Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Catheter Navigation With 3D Electromagnetic Guidance

Purpose To evaluate the in vitro performance of an electromagnetic navigation system (ENS) in aortic arch branch cannulation and describe its role for fenestrated endograft deployment. Methods Reconstructed multidetector computed tomography images of silicone phantoms representing the aortic arch and a thoracoabdominal aortic aneurysm were uploaded onto the StealthStation workstation, which provided 3-dimensional visualization of a guidewire by tracking sensors on its tip. For the evaluation of aortic arch branch cannulation, 9 operators were asked to cannulate the phantom's common carotid and left subclavian arteries using the (1) ENS, (2) a 2-dimensional (2D) screen setting simulating fluoroscopy, and (3) both imaging modalities. Analysis included procedure times, number of wall hits, and the Imperial College Complex Cannulation Scoring Tool (IC3ST) qualitative performance score. To evaluate the ability of the ENS during positioning of a fenestrated stent-graft over the visceral segment, a custom-made 4-vessel fenestrated stent-graft with sensors on the fenestrations was deployed 5 consecutive times using the ENS as the exclusive imaging technique. Results In the aortic arch model, cannulation times were significantly longer in the ENS group. However, compared with the 2D version, using both imaging modalities reduced fluoroscopic times [median 26.5 seconds (IQR 19.7–30.7) vs. 87 seconds (IQR 64–128), p<0.0001] and wall hits [median 8.5 (IQR 16–38) vs. 14 (IQR 11–160, p<0.05), while improving IC3ST performance scores [31/35 (IQR 30–31.2) vs. 25/35 (IQR 24–27), p<0.05]. Following deployment of the endograft with tracked fenestrations, the 4 visceral vessels were cannulated in all cases using only the ENS. Conclusion The use of the ENS as a complementary imaging modality might be beneficial in terms of radiation exposure, cannulation performance, and positioning of intravascular devices.
A Generalized Honest-But-Curious Trust Negotiation Strategy for Harvesting Credentials

Need-to-know is a fundamental security concept: a party should not learn information that is irrelevant to its mission. In this paper we show that during a trust negotiation in which parties show their credentials to one another, an adversary Alice can systematically harvest information about all of a victim Bob’s credentials that Alice is entitled to see, regardless of their relevance to a negotiation. We prove that it is not possible to enforce need-to-know conditions with the trust negotiation model and protocol developed by Yu, Winslett, and Seamons. We also present examples of similar need-to-know attacks with the trust negotiation approaches proposed by Bonatti and Samarati, and by Winsborough and Li. Finally, we propose possible countermeasures against need-to-know attacks, and discuss their advantages and disadvantages.
Severe Lung Lesions Caused by Salmonella Are Prevented by Inhibition of the Contact System

Vascular damage induced by trauma, inflammation, or infection results in an alteration of the endothelium from a nonactivated to a procoagulant, vasoconstrictive, and proinflammatory state, and can lead to life-threatening complications. Here we report that activation of the contact system by Salmonella leads to massive infiltration of red blood cells and fibrin deposition in the lungs of infected rats. These pulmonary lesions were prevented when the infected animals were treated with H-D-Pro-Phe-Arg-chloromethylketone, an inhibitor of coagulation factor XII and plasma kallikrein, suggesting that inhibition of contact system activation could be used therapeutically in severe infectious disease.
Human T Cell Lymphotrophic Virus 1/2 in Solid Organ Transplantation

Abbreviations: ATL, adult T cell leukemia/lymphoma; EIA, enzyme linked immunosorbent assays; FDA, Food and Drug Administration; HAM/TSP, human T cell lymphotrophic virus associated myelopathy/tropical spastic paraparesis; HTLV, human T cell lymphotrophic virus; NHL, Non-Hodgkins lymphoma; PBMC, peripheral blood mononuclear cells; PCR, polymerase chain reaction; PTLD, posttransplant lymphoproliferative disease; SOT, solid organ transplantation; US, United States.
Estimation of Toeplitz Covariance Matrices in Large Dimensional Regime With Application to Source Detection

