Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-term effects of atorvastatin on hemorheologic parameters and endothelial dysfunction in patients with hypercholesterolemia. Lower is better?

We have read with interest the paper published recently by Uyuklu et al. in Clinical Hemorheology and Microcirculation [5]. It provides important experimental information on the effect of high dose atorvastatin on erythrocyte mechanical properties. Numerous randomized trials confirmed the benefit of cholesterol-lowering therapy in patients with atherosclerotic cardiovascular diseases (ASCVD). In high-risk persons, the recommended LDL-C goal now is <100 mg/dl, but a question raised by HPS and PROVE IT studies is whether this goal is sufficiently low in very high-risk patients who already have relatively low LDL cholesterol at baseline. In HPS the subgroup whose LDL-C levels at baseline were <100 mg/dl exhibited significant risk reduction when statin therapy was introduced [3]. In PROVE IT, intensive LDL-C-lowering therapy with high dose atorvastatin reduced major cardiovascular events as compared with standard-dose pravastatin [1]. Based on the available clinical trial evidence, an LDL-C goal of <70 mg/dl is a reasonable clinical strategy when risk is very high [2]. Since cholesterol is one of the basic elements of the cell membranes, Uyuklu et al. addressed the question, whether lowering of cholesterol beyond a certain level – with supra-pharmacological dose of atorvastatin – may cause significant alterations in red blood cell (RBC) deformability. In their study they found no adverse rheological change, despite significant structural and functional alterations of the RBC membrane.
The Mu 3 e Experiment at PSI

Mu3e will search for charged Lepton Flavor Violation in the neutrinoless muon decay μ+ → e+e−e+ with a sensitivity down to 10−16 (90% C.L.) using the world most intense continuous muon beam at PSI. This search requires a large acceptance detector capable of coping with rates of up to 2×109 stopped muons per second with excellent momentum, spatial, and time resolution. The Mu3e detector is based on thin monolithic active silicon pixel sensors for tracking in conjunction with scintillating fibers and tiles for timing measurements. The Mu3e apparatus is under constructions and first data is expected in 2020. Copyright A. Bravar et al. This work is licensed under the Creative Commons Attribution 4.0 International License. Published by the SciPost Foundation. Received 19-11-2018
High-Order Contact-Implicit Trajectory Optimization

Robots that dynamically make and break contact with their environment experience discontinuities in their state trajectories and dynamics. Traditional planning algorithms have modeled these discontinuities using a hybrid systems formulation, where each contact state is assigned a mode and impacts are handled via mode transitions. However, enumerating all possible modes for robots with many contact surfaces is computationally intractable. In contrast, contact-implicit trajectory optimization methods have been used to generate contact sequences as part of the trajectory optimization problem without explicit enumeration of modes [1]. Unfortunately, these methods are currently limited to first-order integration accuracy, which negatively affects tracking performance [2]. We propose a new family of contact-implicit trajectory optimization methods that combine ideas from discrete mechanics and complementarity formulations of rigid-body contact to achieve any desired order of integration accuracy. Several simulated examples will be given using a third-order method.
Cross-modal Knowledge Transfer: Improving the Word Embedding of Apple by Looking at Oranges

Capturing knowledge via learned latent vector representations of words, images and knowledge graph (KG) entities has shown state-of-the-art performance in computer vision, computational linguistics and KG tasks. Recent results demonstrate that the learning of such representations across modalities can be beneficial, since each modality captures complementary information. However, those approaches are limited to concepts with cross-modal alignments in the training data which are only available for just a few concepts. Especially for visual objects exist far fewer embeddings than for words or KG entities. We investigate whether a word embedding (e.g., for "apple") can still capture information from other modalities even if there is no matching concept within the other modalities (i.e., no images or KG entities of apples but of oranges as pictured in the title analogy). The empirical results of our knowledge transfer approach demonstrate that word embeddings do benefit from extrapolating information across modalities even for concepts that are not represented in the other modalities. Interestingly, this applies most to concrete concepts (e.g., dragonfly) while abstract concepts (e.g., animal) benefit most if aligned concepts are available in the other modalities.
BRIoT: Behavior Rule Specification-Based Misbehavior Detection for IoT-Embedded Cyber-Physical Systems

