Miracle-dz/UniFAR-FTUs huggingface dataset:
Activation of LFA-1 through a Ca2(+)-dependent epitope stimulates lymphocyte adhesion

The leukocyte function-associated molecule-1 (LFA-1) plays a key role in cell adhesion processes between cells of the immune system. We investigated the mechanism that may regulate LFA-1-ligand interactions, which result in cell-cell adhesion. To this end we employed an intriguing anti-LFA-1 alpha mAb (NKI-L16), capable of inducing rather than inhibiting cell adhesion. Aggregation induced by NKI-L16 or Fab fragments thereof is not the result of signals transmitted through LFA- 1. The antibody was found to recognize a unique Ca2(+)-dependent activation epitope of LFA-1, which is essentially absent on resting lymphocytes, but becomes induced upon in vitro culture. Expression of this epitope correlates well with the capacity of cells to rapidly aggregate upon stimulation by PMA or through the TCR/CD3 complex, indicating that expression of the NKI-L16 epitope is essential for LFA- 1 to mediate adhesion. However, expression of the NKI-L16 epitope in itself is not sufficient for cell binding since cloned T lymphocytes express the NKI-L16 epitope constitutively at high levels, but do not aggregate spontaneously. Based on these observations we propose the existence of three distinct forms of LFA-1: (a) an inactive form, which does not, or only partially exposes the NKI-L16 epitope, found on resting cells; (b) an intermediate, NKI-L16+ form, expressed by mature or previously activated cells; and (c) an active (NKI-L16+) form of LFA- 1, capable of high affinity ligand binding, obtained after specific triggering of a lymphocyte through the TCR/CD3 complex, by PMA, or by binding of NKI-L16 antibodies.
Orthogonal least squares algorithm for the multiple-measurement vectors problem

The multiple signal classification (MUSIC) algorithm, which was originally proposed to solve the direction of arrival (DOA) estimation problem in sensor array processing, has attracted much attention in recent years as a method to solve the multiple-measurement vectors (MMV) problem. While MUSIC reliably reconstructs the row sparse signals in the full row rank case, it performs poor in the rank deficient case. In order to overcome the limitation of MUSIC, we propose a robust greedy algorithm, henceforth referred to as an MMV orthogonal least squares (MMV-OLS) algorithm, for the MMV problem. Our analysis shows that in the full row rank case, MMV-OLS guarantees exact reconstruction of any row K-sparse signals from K + 1 measurements, which is in fact optimal since K + 1 is the smallest number of measurements to recover the row K-sparse matrices. In addition, we show that the recovery performance of MMV-OLS is competitive even in the rank deficient case by providing empirical results.
SubDiffraction-Limited Optical Imaging with a Silver Superlens

Recent theory has predicted a superlens that is capable of producing sub–diffraction-limited images. This superlens would allow the recovery of evanescent waves in an image via the excitation of surface plasmons. Using silver as a natural optical superlens, we demonstrated sub–diffraction-limited imaging with 60-nanometer half-pitch resolution, or one-sixth of the illumination wavelength. By proper design of the working wavelength and the thickness of silver that allows access to a broad spectrum of subwavelength features, we also showed that arbitrary nanostructures can be imaged with good fidelity. The optical superlens promises exciting avenues to nanoscale optical imaging and ultrasmall optoelectronic devices.
The State of Fatigue Assessment and Management in Offshore Oil and Gas Industry: A Systematic Review

