Miracle-dz/UniFAR-FTUs huggingface dataset:
Dermatitis and Aging-Related Barrier Dysfunction in Transgenic Mice Overexpressing an Epidermal-Targeted Claudin 6 Tail Deletion Mutant

The barrier function of the skin protects the mammalian body against infection, dehydration, UV irradiation and temperature fluctuation. Barrier function is reduced with the skin's intrinsic aging process, however the molecular mechanisms involved are unknown. We previously demonstrated that Claudin (Cldn)-containing tight junctions (TJs) are essential in the development of the epidermis and that transgenic mice overexpressing Cldn6 in the suprabasal layers of the epidermis undergo a perturbed terminal differentiation program characterized in part by reduced barrier function. To dissect further the mechanisms by which Cldn6 acts during epithelial differentiation, we overexpressed a Cldn6 cytoplasmic tail deletion mutant in the suprabasal compartment of the transgenic mouse epidermis. Although there were no gross phenotypic abnormalities at birth, subtle epidermal anomalies were present that disappeared by one month of age, indicative of a robust injury response. However, with aging, epidermal changes with eventual chronic dermatitis appeared with a concomitant barrier dysfunction manifested in increased trans-epidermal water loss. Immunohistochemical analysis revealed aberrant suprabasal Cldn localization with marked down-regulation of Cldn1. Both the proliferative and terminal differentiation compartments were perturbed as evidenced by mislocalization of multiple epidermal markers. These results suggest that the normally robust injury response mechanism of the epidermis is lost in the aging Involucrin-Cldn6-CΔ196 transgenic epidermis, and provide a model for evaluation of aging-related skin changes.
Guiding Through the Fog: Financial Statement Complexity and Voluntary Disclosure

A growing literature documents that complex financial statements negatively affect the information environment. In this paper, we examine whether managers use voluntary disclosure to mitigate these negative effects. Employing cross-sectional and within-firm designs, we find a robust positive relation between financial statement complexity and voluntary disclosure. This relation is stronger when liquidity decreases around the filing of the financial statements, is stronger when firms have more outside monitors, and is weaker when firms have poor performance and greater earnings management. We also examine the relation between financial statement complexity and voluntary disclosure using two quasi-natural experiments. Employing a generalized difference-in-differences design, we find firms affected by the adoption of complex accounting standards (e.g., SFAS 133 and SFAS 157) increase their voluntary disclosure to a greater extent than unaffected firms. Collectively, these findings suggest managers use voluntary disclosure to mitigate the negative effects of complex financial statements on the information environment.
Modeling the Dynamic Relationships between Treasury Bills, Inflation and Exchange Rates in Ghana

Macroeconomic variables are the main signposts signaling the current trends in an economy. Economic stability is desirable because it encourages economic growth that brings prosperity and employment. In this study, data on the 91-day Treasury bill (T-bill), 182-day Treasury bill (T-bill), inflation and exchange rates obtained from the Bank of Ghana from January, 2000 to October, 2012 was modeled using multivariate time series methods to investigate the dynamic interrelationships existing between them. The results revealed that, an optimal lag of one (1) should be included in the VAR process, therefore a VAR (1) model was fitted to describe the relationship between the variables. Results from the VAR (1) model, Granger Causality, Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) analysis showed that; there exist a unidirectional relationship between the 91-day T-bill and 182-day T-bill rate, between the 182-day T-bill and Inflation rate, between inflation and exchange rates and between the two T-bill rates and exchange rate. Bothunivariate and multivariate Ljung-Box and ARCH-LM model diagnostics test performed on the residuals of the individual equations and the overall VAR (1) model revealed that the residuals were white noise series. The chi-square goodness of fit test performed on an out-sample forecasted growth rates of each rate showed that the VAR (1) model fitted was adequate for determining the behavior of the rates over time.
Treatment Default amongst Patients with Tuberculosis in Urban Morocco: Predicting and Explaining Default and Post-Default Sputum Smear and Drug Susceptibility Results