The identification of vulnerabilities in a mission-critical system is one of the challenges faced by a cyber-physical system (CPS). The incorporation of embedded Internet of Things (IoT) devices makes it tedious to identify vulnerability and difficult to control the service-interruptions and manage the operations losses. Rule-based mechanisms have been considered as a solution in the past. However, rule-based solutions operate on the goodwill of the generated rules and perform assumption-based detection. Such a solution often is far from the actual realization of the IoT runtime performance and can be fooled by zero-day attacks. Thus, this paper takes this issue as motivation and proposes better lightweight behavior rule specification-based misbehavior detection for the IoT-embedded cyber-physical systems (BRIoT). The key concept of our approach is to model a system with which misbehavior of an IoT device manifested as a result of attacks exploiting the vulnerability exposed may be detected through automatic model checking and formal verification, regardless of whether the attack is known or unknown. Automatic model checking and formal verification are achieved through a 2-layer Fuzzy-based hierarchical context-aware aspect-oriented Petri net (HCAPN) model, while effective misbehavior detection to avoid false alarms is achieved through a Barycentric-coordinated-based center of mass calculation method. The proposed approach is verified by an unmanned aerial vehicle (UAV) embedded in a UAV system. The feasibility of the proposed model is demonstrated with high reliability, low operational cost, low false-positives, low false-negatives, and high true positives in comparison with existing rule-based solutions.
Proton magnetic resonance spectroscopic imaging of abnormal gray matter in multiple sclerosis

Proton magnetic resonance spectroscopic imaging (MRSI) of the brain was performed on 53 patients with clinically definite relapsing remitting multiple sclerosis (MS). The contributions of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) to the spectroscopic voxels were determined using either double inversion recovery magnetic resonance imaging or segmentation of affirmative images. In 13 patients additional peaks in the 0.8 to 1.5 ppm spectral region, that reflect the demyelinating products, were observed mainly confined to GM. These studies demonstrate that some of the GM that appears normal on magnetic resonance images is biochemically abnormal.
Burden of Hypertension and Associated Risk Factors in Rural Communities of Abuja

Introduction: Hypertension have become of medical and public health concern globally. It is a known major risk factor for stroke, coronary artery disease and heart failure. Important risk factors contributing to hypertension are lifestyle and genetic factors. With rapid urbanization and increasing sedentary lifestyle of our rural populace, an explosion in the prevalence of hypertension becomes inevitable. Therefore, the importance of this study to assess the burden and risk factors of hypertension in these rural communities cannot be over emphasized. Objectives: 1. To determine the prevalence of diabetes in rural communities in Abuja FCT Nigeria. 2. To determine the prevalence of and associated risk factors of hypertension in rural communities in Abuja. Methodology: A descriptive cross-sectional design was employed in this study which was conducted between July and December 2017. A multi-stage sampling technique was used to recruit 420 willing adult participants from rural communities, in four political wards, selected from three area councils of FCT Abuja. Data were collected using an interviewer administered questionnaire while measurements were done with standardized instruments for blood pressure and blood sugar as well as weight and height measurements following recommended techniques and guidelines. Data were analyzed using SPSS 20.0 version. Univariate analyses were performed to evaluate the distribution for each variable. Binomial test was used to test the hypothesis. Multivariate analyses were done to identify the risk factors of hypertension. Results were considered significant at p-value < 0.05. Results: The prevalence of 38.3% and 25.2% were reported for hypertension and obesity in rural communities in Abuja respectively. Risk factors such as female sex, age 45 years and above, overweight/Obesity, physical inactivity, family history of hypertension and family history of diabetes were independent predictors of hypertension. Conclusion: This study has highlighted the fact that hypertension in addition to obesity is on the increase in the rural communities of Abuja, Nigeria. Therefore, concerted and coordinated effort from all stakeholders is urgently required to tame and reverse this ugly trend in view of the debilitating morbidity and mortality associated with hypertension.
Pricing ﬂoating strike lookback put option under heston stochastic volatility

