Miracle-dz/UniFAR-FTUs huggingface dataset:
Coenzyme Q 10 in Combination With Triple Therapy Regimens Ameliorates Oxidative Stress and Lipid Peroxidation in Chronic Gastritis Associated With H . pylori Infection

Chronic gastritis associated with H. pylori infection causes oxidative stress in the stomach. This study aimed to evaluate the therapeutic effects of coenzyme q10 among gastric patients infected by H. pylori. By a clinical trial, chronic gastric patients infected by H. pylori were randomly divided into 2 groups: intervention and placebo. The placebo group received a standard triple therapy regimen, and the intervention group received the triple regimenþ coenzyme Q10 (CoQ10). Mean inflammation score; serum levels of 3 serum markers were then compared. A total of 100 participants of whom 67% were female were evaluated. The mean age of participants was 59.4 11.4 years. The mean inflammation score was considerably decreased at the end of the study, in the intervention group. The mean levels of total antioxidant capacity (TAC) and glutathione peroxidase (GPx) at the end of the study were reduced among the triple therapy group (P< .05, P1⁄4.03 respectively). The mean levels of TAC and GPx were significantly higher among the intervention group at the end of the study compared with those at the start of the study. The combination of triple therapy with CoQ10 demonstrated an effective outcome on the mucosal inflammation, and stress oxidative in patients with chronic gastritis.
IFN-γ AND STAT 1 ARREST MONOCYTE MIGRATION AND MODULATE RAC / CDC 42 PATHWAYS 1

Positive regulation of cell migration by chemotactic factors and downstream signaling pathways has been extensively investigated. In contrast, little is known about factors and mechanisms that induce migration arrest, a process important for retention of cells at inflammatory sites and homeostatic regulation of cell trafficking. In this study we found that IFN-γ directly inhibited monocyte migration by suppressing remodeling of the actin cytoskeleton and cell polarization in response to the chemokine CCL2. Inhibition was dependent on STAT1 and downstream genes, whereas STAT3 promoted migration. IFN-γ did not affect proximal CCL2 signaling, but altered monocyte responses to CCL2 by modulating the activity of the GTPases Rac and Cdc42 and the downstream PAK kinase that regulate the cytoskeleton and cell polarization. These results identify a new role for IFN-γ in arresting monocyte chemotaxis by a mechanism that involves modulation of cytoskeleton remodeling. Crosstalk between Jak-STAT and Rac/Cdc42 GTPase-mediated signaling pathways provides a molecular mechanism by which cytokines can regulate cell migration.
Three-Dimensional ( 3 D ) Trefftz Computational Grains ( TCGs ) for the Micromechanical Modeling of Heterogeneous Media with Coated Spherical Inclusions

Three-dimensional Computational Grains based on the Trefftz Method (TCGs) are developed to directly model the micromechanical behavior of heterogeneous materials with coated spherical inclusions. Each TCG is polyhedral in geometry and contains three phases: an inclusion, coating (or interphase) and the matrix. By satisfying the 3D Navier’s equations exactly, the internal displacement and stress fields within the TCGs are expressed in terms of the Papkovich-Neuber (P-N) solutions, in which spherical harmonics are employed to further express the P-N potentials. Further, the Wachspress coordinates are adopted to represent the polyhedral-surface displacements that are considered as nodal shape functions, in order to enforce the compatibility of deformations between two TCGs. Two techniques are developed to derive the local stiffness matrix of the TCGs: one is directly using the Multi-Field Boundary Variational Principle (MFBVP) while the other is first applying collocation technique for the continuity conditions within and among the grains and then employing a Primal-Field Boundary Variational Principle (PFBVP). The local stress distributions at the interfaces of the 3 phases, as well as the effective homogenized material properties generated by the direct micromechanical simulations using the TCGs, are compared to other available analytical and numerical results, in the literature, and good agreement is always obtained. The material and geometrical parameters of the coatings/interphases are varied to test their influence on the homogenized 25 Mar 2018 06:00:06 PDT Version 1 Submitted to J. Mech. Mater. Struct. and localized interfacial stress responses of the heterogeneous media. Finally, the periodic boundary conditions are applied to the representative volume elements (RVEs) that contain one or more TCGs to model the heterogeneous materials directly.
Enhancement of Primary User Detection in Cognitive Radio by Scattering Transform

The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the misseddetection probability is evaluated and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved on the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysisbased energy detection.
Combining an exoskeleton with 3 D simulation inthe-loop

