Miracle-dz/UniFAR-FTUs huggingface dataset:
Amiloride , a urokinase-type plasminogen activator receptor ( uTPA ) inhibitor , reduces proteinurea in podocytes

This study examined the mechanism of action of amiloride, a urokinase-type plasminogen activator receptor inhibitor, in lowering proteinuria. Podocytes were resuscitated to allow for their proliferation and were observed for morphological changes. In the in vitro experiment, control, lipopolysaccharide, and lipopolysaccharide + amiloride groups were established. The expression of urokinasetype plasminogen activator receptor (uPAR) in podocytes was detected with a flow cytometer and cell motility was detected with the transwell migration assay. In the in vivo test, the urine protein volume of the model was detected at 24 h using Coomassie brilliant blue staining and the morphological changes of the podocytes were detected with immunofluorescence. The protein expression rate of uPAR in the lipopolysaccharide group was significantly higher than those in the control and lipopolysaccharide + amiloride groups (P < 0.05). The viability of cells in the lipopolysaccharide group was significantly 9519 Amiloride lowers proteinuria in podocytes by uTPA inhibition ©FUNPEC-RP www.funpecrp. com.br Genetics and Molecular Research 14 (3): 9518-9529 (2015) higher than those in the control and lipopolysaccharide + amiloride groups (P < 0.05). Compared with the urine protein level in the control group at 24 h, the level in the lipopolysaccharide group increased significantly (P < 0.05), whereas compared with the urine protein level in the lipopolysaccharide group, the level in the lipopolysaccharide + amiloride group decreased (P < 0.05). uPAR expression was significantly downregulated, and the fusion of the podocyte-specific skelemin synaptopodin on the glomerulus podocytes was significantly decreased in the lipopolysaccharide + amiloride group. These results suggest that amiloride is able to reduce cell motility and thus lower proteinuria by inhibiting the expression of uPAR in podocytes.
Inverter-Side Current Control of Grid-Connected Voltage Source Inverters With LCL Filter Based on Generalized Predictive Control

In this paper, an inverter-side current (ISC) control strategy for grid-connected voltage source inverter with LCL filters is proposed based on a generalized predictive control (GPC) formulation as it has the advantages of fixed switching frequency, a systematic design procedure and low computational complexity. As the GPC strategy is a subtype of continuous-control-set model predictive control strategies, a proper model for controlling the ISC is obtained, showing that a full-order model is preferred to its first-order counterpart. The controller is designed taking into consideration harmonic distortion limits and robustness against filter component variations. To this end, a complete three-wire LCL filter model is obtained and impedance sensitivity to each component variation is analyzed. Finally, its performance is evaluated by means of experimental results and compared with a predictive deadbeat controller.
Special solutions to a compact equation for deep-water gravity waves

Abstract Dyachenko & Zakharov (J. Expl Theor. Phys. Lett., vol. 93, 2011, pp. 701–705) recently derived a compact form of the well-known Zakharov integro-differential equation for the third-order Hamiltonian dynamics of a potential flow of an incompressible, infinitely deep fluid with a free surface. Special travelling wave solutions of this compact equation are numerically constructed using the Petviashvili method. Their stability properties are also investigated. In particular, unstable travelling waves with wedge-type singularities, namely peakons, are numerically discovered. To gain insight into the properties of these singular solutions, we also consider the academic case of a perturbed version of the compact equation, for which analytical peakons with exponential shape are derived. Finally, by means of an accurate Fourier-type spectral scheme it is found that smooth solitary waves appear to collide elastically, suggesting the integrability of the Zakharov equation.
Identification of Emergency Blood Donation Request on Twitter

Social media-based text mining in healthcare has received special attention in recent times due to the enhanced accessibility of social media sites like Twitter. The increasing trend of spreading important information in distress can help patients reach out to prospective blood donors in a time bound manner. However such manual efforts are mostly inefficient due to the limited network of a user. In a novel step to solve this problem, we present an annotated Emergency Blood Donation Request (EBDR) dataset to classify tweets referring to the necessity of urgent blood donation requirement. Additionally, we also present an automated feature-based SVM classification technique that can help selective EBDR tweets reach relevant personals as well as medical authorities. Our experiments also present a quantitative evidence that linguistic along with handcrafted heuristics can act as the most representative set of signals this task with an accuracy of 97.89%.
Upper mantle structure beneath Cameroon from body wave tomography and the origin of the Cameroon Volcanic Line