Setting Public tuberculosis (TB) clinics in urban Morocco. Objective Explore risk factors for TB treatment default and develop a prediction tool. Assess consequences of default, specifically risk for transmission or development of drug resistance. Design Case-control study comparing patients who defaulted from TB treatment and patients who completed it using quantitative methods and open-ended questions. Results were interpreted in light of health professionals’ perspectives from a parallel study. A predictive model and simple tool to identify patients at high risk of default were developed. Sputum from cases with pulmonary TB was collected for smear and drug susceptibility testing. Results 91 cases and 186 controls enrolled. Independent risk factors for default included current smoking, retreatment, work interference with adherence, daily directly observed therapy, side effects, quick symptom resolution, and not knowing one’s treatment duration. Age >50 years, never smoking, and having friends who knew one’s diagnosis were protective. A simple scoring tool incorporating these factors was 82.4% sensitive and 87.6% specific for predicting default in this population. Clinicians and patients described additional contributors to default and suggested locally-relevant intervention targets. Among 89 cases with pulmonary TB, 71% had sputum that was smear positive for TB. Drug resistance was rare. Conclusion The causes of default from TB treatment were explored through synthesis of qualitative and quantitative data from patients and health professionals. A scoring tool with high sensitivity and specificity to predict default was developed. Prospective evaluation of this tool coupled with targeted interventions based on our findings is warranted. Of note, the risk of TB transmission from patients who default treatment to others is likely to be high. The commonly-feared risk of drug resistance, though, may be low; a larger study is required to confirm these findings.
An Energy efficient application specific integrated circuit for electrocardiogram feature detection and its potential for ambulatory cardiovascular disease detection

A novel algorithm based on forward search is developed for real-time electrocardiogram (ECG) signal processing and implemented in application specific integrated circuit (ASIC) for QRS complex related cardiovascular disease diagnosis. The authors have evaluated their algorithm using MIT-BIH database and achieve sensitivity of 99.86% and specificity of 99.93% for QRS complex peak detection. In this Letter, Physionet PTB diagnostic ECG database is used for QRS complex related disease detection. An ASIC for cardiovascular disease detection is fabricated using 130-nm CMOS high-speed process technology. The area of the ASIC is 0.5 mm2. The power dissipation is 1.73 μW at the operating frequency of 1 kHz with a supply voltage of 0.6 V. The output from the ASIC is fed to their Android application that generates diagnostic report and can be sent to a cardiologist through email. Their ASIC result shows average failed detection rate of 0.16% for six leads data of 290 patients in PTB diagnostic ECG database. They also have implemented a low-leakage version of their ASIC. The ASIC dissipates only 45 pJ with a supply voltage of 0.9 V. Their proposed ASIC is most suitable for energy efficient telemetry cardiovascular disease detection system.
Calcium signaling in a low calcium environment

Malaria parasites, Plasmodia, spend most of their asexual life cycle within red blood cells, where they proliferate and mature. The erythrocyte cytoplasm has very low [Ca2+] (<100 nM), which is very different from the extracellular environment encountered by most eukaryotic cells. The absence of extracellular Ca2+ is usually incompatible with normal cell functions and survival. In the present work, we have tested the possibility that Plasmodia overcome the limitation posed by the erythrocyte intracellular environment through the maintenance of a high [Ca2+] within the parasitophorous vacuole (PV), the compartment formed during invasion and within which the parasites grow and divide. Thus, Plasmodia were allowed to invade erythrocytes in the presence of Ca2+ indicator dyes. This allowed selective loading of the Ca2+ probes within the PV. The [Ca2+] within this compartment was found to be ∼40 μM, i.e., high enough to be compatible with a normal loading of the Plasmodia intracellular Ca2+ stores, a prerequisite for the use of a Ca2+-based signaling mechanism. We also show that reduction of extracellular [Ca2+] results in a slow depletion of the [Ca2+] within the PV. A transient drop of [Ca2+] in the PV for a period as short as 2 h affects the maturation process of the parasites within the erythrocytes, with a major reduction 48 h later in the percentage of schizonts, the form that re-invades the red blood cells.
Multi-sensors Analysis for Everyday Activity Monitoring