Beyond robot hardware and control, one major element for an efficient, constructive and safe mission of teleoperated robots in disaster scenarios such as Fukushima is the quality of the connection between operator and robot. In this contribution, we present the concept of using an exoskeleton and utilizing 3D simulation as a central interface component for the operator to intuitively collaborate with mobile teleoperated robots. keywords: 3D simulation, exoskeleton, force feedback, operator interface
Redundancy of Lossless Data Compression for Known Sources by Analytic Methods

The term analytic information theory has been coined to describe problems of information theory studied by analytic tools. The approach of applying tools from analysis of algorithms to problems of source coding and, in general, to information theory lies at the crossroad of computer science and information theory. Combining the tools from both areas often provides powerful results, such as computer scientist Abraham Lempel and information theorist Jacob Ziv working together in the late 1970s to develop compression algorithms that are now widely referred to as Lempel-Ziv algorithms and are the basis of the ZIP compression still used extensively in computing today. This monograph surveys the use of these techniques for the rigorous analysis of code redundancy for known sources in lossless data compression. A separate chapter is devoted to precise analyses of each of three types of lossless data compression schemes, namely fixed-to-variable length codes, variable-to-fixed length codes, and variable-to-variable length codes. Each one of these schemes is described in detail, building upon work done in the latter part of the 20th century to present new and powerful techniques. For the first time, this survey presents redundancy for universal variable-to-fixed and variable-to-variable length codes in a comprehensive and coherent manner. The monograph will be of interest to computer scientists and information theorists working on modern coding techniques. Written by two leading experts, it provides the reader with a unique, succinct starting point for their own research into the area.
Design Principles of Routing Protocols in Wireless Sensor Networks

There have been proposed multiple surveys on wireless senso r network routing in the past. However, they use rough operational and network models to classify routing protocols as well as disregard works which are not routing protocols but rather function as separate routing m odules. Moreover, dependability concepts of sensor network routing have not b een addressed by them. In this work, we attempt to factor out the main design pri ciples for sensor network routing, as well as to identify the most im portant dependability concepts in this context. We propose a modular appro ach to design a routing protocol for sensor network applications. We gathe r mainstream implementations of each module to aid this development proc ess.
Distribution characteristic and combined optimization of maximum cogging torque of surface mounted few slots permanent-magnet machines

This paper examines the maximum cogging torque (MCT) distribution characteristic of surface mounted few slots permanent magnet (SMFSPM) machines. The MCT distributions of SMFSPM machines with different pole-arc coefficients and different ratios of slot opening to slot-pitch are firstly analyzed based on the analytical Fourier series analysis with Maxwell stress tensor method and the finite element method (FEM), respectively. Right triangle distribution regions of the optimal MCT are determined by comparing the MCT distribution contour maps calculated by the two methods. Finally, a combined MCT optimization method for SMFSPM machines is proposed to result in a substantial saving in the optimization time.
The Green Solow model Author ( s ) :

We argue that a key empirical finding in environmental economics the Environmental Kuznets Curve (EKC) and the core model of modern macroeconomics the Solow model are intimately related. Once we amend the Solow model to incorporate technological progress in abatement, the EKC is a necessary by product of convergence to a sustainable growth path. We explain why current methods for estimating an EKC are likely to fail; provide an alternative empirical method directly tied to our theory; and estimate our model on carbon emissions from 173 countries over the 1960-1998 period.
Reconstructing Historical Water Quality in Minnesota Lakes from Fossil Diatoms

Diatom reconstructions of historical phosphorus concentration, based on sediment cores from 79 Minnesota lakes, provide a unique opportunity for examining temporal and spatial trends in eutrophication, validating eutrophication models, and providing historical perspective for developing water quality standards. There have been numerous diatombased water quality reconstruction studies in Minnesota that focused on individual lakes, paired comparisons, or a few lakes representing different regions or degrees of anthropogenic influence. However, no previous study used sediment diatoms to assess spatial and temporal changes in trophic status across a wide geographic range of Minnesota lakes.
Interpretable Matrix Factorization with Stochastic Nonnegative DEDICOM

Decomposition into Directed Components (DEDICOM) is a special matrix factorization technique to factorize a given asymmetric similarity matrix into a combination of a loading matrix describing the latent structures in the data and an asymmetric aﬃnity matrix encoding the relationships between the found latent structures. Finding DEDI-COM factors can be cast as a matrix norm minimization problem that requires alternating least square updates to ﬁnd appropriate factors. Yet, due to the way DEDICOM reconstructs the data, unconstrained factors might yield results that are diﬃcult to interpret. In this paper we derive a projection-free gradient descent based alternating least squares algorithm to calculate constrained DEDICOM factors. Our algorithm constrains the loading matrix to be column-stochastic and the aﬃnity matrix to be nonnegative for more interpretable low rank representations. Additionally, unlike most of the available approximate solutions for ﬁnding the loading matrix, our approach takes the entire occurrences of the loading matrix into account to assure convergence. We evaluate our algorithm on a behavioral dataset containing pairwise asymmetric associations between variety of game titles from an online platform.
GHGT-12 Targeted Pressure Management during CO 2 Sequestration : Optimization of Well Placement and Brine Extraction

