Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin D supplementation for patients with alopecia areata: A protocol for systematic review and meta-analysis

Background: Several studies have reported an association between low Vitamin D (VD) levels and Alopecia areata (AA), and suggested VD preparations as a potential therapy. VD has immunomodulatory function closely associated with a variety of skin diseases, but there is no conclusive evidence to support VD supplementation for patients with AA. Therefore, we will conduct a meta-analysis to collect and evaluate the efficacy and safety of VD supplementation in the treatment of AA. Methods: We will search the following databases according to the developed strategy: Cochrane Library, PubMed, Web of Science, EMBASE, Scopus, Google scholar for Randomized controlled trials related to VD supplementation for AA. The retrieval time is from the establishment of each database to July 2022. Two reviewers will independently complete the literature search and screening, risk of bias assessment and data extraction. Severity of Alopecia Tool, Alopecia Density and Extent, Lesional area and senstivity (score) will be the primary results. RevMan V.5. 3 will be used for data analysis and synthesis. For dichotomous outcomes and the continuous outcomes, we will calculate risk ratio with 95% Confidence intervals and mean differences or standardized mean differences with 95% Confidence intervals respectively. The reporting bias will be investigated using funnel plots, and the asymmetry of the funnel plots will be explained using the Harbord modified test or the Egger’s regression test. Results: The results of the study expect to provide a high-quality, evidence-based recommendation on VD supplementation in the treatment of AA for clinicians. Conclusions: The study will provide scientific and useful evidence for better use of VD supplementation in treating AA.
The effect of vibration training on delayed muscle soreness: A meta-analysis

Background: Delayed onset muscle soreness (DOMS) is caused by unaccustomed exercise, especially eccentric exercise, and is highly likely to cause skeletal muscle injury. It mainly manifests as ultrastructural changes in skeletal muscle, as well as decreased muscle strength, muscle soreness, swelling, and elevated levels of creatine kinase (CK). Vibration training (VT) has been attracting increasing attention as a new type of rehabilitation therapy. It can effectively minimize the occurrence and relieve the symptoms of DOMS, reduce muscle stiffness and soreness, and reduce serum concentrations of CK and lactate dehydrogenase (LDH). This article systematically assessed the impact of VT on the mitigation of DOMS through a meta-analysis to provide updated evidence-based information. Methods: Electronic databases such as China Knowledge Network, VIP Electronics, PubMed, EBSCO, and Web of Science were searched to identify randomized controlled trials of VT on DOMS. Searches were performed from database creation to November 2021. The quality of the literature was assessed using the Cochrane Manual for the Systematic Review of Interventions, and meta-analyses were performed using RevMan 5.4 software. Results: VT intervention in DOMS was shown to effectively reduce subjective pain, improve pain tolerance, and accelerate the reduction of serum CK and LDH concentrations. Subgroup analysis of different test time periods showed that subjective pain decreased more significantly after 48 hours than after the other 2 time periods, and pain tolerance increased more significantly after 72 hours than the other 2 time periods; serum CK was significantly increased after 24 and 48 hours of intervention, but showed no significant change compared with the control group after 72 hours. Serum LDH decreased significantly after 24 hours of intervention, but there was no significant difference compared with the control group after 48 hours or 72 hours. Conclusion: VT effectively reduced the subjective pain sensation after DOMS, increased the pain threshold, reduced serum LDH and CK concentrations, and accelerated muscle damage repair compared with control interventions. However, the effect of improving the range of motion of the joints is not clear and should be studied further. Registration number: INPLASY2021120115.
Large-scale structure in brane-induced gravity. II. Numerical simulations