In this paper, we present a multimodal (video and contact sensors) monitoring approach for the automatic monitoring everyday activities of elderly people. The specificity of our approach consists in the integration of video analysis with other information resulting from contact sensors installed at home in order to improve the recognition of observed activities. After reviewing the state of the art, we describe the modeling of the scenarios of interest specified by medical experts. Then we present the multimodal event recognition process based on video and contact sensor analysis. Finally, we conclude by presenting preliminary results.
Best Technologies for Reducing Odor Emissions from Curtain-Sided, Deep Pit Swine Finishing Buildings

Executive Summary A three year research project was funded by the Minnesota Pork Producers Association to address the problems of odors, noxious gases and greenhouse gases produced in the popular deep pit curtain sided building. Several technologies were evaluated in pilot scale testing or laboratory testing while others were installed and monitored long term on full scale production facilities. BIOFILTRATION Odor and hydrogen sulfide emission reduction of 70%-95% were measured from a biofilter placed on a curtain pig finishing barn when the curtains were closed (during mechanical ventilation). During natural ventilation or when the curtains were open, odor and gas reduction decreased to 5%-50%. Ammonia emission reduction was very variable. OIL SPRINKLING The daily sprinkling of soybean oil inside a pig finishing curtain-sided barn using an existing " soaker " distribution system reduced the indoor concentration of NH 3 , H 2 S, and odor by roughly 30%, 20%, and 10% respectively. This technology did provide moderate to high reductions (60 to 80 %) in total dust levels inside the building. Future work with different nozzles that do not clog with the oil and water mixture is needed as well as improving the distribution of the oil-water sprinkling. OZONE AIR TREATMENT Ozone was added to a full scale finishing barn. Ozone air treatment reduced odors 25% as compared to the control barn during the cold months when the building had much less ventilation and the curtains were not open. During warm months when the curtains were providing most of the ventilation, no odor reduction was seen. The hydrogen sulfide situation was similar in that there was an improvement during the colder months (33% reduction) but not during the warmer months. Ammonia during the colder months was essentially the same and better in the control barn during the warmer months. Dust levels were reduced in the ozone treated barns. There is anecdotal evidence of improved pig health in the ozone barn. CHEMICAL ADDITION DURING PUMPOUT Hydrogen peroxide was added to finishing barn pits during agitation and pumping. Data suggest a 67% reduction in hydrogen sulfide concentrations between treatment and control. Laboratory studies showed as much as 90% reduction. DIET FORMULATION The use of Standardized ideal digestibility (SID) formulation and adding synthetic amino acids had no effect on energy and nitrogen digestibility and excretion. However, feeding the SID diet reduced slurry pH, ammonia emissions and tended to reduce hydrogen sulfide emissions during …
An Active helideck testbed for floating structures based on a Stewart-Gough platform

A parallel robot testbed based on Stewart-Gough platform called active-Helideck is designed, developed and tested as a helicopter floating Helideck. The objective of this testbed is to show the advantages of helicopters that use an active Helideck upon landing on and taking off from ships or from offshore structures. Active-helideck compensates simulated movements of a ship at sea. The main goal of this study is to maintain the robotpsilas end effector (Helideck) in a quasi-static position in accordance to an absolute inertial frame. Compensation is carried out through the coordinate action of its six prismatic actuators in function of an inertial measurement unit. Moreover, the simulation of the sea movement is done by a parallel robot called ship platform with three degrees of freedom. The ship platform is built with a vertical oscillation along the z axis, i.e. heave, and rotates on remaining axes, i.e. roll and pitch. Active Helideck is able to compensate simulated movements by considering the ship as an inertial frame as observed in the experiment.
Linking unit tests and properties