In this paper, we derive concentration inequalities for the spectral norm of two classical sample estimators of large dimensional Toeplitz covariance matrices, demonstrating in particular their asymptotic almost sure consistence. The consistency is then extended to the case where the aggregated matrix of time samples is corrupted by a rank one (or more generally, low rank) matrix. As an application of the latter, the problem of source detection in the context of large dimensional sensor networks within a temporally correlated noise environment is studied. As opposed to standard procedures, this application is performed online, i.e., without the need to possess a learning set of pure noise samples.
RAIDR: Retention-aware intelligent DRAM refresh

Dynamic random-access memory (DRAM) is the building block of modern main memory systems. DRAM cells must be periodically refreshed to prevent loss of data. These refresh operations waste energy and degrade system performance by interfering with memory accesses. The negative effects of DRAM refresh increase as DRAM device capacity increases. Existing DRAM devices refresh all cells at a rate determined by the leakiest cell in the device. However, most DRAM cells can retain data for significantly longer. Therefore, many of these refreshes are unnecessary. In this paper, we propose RAIDR (Retention-Aware Intelligent DRAM Refresh), a low-cost mechanism that can identify and skip unnecessary refreshes using knowledge of cell retention times. Our key idea is to group DRAM rows into retention time bins and apply a different refresh rate to each bin. As a result, rows containing leaky cells are refreshed as frequently as normal, while most rows are refreshed less frequently. RAIDR uses Bloom filters to efficiently implement retention time bins. RAIDR requires no modification to DRAM and minimal modification to the memory controller. In an 8-core system with 32 GB DRAM, RAIDR achieves a 74.6% refresh reduction, an average DRAM power reduction of 16.1%, and an average system performance improvement of 8.6% over existing systems, at a modest storage overhead of 1.25 KB in the memory controller. RAIDR's benefits are robust to variation in DRAM system configuration, and increase as memory capacity increases.
Attentional Factors in Conceptual Congruency

Conceptual congruency effects are biases induced by an irrelevant conceptual dimension of a task (e.g., location in vertical space) on the processing of another, relevant dimension (e.g., judging words' emotional evaluation). Such effects are a central empirical pillar for recent views about how the mind/brain represents concepts. In the present paper, we show how attentional cueing (both exogenous and endogenous) to each conceptual dimension succeeds in modifying both the manifestation and the symmetry of the effect. The theoretical implications of this finding are discussed.
Metal Oxide Nanowires – Structural and Mechanical Properties

Metal Oxide nanowires are versatile nanostructured materials with diverse yet unique properties. Potentially, they have a wide range of applications in electrical, chemical and semiconductor technologies (Yang, Wu et al. 2002; Rao, Deepak et al. 2003; Law, Goldberger et al. 2004; Shankar and Raychaudhuri 2005; Lu, Chang et al. 2006; Lu and Lieber 2006). Research interests in metal oxide nanowires commenced in 1990s. Up to now, there have been a considerable number of reports on success in the synthesis of 1-dimensional nanocrystalline structured nanowires of various metal oxides, such as CuO(Wang, Zhan et al. 2001; Jiang, Herricks et al. 2002), MgO(Ma and Bando 2003), ZnO(Tian, Voigt et al. 2003; Vayssieres 2003; Heo, Norton et al. 2004; Wang, Song et al. 2007; Manoharan, Desai et al. 2008), TiO2(Lakshmi, Partissi et al. 1997; Li and Wang 1999; Li and Xia 2003; Wu, Shih et al. 2005; Wu, Shih et al. 2006), Al2O3(Valcarcel, Souto et al. 1998; Xiao, Han et al. 2002), Ga2O3(Wu, Song et al. 2000), In2O3(Li, Zhang et al. 2003), SnO2(Dai, Pan et al. 2001), Sb2O5(Guo, Wu et al. 2000), V2O5(Chen, Sun et al. 2002), BaTiO3(Urban, Spanier et al. 2003), etc. The methodology of synthesis is now well developed. Reported techniques include vapor-solid phase technique(Valcarcel, Souto et al. 1998; Wu, Song et al. 2000; Jiang, Herricks et al. 2002; Ma and Bando 2003; Wu, Shih et al. 2005; Wu, Shih et al. 2006), chemical solution deposition (sol-gel) (Lakshmi, Partissi et al. 1997; Urban, Spanier et al. 2003), template etching(Xiao, Han et al. 2002), percipitation(Tian, Voigt et al. 2003; Vayssieres 2003), micro-emulsion(Guo, Wu et al. 2000), flux growth(Dai, Pan et al. 2001) and others. These are well reviewed by Shangkar et al.(Shankar and Raychaudhuri 2005). Among all the properties of metal oxide nanowires, their mechanical property is one of the most highly structure dependent and features strongly in many applications. The structural and mechanical phenomena and related mechanisms have attracted significant research interests. However, due to the difficulties in manipulating the nano-sized specimens, experimental characterizations are limited to simple mechanical tests to measure quantities like Young’s modulus, strength et al. Comparatively, numerical studies, especially molecular dynamics (MD) simulations, are well suited for nanostructured materials, and have been broadly applied for investigating structural and mechanical properties. In this chapter, we will review the structural characteristics and mechanical properties of different types of metal oxides, both experimentally and numerically. Besides reviewing published literatures, we will be focusing on reporting the outputs from our research group.
CHAPTER 3