The origin of the Cameroon Volcanic Line (CVL), a 1600 km long linear volcanic chain without age progression that crosses the ocean‐continent boundary in west‐central Africa, is investigated using body wave tomography. Relative arrival times from teleseismic P and S waves recorded on 32 temporary seismic stations over a 2‐year period were obtained using a multichannel cross‐correlation technique and then inverted for mantle velocity perturbations. The P and S wave models show a tabular low‐velocity anomaly directly beneath the CVL extending to at least 300 km depth, with perturbations of −1.0 to −2.0% for P and −2.0 to −3.0% for S. The S wave velocity variation can be attributed to a 280 K or possibly higher thermal perturbation, if composition and other effects on seismic velocity are negligible. The near vertical sides of the anomaly and its depth extent are not easily explained by models for the origin of the CVL that invoke plumes or decompression melting under reactivated shear zones, but are possibly consistent with a model invoking edge‐flow convection along the northern boundary of the Congo Craton lithosphere. If edge‐flow convection in the sublithospheric upper mantle is combined with lateral flow channeled along a fracture zone beneath the oceanic sector of the CVL, then the oceanic sector can also be explained by flow in the upper mantle deriving from variations in lithospheric thickness.
Solid tumor spheroid formation by temperature-controlled high voltage ultrasound in a multi-well microdevice

In the present work we demonstrate effective 3D growth of human hepatocellular carcinoma (HCC) HepG2 cell spheroids in parallel in a multi-well microdevice actuated with high voltage ultrasound in a temperature-controlled system. We compare the spheroid formation during continuous ultrasound exposure for one week where we formed spheroids in 59% of the wells, with the spheroid formation without ultrasound actuation, where we obtained 0% spheroids. Furthermore, we present an application of the tumor spheroids for investigating natural killer (NK) cells behavior against solid tumors.
Epithelial cell PPARγ contributes to normal lung maturation

Peroxisome proliferator‐activated receptor (PPAR)‐γ is a member of the nuclear hormone receptor superfamily that can promote cellular differentiation and organ development. PPARγ expression has been reported in a number of pulmonary cell types, including inflammatory, mesenchymal, and epithelial cells. We find that PPARγ is prominently expressed in the airway epithelium in the mouse lung. In an effort to define the physiological role of PPARγ within the lung, we have ablated PPARγ using a novel line of mice capable of specifically targeting the airway epithelium. Airway epithelial cell PPARγ‐targeted mice display enlarged airspaces resulting from insufficient postnatal lung maturation. The increase in airspace size is accompanied by alterations in lung physiology, including increased lung volumes and decreased tissue resistance. Genome‐wide expression profiling reveals a reduction in structural extracellular matrix (ECM) gene expression in conditionally targeted mice, suggesting a disruption in epithelial‐mesenchymal interactions necessary for the establishment of normal lung structure. Expression profiling of airway epithelial cells isolated from conditionally targeted mice indicates PPARγ regulates genes encoding known PPARγ targets, additional lipid metabolism enzymes, and markers of cellular differentiation. These data reveal airway epithelial cell PPARγ is necessary for normal lung structure and function. —Simon, D. M. , Arikan, M. C. , Srisuma, S. , Bhattacharya, S. , Tsai, L. W. , Ingenito, E. P., Gonzalez, F. , Shapiro, S. D. , and Mariani, T. J. Epithelial cell PPARγ contributes to normal lung maturation. FASEB J. 20, E710–E720 (2006)
PARAMETRIC LINK MODELS FOR KNOWLEDGE TRANSFER IN STATISTICAL LEARNING

When a statistical model is designed in a prediction purpose, a major assumption is the absence of evolution in the modeled phenomenon between the training and the prediction stages. Thus, training and future data must be in the same feature space and must have the same distribution. Unfortunately, this assumption turns out to be often false in real-world applications. For instance, biological motivations could lead to classify individuals from a given species when only individuals from another species are available for training. In regression, we would sometimes use a predictive model for data having not exactly the same distribution that the training data used for estimating the model. This chapter presents techniques for transfering a statistical model estimated from a source population to a target population. Three tasks of statistical learning are considered: Probabilistic classification (parametric and semi-parametric), linear regression (includingmixture of regressions) and model-based clustering (Gaussian and Student). In each situation, the knowledge transfer is carried out by introducing parametric links between both populations. The use of such transfer techniques would improve the performance of learning by avoiding much expensive data labeling efforts.
An overview on the seismic design of braced frames

Seismic design of steel braced frames in the modern building codes follow the capacity design approach where some of the members are obliged to dissipate energy whereas others are taken care to be protected. In this paper the seismic design methodologies used by European and American approaches for Concentric Cross Braced Frames (CCBF) and Eccentric Braced Frames (EBF) are highlighted. Synoptic tables for the design of such frames of the most advance seismic codes i.e., Eurocode 8 and the seismic provisions of American Institute of Steel Construction (AISC) are provided. Emphasizes are made on the provisions of Eurocode 8 both for CCBF and EBF. Finally, a general conclusion is drawn when dealing with CCBF and EBF
Volumetric BitWise Memories