The Oil and Gas Industry in the United States has seen a considerable rise in exploration and production activities over the past decade and half, with an increase in drilling rigs by 71% in the period from 2003 to 2014 and a 27.6% increase in worker related fatalities during the same period (Mason, Retzer, Hill, & Lincoln, 2015). The oil and gas extraction industry continues to have a fatality rate about seven times higher than the U.S. workers average, resulting in both industry and federal agencies focusing strategic efforts on decreasing fatigue related injuries and fatalities (Mehta et al., 2017). Fatigue is a complex and multi-dimensional construct (Mehta, 2017) with multiple facets which can negatively affect performance and safety outcomes in the work environment. It is often a result of factors such as sleep loss, circadian phase, work load and has been implicated as a significant risk factor in safety and incidents (Mehta et al., 2016). Risk management in the oil and gas industry has gone beyond management of risk presented by the technical process, but now include psychosocial risk such as work related stress and further development of score cards and key performance indicators (Bergh, Hinna, Leka, & Jain, 2014). A recent study employing physiological monitoring to understand the relationship between shiftwork and fatigue utilized wearable monitors deployed on the workers utilized heart rate variability to monitor the state of the workers. The study found that the ‘swing shift’ (or change of shift during the duration of offshore deployment), resulted in increased fatigue of the operator. Additionally, night shift operators were found to be more fatigued than their day-time counterparts (Shortz, Franke, Kilic, Peres, & Mehta, 2017). There is a need to scale the gap between intensive physiological monitoring-based measures employed at laboratory scales to deployable tools at an industrial scale for monitoring and managing fatigue. The current study is a systematic review that is focused on understanding how fatigue has been assessed in the offshore oil and gas environments, including evaluating prominent measures, types of measures used, laboratory versus field studied, and comprehensiveness of the measures to find possible resolutions to the question of how to assess and address fatigue in these high-risk environments
Unsupervised Texture Segmentation Using Markov Random Field Models

The problem of unsupervised segmentation of textured images is considered. The only explicit assumption made is that the intensity data can be modeled by a Gauss Markov random field (GMRF). The image is divided into a number of nonoverlapping regions and the GMRF parameters are computed from each of these regions. A simple clustering method is used to merge these regions. The parameters of the model estimated from the clustered segments are then used in two different schemes, one being all approximation to the maximum a posterior estimate of the labels and the other minimizing the percentage misclassification error. The proposed approach is contrasted with the algorithm of S. Lakshamanan and H. Derin (1989), which uses a simultaneous parameter estimation and segmentation scheme. The results of the adaptive segmentation algorithm of Lakshamanan and Derin are compared with a simple nearest-neighbor classification scheme to show that if enough information is available, simple techniques could be used as alternatives to computationally expensive schemes. >
Welcome The Costs of Entrenched Boards

This paper investigates empirically how the value of publicly traded firms is affected by protecting management from removal. In a majority of US public companies, charter provisions establishing a staggered board protect the board from removal in a hostile takeover or a proxy contest. We find that staggered boards established by company charters are associated with a lower market value. Staggered boards that are established in company bylaws, which can be amended by shareholders and thus do not insulate incumbents from removal by determined shareholders, do not have a statistically significant association with reduced market value. We also find some evidence that charter-based staggered boards bring about, and not merely reflect, a reduced firm value. The reduction in market value associated with charter-based staggered boards is economically significant, with a median reduction of 4%6%. JEL Classification: G30, G34, K22
Expression of Glucose Transporter 4 (GLUT4) is Increased by Cinnamaldehyde in C2C12 Mouse Muscle Cells

Background: In diabetes mellitus because of the absence or insufficient sensitivity to insulin, glucose transporter protein in cell membrane, glucose transporter 4, is decreased. GLUT4 is the major glucose transporter in skeletal muscle and adipose tissue, which is under control of insulin. It remains, however, unclear whether cinnamaldehyde plays a regulatory role(s) or not. Objectives: The objective of this study was to investigate the effects of cinnamaldehyde on GLUT4 gene expression. Materials and Methods: This study was an experimental trial. Tests were performed in triplicates. This study examined effects of cinnamaldehyde on Glut4 gene expression in C2C12 skeletal muscle cells by using Real Time PCR. C2C12 myoblasts were cultured in DMEM + 10 % FBS. After differentiation of myoblasts to myotubes, the cells were serum deprived for 5 hours and then treated with 10, 20, or 50 µM of cinnamaldehyde for 1 hour. Results: Our data revealed a significant increase in the expression of Glut4 in cinnamaldehyde treated cells. In addition, GLUT4 mRNA level was increased in a dose dependent manner. Analyses were performed using the SPSS 16 for Windows software. Differences between the groups were determined by one-way ANOVA. Conclusions: These results demonstrate that cinnamaldehyde up regulates the expression of mouse skeletal muscle GLUT4 gene expression.
Online energy consumption monitoring of wireless testbed infrastructure through the NITOS EMF framework

