Miracle-dz/UniFAR-FTUs huggingface dataset:
Serious Adverse Events Are Uncommon with Combination Neonatal Antiretroviral Prophylaxis: A Retrospective Case Review

Six weeks of zidovudine (ZDV) is recommended for postnatal prophylaxis of HIV-exposed infants, but combination antiretrovirals are indicated if HIV transmission risk is increased. We investigated the frequency and severity of adverse events (AE) in infants receiving multiple drug prophylaxis compared to ZDV alone. In this retrospective review of 148 HIV-exposed uninfected infants born between 1997–2009, we determined clinical and laboratory AE that occurred between days of life 8–42. Thirty-six infants received combination prophylaxis; among those, a three-drug regimen containing ZDV, lamivudine, and nevirapine was most common (53%). Rates of laboratory AE grade ≥1 were as follows for the combination prophylaxis and ZDV alone groups, respectively: neutropenia 55% and 39%; anemia 50% and 39%; thrombocytopenia 0 and 3%; elevated aspartate aminotransferase 3% and 3%; elevated alanine aminotransferase 0 and 1%; hyperbilirubinemia 19% and 42%. Anemia occurred more frequently in infants who received three-drug prophylaxis compared to infants who received ZDV alone (63% vs. 39%, p = 0.04); all anemia AE were grade 1 or 2 in the three-drug prophylaxis group. Overall, 75% of infants on combination prophylaxis and 66% of infants on ZDV alone developed grade ≥1 AE (p = 0.32), and 17% of infants in either group developed grade ≥3 AE. Stavudine was substituted for ZDV in 23 infants due to anemia or neutropenia. After this antiretroviral change, 50% of evaluable infants demonstrated improvement in AE grade, and 25% had no change. In conclusion, low grade anemia, neutropenia, and hyperbilirubinemia occurred frequently regardless of the prophylactic regimen, but serious AE were uncommon. Although most AE were typical of ZDV toxicity, the combination of ZDV with lamivudine and nevirapine resulted in an increased frequency of low-grade anemia. Further studies are needed to identify prophylactic regimens with less toxicity for infants born to HIV-infected mothers.
Improved cardiac wall motion tracking based on harmonic phase technique

The problem of detecting and tracking SPAMM tags has been the focus of cardiac MRI in the past few years. Among the many methods proposed to do that, the harmonic phase method (called HARP) has a large potential to enable real-time tracking. We propose two improvements to the original HARP technique to address the problem of magnetic field inhomogeneity and improve tracking. We derive a theoretical model for the problem of field inhomogeneity and propose an extension of the simulated phase evolution rewinding technique (SPHERE) whereby consecutive images are acquired using alternating echo time. Then, we propose a simple and computationally efficient approach that allows the problems of disappearing tag lines to be addressed. In particular, the geodesic horizontal and vertical distances between neighboring corner points in the detected tag lines are computed for each image. Once the correspondence between tag lines is established, the tracking of any point on the wall can be obtained given its relationship to the four corner points surrounding its location. The proposed improvements were implemented and applied to numerical phantoms as well as experimental data obtained for the original HARP technique to demonstrate the potential of the new techniques.
Argos: An efficient algorithm for simulating the coalescent with recombination

A method of manufacturing a solid rubber adaptor for converting an existing sheet metal highway barrier. The method includes the steps of: mixing and knead melting a mixture of: 80 to 90 percent by weight particles of recycled waste rubber; 10 to 20 percent by weight virgin rubber; and an accelerator composition; forming the mixture to a selected adaptor configuration thus defining an adaptor; curing the mixture within a chamber at a temperature of 350 DEG C. to 400 DEG C. for a period of time from 3 to 5 hours; and removing the cured barrier from the chamber.
Computational Study of Fast Methods for the Eikonal Equation

A computational study of the fast marching and the fast sweeping methods for the eikonal equation is given. It is stressed that both algorithms should be considered as "direct" (as opposed to iterative) methods. On realistic grids, fast sweeping is faster than fast marching for problems with simple geometry. For strongly nonuniform problems and/or complex geometry, the situation may be reversed. Finally, fully second order generalizations of methods of this type for problems with obstacles are proposed and implemented.
A Model of Gene Library Evolution in the Dynamic Cl onal Selection Algorithm

