Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell models of arrhythmogenic cardiomyopathy: advances and opportunities

ABSTRACT Arrhythmogenic cardiomyopathy is a rare genetic disease that is mostly inherited as an autosomal dominant trait. It is associated predominantly with mutations in desmosomal genes and is characterized by the replacement of the ventricular myocardium with fibrous fatty deposits, arrhythmias and a high risk of sudden death. In vitro studies have contributed to our understanding of the pathogenic mechanisms underlying this disease, including its genetic determinants, as well as its cellular, signaling and molecular defects. Here, we review what is currently known about the pathogenesis of arrhythmogenic cardiomyopathy and focus on the in vitro models that have advanced our understanding of the disease. Finally, we assess the potential of established and innovative cell platforms for elucidating unknown aspects of this disease, and for screening new potential therapeutic agents. This appraisal of in vitro models of arrhythmogenic cardiomyopathy highlights the discoveries made about this disease and the uses of these models for future basic and therapeutic research. Summary: In vitro models of ACM provide insights into the molecular mechanisms of this disease. This reappraisal offers a comprehensive vision of past discoveries and constitutes a tool for future research.
What do you think of my picture? Investigating factors of influence in profile images context perception

Multimedia quality assessment has been an important research topic during the last decades. The original focus on artifact visibility has been extended during the years to aspects as image aesthetics, interestingness and memorability. More recently, Fedorovskaya proposed the concept of 'image psychology': this concept focuses on additional quality dimensions related to human content processing. While these additional dimensions are very valuable in understanding preferences, it is very hard to define, isolate and measure their effect on quality. In this paper we continue our research on face pictures investigating which image factors influence context perception. We collected perceived fit of a set of images to various content categories. These categories were selected based on current typologies in social networks. Logistic regression was adopted to model category fit based on images features. In this model we used both low level and high level features, the latter focusing on complex features related to image content. In order to extract these high level features, we relied on crowdsourcing, since computer vision algorithms are not yet sufficiently accurate for the features we needed. Our results underline the importance of some high level content features, e.g. the dress of the portrayed person and scene setting, in categorizing image.
Improved Pathogenicity of a Beet Black Scorch Virus Variant by Low Temperature and Co-infection with Its Satellite RNA

Co-infection of none-coding satellite RNAs (sat-RNAs) usually inhibits replication and attenuates disease symptoms of helper viruses. However, we find that the sat-RNA of Beet black scorch virus (BBSV) and low temperature (18°C) additively enhance the systemic infection of BBSV in Nicotiana benthamiana. Northern blotting hybridization revealed a relatively reduced accumulation of BBSV-derived small interfering RNAs (siRNAs) in presence of sat-RNA as compared to that of BBSV alone. Cloning and sequencing of total small RNAs showed that more than 50% of the total small RNAs sequenced from BBSV-infected plants were BBSV-siRNAs, whereas the abundance of sat-siRNAs were higher than BBSV-siRNAs in the sat-RNA co-infected plants, indicating that the sat-RNA occupies most of the silencing components and possibly relieves the RNA silencing-mediated defense against BBSV. Interestingly, the 5′ termini of siRNAs derived from BBSV and sat-RNA were dominated by Uridines (U) and Adenines (A), respectively. Besides, the infection of BBSV alone and with sat-RNA induce down-regulation of miR168 and miR403, respectively, which leads to high accumulation of their targets, Argonaute 1 (AGO1) and AGO2. Our work reveals the profiles of siRNAs of BBSV and sat-RNA and provides an additional clue to investigate the complicated interaction between the helper virus and sat-RNA.
Determination of Soil Moisture and Vegetation Parameters from Spaceborne C-Band SAR on Agricultural Areas