Field work was carried out during several field cam p igns within the states of Morelos and México (see chapter 1). Lithological units were map ped in the field at a scale of 1:10,000 at five localities, recording approximately 30 % of th e 180 km of the Tepoztlán Formation within the study area (Fig. 5). The mapped areas we re chosen on account of their good outcrop conditions and are supposed to be represent ative for the geological conditions of the study area as a whole. The remaining area of the st udy area was mapped through interpretation of arial photographs and satellite i mages. All data were integrated into a geographic information system (GIS) environment. Fu rthermore, eight stratigraphic sections, ranging in thickness from 78 to 378 m, were logged and sampled for petrographical, sedimentological and palaeomagnetic analyses (Fig. 5). The sections provide a large and wellconstrained sample suite covering all major deposit ional units and geological characteristics.
Dynamical queue-based task management policies for human operators

Formal methods for task management for human operators are gathering increasing attention to improve efficiency of human-in-the-loop systems. In this paper, we consider a dynamical queue approach to task management for human operators. We consider the model of dynamical queue proposed in our earlier work [1], in which the service time depends on the server utilization history. The focus of the paper is to characterize the throughput of the dynamical queue and design corresponding maximally stabilizing task release control policies, assuming deterministic arrivals. We focus extensively on threshold policies that release a task to the server only when the server state is less than a certain threshold. When every task brings in the same deterministic amount of work, we give an exact characterization of the throughput and show that an appropriate threshold policy is maximally stabilizing. When the amount of work associated with the tasks is an i.i. d. random variable with finite support, we show that the maximum throughput increases in comparison to the case where the tasks have deterministic amount of work.
Improved shape and consistency after lipofilling of the breast: Patients' evaluation of the outcome

Abstract Autologous transplantation of fat, or lipofilling, of the breast can correct deformities after reconstruction and after conservation surgery for cancer. We have made a retrospective evaluation of morbidity and patients' experiences of the method. Forty-four patients have had lipofilling once, twice, or three times (mean transplanted volume 40 ml, range 6–200 ml). One minor complication, a local infection, was treated with antibiotics given orally, and recorded at follow up. A questionnaire was sent to all 44 patients and answered by 43. Twenty-nine of the 43 patients reported improvement of irregularities after lipofilling, 26 reported that the shape of the breast had improved, 26 that the consistency had improved, and 20 that the size had increased postoperatively. Five of the patients reported some adverse effects; one case of liponecrosis that did not need any treatment was found one year postoperatively. No problems were reported at the donor site at follow-up.
Towards good practice in large-scale learning for image classification