The dynamic clonal selection algorithm (dynamiCS) was created to tackle the difficulties of anomaly detection in continuously changing environments (Kim and Bentley, 2002a). This algorithm was extended in a sister paper (Kim and Bentley, 2002b), so that memory detectors that are no longer valid are automatically deleted. Here we describe a further extension to the system: the use of hypermutation on deleted memory detectors to produce, in effect, a " virtual gene library " which seeds the immature detector population. When using an Artificial Immune System (AIS) in a r eal environment (e.g., monitoring network traffic), nor mal or self behaviours can change after a certain period. In addition, the system may only see a small subset of self antigens at any one time. In order for our AIS to be able to deal with such an environment, a dynamic clonal selectionalgorithm(DynamiCS)wasintroducedin previous work (Kim and Bentley, 2002a). The results described there showed that DynamiCS could incrementally learn the globally converged distribu tions even though only one subset distribution was given at each generation. This feature was achieved by emplo ying three important parameters: tolerisation period of an immature detector (T), activation threshold of a mature detector (A) and the life span of a mature detector. However, the original DynamiCS could not learn new self-antigens when learned self and non-self behavi ours suddenly altered due to legal self change. This res ulted in high false positive (FP) rates when new antigens we re monitored by DynamiCS, although it produced high tr ue positive (TP) rates. A sister paper to this describes a further extensio n of DynamiCS, which reduces FP rates increased by memor y detectors (Kim and Bentley 2002b). The extended DynamiCS handles generated memory detectors based o n their detection results. The original DynamiCS pres erved memory detectors for an infinite lifespan. In contr ast, the extended DynamiCS kills memory detectors if they sh ow poor self-tolerance to new antigens (Kim and Bentle y 2002b). This extended system was tested to determin e whether surviving memory detectors no longer cause seriously high FP error rates or not. From this tes t, it was analysed to see whether any other problems occur as a consequence of killing memory detectors. The analys is showed that the extended DynamiCS requires a larger amount of co-stimulation if it yielded high TP rate s. This analysis led to the work described in this …
On Constructing a Financial Decision Support System

Financial decision support system development usually involves a number of recognizable steps: data preparation – cleaning, selecting, making data suitable for the predictor; prediction algorithm development and tuning – for performance on the quality of interest and evaluation – to see if indeed the system performs on unseen data. But since financial prediction is very difficult, extra insights are needed. This work is twofold aiming to provide data enhancing techniques, performance improvements, evaluation hints and pitfalls to avoid as well as to exploit them by using a prototype tool that can automate the financial decision support process.
Do Imf-Supported Programs Work? A Survey of the Cross-Country Empirical Evidence

Over the last two decades a number of cross-country empirical studies have been undertaken to assess whether IMF-supported adjustment programs have led to an improved balance of payments and current account balance, lower inflation, and higher growth. These studies use a variety of methodologies and cover different country samples and time periods. This paper critically surveys the evidence yielded by the cross-country studies, paying special attention to the pros and cons of the respective empirical methodologies employed. These studies, particularly the more recent ones, conclude that IMF-supported programs have generally been successful in stabilizing the economy.
Factors Affecting the Clearance and Biodistribution of Polymeric Nanoparticles

Nanoparticle (NP) drug delivery systems (5−250 nm) have the potential to improve current disease therapies because of their ability to overcome multiple biological barriers and releasing a therapeutic load in the optimal dosage range. Rapid clearance of circulating nanoparticles during systemic delivery is a critical issue for these systems and has made it necessary to understand the factors affecting particle biodistribution and blood circulation half-life. In this review, we discuss the factors which can influence nanoparticle blood residence time and organ specific accumulation. These factors include interactions with biological barriers and tunable nanoparticle parameters, such as composition, size, core properties, surface modifications (pegylation and surface charge), and finally, targeting ligand functionalization. All these factors have been shown to substantially affect the biodistribution and blood circulation half-life of circulating nanoparticles by reducing the level of nonspecific uptake, delaying opsonization, and increasing the extent of tissue specific accumulation.
Optimization with skewed majorization constraints: Application to MIMO systems

This paper considers the problem of optimizing a Schur-convex objective under a linearly shifted, or skewed, majorization constraint. Similar to the case with a regular majorization constraint, the solution is found to be the same for the entire class of cost functions. Furthermore, it is shown that the problem is equivalent to identifying the convex hull under a simple polygon defined by the constraint parameters. This leads to an algorithm that produces the exact optimum with linear computational complexity. As an application, we present a novel precoder design for a multi-input multi-output communication system with heterogeneous signal constellations utilizing decision feedback detection at the receiver.
Interactive visual exploration of a trillion particles

We present a method for the interactive exploration of tera-scale particle data sets. Such data sets arise from molecular dynamics, particle-based fluid simulation, and astrophysics. Our visualization technique provides a focus+context view of the data that runs interactively on commodity hardware. The method is based on a hybrid multi-scale rendering architecture, which renders the context as a hierarchical density volume. Fine details in the focus are visualized using direct particle rendering. In addition, clusters like dark matter halos can be visualized as semi-transparent spheres enclosing the particles. Since the detail data is too large to be stored in main memory, our approach uses an out-of-core technique that streams data on demand. Our technique is designed to take advantage of a dual-GPU configuration, in which the workload is split between the GPUs based on the type of data. Structural features in the data are visually enhanced using advanced rendering and shading techniques. To allow users to easily identify interesting locations even in overviews, both the focus and context view use color tables to show data attributes on the respective scale. We demonstrate that our technique achieves interactive performance on a one trillionpar-ticle data set from the DarkSky simulation.
Connectionist F-structure transfer

A traditional transfer system in machine translation maps between language structures and an intermediate representation. Our connectionist transfer system maps from f-structures of one language to f-structures of another language. It encodes the intermediate representation implicitly in neural networks' activation patterns. The system is learnable, therefore it does not need any e ort in handcrafting the representation and mapping rules. Experiments show the system has good scalability and generalizability performance.
The CoRoT space mission : early results Special feature Abundance analysis of prime B-type targets for asteroseismology II . B 6 – B 9 . 5 stars in the field of view of the CoRoT satellite