QuickCheck allows us to verify software against particular properties. A property can be regarded as an abstraction over many unit tests. QuickCheck uses generated random input data to test such properties. If a counterexample is found, it becomes immediately clear what we have tested. This is not the case when all tests pass, since we do not (and shall not) see the actual generated test cases. How can we be sure about what is tested? QuickCheck has the ability to gather statistics about the test cases, which is insightful. But still it does not tell us whether the particular unit test scenarios we have in mind are included. For this reason, we have developed a tool that can answer this question. It checks if a given unit test can be generated by a property, making it easier to judge the property's quality. We have applied our tool to an industrial use case of testing the AUTOSAR basic software modules and shows that it can handle complex models and large unit tests.
A Review of Smart Antenna System (sas) with Array Processing Algorithms

Smart Antenna System (SAS) is one the emerging technologies for the next generation of wireless communication systems. SAS lead to communication networks with higher capacity and better performance [1]. Performance is also enhanced by employing suitable adaptive algorithm to achieve high data rate and increased user base [2]. This paper introduces the need of SAS in existing and upcoming generation of wireless communication. This paper explains the working of SAS and the algorithms which makes the whole system smart. Also this paper throws light on the classification of SAS. This study demonstrates the practical requirement of SAS at the Base Station.
Spatiotemporal Analysis of Bluetooth Data: Application to a Large Urban Network

The emergence of new technologies allows better monitoring of traffic conditions and understanding of urban network dynamics. Bluetooth technology is becoming widespread, as it represents a cost-effective means for capturing road traffic in both arterials and motorways. Although the extraction of travel time from Bluetooth data is fairly straightforward, data reliability and processing is still challenging with the issues of penetration rate, mode discrimination, and detection quality. This paper presents a methodological contribution to the use of Bluetooth data for the spatiotemporal analysis of a large urban network (Brisbane, Australia). It introduces the concept of the Bluetooth origin-destination (B-OD) matrix, which is built from a network of 79 Bluetooth detectors located within the Brisbane urban area. The B-OD matrix describes the dynamics of a subpopulation of vehicles, between pairs of detectors. The results show that the characteristics of urban networks can be effectively represented through B-OD matrices. A comparison with loop detector data enables an assessment of the results' significance. Then, the spatiotemporal structure of the network is analyzed with two different clustering analyses, namely, latent Dirichlet allocation (LDA) and $K$-means. While LDA is used to detect a temporal pattern, the $K$-means algorithm highlights Bluetooth fundamental diagram (BFD) classes. The results show that Bluetooth data has the potential to be a reliable data source for traffic monitoring. By highlighting hidden structures of a large area, the algorithm outputs allow us to provide the road operators with a fine spatiotemporal analysis of their network, in terms of traffic conditions.
Hexagonal circle patterns with constant intersection angles and discrete Painlevé and Riccati equations

Hexagonal circle patterns with constant intersection angles mimicking holomorphic maps zc and log(z) are studied. It is shown that the corresponding circle patterns are immersed and described by special separatrix solutions of discrete Painleve and Riccati equations. The general solution of the Riccati equation is expressed in terms of the hypergeometric function. Global properties of these solutions, as well as of the discrete zc and log(z), are established.
Nash Equilibrium Computation in Subnetwork Zero-Sum Games With Switching Communications