We use N-body simulations to study the nonlinear structure formation in brane-induced gravity, developing a new method that requires alternate use of Fast Fourier Transforms and relaxation. This enables us to compute the nonlinear matter power spectrum and bispectrum, the halo mass function, and the halo bias. From the simulation results, we confirm the expectations based on analytic arguments that the Vainshtein mechanism does operate as anticipated, with the density power spectrum approaching that of standard gravity within a modified background evolution in the nonlinear regime. The transition is very broad and there is no well defined Vainshtein scale, but roughly this corresponds to k{sub *}{approx_equal}2h Mpc{sup -1} at redshift z=1 and k{sub *}{approx_equal}1h Mpc{sup -1} at z=0. We checked that while extrinsic curvature fluctuations go nonlinear, and the dynamics of the brane-bending mode C receives important nonlinear corrections, this mode does get suppressed compared to density perturbations, effectively decoupling from the standard gravity sector. At the same time, there is no violation of the weak field limit for metric perturbations associated with C. We find good agreement between our measurements and the predictions for the nonlinear power spectrum presented in paper I, that rely on a renormalization of themore » linear spectrum due to nonlinearities in the modified gravity sector. A similar prediction for the mass function shows the right trends. Our simulations also confirm the induced change in the bispectrum configuration dependence predicted in paper I. « less
Management and treatment of ankle sprain according to clinical practice guidelines: A PRISMA systematic review

Background: The lateral sprain of the ankle is a very frequent injury in the population in general, appearing in the emergency services frequently. The general objective was to review the current clinical practice guidelines (CPGs) on management and treatment of ankle sprains, assess their quality, analyze the levels of evidence and summarize the grades of recommendation. Methods: A systematic search of the literature in relevant databases with the search terms “ankle,” “sprain,” “practice guideline,” and “guideline” was carried out. There were included those guidelines that had the system of grades of recommendation and level of evidence concerning to management and treatment of ankle sprain. The quality of the guides was assessed using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. Results: Seven clinical practice guides were included in this review. The AGREE II scores ranged from 42% to 100%, with only six CPGs explicitly declaring the use of a systematic methodology. Seventeen recommendations were extracted and summarized. Discussion: Six of the recommendations analyzed present enough evidence to be applied in clinical practice and are highly recommended for ankle sprain management: Ottawa rules, manual therapy, cryotherapy, functional supports, early ambulation, short term NSAIDs and rehabilitation.
Improved Astrometry and Photometry for the Luyten Catalog. I. Bright Stars

We outline the construction of a refined version of the New Luyten Two-Tenths (NLTT) catalog of high proper motion stars, which will contain improved astrometry and photometry for the vast majority of the ~59,000 stars in NLTT. The bright end is constructed by matching NLTT stars to Hipparcos, Tycho-2, and Starnet; the faint end by matching to USNO-A and the Two Micron All Sky Survey (2MASS). In this first paper, we detail the bright-end matching procedure. We show that for the majority of stars in his catalog, Luyten measured positions accurate to 1'' even though he recorded his results much more coarsely. However, there is a long tail of position errors, with one error as large as 11°. Proper-motion errors for the stars with small position errors are 24 mas yr-1 (1 σ) but deteriorate to 34 mas yr-1 for stars with inferior positions. NLTT is virtually 100% complete for V ≲ 11.5 and |b| > 15°, but completeness in this magnitude range falls to ~75% at the Galactic plane. Incompleteness near the plane is not uniform, but is rather concentrated in the interval -80° < l < 20°, where the Milky Way is brightest.
Continuous Modulated Shearlet Transform (Revised).dvi

ABSTRACT. We generalize the well-known transforms such as short-time Fourier transform, wavelet transform and shearlet transform and refer it as Continuous Modulated Shearlet Transform. Important properties like Plancherel formula and inversion formula have been investigated. Uncertainty inequalities associated with this transform are presented. 2010 Mathematics Subject Classification. Primary 43A32; Secondary 43A30; 43A65; 22D10; 22D30.
8 KNOWLEDGE EXTRACTION FROM SCHOLARLY PUBLICATIONS: THE GESIS CONTRIBUTION TO THE RICH CONTEXT COMPETITION

Introduction . 108 Approach, Data and Preprocessing . 109 Dataset Extraction . 111 Research Method Extraction . 114 Research Field Classification . 120 Discussion and Limitations . 122 Conclusion. 124 Acknowledgements . 124 References . 124 Notes . 126
Service scheduling for the EdgeIO platform

