Miracle-dz/UniFAR-FTUs huggingface dataset:
Randomized comparison of intra-aortic balloon support with a percutaneous left ventricular assist device in patients with revascularized acute myocardial infarction complicated by cardiogenic shock.

AIMS Mortality in cardiogenic shock (CS) following acute myocardial infarction (AMI) remains unacceptably high despite percutaneous coronary intervention (PCI) of the infarcted artery and use of intra-aortic balloon pump (IABP) counterpulsation. A newly developed percutaneous left ventricular assist device (VAD) (Tandem Heart, Cardiac Assist, Pittsburgh, PA, USA) with active circulatory support might have positive haemodynamic effects and decrease mortality. METHODS AND RESULTS Patients in CS after AMI, with intended PCI of the infarcted artery, were randomized to either IABP (n=20) or percutaneous VAD support (n=21). The primary outcome measure cardiac power index, as well as other haemodynamic and metabolic variables, could be improved more effectively by VAD support from 0.22 [interquartile range (IQR) 0.19-0.30] to 0.37 W/m2 (IQR 0.30-0.47, P<0.001) when compared with IABP from 0.22 (IQR 0.18-0.30) to 0.28 W/m2 (IQR 0.24-0.36, P=0.02; P=0.004 for intergroup comparison). However, complications like severe bleeding (n=19 vs. n=8, P=0.002) or limb ischaemia (n=7 vs. n=0, P=0.009) were encountered more frequently after VAD support, whereas 30 day mortality was similar (IABP 45% vs. VAD 43%, log-rank, P=0.86). CONCLUSION Haemodynamic and metabolic parameters can be reversed more effectively by VAD than by standard treatment with IABP. However, more complications were encountered by the highly invasive procedure and by the extracorporeal support.
Fading-Aware Packet Scheduling Algorithm in OFDM-MIMO Systems

To maximize system throughput and guarantee the quality of service (QoS) of multimedia traffic in orthogonal frequency division multiplexing (OFDM) systems with smart antennas, a new packet scheduler is introduced to consider QoS requirements, packet location in the frame, and modulation level. In the frequency domain, several consecutive subchannels are grouped as a frequency subband. Each subband in a frame can be used to transmit a packet, and can be reused by several users in a multiple-input and multiple-output (MIMO) systems. In this paper, we consider the adaptive packet scheduling algorithms design for OFDM/SDMA system. Based on the BER requirements, all traffics are divided into classes. Based on such classification, a dynamic packet scheduler is proposed, which greatly improves system capacity, and can guarantee QoS requirements. Adaptive modulation is also applied in the scheduler. Then, the complexity analysis of these algorithms is given. When compared with existing schedulers, our scheduler achieves higher system capacity with much reduced complexity. The use of adaptive modulation further enhances the system capacity. Simulation results demonstrate that as the traffic load increases, the new scheduler has much better performance in system throughput, average delay, and packet loss rate.
On System Scalability

Abstract : A significant number of systems fail in initial use or even during integration because factors that have a negligible effect when systems are lightly used have a harmful effect as the level of use increases. This scalability problem (i.e. the inability of a system to accommodate an increased workload) is not new. However the increasing size (more lines of code, greater number of users, widened scope of demands and the like) of US Department of Defense systems makes the problem more critical today than in the past. This technical note presents an analysis of what is meant by scalability and a description of factors to be considered when assessing the potential for system scalability. The factors to be considered are captured in a scalability audit, a process intended to expose issues that if overlooked can lead to scalability problems
STT-RAM for Shared Memory in GPUs

In the context of massively parallel processors such as Graphics Processing Units (GPUs), an emerging non-volatile memory – STT-RAM – provides substantial power, area savings, and increased capacity compared to the conventionally used SRAM. The use of highly dense, low static power STT-RAM in processors that run just few threads of execution does not seem attractive because of several times slower write latency, which can relatively impair the performance of the system. However, hundreds to thousands of threads executing in parallel in high-throughput GPUs hide the long write latency of STT-RAM through fine-grained multithreading. In this thesis, evaluation of possibility of STT-RAM for the shared memory in GPUs was done. Performance, energy and area were evaluated across various configurations of shared memory capacity, banks and ports across a set of benchmarks displaying different characteristics. Results show performance degrades only up to 2% on average for an STT-RAM write latency, which is four times that of SRAM write latency. Performance is even increased by 20% on average when the denser STT-RAM is used to increase shared memory capacity, banks and ports. The energy savings are up to 17% and area savings up to 50%. The evaluation helps understand the trade-offs involved in the use of STT-RAM in GPUs. In the process, a few configurations were identified which encourage their use. To better understand the low impact of high shared memory latency on GPU’s performance, a theoretical analysis was done.
Multi-view Based Estimation of Human Upper-Body Orientation