The pricing problems of the exotic options in the finance do not have the analytic solutions under stochastic volatility and so it is difficult to calculate the option prices or at least it requires much of time to compute them. This study provides the required theoretical framework to practitioners for the option price estimation. This paper focuses on pricing for floating strike lookback put option and testing option pricing formulas for the Heston stochastic volatility model, which defines the asset volatility as the stochastic process. Our pricing method is depending on the PDE approach on Heston stochastic volatility model and homotopy analysis method. Heston model has received the most attention then it can give a acceptable explanation of the underlying asset dynamics. The resulting formula is well connected to a Black–Scholes price that is the first term of the series expansion, which makes computing the option prices fairly efficient. AMS subject classification:
Efficient CNF Encoding for Selecting 1 from N Objects

In many boolean-satisfiability problems, one must encode the constraint that at most one of n propositional variables is true. With a naïve encoding, this requires O(n) CNF clauses. We present a flexible alternative encoding that only requires O(n) clauses, at the expense of O(n) extra variables. The proposed encoding technique also allows efficie nt encoding of canonicalordering constraints that can aid in the determinat io of unsatisfiable problem instances. Sample applications are given for the pi geon-hole problem and Sudoku puzzles.
A Feature-Oriented Software Engineering Approach Supporting Extension and Testing

Software Engineering represents a structured, disciplined approach to the design and implementation of software systems. Adhering to such an approach enables greater planning for and management of systemic complexity. By augmenting the process to emphasize desired features that are to be present in the final software system, we can ensure that the final system will be modular, extensible, and testable with respect to individual features. Moreover, an existing system can be characterized according to its features and refactored in the same way. This thesis investigates feature-oriented augmentation to the standard software engineering approach. We employ logic-based feature models to characterize the features in the product family of an existing system. We use the characterized features to refactor a case study to reflect the approach using aspects. We demonstrate using the AspectJ Eclipse plugin how to publish different frameworks in a framework product line. Our results show that the refactoring efforts produce a modular, extensible, and testable system in which individual behavioral features selected from a product family of features can be added to or subtracted from the system with ease.
Perfect error identification in at-speed BIST environment

In this paper, we provide a practical formulation of the problem of identifying all error occurrences and all failed scan cells in at-speed scan based BIST environment. We propose a method that can be used to identify every error when the circuit test frequency is higher than the tester frequency. Our approach requires very little extra hardware for diagnosis and identifies errors in practical test application time decided by the frequency ratio between the CUT and the tester. We also propose a diagnosable BIST architecture with error detectors, which reduces the test application time in the proposed error identification method.
Prevascularization of porous biodegradable polymers

Highly porous biocompatible and biodegradable polymers in the form of cylindrical disks of 13.5 mm diameter were implanted in the mesentery of male syngeneic Fischer rats for a period of 35 days to study the dynamics of tissue ingrowth and the extent of tissue vascularity, and to explore their potential use as substrates for cell transplantation. The advancing fibrovascular tissue was characterized from histological sections of harvested devices by image analysis techniques. The rate of tissue ingrowth increased as the porosity and/or the pore size of the implanted devices increased. The time required for the tissue to fill the device depended on the polymer crystallinity and was smaller for amorphous polymers. The vascularity of the advancing tissue was consistent with time and independent of the biomaterial composition and morphology. Poly(L‐lactic acid) (PLLA) devices of 5 mm thickness, 24.5% crystallinity, 83% porosity, and 166 μm median pore diameter were filled by tissue after 25 days. However, the void volume of prevascularized devices (4%) was minimal and not practical for cell transplantation. In contrast, for amporphous PLLA devices of the same dimensions, and the similar porosity of 87% and median pore diameter of 179 μm, the tissue did not fill completely prevascularized devices, and an appreciable percentage (21%) of device volume was still available for cell engraftment after 25 days of implantation. These studies demonstrate the feasibility of creating vascularized templates of amorphous biodegradable polymers for the transplantation of isolated or encapsulated cell populations to regenerate metabolic organs and tissues. © 1993 John Wiley & Sons, Inc.
Clustering and Prediction of Solar Radiation Daily Patterns