We propose a benchmark of several objective functions for large-scale image classification: we compare the one-vs-rest, multiclass, ranking and weighted average ranking SVMs. Using stochastic gradient descent optimization, we can scale the learning to millions of images and thousands of classes. Our experimental evaluation shows that ranking based algorithms do not outperform a one-vs-rest strategy and that the gap between the different algorithms reduces in case of high-dimensional data. We also show that for one-vs-rest, learning through cross-validation the optimal degree of imbalance between the positive and the negative samples can have a significant impact. Furthermore, early stopping can be used as an effective regularization strategy when training with stochastic gradient algorithms. Following these "good practices", we were able to improve the state-of-the-art on a large subset of 10K classes and 9M of images of lmageNet from 16.7% accuracy to 19.1%.
Stream-dataflow acceleration

Demand for low-power data processing hardware continues to rise inexorably. Existing programmable and “general purpose” solutions (eg. SIMD, GPGPUs) are insufficient, as evidenced by the order-of-magnitude improvements and industry adoption of application and domain-specific accelerators in important areas like machine learning, computer vision and big data. The stark tradeoffs between efficiency and generality at these two extremes poses a difficult question: how could domain-specific hardware efficiency be achieved without domain-specific hardware solutions? In this work, we rely on the insight that “acceleratable” algorithms have broad common properties: high computational intensity with long phases, simple control patterns and dependences, and simple streaming memory access and reuse patterns. We define a general architecture (a hardware-software interface) which can more efficiently expresses programs with these properties called stream-dataflow. The dataflow component of this architecture enables high concurrency, and the stream component enables communication and coordination at very-low power and area overhead. This paper explores the hardware and software implications, describes its detailed microarchitecture, and evaluates an implementation. Compared to a state-of-the-art domain specific accelerator (DianNao), and fixed-function accelerators for MachSuite, Softbrain can match their performance with only 2× power overhead on average.
Panic disorder and its subtypes: a comprehensive analysis of panic symptom heterogeneity using epidemiological and treatment seeking samples

Background Panic disorder (PD) is a heterogeneous syndrome that can present with a variety of symptom profiles that potentially reflect distinct etiologic pathways. The present study represents the most comprehensive examination of phenotypic variance in PD with and without agoraphobia for the purpose of identifying clinically relevant and etiologically meaningful subtypes. Method Latent class (LC) and factor mixture analysis were used to examine panic symptom data ascertained from three national epidemiologic surveys [Epidemiological Catchment Area (ECA), National Comorbidity Study (NCS), National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 1], a twin study [Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)] and a clinical trial (Cross-National Collaborative Panic Study [CNCPS]). Results Factor mixture models (versus LC) generally provided better fit to panic symptom data and suggested two panic classes for the ECA, VATSPSUD and CNCPS, with one class typified by prominent respiratory symptoms. The NCS yielded two classes, but suggested both qualitative and quantitative differences. The more contemporary NESARC sample supported a two and three class model, with the three class model suggesting two variants of respiratory panic. The NESARC's three class model continued to provide the best fit when the model was restricted to a more severe form of PD/panic disorder with agoraphobia. Conclusions Results from epidemiologic and clinical samples suggest two panic subtypes, with one subtype characterized by a respiratory component and a second class typified by general somatic symptoms. Results are discussed in light of their relevance to the etiopathogenesis of PD.
Influence of Parameter Identification of Anisotropic Yield Function on Spring-Back Prediction in Finite Element Simulation of Sheet Metal Forming Process

The anisotropic plastic behavior of metallic sheet has a significant influence on spring-back, and is usually modeled by anisotropic yield function in numerical simulation. Material parameters of anisotropic yield function are generally identified either by yield stresses or by r-values, or both of them. For Hill1948 and Yld89 anisotropic yield functions, r-values are still widely used to calibrate their material parameters in spring-back prediction. Here, yield stresses and r-values were respectively used to calibrate them, and the differences of the spring-back simulated by these two identification methods were discussed. To evaluate their accuracy, the simulation results were compared with the spring-back calculated by Yld2000-2d anisotropic yield function. The result shows that when yield stresses were used to identify the material parameters of Hill1948 and Yld89 yield functions, the simulated spring-back was closer to that of Yld2000-2d yield function.
Effects of Sintering Process on the Properties of Ti3SiC2/Cu Composite

