Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydrogen-Rich Saline Promotes the Recovery of Renal Function after Ischemia/Reperfusion Injury in Rats via Anti-apoptosis and Anti-inflammation

Purpose: Hydrogen is a proven novel antioxidant that selectively reduces hydroxyl radicals. In this study, we investigated the effects of hydrogen-rich saline solution on the prevention of renal injury induced by ischemia/reperfusion (I/R) and on renal function recovery. Methods: A rat model of renal I/R injury was induced by 45 min occlusion of the left renal pedicle, followed by 108 h reperfusion. The right kidney was surgically removed. Then, 0.9% NaCl solution (1 ml/kg) or hydrogen-rich saline solution (HRSS; 1 ml/kg) was injected into the abdominal cavity at 4 h intervals. We assessed the influence of HRSS or control saline solution on the recovery of renal function after I/R injury. Kidney tissues were taken at different time points (24, 36, 48, 72, and 108 h after reperfusion) and frozen (-80°C). Kidney cell apoptosis was evaluated using terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL)-positive staining. Additionally, the apoptotic factors (Bcl-2, Bax, caspase-3, caspase-9, and caspase-8) and the pro-inflammatory cytokines (IL-6 and TNF-α) were measured in the kidney tissues. Finally, serum blood urea nitrogen (BUN) and creatinine (Cr) levels were measured. Results: Histological analyses revealed a marked reduction of interstitial congestion, edema and hemorrhage in renal tissue after HRSS treatment compared to saline treatment. After I/R injury, BUN, Cr, Bcl-2, caspase-3, caspase-9, caspase-8, IL-6, and TNF-α were all significantly increased, while Bax expression was decreased. HRSS remarkably reversed these changes. Moreover, BUN and Cr decreased more rapidly in the rats treated with HRSS compared to the rats treated with control saline solution. Conclusions: HRSS showed a protective effect in the prevention of renal injury and could promote renal function recovery after I/R injury in rats. HRSS might partially exert its role through an anti-apoptotic and anti-inflammatory action in kidney cells.
Time delay oriented reliability analysis of Avionics Full Duplex Switched Ethernet

Besides the hardware/software failure of switched Ethernet, the capability of data transmission affects its performance and reliability. After summarizing the influence factors of Ethernet service capability, this paper focuses on the time delay oriented reliability model and analysis method. Based on the operational mechanism analysis of Avionics Full Duplex Switched Ethernet (AFDX), this paper emphasizes on the main factors that affect the data transmission capability, viz. the traffic shaping delay and scheduling delay. With the token bucket principle, this paper carries out the traffic shaping to decrease the sudden traffic disturbance. Based on First Come First Service (FCFS) strategy, this paper provides the appropriate service and controls the multiple virtual links in real time. Combining the traffic shaping delay and adjustment delay to traditional reliability model, this paper establishes the integrated reliability model to evaluate the reliability of AFDX.
Mining event logs with SLCT and LogHound

With the growth of communication networks, event logs are increasing in size at a fast rate. Today, it is not uncommon to have systems that generate tens of gigabytes of log data per day. Log data are likely to contain information that deserves closer attention - such as security events - but the task of reviewing logs manually is beyond the capabilities of a human. This paper discusses data mining tools SLCT and log hound that were designed for assisting system management personnel in extracting knowledge from event logs.
AUTOMATION IN 3 D RECONSTRUCTION : RESULTS ON DIFFERENT KINDS OF CLOSE-RANGE BLOCKS

Automation in 3D reconstruction involves mainly two tasks: (i) image orientation and (ii) 3D scene reconstruction. Nowadays, automation in (i) can be considered solved for aerial photogrammetric projects, but a general and commercial solution is still pending in case of close-range image blocks. Here, the complexity and diversity of the network geometry make the automatic identification of the image correspondences a challenging task. In this paper we present a methodology to automatically orient a set of targetless close-range images taken with a calibrated camera and the following creation of 3D models with a multi-image matching algorithm. Several real cases, comprehending free-form objects (e.g. bas-relieves, decorations, etc.), building facades and images taken with UAVs are reported and discussed. Lastly, some preliminary results on a methodology for markerless camera calibration are presented.
Informal communication re-examined: New functions for video in supporting opportunistic encounters

Many systems have used video to support formal distributed meetings. Rrecent research, however, indicates that most workplace interactions are not group meetings. Instead they occur spontaneously for short periods of time, frequently between two people who discuss topics that build on prior discussions. In this paper, we characterise these informal interactions, describe their value, enumerate the functions they accomplish. We consider ways to design video-based systems to support such informal interactions among different types of distributed groups. We discuss some existing applications that support various aspects of informal communication and consider ways to build on those ideas to build systems designed specifically for opportunistic and spontaneous encounters.
Identification of Proteins in the Postsynaptic Density Fraction by Mass Spectrometry