This paper addresses the problem of clustering daily patterns of global horizontal solar radiation by using a feature-based approach. A pair of features, referred to as Sr and Hr, representing a measure of the normalized daily solar energy and of the energy fluctuations, respectively, is introduced. Clustering allows to perform some useful statistics at daily scale such as estimating the class weight and persistence. Furthermore, the problem of one-day ahead prediction of the class is addressed by using both hidden Markov models (HMM) and Non-linear Autoregressive (NAR) models. Performances are then assessed in terms of True Positive Rate (TPR) and True Negative Rate (TNR).
APPLICATION OF THE MODAL PUSHOVER PROCEDURE TO ESTIMATE NONLINEAR RESPONSE ENVELOPES

Traditional nonlinear static pushover analyses cannot fully address the multi-mode effects and response interaction that occur in a seismically excited structure. The recently developed modal pushover analysis (MPA) procedure improves on traditional pushover analyses by including multi-modal effects; however, its application is currently restricted to predicting the peak values of scalar response quantities. The peak responses computed using the MPA procedure could be used to form a rectangular demand envelope for any two specified response quantities. However, this rectangular envelope may be overly conservative as compared to the corresponding values computed by nonlinear time-history analyses. This paper describes a procedure, which uses the results of MPA analyses, to predict the envelope that bounds a vector of responses in a nonlinear structure. The accuracy of the proposed procedure is examined for selected pairs of responses by comparing the predicted envelope to the mean simulated response envelope obtained from an ensemble of nonlinear dynamic analyses. The response pairs considered include bi-directional interstory drifts and bending-moment-axial-load interaction in columns within a three-dimensional model of a three-story steel-moment-resisting-frame building. It is shown that the procedure has a level of accuracy that is appropriate for estimating the impact of seismic response interaction on the performance of a structure loaded into its nonlinear range.
Automatic Calibration of Hydrologic Models With Multi‐Objective Evolutionary Algorithm and Pareto Optimization 1

Abstract: In optimization problems with at least two conflicting objectives, a set of solutions rather than a unique one exists because of the trade‐offs between these objectives. A Pareto optimal solution set is achieved when a solution cannot be improved upon without degrading at least one of its objective criteria. This study investigated the application of multi‐objective evolutionary algorithm (MOEA) and Pareto ordering optimization in the automatic calibration of the Soil and Water Assessment Tool (SWAT), a process‐based, semi‐distributed, and continuous hydrologic model. The nondominated sorting genetic algorithm II (NSGA‐II), a fast and recent MOEA, and SWAT were called in FORTRAN from a parallel genetic algorithm library (PGAPACK) to determine the Pareto optimal set. A total of 139 parameter values were simultaneously and explicitly optimized in the calibration. The calibrated SWAT model simulated well the daily streamflow of the Calapooia watershed for a 3‐year period. The daily Nash‐Sutcliffe coefficients were 0.86 at calibration and 0.81 at validation. Automatic multi‐objective calibration of a complex watershed model was successfully implemented using Pareto ordering and MOEA. Future studies include simultaneous automatic calibration of water quality and quantity parameters and the application of Pareto optimization in decision and policy‐making problems related to conflicting objectives of economics and environmental quality.
TORC 2 and eisosomes are spatially interdependent , requiring optimal level of phosphatidylinositol 4 , 5-bisphosphate for their