Development of energy-efficient protocols and algorithms requires in-depth understanding of the power consumption characteristics of real world devices. To this aim, energy efficiency analysis is performed by the research community, mainly focusing on the development of power consumption models. However, recent studies [1] have highlighted the inability of existing models to accurately estimate energy consumption even in non-composite scenarios, where the operation of a single device is analyzed. The inability of such models is further highlighted under real life scenarios, where the impact induced by the simultaneous operation of several devices renders the application of traditional models completely inappropriate. As a result, energy efficiency evaluation under complex configurations and topologies, needs to be experimentally investigated through the application of online monitoring solutions. In this work, we propose the innovative NITOS Energy consumption Monitoring Framework (EMF) able to support online monitoring of energy expenditure, along with the experiment execution. The developed framework is built on a distributed network of low-cost, but highly accurate devices and is fully integrated with the large-scale wireless NITOS testbed. Framework evaluation is performed under both low-level experiments that demonstrate the platform's high-level accuracy, as well as through high-level experiments that showcase how online and distributed monitoring can facilitate energy performance assessment of realistic testbed experiments.
Nonparametric spectral density estimation with missing observations

Self-consistency is a fundamental principle in statistics for retaining maximum amount of information in the data. In this paper this principle is applied to develop a new method for nonparametric spectrum estimation with missing data. One major advantage of the proposed method is that it can be coupled with any complete data nonparametric spectrum estimation procedure, including kernel smoothing, wavelet and spline estimators. The practical performance of the method is illustrated by a simulation study.
Towards a Cost Causation-Based Tariff for Distribution Networks With DG

This paper decomposes the effects of the transition from an average cost distribution tariff to a cost causation-based distribution tariff, in terms of time and location, that uses nodal prices to recover losses and an "extent-of-use" method to recover fixed network costs based on use at coincident peak. Our decomposition is designed so that the effects of using coincident peak and location for fixed network charges, as well as using marginal losses under constraints recovering the exact amount of losses, and recovering exactly the cost of network service in total can be isolated and analyzed separately. We apply our tariff transition and decomposition method to an example network with data from Uruguay to isolate the various effects with and without a distributed generation (DG) resource. We show moving to coincident peak charges and to fully charging for marginal losses while rebating the merchandising surplus through the fixed charges have the greatest effects on changes in distribution tariff charges. DG provides countervailing cost changes to distribution tariffs for loads through loss reductions and the implicit "creation" of new network capacity for which it is paid. The interaction of all these effects may lead to outcomes that are counter-intuitive, which further supports the need to decompose the tariff changes to fully understand the reasons for the direction and magnitude of changes in tariff charges in the transition to tariffs based more on cost causation.
Removal of Phenol by A. belladonna L. Hairy Root

Phenolic compounds that present in the several industries are harmful and dangerous for human health. In this study we have studied the potential of Atropa belladonna hairy roots in phenol removal of wastewater. The optimal conditions for the removal process were evaluated using different phenol (10–500 mg.1−1) and H2O2 (1–15 Mm) concentrations. In the presence of H2O2, Roots were able to remove phenol concentrations up to 500 mg.1−1. in the wide range of pH (4–9), reaching high removal efficiency. When roots were re-used for five consecutive cycles, phenol removal efficiency decreased from 98–62%, in the last cycle. After the removal process, the solutions were obtained from the experiment were estimated for their toxicity using a test with Lactaca sativa L. seeds. Results showed that the treated solution was less toxic than the parent solution.
Verificarlo: Checking Floating Point Accuracy through Monte Carlo Arithmetic