Our understanding of the organization of postsynaptic signaling systems at excitatory synapses has been aided by the identification of proteins in the postsynaptic density (PSD) fraction, a subcellular fraction enriched in structures with the morphology of PSDs. In this study, we have completed the identification of most major proteins in the PSD fraction with the use of an analytical method based on mass spectrometry coupled with searching of the protein sequence databases. At least one protein in each of 26 prominent protein bands from the PSD fraction has now been identified. We found 7 proteins not previously known to be constituents of the PSD fraction and 24 that had previously been associated with the PSD by other methods. The newly identified proteins include the heavy chain of myosin-Va (dilute myosin), a motor protein thought to be involved in vesicle trafficking, and the mammalian homolog of the yeast septin protein cdc10, which is important for bud formation in yeast. Both myosin-Va and cdc10 are threefold to fivefold enriched in the PSD fraction over brain homogenates. Immunocytochemical localization of myosin-Va in cultured hippocampal neurons shows that it partially colocalizes with PSD-95 at synapses and is also diffusely localized in cell bodies, dendrites, and axons. Cdc10 has a punctate distribution in cell bodies and dendrites, with some of the puncta colocalizing with PSD-95. The results support a role for myosin-Va in transport of materials into spines and for septins in the formation or maintenance of spines.
Adapting radio transmit power in wireless body area sensor networks

Emerging body-wearable devices for continuous health monitoring are severely energy constrained and yet required to offer high communication reliability under fluctuating channel conditions. This paper investigates the dynamic adaptation of radio transmit power as a means of addressing this challenge. Our contributions are three-fold: we present empirical evidence that wireless link quality in body area networks changes rapidly when patients move; fixed radio transmit power therefore leads to either high loss (when link quality is bad), or wasted energy (when link quality is good). This motivates dynamic transmit power control, and our second contribution characterises the off-line optimal transmit power control that minimises energy usage subject to lower-bounds on reliability. Though not suited to practical implementation, the optimal gives insight into the feasibility of adaptive power control for body area networks, and provides a benchmark against which practical strategies can be compared. Our third contribution is to develop simple and practical on-line schemes that trade-off reliability for energy savings by changing transmit power based on feedback information from the receiver. Our schemes offer on average 9--25% savings in energy compared to using maximum transmit power, with little sacrifice in reliability, and demonstrate adaptive transmission power control as an effective technique for extending the lifetime of wireless body area sensor networks.
International Conference on Information Systems ( ICIS ) 1231-2006 Measures for Quantitative Process-Tracing Methods

To know the decision strategy and the underlying information acquisition behavior of a person is essential for the design of computer programs that support managerial and consumer decision making. Both quantitative methods (e.g. computer-assisted process-tracing systems) and qualitative methods (e.g. verbal protocols) are used to investigate information acquisition behavior of managers and consumers, respectively, and to detect their decision strategies. This article presents measures that allow for the detection of important decision strategies—that is, one is able to distinguish decision strategies from each other. The presented measures are the methodological basis of widely used quantitative process-tracing methods such as computerized process-tracing (CPT) tools or eye-tracking systems. The article concludes that the measures and their application within CPT tools or eye-tracking systems constitute the basic foundation of an emerging research field called clickstream analysis, which is a method to investigate human decision processes by analyzing computer log files.
Characterization of Naturally-Occurring Humoral Immunity to AAV in Sheep

AAV vectors have shown great promise for clinical gene therapy (GT), but pre-existing human immunity against the AAV capsid often limits transduction. Thus, testing promising AAV-based GT approaches in an animal model with similar pre-existing immunity could better predict clinical outcome. Sheep have long been used for basic biological and preclinical studies. Moreover, we have re-established a line of sheep with severe hemophilia A (HA). Given the impetus to use AAV-based GT to treat hemophilia, we characterized the pre-existing ovine humoral immunity to AAV. ELISA revealed naturally-occurring antibodies to AAV1, AAV2, AAV5, AAV6, AAV8, and AAV9. For AAV2, AAV8, and AAV9 these inhibit transduction in a luciferase-based neutralization assay. Epitope mapping identified peptides that were common to the capsids of all AAV serotypes tested (AAV2, AAV5, AAV8 and AAV9), with each animal harboring antibodies to unique and common capsid epitopes. Mapping using X-ray crystallographic AAV capsid structures demonstrated that these antibodies recognized both surface epitopes and epitopes located within regions of the capsid that are internal or buried in the capsid structure. These results suggest that sheep harbor endogenous AAV, which induces immunity to both intact capsid and to capsid epitopes presented following proteolysis during the course of infection. In conclusion, their clinically relevant physiology and the presence of naturally-occurring antibodies to multiple AAV serotypes collectively make sheep a unique model in which to study GT for HA, and other diseases, and develop strategies to circumvent the clinically important barrier of pre-existing AAV immunity.
Enclosing Machine Learning

