesised for almost three decades. Therefore, understanding the regulation of leaf water losses in plant canopy, first when there is no water limitation and secondly when plants are progressively exposed to water deficit, are likely to be equally critical to roots for achieving high chickpea yield under terminal drought. Present study was carried out with an aim to evaluate the use of physiological traits such as canopy temperature depression (CTD) and chlorophyll content to determine drought tolerance of chickpea genotypes under varying environmental conditions.Methods: Trials were conducted in 2009-2010 and 2010-2011 growing seasons at Gachsaran agricultural research station situated located in south-western of Iran. Chickpea genotypes were planted in two sets (each set had 3 replicates) by using a RCBD under two supplementary irrigation and rain-fed conditions. CTD measurements were made by infrared thermometer which was focused to 10:1 meter and at late morning to early afternoon cloudless periods (11:00 to 13:00 hours). Leaf chlorophyll content was measured at flowering and grain filling stages by using of a Minolta SPAD meter on 5-8 flag leaves per plot.Result: The CTD results in emergence of fifty percent of inflorescence stage and CHL in grain filling stage had high significant differences. The significant and positive correlation of DI, K2STI, Ys, GMP, STI, MP, Yp, K1STI showed that these indices were more effective in identifying high yielding genotypes under both conditions and result showed that CTD and CHL have played important roles to search physiological basis of grain yield of chickpea and CTD and CHL can successfully use as a selection criterions in breeding programs.
Hardening the Channels by Precoder Design in Massive MIMO With Multiple-Antenna Users

In this paper, we investigate the potential of a novel precoder for a massive multiple-input multiple-output (MIMO) system with multiple-antenna users under the influence of both Rayleigh and keyhole channel models. The proposed precoder is based on maximum-ratio processing and aims to enhance the channel hardening effect at the users. This is achieved through dividing each channel vector by its norm square. Closed-form expressions for the achievable spectral efficiency of the conventional and proposed precoders are derived. If modeled with Rayleigh fading, due to the physical hardening property of this channel, a moderate gain in performance is produced by the proposed precoding method, where the highest spectral efficiency gain occurs for a small number of users and user antennas. Under Rayleigh fading, the results also demonstrate that similar performance is returned by increasing the number of users or user antennas. By comparison, the proposed precoder is shown to produce significant performance gains in the keyhole channels under the condition that the system is limited to single-antenna users. Corresponding to this, the results showcase how the performance of massive MIMO under keyhole channels is heavily dependent on increasing the number of served users over user antennas.
An Integrated Robust Design and Robust Control Strategy Using the Genetic Algorithm

Sequential strategies and integrated design and control (IDC) strategies have been developed to optimize engineering systems. Nevertheless, neither of them considers the impact of uncertainty when optimizing system performance. To improve the robustness of the system performance and ensure the systematic optimality, this article proposes an integrated robust design and robust control (IRDRC) strategy for a general engineering system using the genetic algorithm. The proposed IRDRC strategy is applied to a rocket flight attitude control system to test its effectiveness. The results show that the IRDRC strategy outperforms existing sequential strategies and IDC strategies, concerning system-level optimization and system robustness.
Advances of ECG Sensors from Hardware, Software and Format Interoperability Perspectives

It is well-known that cardiovascular disease is one of the major causes of death worldwide nowadays. Electrocardiogram (ECG) sensor is one of the tools commonly used by cardiologists to diagnose and detect signs of heart disease with their patients. Since fast, prompt and accurate interpretation and decision is important in saving the life of patients from sudden heart attack or cardiac arrest, many innovations have been made to ECG sensors. However, the use of traditional ECG sensors is still prevalent in the clinical settings of many medical institutions. This article provides a comprehensive survey on ECG sensors from hardware, software and data format interoperability perspectives. The hardware perspective outlines a general hardware architecture of an ECG sensor along with the description of its hardware components. The software perspective describes various techniques (denoising, machine learning, deep learning, and privacy preservation) and other computer paradigms used in the software development and deployment for ECG sensors. Finally, the format interoperability perspective offers a detailed taxonomy of current ECG formats and the relationship among these formats. The intention is to help researchers towards the development of modern ECG sensors that are suitable and approved for adoption in real clinical settings.
Faraday Spectroscopy of Atoms Confined in a Dark Optical Trap