Three-dimensional (3D) optical memory is a revolutionary technology that has the benefits of lower cost (tens of dollars/Gbit), low risk, and an order of magnitude smaller size and mass. Our research centers on a 3D optical memory device based on a new class of light-absorbing (photochromic) compounds that absorb photons two at a time when pulsed with a high-power laser, triggering chemical and physical changes with micrometer-sized resolution in three dimensions. We describe progress on media characterization at elevated temperatures and estimation of media performance based on modeling and experiment. We also describe an advanced test stand for recording and reading 2-photon media, featuring a compact design and a novel tracking servo system.
Patterns of entropy production in dissolving natural porous media with flowing fluid

The tendency for irreversible processes to generate entropy is the ultimate driving force for structure evolution in nature. In engineering, entropy production is often used as an indicator for loss of usable energy. In this study, we show that the analysis of entropy production patterns can provide insight into the diverse observations from experiments that investigate porous medium dissolution in imposed flow field. We first present a numerical scheme for the analysis of entropy production in dissolving porous media. Our scheme uses a greyscale digital model for chalk (an extremely fine grained rock), that was obtained using X-ray nanotomography. Greyscale models preserve structural heterogeneities with very high fidelity. We focussed on the coupling between two types of entropy production: the percolative entropy, generated by dissipating the kinetic energy of fluid flow, and the reactive entropy, originating from the consumption of chemical free energy. Their temporal patterns pinpoint three stages of microstructural evolution. We then showed that local mixing deteriorates fluid channelisation by reducing local variations of reactant concentration. We also showed that microstructural evolution can be sensitive to the initial transport heterogeneities, when the macroscopic flowrate is low. This dependence on flowrate indicates the need to resolve the structural features of a porous system when fluid residence time is long.
Exploring a Topical Representation of Documents for Recommendation Systems

In this paper, we address the performance problems inherited when we use word embedding for recommendation. Free-text documents has no structural constructing rules, and are hard to model. Hence, the problem of having an accurate model, that conveys all the important information is a nontrivial problem. We convert the document to a numeric structure using word-embedding and test two document representations: one based in the center of this numeric representation and the other one based on pre-defined set of topics. We build a free text recommendation system and study how the performance, in terms of precision and recommendation time, is affected by both representations. We then vary the number of topics used to represent documents and verify the tradeoffs inherited from having a compact representation. The more compact the recommendation, the shorter the recommendation time, however more information is lost in the compactation process. We empirically test different possibilities for the topics and find an optimal point that is 3 times faster than a baseline and almost as accurate as it.
IN VITRO NITRIC OXIDE SCAVENGING AND ANTI INFLAMMATORY ACTIVITIES OF DIFFERENT SOLVENT EXTRACTS OF VARIOUS PARTS OF Musa paradisiaca

Inflammatory diseases are an important health concern, and the growing rate is on the rise. Finding a safe drug for these diseases remains an important issue. The study aimed to determine the nitric oxide (NO) scavenging as well as anti-inflammatory activities of Musa paradisiaca (banana). Musa paradisiaca plant parts used in this study namely tepal, skin (peel) and flesh (pulp) were extracted with methanol (tepal, flesh and skin), ethanol (tepal) and water (tepal) using cold maceration technique. Phytochemicals screening of the extracts was carried out. The ability of the extracts to scavenge NO radical was evaluated using Griess reagent. The anti-inflammatory activity of the extracts was assessed by evaluating the ability of the extract to inhibit RAW 264.7 macrophage cell line from generating harmful NO induced by bacterial lipopolysaccharide (LPS). In order to determine the toxicity of the extracts to the cells while exerting its anti-inflammatory activity,cytotoxicity was measured using MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay.The extract was found to contain bioactive chemicals like flavonoids, saponins, phenols, etc. Maximum NO radical inhibition of 41.05% was recorded in the tepal aqueous extract, and minimum inhibition of 22.34% was recorded in the flesh extract. All others showed mild inhibition as well. Flesh extract has the highest NO (generated by LP) inhibitory activity, with the maximum inhibition of 52.21% at 250 µg/mL, followed by tepal aqueous extract with maximum inhibition of 48.16% at 62.5 μg/mL. The least inhibition was noted in the tepal methanol extract that has the maximum inhibition of 19.63% at 62.5 μg/mL. The viability of the activated macrophages was not affected by the extracts as confirmed by the MTT assay, thereby indicating that the inhibition of NO synthesis by the extracts was not due to cytotoxic effects. Overall, Musa paradisiaca plant parts have the potential as anti-inflammatory and studies in this aspect should be intensified.
Recursive Least Squares Filtering Algorithms for On-Line Viscoelastic Characterization of Biosamples