Soil moisture is an important factor influencing hydrological and meteorological exchange processes at the land surface. As ground measurements of soil moisture cannot provide spatial-ly distributed information, remote sensing of soil moisture using Synthetic Aperture Radar (SAR) offers an alternative. To derive soil moisture from vegetated areas with SAR, the influ-ence of vegetation parameters on SAR backscatter must be considered, though. The first part of the study analyses the potential to use a qualitative soil moisture index from ERS-SAR with high spatial resolution that can be used without ground truth soil moisture and vegetation data. The index ranges from low to high soil moisture instead of giving absolute soil moisture values. The method is applied to agricultural areas in the catchment of the river Rur in Germany. The soil moisture index represents wetting and drying tendencies well when compared to precipitation records and behaves like in-situ soil moisture regarding its variabil-ity. The analysis of spatial patterns from the soil moisture index by using semivariograms re-veals that differences in management that result for example in differences in evapotranspira-tion from one to the next agricultural field, are the only influence on spatial patterns of soil moisture in the Rur catchment. This study confirms the applicability of a high-resolution soil moisture index for monitoring soil moisture changes and to analyze spatial soil moisture pat-terns. The soil moisture index could be used as input to hydrological models and could substi-tute antecedent precipitation, which needs precipitation stations, as a proxy to soil moisture. The second part of the study examines the capability of dual-polarimetric C-Band SAR data with high incidence angles from the Sentinel-1 satellites to derive soil moisture and vegetation parameters quantitatively. A processing scheme for Sentinel-1 Level-1 data is presented to produce images of different SAR observables that are compared to extensive ground meas-urements of soil moisture and vegetation parameters. It shows that soil moisture retrieval is feasible from bare soil and maize with an RMSE of 7 Vol%. From other land use types, dif-ferent vegetation parameters could be retrieved with an error of around 25 % of their range, in median. Neither soil moisture nor vegetation parameters could be derived from grassland and triticale due to the influence of the thatch layer and the missing of a clear row structure. Both grassland and triticale are in contrast to the other crops not sown in rows on our research fields. The analysis has shown that the incidence angle is of main importance for the capability of C-band SAR to derive soil moisture and that the availability of at least one co- and cross-polarized channel is important for the quantitative retrieval of land surface parameters. The dual-pol H2α parameters were not meaningful for soil moisture and vegetation parameter re-trieval in this study.
Extended TDDB power-law validation for high-voltage applications such as OTP memories in High-k CMOS 28nm FDSOI technology

This paper aims to provide reliability projections and modeling for wearout current consumption and oxide lifetime (or programming time) under programming conditions regarding OTP memories perimeter. TDDB reliability methodology have been carried out to high voltages and the power law dependent TBD equations terms have been discussed. Adjustments focusing on the temperature impact on voltage acceleration offer us a compact model for TDDB HV.
Galaxy pairs in cosmological simulations: effects of interactions on star formation

We carried out a statistical analysis of galaxy pairs in hydrodynamical ΛCDM simulations. We focus on the triggering of star formation by interactions and analysed the enhancement of star formation activity in terms of orbital parameters. By comparing the data to a suitable sample of simulated galaxies without a nearby companion, we find that close encounters (r < 30 kpch −1 )m ay effectively induce star formation. However, our results suggest that the stability properties of systems and the spatial proximity are both relevant factors in the process of triggering star formation by tidal interactions. In order to assess the effects of projection and spurious pairs in observational samples, we constructed and analysed samples of pairs of galaxies in the simulations obtained in projection. We found a good agreement with observational results with a threshold at rp ∼ 25 kpch −1 for interactions to statistically enhance star formation activity. For pairs within rp < 100 kpch −1 , we estimated a ∼27% contamination by spurious pairs, reduced to ∼19% for close systems. We also found that spurious pairs more strongly affect high density regions, with 17% of spurious pairs detected for low density regions compared to 33% found in high density ones. We analysed the dependence of star formation on environment by defining the usual projected density parameter for both pairs and isolated galaxies in the simulations. We find the expected star formation-local density relation for both galaxies in pairs and without a close companion, with a stronger density dependence for close pairs which suggests a relevant role for interactions in driving this relation.
Method for Automated Discovery of Network Communities within Mobile Communication Data