Numerical accuracy of floating point computation is a well studied topic which has not made its way to the end-user in scientific computing. Yet, it has become a critical issue with the recent requirements for code modernization to harness new highly parallel hardware and perform higher resolution computation. To democratize numerical accuracy analysis, it is important to propose tools and methodologies to study large use cases in a reliable and automatic way. In this paper, we propose verificarlo, an extension to the LLVM compiler to automatically use Monte Carlo Arithmetic in a transparent way for the end-user. It supports all the major languages including C, C++, and Fortran. Unlike source-to-source approaches, our implementation captures the influence of compiler optimizations on the numerical accuracy. We illustrate how Monte Carlo Arithmetic using the verificarlo tool outperforms the existing approaches on various use cases and is a step toward automatic numerical analysis.
Structural Studies of the Giant Mimivirus

Mimivirus is the largest known virus whose genome and physical size are comparable to some small bacteria, blurring the boundary between a virus and a cell. Structural studies of Mimivirus have been difficult because of its size and long surface fibers. Here we report the use of enzymatic digestions to remove the surface fibers of Mimivirus in order to expose the surface of the viral capsid. Cryo-electron microscopy (cryoEM) and atomic force microscopy were able to show that the 20 icosahedral faces of Mimivirus capsids have hexagonal arrays of depressions. Each depression is surrounded by six trimeric capsomers that are similar in structure to those in many other large, icosahedral double-stranded DNA viruses. Whereas in most viruses these capsomers are hexagonally close-packed with the same orientation in each face, in Mimivirus there are vacancies at the systematic depressions with neighboring capsomers differing in orientation by 60°. The previously observed starfish-shaped feature is well-resolved and found to be on each virus particle and is associated with a special pentameric vertex. The arms of the starfish fit into the gaps between the five faces surrounding the unique vertex, acting as a seal. Furthermore, the enveloped nucleocapsid is accurately positioned and oriented within the capsid with a concave surface facing the unique vertex. Thus, the starfish-shaped feature and the organization of the nucleocapsid might regulate the delivery of the genome to the host. The structure of Mimivirus, as well as the various fiber components observed in the virus, suggests that the Mimivirus genome includes genes derived from both eukaryotic and prokaryotic organisms. The three-dimensional cryoEM reconstruction reported here is of a virus with a volume that is one order of magnitude larger than any previously reported molecular assembly studied at a resolution of equal to or better than 65 Å.
An arctic lagerstätte – the slottsmøya member of the Agardhfjellet formation (Upper Jurassic – Lower Cretaceous) of Spitsbergen

Paleontological fieldwork on Spitsbergen, 2004-2011, has revealed the presence of abundant plesiosaur and ichthyosaur remains, a series of 15 seep carbonate bodies, as well as a rich invertebrate fauna from the Upper Jurassic – Lower Cretaceous Slottsmoya Member of the Agardhfjellet Formation, a 70-100 metre-thick unit of dark grey to black shale and paper shale. Deposition of the Slottsmoya Member occurred at high paleolatitudes, at or near the Arctic Circle, and molluscan and foraminiferal biostratigraphy indicates an Early Volgian – Ryazanian age for the unit. In this volume we present the organic carbon isotope chemostratigraphy, cyclostratigraphy, lithostratigraphy and sedimentology for the Member. A well preserved assemblage of fossil echinoderms, the first ultrastructural information on the lingulid brachiopod Lingularia and microfacies of nine seep carbonates are described. Comparative analyses of the marine reptile material found in the Slottsmoya Member indicate a diverse assemblage of new plesiosaurians (two new genera and three new species of plesiosauroids and one new species of pliosaurid) and ichthyosaurians (two new genera and species). Placed within a high-resolution stratigraphic framework, the diverse invertebrate and vertebrate assemblage of the Slottsmoya Lagerstatte provides an unparallelled opportunity to study the evolution and paleoecology of a high-latitude, Mesozoic, marine ecosystem.
Correlation between trunk control, respiratory muscle strength and spirometry in patients with stroke: an observational study.