The mechanical characterization of biological samples is a fundamental issue in biology and related fields, such as tissue and cell mechanics, regenerative medicine and diagnosis of diseases. In this paper, a novel approach for the identification of the stiffness and damping coefficients of biosamples is introduced. According to the proposed method, a MEMS-based microgripper in operational condition is used as a measurement tool. The mechanical model describing the dynamics of the gripper-sample system considers the pseudo-rigid body model for the microgripper, and the Kelvin–Voigt constitutive law of viscoelasticity for the sample. Then, two algorithms based on recursive least square (RLS) methods are implemented for the estimation of the mechanical coefficients, that are the forgetting factor based RLS and the normalised gradient based RLS algorithms. Numerical simulations are performed to verify the effectiveness of the proposed approach. Results confirm the feasibility of the method that enables the ability to perform simultaneously two tasks: sample manipulation and parameters identification.
Electron scattering from molecules and molecular aggregates of biological relevance

In this Topical Review we survey the current state of the art in the study of low energy electron collisions with biologically relevant molecules and molecular clusters. We briefly describe the methods and techniques used in the investigation of these processes and summarise the results obtained so far for DNA constituents and their model compounds, amino acids, peptides and other biomolecules. The applications of the data obtained is briefly described as well as future required developments.
Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network

In this paper we present our system for the FEVER Challenge. The task of this challenge is to verify claims by extracting information from Wikipedia. Our system has two parts. In the first part it performs a search for candidate sentences by treating the claims as query. In the second part it filters out noise from these candidates and uses the remaining ones to decide whether they support or refute or entail not enough information to verify the claim. We show that this system achieves a FEVER score of 0.3927 on the FEVER shared task development data set which is a 25.5% improvement over the baseline score.
Improved Traffic Prediction by Applying KNN and Euclidean Distance ARIMA (Ke-Arima) Approach

In the modern era, the road infrastructure failed to cope up with the exponential increase of road traffic. There is a thrust to find a smarter way to deal with such transportation system. Intelligent Transport System is at the forefront edge of this, one of the points is exact and hassle-free forecasts that guarantee smooth and bother free driving and authoritative experience. In such manner, Intelligent Transport System (ITS) being looked into for quite a few years and furthermore a field of consistent growth of works and advancement after some time, there is a wealth of writing on traffic expectation. Traffic datasets generated through the application of IOT are operated upon by the existing techniques. Traffic flow analysis is conducted to tackle the issues of traffic forecasting. This paper presents a systematic analysis of previous aggregate work on traffic prediction, highlight the marked changes and presents future directions for research work.
Undergraduate’s Perception on Massive Open Online Course (MOOC) Learning to Foster Employability Skills and Enhance Learning Experience

The Massive Open Online Course (MOOC) is a very recent development in higher education institutions in Malaysia. As in September 2015, Universiti Teknikal Malaysia Melaka (UTeM) has introduced Mandarin course under Malaysia MOOCs. The study has focused on undergraduate’s perception of MOOC in Mandarin subject in fostering their employability skills as a research variable. The researcher used qualitative and quantitative method as a research design. An interview was used to investigate their perception of MOOC in Mandarin subject to foster their employability skills. An online survey was also conducted to investigate the effectiveness of MOOC learning. Undergraduates in UTeM were selected as the respondents of this study. The findings show that among all the employability skill, students believe Mandarin Massive online learning course fosters two employability skills which are ‘information gaining skill’ and ‘system and technology skill’. This study on MOOCs is important for the decision-making of the government and relevant institution to make sound decisions. This research is also significant for its contribution towards teaching practices in higher education institution.
Friendship: A hidden form of gender in business organizations

This thesis reviews the concept of friendship and contributes to discussion on gender and equality in business organizations by addressing friendship as a gendered concept that plays a part in maintaining gendered hierarchies in business organizations. By drawing on social psychology, sociology and philosophy, a greater, more inclusive understanding of the concept of friendship is gained to include investigating the whole phenomenon of friendship from negative acts and exclusion to the marking of social boundary as well as understanding friendship as a gendered concept that makes masculine, contextual friendships invisible in the organizational setting. It is concluded that to the extent that gender is a meaningful category to a person or other people, it will continue to be a significant dimension of similarity in structuring friendships in organizations, yet the category around which contextual, masculine, friendships are formed in organizations is not necessarily dependent on gender. It is suggested that contextual, inclusive friendships should be encouraged to be formed around membership to a given organization or department instead of gender category.