In this paper, a new type of Ti3SiC2/Cu composites with the volume fractions of 30% Ti3SiC2 particle was prepared by hot pressing and vacuum sintering respectively. The effects of sintering temperature and holding time on the density, resistance and Vickers hardness of Cu-30vol%Ti3SiC2 composite were investigated. The results show that the mechanical properties of the composites prepared by hot pressing are better than that prepared by vacuum sintering. The relative densities of Cu-30vol% Ti3SiC2 composites are rather high in suitable sintering conditions. It achieved 100% for the composites prepared by hot pressing at 930°C for 2h, and 98.4% for the composites prepared by vacuum sintering at 1250°C for 1h. At the same time, the maximum Vickers hardness reached 1735MPa at 900°C by hot pressing. The resistance and Vickers hardness of the composites decreased with an increase in sintering temperature, whereas the density increased. Scanning electron microscope (SEM) and energy-dispersive spectroscopy (EDS) were used to observe the microstructure of the composites. The relationship between microstructure and mechanical properties was discussed.
Multiple scales of genetic connectivity in a brooding coral on isolated reefs following catastrophic bleaching

Understanding the pattern of connectivity among populations is crucial for the development of realistic and spatially explicit population models in marine systems. Here we analysed variation at eight microsatellite loci to assess the genetic structure and to infer patterns of larval dispersal for a brooding coral, Seriatopora hystrix, at an isolated system of reefs in northern Western Australia. Spatial autocorrelation analyses show that populations are locally subdivided, and that the majority of larvae recruit to within 100 m of their natal colony. Further, a combination of F‐ and R‐ statistics showed significant differentiation at larger spatial scales (2–60 km) between sites, and this pattern was clearly not associated with distance. However, Bayesian analysis demonstrated that recruitment has been supplemented by less frequent but recent input of larvae from outside the local area; 2–6% of colonies were excluded from the site at which they were sampled. Individual assignments of these migrants to the most likely populations suggest that the majority of migrants were produced at the only site that was not decimated by a recent and catastrophic coral bleaching event. Furthermore, the only site that recovered to prebleaching levels received most of these immigrants. We conclude that the genetic structure of this brooding coral reflects its highly opportunistic life history, in which prolific, philopatric recruitment is occasionally supplemented by exogenously produced larvae.
Metaheuristic tuning of type-II fuzzy inference systems for data mining

Introduction of the fuzzy-set enabled the modeling of uncertain and noisy information. Type-2 fuzzy set took this further ahead by allowing fuzzy membership function to be fuzzy itself. In this work, we discussed an interval type-2 fuzzy inference system (IT2FIS). The training of the IT2FIS was provided in supervised manner by using metaheuristic algorithms. We comprehensively illustrated the formulation of the IT2FIS into an optimization problem. A precise genotype (a real vector) mapping of IT2FIS and a population-based strategy for optimum rule-base selection is described in this work. Since the IT2FIS learning is computationally difficult and costly, which we described in detail in this work, a comprehensive comparison between the performances of the metaheuristic algorithms were examined. The obtained results suggest that the IT2FIS learning was faster at the initial iterations of the metaheuristic learning, but tend to slow and get stuck in local minima. However, the metaheuristic algorithms, differential evaluation and bacteria foraging optimization offered significantly better results when compared to artificial bee colony, gray wolf optimization, particle swarm optimization and the other fuzzy inference models chosen for comparisons from literature.
Content Replication in Mobile Networks

Performance and reliability of content access in mobile networks is conditioned by the number and location of content replicas deployed at the network nodes. In this work, we design a practical, distributed solution to content replication that is suitable for dynamic environments and achieves load balancing. Simulation results show that our mechanism, which uses local measurements only, approximates well an optimal solution while being robust against network and demand dynamics. Also, our scheme outperforms alternative approaches in terms of both content access delay and access congestion.