INTRODUCTION Stroke is the main cause of chronic disability in adults, and the effect of a stroke on the respiratory system depends on the structures affected by the lesion. OBJECTIVES To evaluate the correlation between trunk control, respiratory muscle strength and pulmonary function in individuals who suffered stroke. METHODS Observational, quantitative and descriptive study. Twenty-three patients who had a clinical diagnosis of ischaemic or haemorrhagic stroke. The trunk control was assessed through the Trunk Impairment Scale (TIS), and the respiratory muscle strength was assessed by manovacuometry by measuring the maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP). For pulmonary function analysis, we measured forced vital capacity (FVC), forced expiratory volume in one second (FEV₁), peak expiratory flow (PEF) and the Tiffeneau index (TIFF) through spirometry. RESULTS A consistent and statistically significant correlation was found between TIS and PEF (r = 0.489, p = 0.024) and between TIS and EPmax (r = 0.517, p = 0.016). No relation was found between the other variables of pulmonary function and TIS. CONCLUSION This study demonstrated that there is a relation between trunk control and respiratory muscular strength, especially concerning the expiratory muscles. However, there seems to be no relation between trunk control and pulmonary function in this series of individuals who suffered stroke.
Compressed data structures for annotated web search

Entity relationship search at Web scale depends on adding dozens of entity annotations to each of billions of crawled pages and indexing the annotations at rates comparable to regular text indexing. Even small entity search benchmarks from TREC and INEX suggest that the entity catalog support thousands of entity types and tens to hundreds of millions of entities. The above targets raise many challenges, major ones being the design of highly compressed data structures in RAM for spotting and disambiguating entity mentions, and highly compressed disk-based annotation indices. These data structures cannot be readily built upon standard inverted indices. Here we present a Web scale entity annotator and annotation index. Using a new workload-sensitive compressed multilevel map, we fit statistical disambiguation models for millions of entities within 1.15GB of RAM, and spend about 0.6 core-milliseconds per disambiguation. In contrast, DBPedia Spotlight spends 158 milliseconds, Wikipedia Miner spends 21 milliseconds, and Zemanta spends 9.5 milliseconds. Our annotation indices use ideas from vertical databases to reduce storage by 30%. On 40x8 cores with 40x3 disk spindles, we can annotate and index, in about a day, a billion Web pages with two million entities and 200,000 types from Wikipedia. Index decompression and scan speed are comparable to MG4J.
Building a smart maintenance architecture using smart devices: A web 2.0 based approach

In industrial environment to optimize and to improve maintenance operations could be one of main goals to achieve for enhancing revenues for machinery manufacturers providing after-sales services to their customers. Especially remote maintenance and diagnosis are aspects investigated in literature and in real environments in the last years. In fact, remote access and role-specific data distribution can become the next level upgrade of maintenance, diagnostic and flow control management using smart sensors, actuators and smart consumer devices (smartphone, tablet, etc.). In this paper, a real case study has been proposed: a new web-services based server application in order to have remote access to the data streams and to analyze them in an Italian machinery company manufacturer has been provided. This solution permits to have the machine status available on a web page, very strict time responses, a better user profiling and innovative control system based on line smart devices monitoring machine data and sending notification sounds when needed. The result is a platform connecting, by using the Internet of Things (IoT) paradigm, industrial machineries with a smart device android app and with a web application build with web 2.0 based technologies.
Forensic analysis of file system intrusions using improved backtracking

Intrusion detection systems alert the system administrators of intrusions but, in most cases, do not provide details about which system events are relevant to the intrusion and how the system events are related. We consider intrusions of file systems. Existing tools, like BackTracker, help the system administrator backtrack from the detection point, which is a file with suspicious contents, to possible entry points of the intrusion by providing a graph containing dependency information between the various files and processes that could be related to the detection point. We improve such backtracking techniques by logging certain additional parameters of the file system during normal operations (real-time) and examining the logged information during the analysis phase. In addition, we use dataflow analysis within the processes related to the intrusion to prune unwanted paths from the dependency graph. This results in significant reduction in search space, search time, and false positives. We also analyze the effort required in terms of storage space and search time.