As known to us, the cognition process is the instinct learning ability of the human being. This process is perhaps one of the most complex human behaviors. It is a highly efficient and intelligent information processing process. For a cognition process of the natural world, humans always transfer the feature information to the brain through their perception, and then the brain processes the feature information and remembers it. Due to the invention of computers, scientists are now working toward improving its artificial intelligence, and they hope that one day the computer could have its intelligent “brain” as human does. However, it is still a long way for us to go in order to let a computer truly “think” by itself. Currently, artificial intelligence is an important and active research topic. It imitates the human brain using the idea of function equivalence. Traditionally, the neural computing and neural networks families are the majority parts of the direction (Haykin, 1994). By imitating the working mechanism of the human-brain neuron, scientists have built the neural networks theory following experimental research such as perception neurons and spiking neurons (Gerstner & Kistler, 2002) in order to understand the working mechanism of neurons. Neural-computing and neural networks (NN) families (Bishop, 1995) have made great achievements in various aspects. Recently, statistical learning and support vector machines (SVM) (Vapnik, 1995) have drawn extensive attention and shown better performances in various areas (Li, Wei & Liu, 2004) than NN, which implies that artificial intelligence can also be made via advanced statistical computing theory. Nowadays, these two methods tend to merge under the statistical learning theory framework. BACKGROUND
Quantized neural network design under weight capacity constraint

The complexity of deep neural network algorithms for hardware implementation can be lowered either by scaling the number of units or reducing the word-length of weights. Both approaches, however, can accompany the performance degradation although many types of research are conducted to relieve this problem. Thus, it is an important question which one, between the network size scaling and the weight quantization, is more effective for hardware optimization. For this study, the performances of fully-connected deep neural networks (FCDNNs) and convolutional neural networks (CNNs) are evaluated while changing the network complexity and the word-length of weights. Based on these experiments, we present the effective compression ratio (ECR) to guide the trade-off between the network size and the precision of weights when the hardware resource is limited.
Multistate Nonhomogeneous Semi-Markov Model of Daily Activity Type, Timing, and Duration Sequence

Understanding travelers’ daily travel activity pattern formation is an important issue for activity-based travel-demand analysis. The activity pattern formation concerns not only complex interrelations between household members and individuals’ sociodemographic characteristics but also urban form and transport system settings. To investigate the effects of these attributes and the interrelationship between conducted activities, a multistate semi-Markov model is applied. The underlying assumption of the proposed model is that the state transition probability depends on its adjoining states. The statistical tests of significance affirm that the duration of activity depends not only on its beginning time of day but also on the duration of travel or activity previously conducted. An empirical study based on the Belgian mobility survey is conducted to estimate individuals’ daily activity durations of different episodes and provides useful insight for the effects of sociodemographic characteristics, urban and transportation system settings on the activity pattern formation.
Simulation of PMSM based on current hysteresis PWM and Fed PI controller

The Permanent Magnet Synchronous Motors (PMSM) have gained an increasing interest recently. The wide varieties of applications of PMSM drive make it necessary to achieve fast and reliable control system. At the basis of analysis of the mathematical model of PMSM and the principle of current hysteresis PWM (Pulse Width Modulation) is proposed. In MATLAB/Simulink, the simulation model of whole system is built, two control loops are used, which are inner current loop and outer speed loop. A new PI control method is proposed in this paper. In this system, PI control is used in current loop and Fed PI control is used in speed loop instead of traditional PI control. The effectiveness of the proposed control method is verified by simulation based on MATLAB. The FedPI controller has better performance than conventional PI controller in PMSM drive system.
Will Sofosbuvir/Ledipasvir (Harvoni) Be Cost-Effective and Affordable for Chinese Patients Infected with Hepatitis C Virus? An Economic Analysis Using Real-World Data