The knowledge about the body orientation of humans can improve speed and performance of many service components of a smart-room. Since many of such components run in parallel, an estimator to acquire this knowledge needs a very low computational complexity. In this paper we address these two points with a fast and efficient algorithm using the smart-room's multiple camera output. The estimation is based on silhouette information only and is performed for each camera view separately. The single view results are fused within a Bayesian filter framework. We evaluate our system on a subset of videos from the CLEAR 2007 dataset and achieve an average correct classification rate of 87.8%, while the estimation itself just takes 12 ms when four cameras are used.
Neo-Hertzian Wave Equation for Variable Detector Velocity

It is shown that a d’Alembertian solution previously obtained for the neoHertzian wave equation under the restriction that detector (absorber) velocity is constant holds likewise with minor modification in the more general case in which that velocity is an arbitrary function of time. Remarks are made also on the two-way averaging of light speed in neo-Hertzian electromagnetism.
Post stroke interpersonal communication: An intimate exploration of stroke survivors' lived experiences

This qualitative study explores the personal and intimate lived experiences of stroke survivors who suffer the comorbid emotional sequelae of Post Stroke Depression (PSD) and how it affects their rehabilitation and interpersonal relationships post stroke. By using Uncertainty Reduction Theory (URT), the idea of Social Construction of Identity, the epistemology of Narrative Inquiry (NI), and conversational interviews (CI), with stroke survivors, their spouses/significant others, friends, and other family members, the aim of this body of research has been to take on the difficult task of observing how stroke survivors navigate the difficult and sometimes daunting path that all stroke survivors must travel as they attempt the reconstruction of their se lf post stroke. They face every new day with the knowledge of who they once were and who they are now. The person that they are now has become their reality. Many stroke survivors regardless of the hemisphere in which the brain lesion occurs, suffer from some degree of the post stroke emotional sequelae, or a condition following and resulting from a disease, of post stroke depression (PSD). With the comorbid occurrence of PSD comes yet another challenge to their reconstruction process. The findings of this research study have remained consistent with the current research data and literature on stroke, stroke recovery, PSD, and aphasia.
Vibrations of a beam between stops: convergence of a fully discretized approximation

We consider the dynamics of an elastic beam which is clamped at its left end to a vibrating support and which can move freely at its right end between two rigid obstacles (the stops). We model the contact with Sig- norini’s complementary conditions between the displacement and the shear stress. For this inﬁnite dimensional contact problem, we propose a family of fully discretized approximations and their convergence is proved. Moreover some examples of implementation are presented.
Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host’s inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.
Inhibition of PI3K/AKT/mTOR axis disrupts oxidative stress-mediated survival of melanoma cells

Elevated oxidative stress in cancer cells contributes to hyperactive proliferation and enhanced survival, which can be exploited using agents that increase reactive oxygen species (ROS) beyond a threshold level. Here we show that melanoma cells exhibit an oxidative stress phenotype compared with normal melanocytes, as evidenced by increased total cellular ROS, KEAP1/NRF2 pathway activity, protein damage, and elevated oxidized glutathione. Our overall objective was to test whether augmenting this high oxidative stress level in melanoma cells would inhibit their dependence on oncogenic PI3K/AKT/mTOR-mediated survival. We report that NexrutineR augmented the constitutively elevated oxidative stress markers in melanoma cells, which was abrogated by N-acetyl cysteine (NAC) pre-treatment. NexrutineR disrupted growth homeostasis by inhibiting proliferation, survival, and colony formation in melanoma cells without affecting melanocyte cell viability. Increased oxidative stress in melanoma cells inhibited PI3K/AKT/mTOR pathway through disruption of mTORC1 formation and phosphorylation of downstream targets p70S6K, 4EBP1 and rpS6. NAC pre-treatment reversed inhibition of mTORC1 targets, demonstrating a ROS-dependent mechanism. Overall, our results illustrate the importance of disruption of the intrinsically high oxidative stress in melanoma cells to selectively inhibit their survival mediated by PI3K/AKT/mTOR.
Event Tracking for Real-Time Unaware Sensitivity Analysis (EventTracker)