The elucidation of the organization and maintenance of the plasma membrane has been sought due to its numerous roles in cellular function. In the budding yeast Saccharomyces cerevisiae, a novel paradigm has begun to emerge in the understanding of the distribution of plasma membrane microdomains and how they are regulated. We aimed to investigate the dynamic interdependence between the protein complexes eisosome and TORC2, representing microdomains MCC and MCT, respectively. In this study, we reveal that the eisosome organizer Pil1 colocalizes with the MCT marker Avo2. Furthermore, we provide evidence that the formation of MCT is dependent on both eisosome integrity and adequate levels of the plasma membrane phosphoinositide PI(4,5)P2. Taken together, our findings indicate that TORC2, eisosomes, and PI(4,5)P2 exist in an interconnected relationship, which supports the emerging model of the plasma membrane.
Determination of Neutrino Masses with Tritium Beta Decay Experiments

Models that can answer these questions also predict non-standard neutrino interactions. The determination of absolute neutrino masses is critical because most predicted non-standard neutrino interactions, depend on a combination of these masses (For example Majorana mass responsible from the neutrinoless double beta decay). Lack of knowledge on the absolute neutrino masses prevents elimination of certain theories despite null observations, because these theories could still be correct for lower neutrino masses. Therefore a model independent measurement of absolute neutrino mass is necessary in the case of continuing null observations of these interactions. One model independent way to determine neutrino masses is inspecting the electron energy spectrum of tritium beta decay.
Polyaspartamide-Based Nanoparticles Loaded with Fluticasone Propionate and the In Vitro Evaluation towards Cigarette Smoke Effects

This paper describes the evaluation of polymeric nanoparticles (NPs) as a potential carrier for lung administration of fluticasone propionate (FP). The chosen polymeric material to produce NPs was a copolymer based on α,β-poly(N-2-hydroxyethyl)-d,l-aspartamide (PHEA) whose backbone was derivatised with different molecules, such as poly(lactic acid) (PLA) and polyethylenglycol (PEG). The chosen method to produce NPs from PHEA-PLA-PEG2000 was the method based on high-pressure homogenization and subsequent solvent evaporation by adding Pluronic F68 during the process and trehalose before lyophilisation. Obtained colloidal FP-loaded NPs showed a slightly negative surface charge and nanometric dimensions that are maintained after storage for one year at −20 °C and 5 °C. The FP loading was about 2.9 wt % and the drug was slowly released in simulated lung fluid. Moreover, the obtained NPs, containing the drug or not, were biocompatible and did not induce cell necrosis and cell apoptosis on bronchial epithelial cells (16-HBE). Further in vitro testing on cigarette smoke extract (CSE)-stimulated 16-HBE revealed that FP-loaded NPs were able to reduce the survivin expression, while either free FP or empty NPs were not able to significantly reduce this effect.
Aerodynamic Design of a Martian Micro Air Vehicle

The present study aims at developing a reliable propulsion system for a rotary wing micro air vehicle (MAV) associated to rovers in order to enhance Martian exploration rate. The main challenge encountered for MAV design is Martian atmosphere’s density and speed of sound that are significantly lower than on Earth. Leading to compressible ultra low Reynolds number (2, 000 ă Redom ă 10, 000) flows met at blades tip that are unusual and unknown in the biosphere. Consequently, evaluations of numerical tools have been carried out recreating a depressurized experiment. 2D and 3D steady and unsteady Navier-Stokes computations are compared to XFoil for flow behavior apprehension and solver assessment. Based on XFoil’s performances evaluations, camber line and thickness distribution have been optimized for 2D incompressible and compressible flows. Optimal shape for a steady solver is a highly cambered airfoil shifting the boundary layer separation downstream. 2D unsteady Navier-Stokes computations show that airfoils delaying heavy unsteadiness generation are producing higher lift and lower drag in 2D than the picked airfoils enhancing vortex production, such as dragonfly airfoils. The impact of airfoil shape on 3D flows is evaluated with a first of its kind experimental campaign in collaboration with CNES. The experimental facility is a ONERA’s 18m tank recreating Martian atmosphere in terms on kinematic viscosity and composition. The tank size allows to reduce wall effects and provide as compared to previous studies a more accurate evaluation of rotor performances.