There has been considerable interest in methods for finding community structure in recent years. By using mobile communication data as the indicator of social relationships, we propose a fully automated method for identifying communities of practice within an organization. We use an improved G-N algorithm which can rapidly find communities within a network. We test this method on a set of mobile communication data and the result shows that the method is effective at identifying true communities. The efficiency and accuracy of the method make it feasible to be used for the accurate identification of community structure in social networks
Estimating Transpiration from Turfgrass Using Stomatal Conductance Values Derived from Infrared Thermometry

Infrared thermometry provides accurate measurements of plant canopy temperature, which, along with basic weather variables, allows estimation of canopy stomatal conductance to water vapor flux (gc) and transpiration. Using this method we compared modeled estimates of transpiration (CONDT) with evapotranspiration (ET) measurements from nearby microlysimeters (LYSET) in tall fescue (Schedonorus arundinaceus Schreb.) turfgrass. Results indicated transpiration may be reliably estimated via calculation of gc in turfgrass.
Beyond the blot: cutting edge tools for genomics, proteomics and metabolomics analyses and previous successes

The skin has an amazing array of complex interacting biological processes. Recent advances in investigational techniques now allow evaluation of these processes at the level of the gene, protein and metabolite. Sometimes collectively known as the omics, these fields of inquiry, known as genomics, proteomics and metabolomics, respectively, are yielding new and important insights into skin structure and processes, its responses to injury and age, and the mechanisms by which new interventions and compounds may work to improve the health and integrity of this crucial organ.
Performance Evaluation and Delay Modelling of VoIP Traffic over 802.11 Wireless Mesh Network

This paper analyzes voice quality in terms of R-Factor and MOS in IEEE 802.11s Wireless Mesh Network (WMN). Another issue addressed in this paper is the effect of increasing nodes on voice transmission in wireless mesh network. The simulation model developed allows identifying the main reasons for voice quality degradation in Mesh network. Results show that voice quality measured in terms of R-Factor and MOS degrades with increase in number of hops (Wireless Mesh Points) in Wireless Mesh network. Wireless mesh network has been modeled using M/D/1 queue and based on this analytical delay model, the average one way delay suffered by Voice over IP (VoIP) traffic has been calculated. Simulations have been conducted to validate the correctness of the analytical model.
Bypass Suppression of Small-Plaque Phenotypes by a Mutation in Poliovirus 2A That Enhances Apoptosis

ABSTRACT The rate of protein secretion in host cells is inhibited during infection with several different picornaviruses, with consequences likely to have significant effects on viral growth, spread, and pathogenesis. This Sin+ (secretion inhibition) phenotype has been documented for poliovirus, foot-and-mouth disease virus, and coxsackievirus B3 and can lead to reduced cell surface expression of major histocompatibility complex class I and tumor necrosis factor receptor as well as reduced extracellular secretion of induced cytokines such as interleukin-6 (IL-6), IL-8, and beta interferon. The inhibition of protein secretion is global, affecting the movement of all tested cargo proteins through the cellular secretion apparatus. To test the physiological significance of the Sin− and Sin+ phenotypes in animal models, Sin− mutant viruses are needed that fail to inhibit host protein secretion and also exhibit robust growth properties. To identify such Sin− mutant polioviruses, we devised a fluorescence-activated cell sorter-based screen to select virus-infected cells that nevertheless expressed newly synthesized surface proteins. After multiple rounds of selection, candidate Sin− mutant viruses were screened for genetic stability, increased secretion of cargo molecules and wild-type translation and growth properties. A newly identified Sin− mutant poliovirus that contained coding changes in nonstructural proteins 2A (N32D) and 2C (E253G) was characterized. In this virus, the 2C mutation is responsible for the Sin− phenotype and the 2A mutation suppresses a resulting growth defect by increasing the rate of cell death and therefore the rate of viral spread. The 2A-N32D suppressor mutation was not allele specific and, by increasing the rate of cellular apoptosis, affected a completely different pathway than the 2C-E253G Sin− mutation. Therefore, the 2A mutation suppresses the 2C-E253G mutant phenotype by a bypass suppression mechanism.
Study of dielectric behavior of aromatic polyimide films