This paper introduces a platform for online Sensitivity Analysis (SA) that is applicable in large scale real-time data acquisition (DAQ) systems. Here, we use the term real-time in the context of a system that has to respond to externally generated input stimuli within a finite and specified period. Complex industrial systems such as manufacturing, healthcare, transport, and finance require high-quality information on which to base timely responses to events occurring in their volatile environments. The motivation for the proposed EventTracker platform is the assumption that modern industrial systems are able to capture data in real-time and have the necessary technological flexibility to adjust to changing system requirements. The flexibility to adapt can only be assured if data is succinctly interpreted and translated into corrective actions in a timely manner. An important factor that facilitates data interpretation and information modeling is an appreciation of the affect system inputs have on each output at the time of occurrence. Many existing sensitivity analysis methods appear to hamper efficient and timely analysis due to a reliance on historical data, or sluggishness in providing a timely solution that would be of use in real-time applications. This inefficiency is further compounded by computational limitations and the complexity of some existing models. In dealing with real-time event driven systems, the underpinning logic of the proposed method is based on the assumption that in the vast majority of cases changes in input variables will trigger events. Every single or combination of events could subsequently result in a change to the system state. The proposed event tracking sensitivity analysis method describes variables and the system state as a collection of events. The higher the numeric occurrence of an input variable at the trigger level during an event monitoring interval, the greater is its impact on the final analysis of the system state. Experiments were designed to compare the proposed event tracking sensitivity analysis method with a comparable method (that of Entropy). An improvement of 10 percent in computational efficiency without loss in accuracy was observed. The comparison also showed that the time taken to perform the sensitivity analysis was 0.5 percent of that required when using the comparable Entropy-based method.
ANALISIS PENGARUH KEPERCAYAAN, RELIGIUSITAS DAN KONTRIBUSI TERHADAP MINAT PEDAGANG MENGELUARKAN ZAKAT DI BAITUL MAL (STUDI KASUS PADA PEDAGANG PASAR LOS LHOKSEUMAWE)

The purpose of this study to analyze the influence of trust, religiosity, and contributing to the interest of traders in Pasar Los Kota Lhokseumawe issue a zakat in Baitul Mal. The object of this research is the traders with the sampling technique using a simple random sample (sample random sampling). Samples numbered 69 merchants. Collecting data using questionnaires. Data analysis techniques with descriptive approach qualitative and quantitative analysis in linear regression. Measurements using a Likert scale with an answer from one to five. From the results if the data using regression model showed that Y = 4, 295 + 0, 406 X 1 - 0.261 X 2 + 0,645 X 3 . While the test results partially to the influence of the trust factor (X 1 ) significantly at 4.988, greater than the value t table is 1.997 at α = 5% influence factor religiustas (X 2 ) is 2.733, larger than the value of t is 1.997 at α = 5 % and the effect of contributing factors (X 3 ) of 7.738, is greater than the value t table is 1.997 at a = 5%. Means partial trust factor and the contribution of each positive effect on the interest issue a zakat in the treasury, while the religiosity factor negatively affect the interests issued zakat in treasury. Each independent variable has a value of t is greater than t table on significant α = 5%. Simultaneous testing of the trust factor, religiosity can contribute to the effects of issuing zakat in treasury conducted by market traders Los town of Lhokseumawe result f calculated at 132.278 and f table 3.14. f indicate when the count is greater than f table by using an interest rate of 95 %, α = 5 % (0.05). Results of the data showed no significant effect simultaneously, then the hypothesis Ho is rejected. From these studies it can be concluded that there is influence of trust and contributing to the process of determining interest by traders in issuing zakat either partially or simultaneously testing, while for the factor of religiosity have smaller influence in determining the interest of traders in issuing treasury zakat in Lhokseumawe.
Towards Localizing Root Causes of BGP Dynamics

Today, we lack a clear understanding of the dynamics of the Border Gateway Protocol (BGP) and this has largely restricted our ability to address BGP’s shortcomings. To gain more insight into BGP’s dynamics, this paper proposes the design of a BGP health inferencing system that localizes the root causes of routing changes. Specifically, the inference system addresses two questions:What is the cause of a routing change? Where does a routing change originate? The inference system correlates routing updates across multiple vantage points to narrow down thesuspect set of AS’s that might have triggered routing changes. Our methodology is primarily targeted towards analyzing events affecting relatively stable prefixes (composing roughly 80% of the routing table), which are known to be the most popular destinations of Internet traffic. For 70% of observed updates to these prefixes, our approach can pinpoint the location of origin to a single inter-AS link. We analytically and empirically argue correctness of several key steps of our methodology and additionally show that our technique can correctly pinpoint the source of several well-known/ documented routing events.
A Novel SURE-Based Criterion for Parametric PSF Estimation