We demonstrate Faraday spectroscopy with a high duty cycle and sampling rate using atoms confined to a blue-detuned optical trap. Our trap consists of a crossed pair of high-charge-number hollow laser beams, which forms a dark, boxlike potential. We have used this to measure transient magnetic fields in a $500\text{\ensuremath{-}}\ensuremath{\mu}\text{m}$-diameter spot over a 400 ms time window with nearly unit duty cycle at a 500-Hz sampling rate. We use these measurements to quantify and compensate time-varying magnetic fields to $\ensuremath{\approx}10\text{ }$ nT per time sample.
FORMULATION, OPTIMIZATION, CHARACTERIZATION AND IN VIVO ANTI-ULCER ACTIVITY OF ESOMEPRAZOLE MAGNESIUM TRIHYDRATE GASTRORESISTANT MICROSPHERES

Objective: The objective of the present investigation was to prepare gastro-resistant microspheres of esomeprazole magnesium trihydrate (EMT) to prevent its degradation in the acidic environment of the stomach and enhance its bioavailability via intestinal absorption. Methods: EMT loaded gastro-resistant microspheres were prepared using hypromellose acetate succinate (HPMCAS) as the gastro-resistant polymer by ‘non-aqueous solvent evaporation’ technique. A 3-factor 3 level factorial design was used to optimise EMT: HPMCAS ratio, the concentration of Span 80 and stirring speed with respect to percent entrapment efficiency and particle size. Further characterization was carried out using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), In vitro release study and In vivo anti-ulcer activity. Results: Fourier transform infrared ( FTIR) study indicated compatibility between drug and polymer. DSC study revealed that the drug was molecularly dispersed in the polymer. The optimised batch showed 49.63±1.23% drug entrapment and 170.12±3.36 μm particle size. SEM study showed that microspheres were spherical in shape . In vitro drug release study showed only 4.28±1.23% drug release in simulated gastric media in 2 hr and 93.46±1.20% release in simulated intestinal media after 1 hr from the optimised batch. Conclusion: Results of in vitro release studies indicated the gastro-resistant nature of the developed microspheres. In vivo anti-ulcer activity demonstrated that EMT loaded microspheres were able to significantly reduce ethanol-induced ulcer formation in rats’ stomach as compared to the aqueous solution of EMT. So it can be concluded that the developed gastro-resistant microspheres of EMT prevented drug release in the stomach which would lead to a significant improvement in its bioavailability through enhanced intestinal absorption
Impacts of large-scale aquaculture activities on the seawater carbonate system and air-sea CO2 flux in a subtropical mariculture bay, southern China

In this study, the variations of the seawater carbonate system parameters and air−sea CO2 flux (FCO2) of Shen’ao Bay, a typical subtropical aquaculture bay located in China, were investigated in spring 2016 (March to May). Parameters related to the seawater carbonate system and FCO2 were measured monthly in 3 different aquaculture areas (fish, oyster and seaweed) and in a non-culture area near the bay mouth. The results showed that the seawater carbonate system was markedly influenced by the biological processes of the culture species. Total alkalinity was significantly lower in the oyster area compared with the fish and seaweed areas, mainly because of the calcification process of oysters. Dissolved inorganic carbon (DIC) and CO2 partial pressure (pCO2) were highest in the fish area, followed by the oyster and non-culture areas, and lowest in the seaweed area. Oysters and fish can have indirect influences on DIC and pCO2by releasing nutrients, which facilitate the growth of seaweed and phytoplankton and therefore promote photosynthetic CO2 fixation. For these reasons, Shen’ao Bay acts as a potential CO2 sink in spring, with an average FCO2 ranging from −1.2 to −4.8 mmol m −2 d−1. CO2 fixation in the seaweed area was the largest contributor to CO2 flux, accounting for ca. 58% of the total CO2 sink capacity of the entire bay. These results suggest that the carbonate system and FCO2 of Shen’ao Bay were significantly affected by large-scale mariculture activities. A higher CO2 sink capacity could be acquired by extending the culture area of seaweed.