With the proliferation of Internet of Things (IoT) and data-intensive and latency-sensitive applications, there was a call for the cloud computing paradigm to evolve so that the processing and collection of data happens closer to the edge or end users, where that data is often generated. This crystallized the idea of cloud computing into a new paradigm called edge computing, which aims to create a continuum from the cloud to the edge of the network to achieve low latency by being closer to users, thus providing a better user experience. In order to leverage the potential benefits that edge computing brings, a sophisticated and efficient strategy for placing services within the edge network is immensely important. Service scheduling is a well-known NP-hard problem that becomes more complex as the number of variables increases. For this purpose, an algorithm has been designed within the scope of this Master’s thesis that, based on the available information about the edge network, finds suitable nodes that can deploy a service with several different requirements on e.g., computational capacity, geographical location and maximum latencies. In this work, an algorithm, namely constraint-aware scheduling algorithm (CASA) is proposed, that finds suitable nodes using information about computational capacity, geographic position, and latencies to users and other nodes in the network. To minimize the additional overhead caused by active network measurements, the algorithm uses a network coordinate system (NCS) that maps the nodes in the network into a 2-dimensional coordinate system in a way, that the Euclidean distance of two nodes approximates the round trip time between them. Based on this, multilateration can be used to determine the position of users that are not an active part of the network coordinate system (NCS) in order to estimate the latencies of edge devices to user groups. Furthermore, a prototype implementation of this algorithm and integration into EdgeIO, a flexible multi-cluster edge orchestration platform, is described. In addition, existing service placement solutions in cloud and edge environments are analyzed and the results of the newly developed scheduling algorithm are evaluated.
A Survey on Grab-cut based Image Segmentation Techniques

In Digital image processing the image Segmentation process plays a vital role to classify different areas in an image There are different kinds of Image Segmentation techniques such as Edge-based, Region-based, Threshold-based, GrabCut based to name a few. In this paper, a comparative study is done on different GrabCut based Image Segmentation Techniques such as (a). CIE color spaces, (b). Deep Convolutional Neural Networks, (c). Local Prior Distribution, (d). Superpixel, and (e). Bayes classification and Simple Linear Iterative Clustering. The scope of this paper is to study, analyze, and list the merits and demerits of these techniques. It will open up more research areas in this topic for better Image Segmentation results.
Tolerate Silent Data Errors with Coded Computation

—While hyper-scale data centers are reporting a growing number of Silent Data Errors (SDEs), existing techniques alone are still insufficient to build an SDE-resilient system. In this work, we propose the adoption of Coded Computation to mitigate SDE computation errors efficiently. Based upon error correcting codes (ECC), which have been proven valuable to the mitigation of SDEs in storage and communication, coded computation performs computations in parallel that are homomorphic to ECC encoding/decoding functions, thus tolerating a configurable amount of computation errors. We first give a motivating example to compare coded computation with traditional triple modular redundancy. Then we introduce state of the art in coded computation, its applications to SDE mitigation mechanisms, and open questions for future work.
New Transfer Learning Approach Based on CNN Network for Fault Diagnosis

: Induction motors operate in difficult environments in the industry. Monitoring the performance of motors in such circumstances is significant which can provide a reliable operation sys-tem. This paper intends to develop a new model for fault diagnosis based on the knowledge of transfer learning using the ImageNet dataset. The development of this framework provides a novel technique for the diagnosis of single and multiple induction motor faults. A transfer learning model based on a VGG-19 convolutional neural network (CNN) is implemented, which provides a quick and fast training process with a higher accuracy. Thermal images with different induction motor conditions are captured with the help of flir camera and applied as inputs to investigate the proposed model. The implementation of this task is to use VGG19 (CNN) based pre-trained network which gives autonomous features learning based on minimum human intervention. Then applying a dense-connected classifier to predict the true class. The experimental results confirm that the robustness and reliability of the developed technique which is successfully able to classify the induction motor faults and achieving a classification accuracy of 99.8%. The use of a VGG19network has allowed the attributes to be automatically extracted and associated with the decision-making part. Furthermore, this model is further compared with other applications based on related topics, it has successfully proved the its superiority and robustness.
Rapid Prototyping of Para�lm ® -based analytical micro�uidic devices using laser ablation and thermal fusion bonding