We propose an unbiased estimate of a filtered version of the mean squared error - the blur-SURE (Stein's unbiased risk estimate)-as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.
An Analysis of the Impact of 2.0 Tools and Technologies on Organizational Processes

In this paper, the authors present results from a study on the usage rate of 2.0 tools and technologies among Spanish enterprises. The main objective of the study is to analyze, from the perceptions of executives, the influence of social software tools on a set of business processes. This analysis has been made using two graphic tools: the â€œ2.0 Success Matrixâ€ and the â€œToolâ€™s Footprintâ€ . Both the review of literature and the empirical work have lead to important findings and conclusions.
Arthrobacter aurescens TC1 Metabolizes Diverse s-Triazine Ring Compounds

ABSTRACT Arthrobacter aurescens strain TC1 was isolated without enrichment by plating atrazine-contaminated soil directly onto atrazine-clearing plates. A. aurescens TC1 grew in liquid medium with atrazine as the sole source of nitrogen, carbon, and energy, consuming up to 3,000 mg of atrazine per liter. A. aurescens TC1 is metabolically diverse and grew on a wider range of s-triazine compounds than any bacterium previously characterized. The 23 s-triazine substrates serving as the sole nitrogen source included the herbicides ametryn, atratone, cyanazine, prometryn, and simazine. Moreover, atrazine substrate analogs containing fluorine, mercaptan, and cyano groups in place of the chlorine substituent were also growth substrates. Analogs containing hydrogen, azido, and amino functionalities in place of chlorine were not growth substrates. A. aurescens TC1 also metabolized compounds containing chlorine plus N-ethyl, N-propyl, N-butyl, N-s-butyl, N-isobutyl, or N-t-butyl substituents on the s-triazine ring. Atrazine was metabolized to alkylamines and cyanuric acid, the latter accumulating stoichiometrically. Ethylamine and isopropylamine each served as the source of carbon and nitrogen for growth. PCR experiments identified genes with high sequence identity to atzB and atzC, but not to atzA, from Pseudomonas sp. strain ADP.
Peritruncal Coronary Endothelial Cells Contribute to Proximal Coronary Artery Stems and Their Aortic Orifices in the Mouse Heart

Avian embryo experiments proved an ingrowth model for the coronary artery connections with the aorta. However, whether a similar mechanism applies to the mammalian heart still remains unclear. Here we analyzed how the main coronary arteries and their orifices form during murine heart development. Apelin (Apln) is expressed in coronary vascular endothelial cells including peritruncal endothelial cells. By immunostaining, however, we did not find Apln expression in endothelial cells of the aorta during the period of coronary vessel development (E10.5 to E15.5). As a result of this unique expression difference, AplnCreERT2/+ genetically labels nascent coronary vessels forming on the heart, but not the aorta endothelium when pulse activated by tamoxifen injection at E10.5. This allowed us to define the temporal contribution of these distinct endothelial cell populations to formation of the murine coronary artery orifice. We found that the peritruncal endothelial cells were recruited to form the coronary artery orifices. These cells penetrate the wall of aorta and take up residence in the aortic sinus of valsalva. In conclusion, main coronary arteries and their orifices form through the recruitment and vascular remodeling of peritruncal endothelial cells in mammalian heart.
Information-Based Bank Runs or Panics ?

This paper proposes a novel approach to distinguish between di¤erent theories of bank runs. Our method identi es bank runs from raw deposit market data, while controlling for the e¤ects of alternative shocks. We construct hypothesis tests, conditional on bank runs, which quantify the role of panic-induced deposit withdrawals as well as the extent to which withdrawals are based on information. We provide an application for the Russian deposit market. The method identi es one severe bank run. Information external to the model con rms the timing of the run. We nd evidence in favor of both the panic and the information-based views of bank runs. In particular, panic e¤ects induce signi cant runs at solvent banks with uninsured deposits, relative to banks whose deposits are insured. In addition, insolvent banks face runs that are four times as harsh, which establishes the signi cance of information-based theories. In the aggregate, panic accounts for almost 90% of the deposit run, while information is responsible for the remaining 10%. The fact that, in our application, both the panic and fundamentals view exert e¤ects has strong policy implications. While market discipline adds to the stability of the deposit market, it does not eliminate the possibility of panic runs. Our approach builds on structural identi cation techniques frequently used in macroeconomics. We extend these time-series methods by extracting information from cross-sectional heterogeneity. We show that such information is very useful for identifying structural shocks, cross-validating the model and extracting testable implications. The method can easily be extended to apply to alternative types of shocks, as well as other markets. Keywords: Bank run, Panic, Information-based, Identi cation, SVAR, panel-VAR