Aromatic polyimide films were prepared and their dielectric constant and relaxation behavior were studied. Polyimide films have good insulating properties with dielectric constant values in the range of 2.88 – 3.48 at 1Hz and room temperature. Three relaxation processes (γ, β<inf>1</inf> and β<inf>2</inf>) at sub-glass temperatures were observed and investigated. The cooperativity of the molecular motions associated with the relaxation processes was discussed.
Automatic re-initialization and failure recovery for aggressive flight with a monocular vision-based quadrotor

Autonomous, vision-based quadrotor flight is widely regarded as a challenging perception and control problem since the accuracy of a flight maneuver is strongly influenced by the quality of the on-board state estimate. In addition, any vision-based state estimator can fail due to the lack of visual information in the scene or due to the loss of feature tracking after an aggressive maneuver. When this happens, the robot should automatically re-initialize the state estimate to maintain its autonomy and, thus, guarantee the safety for itself and the environment. In this paper, we present a system that enables a monocular-vision-based quadrotor to automatically recover from any unknown, initial attitude with significant velocity, such as after loss of visual tracking due to an aggressive maneuver. The recovery procedure consists of multiple stages, in which the quadrotor, first, stabilizes its attitude and altitude, then, re-initializes its visual state-estimation pipeline before stabilizing fully autonomously. To experimentally demonstrate the performance of our system, we aggressively throw the quadrotor in the air by hand and have it recover and stabilize all by itself. We chose this example as it simulates conditions similar to failure recovery during aggressive flight. Our system was able to recover successfully in several hundred throws in both indoor and outdoor environments.
Fuzzy Model Reference Adaptive Controller Design for Multivariable Nonlinear System

This paper describes the fuzzy model reference adaptive controller design for nonlinear system based on TSK model. The stability of closed-loop system can be assured by Lyapunov function and the adaptive law is developed. The parameters of the controller can be regulated by the adaptive rules and the control scheme is applied on the automatic gauge control system and spherical motor system as two examples. The analysis of dynamic performance for ordinary PID controller and fuzzy adaptive controller is performed in detail with simulation software. Simulation results verify the systems with strong adaptive ability and can adapt to the changes and disturbances of the controlled object. This study provides a theoretical guide for the configuration design, optimization and control research of multivariable nonlinear systems.
An Identification of Technology Opportunity on Dye-Sensitized Solar Cell

Solar cell, one of green energies, is growing at a fast pace with its clean and renewable characters in recent 20 years. Patent data contains plentiful technological information from which it is worthwhile to extract further knowledge. Thus, a research framework of grounded theory and text mining has been proposed in order to analyze the patent data of thin-film solar cell so as to explore its technology opportunity. Grounded theory is employed to provide a coding procedure for directing the human involvement, while text mining is adopted to provide the computing ability for performing the computer-aided data analysis. Consequently, the axial categories were identified, the selective category was recognized, the technology opportunity was explored, and the contributive organizations were also observed.
A General Framework for Compressed Sensing and Parallel MRI Using Annihilating Filter Based Low-Rank Hankel Matrix