Large-scale pressure increases resulting from carbon dioxide (CO2) injection in the subsurface can potentially impact caprock integrity, induce reactivation of critically stressed faults, and drive CO2 or brine through conductive features into shallow groundwater. Pressure management involving the extraction of native fluids from storage formations can be used to minimize pressure increases while maximizing CO2 storage. However, brine extraction requires pumping, transportation, possibly treatment, and disposal of substantial volumes of extracted brackish or saline water, all of which can be technically challenging and expensive. This paper describes a constrained differential evolution (CDE) algorithm for optimal well placement and injection/ extraction control with the goal of minimizing brine extraction while achieving predefined pressure contraints. The CDE methodology was tested for a simple optimization problem whose solution can be partially obtained with a gradient-based optimization methodology. The CDE successfully estimated the true global optimum for both extraction well location and extraction rate, needed for the test problem. A more complex example application of the developed strategy was also presented for a hypothetical CO2 storage scenario in a heterogeneous reservoir consisting of a critically stressed fault nearby an injection zone. Through the CDE optimization algorithm coupled to a numerical vertically-averaged reservoir model, we successfully estimated optimal rates and locations for CO2 injection and brine extraction wells while simultaneously satisfying multiple pressure buildup constraints to avoid fault activation and caprock fracturing. The study shows that the CDE methodology is a very promising tool to solve also other optimization problems related to GCS, such as reducing ‘Area of Review’, monitoring design, reducing risk of leakage and increasing storage capacity and trapping. © 2013 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of GHGT.
Alcohol Ban and Crime: The ABC's of the Bihar Prohibition

While alcohol regulation policies may help control crime, the eﬀects of such policies are highly dynamic and may be diﬃcult to understand using the annual crime data normally available in developing countries. We use district-level monthly crime data from the Indian states of Bihar and Jharkhand and a diﬀerence-in-diﬀerences reasearch design to provide evidence that a prohibition imposed in Bihar led to a 0.21 standard deviation reduction in the incidence of violent crimes but had no signiﬁcant impact on non-violent crimes. These results illustrate the idea that intoxication may reduce risk aversion, thereby increasing the probability of committing a violent crime. Our results are concentrated in areas where the ban may have had a larger impact - due to either higher alcoholism at the baseline or where the ban may be easier to implement - and are robust to a number of alternate speciﬁcations, including the use of a synthetic control group.
Pothole Detection with Image Processing and Spectral Clustering

Pothole detection is one of the important tasks for the proper planning of repairs and rehabilitation of the asphalt-surfaced pavements. Pothole repair is necessary in those situations where potholes compromise safety and pavement ride-ability. Existing methods for detection and estimation of potholes usually use sophisticated equipment and impose computationally intensive tasks. In this paper, we present a new unsupervised vision-based method, which does not require expensive equipment, additional filtering and training phase. Our method deploys image processing and spectral clustering for identification and rough estimation of potholes. Spectral clustering is used for identification of regions with histogram-based data from gray-scaled image. Based on these results, we identify potholes and estimate their surface. Method is tested on images with different pothole shapes and the results show that this method estimates potholes with reasonable accuracy. Key–Words: Pothole detection, Unsupervised method, Spectral clustering, Image processing, Image segmentation, Vision-based approach
MicroRNA-34 a Inhibits Uveal Melanoma Cell Proliferation and Migration through Downregulation of c -

METHODS. Northern blot analysis was performed to detect the expression level of miR-34a in uveal melanoma cells and melanocytes. Subsequently, melanoma cell proliferation and migration were examined by MTS cell proliferation and transwell migration assays, respectively. The target of miR-34a was predicted by bioinformatics and confirmed using a luciferase assay. In addition, expression of c-Met and cell cycle-related proteins was determined by Western blotting and immunofluorescence after the introduction of miR-34a.
Running Head : Critically Assessing Forms of Resistance Oxford Handbook of Philosophical and Qualitative Perspectives on Assessment in Music Education