Parafilm ® is a thermoplastic film extensively used in laboratories for sealing or protecting flasks or cuvettes. In this paper, we report a simple, low-cost, biocompatible and detachable microfluidic chip incorporating easily accessible polymethylmethacrylate (PMMA), PVC and glass slides as the substrate materials, along with Parafilm ® as the bonding material. Multi-layer microfluidic chips can be fabricated by laser ablation followed by thermal fusion of constituent layers. A CO 2 laser ablation method was employed to cut substrates as well as the Parafilm ® to obtain desired patterns. A thermal fusion bonding method was developed to bond the substrates in a single step. The patterned Parafilm ® was sandwiched in the PMMA, PVC or glass layers, and heating of the assembly with the addition of a static pressure, various functional microfluidic elements including microvalves, micropumps, and bioreactors were demonstrated. With Parafilm ® serving as a flexible membrane integrated to a fluidic channel, it was possible to implement a microvalve. A peristaltic micropump consisting of a sequence of interconnected gas-actuated microvalves was also fabricated. In addition, the biocompatibility of the PLT (Parafilm ® based laser ablation and thermal fusion bonding fabrication method) fabricated bioreactor was validated by culturing GFP-expressing E. coli , results showed bacterium were able maintain growth in a 7-day post-cultivation. In summary, the reported fabrication scheme, offers an inexpensive and versatile alternative for rapid prototyping of common microfluidic devices.
The Survey of Nearby Nuclei with the Space Telescope Imaging Spectrograph: Emission-Line Nuclei at Hubble Space Telescope Resolution

We present results from a program of optical spectroscopy for 23 nearby galaxies with emission-line nuclei. This investigation takes advantage of the spatial resolution of the Hubble Space Telescope to study the structure and energetics of the central ~10-20 pc, and the resulting data have value for quantifying central black hole masses, star formation histories, and nebular properties. This paper provides a description of the experimental design, and new findings from the study of emission lines. The sample targets span a range of nebular spectroscopic class, from H II to Seyfert nuclei. This data set and the resulting measurements are unique in terms of the sample size, the range of nebular class, and the investigation of physical scales extending down to parsecs. The line ratios indicative of nebular ionization show only modest variations over order-of-magnitude differences in radius, and demonstrate in a systematic way that geometrical dilution of the radiation field from a central source cannot be assumed as a primary driver of ionization structure. Comparisons between large- and small-aperture measurements for the H II/LINER transition objects provide a new test that challenges conventional wisdom concerning the composite nature of these systems. We also list a number of other quantitative results that are of interest for understanding galaxy nuclei, including (1) the spatial distribution/degree of concentration of Hα emission as a function of nebular type; (2) the radial variation in electron density as a function of nebular type; and (3) quantitative broad Hα estimates obtained at a second epoch for these low-luminosity nuclei. The resulting measurements provide a new basis for comparing the nuclei of other galaxies with that of the Milky Way. We find that the Galactic center is representative across a wide span of properties as a low-luminosity emission-line nucleus.
Resolution IV Designs with 128 Runs

Chen, Sun, and Wu (1993) enumerated all possible 2k-p fractional factorial designs of size 16 and 32 and all resolution four (or higher) fractions of size 64. By enumerating all possible designs, they not only provided the minimum aberration design for each value of k but also listed designs attractive for other reasons, e.g., having the most clear two-factor interactions. Here we present the results of an enumeration of n = 128 run resolution IV designs. As in Chen, Sun, and Wu (1993), we constructed new designs by building up, adding one factor at a time. However, rather than determining whether a new candidate design was isomorphic to an existing design based on a complete permutation check, we retained all designs that differed in their projections. Resolution IV designs are tabulated for k = 12, …, 64 factors.
Statics Analysis of 3-PRS Ankle Rehabilitation Robot