Parallel MRI (pMRI) and compressed sensing MRI (CS-MRI) have been considered as two distinct reconstruction problems. Inspired by recent k-space interpolation methods, an annihilating filter-based low-rank Hankel matrix approach is proposed as a general framework for sparsity-driven k-space interpolation method which unifies pMRI and CS-MRI. Specifically, our framework is based on a novel observation that the transform domain sparsity in the primary space implies the low-rankness of weighted Hankel matrix in the reciprocal space. This converts pMRI and CS-MRI to a k-space interpolation problem using a structured matrix completion. Experimental results using in vivo data for single/multicoil imaging as well as dynamic imaging confirmed that the proposed method outperforms the state-of-the-art pMRI and CS-MRI.
Circulant Preconditioners for Solving Three-Dimensional Convection-Diffusion Equations

We consider the system of equations arising from finite difference discretization of a three-dimensional convection-diffusion model problem. This system is typically nonsymmetric. Krylov subspace methods (for instance, the GMRES method) with the Strang block-circulant preconditioners are proposed for solving this linear system. We prove that our preconditioners are invertible and all the eigenvalues of the preconditioned systems are 1 except at most 2n outliers, where n is the number of grid points. We further demonstrate that the convergence rate of the GMRES method depends only on the cell Reynolds numbers but does not on n. Numerical results are reported to illustrate the effectiveness of our methods. Key-Words: Circulant preconditioners, Krylov subspace methods, convection diffusion equations 1 Research supported by RGC Grant No. HKU 7147/99P and HKU CRCG Grant No. 10201939.
Prevention of Surgical Malpractice Claims by Use of a Surgical Safety Checklist

Objective:To assess what proportion of surgical malpractice claims might be prevented by the use of a surgical safety checklist. Background:Surgical disciplines are overrepresented in the distribution of adverse events. The recently described multidisciplinary SURgical PAtient Safety System (SURPASS) checklist covers the entire surgical pathway from admission to discharge and is being validated in various ways. Malpractice claims constitute an important source of information on adverse events. In this study, surgical malpractice claims were evaluated in detail to assess the proportion and nature of claims that might have been prevented if the SURPASS checklist had been used. Methods:A retrospective claim record review was performed using the database of the largest Dutch insurance company for medical liability. All accepted or settled closed surgical malpractice claims filed as a consequence of an incident that occurred between January 1, 2004 and December 31, 2005 were included. Data on the type and outcome of the incident and contributing factors were extracted. All contributing factors were compared to the SURPASS checklist to assess which incidents the checklist might have prevented. Results:We included 294 claims. Failure in diagnosis and peroperative damage were the most common types of incident; cognitive contributing factors were present in two-thirds of claims. Of a total of 412 contributing factors, 29% might have been intercepted by the SURPASS checklist. The checklist might have prevented 40% of deaths and 29% of incidents leading to permanent damage. Conclusion:Nearly one-third of all contributing factors in accepted surgical malpractice claims of patients that had undergone surgery might have been intercepted by using a comprehensive surgical safety checklist. A considerable amount of damage, both physical and financial, is likely to be prevented by using the SURPASS checklist.
A scale-space based hierarchical representation of discrete data

A new hierarchical representation of general discrete data sets living on graphs is proposed. The approach takes advantage of recent works on graph regularization. The different levels of the hierarchy are discovered as the regularization process is performed. The role of the merging criterion that is common to hierarchical representations is greatly reduced due to the regularization step. This yields a robust representation of data sets. Moreover, the approach is particularly well adapted to the processing of digital images, where nonlocal processing allows to better handle repetitive patterns usually present in natural images.
Fluctuations in intra‐ocular pressure with sleep:

Intra‐ocular pressure (IOP) was measured immediately after normal subjects were woken from at least 5 hours sleep. Measurements were made at approximately 15 s intervals, for about 20 minutes. The IOP of all 14 subjects was elevated after sleep and returned to baseline levels with a time course which was approximately exponential; the longest time constant of return of IOP to baseline was 1056.9 s, and the shortest 133.5 s. Mean time constant of recovery was 404.8 s. The decrease in IOP may be related to melatonin levels which increase during sleep and decrease in the light, or be related to accommodation and eye movements which may act to ‘pump’ aqueous from the eye.