In their classrooms, music educators draw upon critical pedagogy (as described by Freire, Giroux, and hooks) for the express purpose of cultivating a climate for conscientização. Conscientização, according to Paulo Freire (2006), “refers to learning to perceive social, political, and economic contradictions and to take action against the oppressive elements of reality” (p. 35). This consciousness raising is a journey teachers pursue with students, together interrogating injustices in communities and the world in order to transform the conditions that inform them. Learning to perceive social, political, and economic contradictions often leads to multiple forms of resistance in and out of music classrooms. This chapter explores the following question: What do critical forms of assessment look like in music classrooms that use critical pedagogy and embrace resistance to foster conscientization?
Schema Mapping and Record Matching are two necessary steps in merging Article , Shvaiko , P . , Euzenat , J . : A survey of schema-based matching approaches

Creating a Mediated Schema Based on Initial Correspondences. IEEE Data Eng. Bull. A survey of approaches to automatic schema matching. VLDB J. 10(4):. Many approaches to ontology matching have been proposed: the Shvaiko, P. and Euzenat, J.: A survey of schema-based matching approaches. Journal. process and moreover, the outcome of these approaches is a single integrated schema. get schema, based on a set of correspondences between their attributes. From the also infer correspondences using schema matching techniques (9). For simplicity, we A survey of approaches to automatic schema matching.
Breaking the endosymbiont-organelle border : the case of Paulinella chromatophora

Primary endosymbiosis gave rise to photosynthetic eukaryotes (glaucophytes, red algae and green plants) about 1.5 billion years ago, when a phagotrophic eukaryote enslaved a cyanobacterium, transforming it into a true cellular organelle called primary plastid. Such cyanobacterium-to-organelle transformation had been considered to be a singular event in the history of life on our planet until Paulinella chromatophora was discovered. This testate amoeba carries two photosynthetic endosymbionts (chromatophores) of cyanobacterial origin, which were acquired relatively recently, about 60-140 million years ago. The chromatophores have already experienced a significant genome reduction, endosymbiotic gene transfer of more than 30 genes, including those involved in photosynthesis, and evolved import machinery for nuclear-encoded proteins. These features make the chromatophores bona fide organelles but, in contrast to primary plastids, they import only proteins characterised by low molecular weight and nearly neutral charge. These restrictions in the protein import seem to result from the presence of the peptidoglycan wall and the lack of a channel-like translocon in the outer chromatophore membrane, which could perforate this wall together with a channel in the inner membrane.
Blind Estimation of Spreading Sequence based on the Wide Window and PAST Algorithm

The problem of blind estimation of spreading sequence is an important aspect in the context of spectrum surveillance, which the pseudo-random sequence used by the transmitter is unknown. In this paper, the approach of the spreading sequence recovery is proposed by using projection approximation subspace tracking (PAST) method and sliding window technique, when the received signal is sampled and divided into temporal windows, the size of which is double the pseudorandom sequence period. The calculation of the main eigenvector is only needed, and sliding window technique is used to realize the spreading sequence synchronization. The PAST method avoids the calculation of eigenvalue decomposition, the main way is to obtain the convergence weights in an iterative method. Therefore, it is easy to realize in hardware and has less computational cost. Experimental results show that the proposed method eliminates the problem of phase ambiguity and can provide a good estimation, even when the received signal is far below the noise level. Keywords—spreading sequence; subspace tracking; sliding window; phase ambiguity; blind estimation
A Review on Multilevel Inverter Topologies and Modulation Techniques

Multilevel inverters have been drawing attention in the recent years especially in the distributed energy resources area due to the fact that various batteries and solar cell can be connected through multilevel inverter to feed a load or the ac grid. Multilevel inverter becomes an alternative in the area of highpower medium-voltage energy control. Hence, Harmonic mitigation in multi-level inverters are to be considered very important task nowadays. For eliminating the harmonics lot of researchers have suggested modifications in the circuit topology and optimal selection of firing angle using various types of optimization algorithms. This paper discusses a review application by different optimization techniques for harmonic mitigation in multilevel inverters. Finally the investigation on various multilevel inverter topologies, methods of elimination of harmonics and conclusion has also been discussed.
Language learning using Speech to Image retrieval

Humans learn language by interaction with their environment and listening to other humans. It should also be possible for computational models to learn language directly from speech but so far most approaches require text. We improve on existing neural network approaches to create visually grounded embeddings for spoken utterances. Using a combination of a multi-layer GRU, importance sampling, cyclic learning rates, ensembling and vectorial self-attention our results show a remarkable increase in image-caption retrieval performance over previous work. Furthermore, we investigate which layers in the model learn to recognise words in the input. We find that deeper network layers are better at encoding word presence, although the final layer has slightly lower performance. This shows that our visually grounded sentence encoder learns to recognise words from the input even though it is not explicitly trained for word recognition.