In this paper, we investigate a distributed Nash equilibrium computation problem for a time-varying multi-agent network consisting of two subnetworks, where the two subnetworks share the same objective function. We first propose a subgradient-based distributed algorithm with heterogeneous stepsizes to compute a Nash equilibrium of a zero-sum game. We then prove that the proposed algorithm can achieve a Nash equilibrium under uniformly jointly strongly connected (UJSC) weight-balanced digraphs with homogenous stepsizes. Moreover, we demonstrate that for weighted-unbalanced graphs a Nash equilibrium may not be achieved with homogenous stepsizes unless certain conditions on the objective function hold. We show that there always exist heterogeneous stepsizes for the proposed algorithm to guarantee that a Nash equilibrium can be achieved for UJSC digraphs. Finally, in two standard weight-unbalanced cases, we verify the convergence to a Nash equilibrium by adaptively updating the stepsizes along with the arc weights in the proposed algorithm.
Exploring the Effect of Differences in the Acoustic Correlates of Adults' and Children's Speech in the Context of Automatic Speech Recognition

This work explores the effect of mismatches between adults' and children's speech due to differences in various acoustic correlates on the automatic speech recognition performance under mismatched conditions. The different correlates studied in this work include the pitch, the speaking rate, the glottal parameters (open quotient, return quotient, and speech quotient), and the formant frequencies. An effort is made to quantify the effect of these correlates by explicitly normalizing each of them using the already existing techniques available in literature. Our initial study done on a connected digit recognition task shows that among these parameters only the formant frequencies, the pitch, and the speaking rate affect the automatic speech recognition performance. Significant improvements are obtained in the performance with normalization of these three parameters. With combined normalization of the pitch, the speaking rate, and the formant frequencies, 80% and 70% relative improvements are obtained over the baseline for children's speech and adults' speech recognition under mismatched conditions.
A Second Order Approximation for Quasilinear Non-Fickian Diffusion Models

Abstract. In this paper initial boundary value problems, defined using quasilinear diffusion equations of Volterra type, are considered. These equations arise for instance to describe diffusion processes in viscoelastic media whose behavior is represented by a Voigt–Kelvin model or a Maxwell model. A finite difference discretization defined on a general non-uniform grid with second order convergence order in space is proposed. The analysis does not follow the usual splitting of the global error using the solution of an elliptic equation induced by the integro-differential equation. The new approach enables us to reduce the smoothness required to the theoretical solution when the usual split technique is used. Non-singular and singular kernels are considered. Numerical simulations which show the effectiveness of the method are included.
A Difference Fitting Residuals algorithm for lossless data compression in wireless sensor nodes

Efficient utilization of energy is a core area of research in wireless sensor networks. Data compression methods to reduce the number of bits to be transmitted by the communication module will significantly reduce the energy requirement and increase the lifetime of the sensor node. Through analysis the probability distribution of sensor data and a classic compression algorithm named ND-Encoding, this paper proposed a new algorithm specifically designed for lossless data compression in sensor nodes called Difference Fitting Residuals compression algorithm. The proposed algorithm will calculate the linear fitting values of sensor data's differences and then calculate the fitting residuals which will be input to an entropy encoder to achieve data compression. Compared with two typical lossless compression algorithms, the proposed algorithm indicated better compression ratios, despite a less computational effort.
Energy Efficient Technology Diffusion Factors : A Systematic Review

Due to the escalating population and the resulting increase in energy use, the world is faced with the challenge of energy crisis. To mitigate the rise in energy crisis, innovation, adoption, and diffusion of energy efficient technologies is imperative. Review of available literatures indicates that expected improvement in energy consumption has not been achieved in spite of the innovation and improvement in energy efficient technologies. This imbalance points towards the lack of proper adoption and diffusion of these technologies. This paper has looked into prior arts to determine the factors responsible for this diffusion process. Upon identifying the factors, it is evident that some factors can be improved to act as accelerators to the diffusion process. The other set of factors tend to remain as hindrances which can be reduced to an extent, but not removed completely. The paper further investigates the reasons behind these factors and categorizes them under three groups – financial, informational, and behavioral. Findings prove that most of the factors can be attached to a financial cause. Thus research and development alone is not the answer to the rising energy demand, but effective economic motivation is necessary to curb the demand. Future research will look into the present energy policies and group them based on their targeted sector. This will enable to locate the gaps in the policies already implemented and subsequently help in the creation of new policies.