Background Little is known on the cost-effectiveness of novel regimens for hepatitis C virus (HCV) compared with standard-of-care with pegylated interferon (pegIFN) and ribavirin (RBV) therapy in developing countries. We evaluated cost-effectiveness of sofosbuvir/ledipasvir for 12 weeks compared with a 48-week pegIFN-RBV regimen in Chinese patients with genotype 1b HCV infection by economic regions. Methods A decision analytic Markov model was developed to estimate quality-adjusted-life-years, lifetime cost of HCV infection and incremental cost-effectiveness ratios (ICERs). SVR rates and direct medical costs were obtained from real-world data. Parameter uncertainty was assessed by one-way and probabilistic sensitivity analyses. Threshold analysis was conducted to estimate the price which can make the regimen cost-effective and affordable. Results Sofosbuvir/ledipasvir was cost-effective in treatment-experienced patients with an ICER of US$21,612. It varied by economic regions. The probability of cost-effectiveness was 18% and 47% for treatment-naive and experienced patients, and it ranged from 15% in treatment-naïve patients in Central-China to 64% in treatment-experienced patients in Eastern-China. The price of 12-week sofosbuvir/ledipasvir treatment needs to be reduced by at least 81% to US$18,185 to make the regimen cost-effective in all patients at WTP of one time GDP per capita. The price has to be US$105 to make the regimen affordable in average patients in China. Conclusion Sofosbuvir/ledipasvir regimen is not cost-effective in most Chinese patients with genotype 1b HCV infection. The results vary by economic regions. Drug price of sofosbuvir/ledipasvir needs to be substantially reduced when entering the market in China to ensure the widest accessibility.
ON THE LABOUR MARKET BWP . 2003 / 5 Job-training of Hungarian higher-education graduates

Considerable amounts of time and money are spent on job-training of school-leavers graduated from higher-education institutions. More than a half of the employees in our sample participated in job-training between graduation date (1999) and September 2000. The work in this paper considers two aspects of the problem. First, the relationship between training probability/training length and the initial human capital (proxied by level of education and in-school labour market experience) is concerned with, and, second, some elements of the training-costsharing decision is analysed. There are some signs that university education reduces the probability of training as compared to college education, whereas in-school labour market experience increases it. University education reduces training length, as well. In-school labour market experience has no effect on the length of job-training. Another important result is that school-leavers holding diplomas with “narrower” types of education are more likely to obtain training, and also to have longer training programmes. This implies a more severe matching problem in the case of “narrower” types of education, possibly due to prohibitive searching costs for finding a good-quality match. Results for the cost-sharing decision are in line with Becker’s idea, since the firm is less likely to entirely cover the costs of general training and more likely to finance job-specific training programmes.
Low complexity blind separation technique to solve the permutation ambiguity of convolutive speech mixtures

Microphone arrays can be incorporated in several devices ranging from hearing aids and bioacoustic recording equipment to teleconference phones and forensic sound recorders in order to attenuate the interference of unwanted sounds. The separation of speech mixtures can be easily performed on the frequency domain independently for each frequency component. However, in order to combine the separated signals of each frequency component, the permutation ambiguity should be solved. The state-of-the-art technique relies on an iterative computation of the dispersions of the differences between the source profiles. In this paper, we propose a low complexity solution for the permutation ambiguity with similar accuracy based on one dispersion.
EVD-based channel estimation in multicell multiuser MIMO systems with very large antenna arrays

This paper considers multicell multiuser MIMO systems with very large antenna arrays at the base station. We propose an eigenvalue-decomposition-based approach to channel estimation, that estimates the channel blindly from the received data. The approach exploits the asymptotic orthogonality of the channel vectors in very large MIMO systems. We show that the channel to each user can be estimated from the covariance matrix of the received signals, up to a remaining scalar multiplicative ambiguity. A short training sequence is required to resolve this ambiguity. Furthermore, to improve the performance of our approach, we combine it with the iterative least-square with projection (ILSP) algorithm. Numerical results verify the effectiveness of our channel estimation approach.
Hippocampal CA1 Pyramidal Neurons Dendritic Mechanisms of Phase Precession in

You might find this additional info useful.This article cites€22 articles, 9 of which you can access for free at: http://jn.physiology. org/content/86/1/528.full#ref-list-1This article has been cited by€15 other HighWire-hosted articles: http://jn.physiology. org/content/86/1/528#cited-by Updated information and services including high resolution figures, can be found at: http://jn.physiology. org/content/86/1/528.fullAdditional material and information about Journal of Neurophysiology can be found at: http://www.the-aps.org/publications/jnThis information is current as of June 12, 2013.
Automatic lesion detection in wireless capsule endoscopy — A simple solution for a complex problem

Wireless capsule endoscopy (WCE) is performed with a swallowable miniature optical endoscope which transmits color images wirelessly during its journey in the gastrointestinal tract. In this paper we present a computationally efficient and effective approach to cope with automatic detection of possible abnormalities in the WCE videos and consequently with the reduction of the time required for the WCE inspection. It involves automatic detection of salient points based on color information and supervised classification of simple color vectors extracted from the neighborhood of each point. The experiments performed aim to determine the optimal color space components for feature extraction, and identification of abnormalities. Main advantages of this approach are its computational efficiency, its sensitivity to detect small lesions, and its generality. The results obtained from experimentation with a dataset with various types of abnormalities and non-ideal normal frames, approximate 0.9 in terms of the area under receiver operating characteristic (ROC).