: Aiming at the rehabilitation training of the injured ankle, two prototypes of the ankle rehabilitation robots are proposed and selected and analyzed. Based on the parallel mechanism, two kinds of the 3-PRS ankle rehabilitation robots are designed in the paper. The first structure is that the moving platform is located above and the second structure is that the moving platform is located below. Two kinds of the 3-PRS ankle rehabilitation robots are applied with load, the static simulation under the different moving platform poses is performed and the analysis is carried out according to the static simulation results. The experiment shows that the structure of the 3-PRS ankle rehabilitation robot moving platform located below has higher stability and more reasonable stress analysis.
“ ImposTer : Towards an extensible privacy analysis framework for Smart Home ecosystem”

The IoT ecosystem is an intricate network of stakeholders ( e.g., developers, advertising networks, platform operators) that often exploit data-driven business models. The ability of smart home platforms and devices to interact and exchange personal user data with each other opens potential privacy risks. But proposed black-box approaches to audit IoT platforms lack techniques to automatically and wholistically study their behaviour in rich execution environments where other devices and applications operate. This thesis proposes ImposTer, a cost-effective yet extensible privacy and security analysis framework for exhaustively studying the IoT ecosystem in conjunction with other devices. ImposTer utilizes a suite of analysis techniques to automatically capture and model the horizontal interaction across multiple devices in a consumer household. To this extent, along with multiple smart home devices, traffic interception techniques, and network protocol honeypots, I introduce a highly instrumented smart TV to empirically characterize inter-device communication. Using a dataset of 415 Smart TV applications, we expose information leakage and characterize interconnected nature of the smart home ecosystem, including the presence and interaction of potentially intrusive advertising and tracking services.
GPPS-TC-2022-0008 INVESTIGATION OF IMPLICIT TREATMENT OF THE TIME SPECTRAL SOURCE TERM FOR AN EFFICIENT SOLUTION OF THE TIME DOMAIN HARMONIC BALANCE EQUATION SYSTEMS

The time domain harmonic balance method is an efficient numerical method for analyzing turbomachinery unsteady flow for which unsteady flow frequencies can be known a priori. However, the solution performance of the method degrades dramatically when the maximum frequency of unsteadiness being retained in an analysis increases. Some methods have been proposed to solve or at least alleviate the problem. These methods include the block Jacobi successive symmetric over-relaxation method, the lower upper symmetric Gauss Seidel (LU-SGS) /block Jacobi (BJ) method, the LU-SGS/Jacobian iteration (JI) method and the LU-SGS/Gauss Siedel (GS) method. The paper aims at comparing the LU-SGS/BJ, LU-SGS/JI and LU-SGS/GS methods and propose variants to them. Numerical tests are presented to show the effectiveness of the proposed methods over their original counterparts.
Inverse Policy Evaluation for Value-based Decision Making

Value-based methods for control often involve approximate value iteration (e.g., Q -learning), and behaving greedily with respect to the resulting value estimates with some degree of entropy to ensure the state-space is sufﬁciently explored. Such a greedy policy is an improvement over the policy of which the current values reﬂect. As learning progresses, value-iteration may produce value functions that do not correspond with any policy. This is especially relevant with function-approximation, when the true value function cannot be perfectly represented. This raises questions about what such inaccurate value functions represent, and whether there exists alternative ways to derive value-based behavior. In this work, we explore the use of Inverse Policy Evaluation , the process of solving for a likely policy given a value function. We derive a simple, incremental algorithm for the procedure, analyze how inaccuracies in the value function manifest in the corresponding policy, and provide empirical results emphasizing key properties of the mapping from value functions to policies. This sets up a framework for matching proposed returns , as opposed to explicit maximization. Coupling this procedure with value-iteration, this provides a novel approach for deriving behavior from a value function which also tends toward an optimal policy, but appears to account for estimation error in the resulting behavior.