Aims. The main goal of the ground-based seismology support program for the CoRoT mission was to obtain photometric and spectroscopic data for stars in the fields monitored by the satellite. These ground-based observations were collected in the GAUDI archive. High-resolution spectra of more than 200 B-type stars are available in this database, and about 45% of them is analysed here. Methods. To derive the effective temperature of the stars, we used photometric indices. Surface gravities were obtained by comparing observed and theoretical Balmer line profiles. To determine the chemical abundances and rotational velocities, we used a spectrum synthesis method, which consisted of comparing the observed spectrum with theoretical ones based on the assumption of LTE. Results. Atmospheric parameters, chemical abundances, and rotational velocities were determined for 89 late-B stars. The dominant species in their spectra are iron-peak elements. The average Fe abundance is 7.24 ± 0.45 dex. The average rotational velocity is 126 km s−1, but there are 13 and 20 stars with low and moderate V sin i values, respectively. The analysis of this sample of 89 late B-type stars reveals many chemically peculiar (CP) stars. Some of them were previously known, but at least 9 new CP candidates, among which at least two HgMn stars, are identified in our study. These CP stars as a group exhibit V sin i values lower than the stars with normal surface chemical composition.
Experiences with the NoAH Honeynet Testbed to Detect new Internet Worms

Recently, major advances have been made in the area of honeypot technologies. These include the development of very accurate and reliable detection methods for unknown attacks targeted at memory corruption vulnerabilities and the design of efficient network architectures. These architectures allow to monitor a large network of IP addresses applying advanced detection methods for zero-day exploits and new Internet worms. Such an advanced architecture and detection method was developed by the NoAH research project funded by the Sixth EU’s Framework Programme for Research and Technological Development. A pilot testbed was set up to demonstrate its effectiveness to detect well-known as well as new attacks on the Internet. While the technical components are well-understood, the interpretation and analysis of the resulting information is to the best of our knowledge still not fully explored by research projects. For the NoAH pilot testbed, a critical test to demonstrate its effectiveness arose with the appearance of the W32.Conficker worm in November 2008. In this paper we present the experimental results of this testbed focusing on the detection and analysis of the W32.Conficker worm which is still widely spread and an ongoing threat to the Internet. In detail, we introduce the detection process starting with the first suspicion of a new Internet worm towards its analysis and capture of malware.
Biclustering of gene expression patterns with an advanced overlapping control strategy

Conventional Biclustering methods give critical information regarding correlated patterns in gene expression patterns with similar expressions. These data mining techniques are considered to be the crucial in microarray data analysis. These kinds of data analysis always put focus to the ideal functions of genes and transcription factor target relationships. However by applying traditional clustering methods, a set of genes with its similar expressions can be determined. But these methods usually fail to find more correlated patterns that are present in the microarray data which can be achieved by using biclustering techniques. Here we propose a novel biclustering algorithm that not only determines the co-related gene expression patterns in microarray data along but also provides an effective strategy to control the overlapping in biclusters.
Energy trade-offs among content delivery architectures

It is envogue to consider how to incorporate various home devices such as set-top boxes into content delivery architectures using the Peer-to-Peer (P2P) paradigm. The hope is to enhance the efficienc of content delivery, e.g., in terms of reliability, availability, throughput, or to reduce the cost of the content delivery platform or to improve the end user experience. While it is easy to point out the benefit of such proposals they usually do not consider the implications with regards to the energy costs. In this paper we explore the energy trade-offs of such P2P architectures, data center architectures, and content distribution networks (CDNs) by building upon an energy consumption model of the transport network and datacenters developed in the context of Internet TV (IPTV). Our results show that a CDN within an ISP is able to minimize the overall power consumption. While a P2P architecture may reduce the power consumption of the service provider it increases the overall energy consumption.
MIMO-a solution for advanced wireless access?

The application of smart antenna technology to wireless communication systems has attracted considerable attention over the last decade or so, as a means of capacity enhancement. Here, the application of space-time processing using a single antenna array at the base-station has been considered in order to obtain interference reduction (both co-channel and multipath) as well as range extension. The application of dual antenna array architectures to create multiple-input multiple-output (MIMO) configurations, has attracted considerable interest both within academia and industry as a means of providing significant capacity gains over conventional array-based enhancement methods. This paper provides an introduction to these MIMO communication systems and explains how such capacity gains can be achieved using this technology.
3D WLAN indoor positioning in multi-storey buildings

Many scenarios for indoor positioning require position estimation not only in two dimensions but in the third dimension as well. This paper presents the expansion of two two-dimensional WLAN fingerprinting localization algorithms based on received signal strength indication (RSSI) to the third dimension. The third dimension is regarded discretely as the floor level. Both algorithms were evaluated in two different test beds. Evaluation results will be presented and discussed.
Object Identification by enhanced Local SIFT Features

The project is to design and implement a framework for our smart camera network, to effectively identify an object when given a certain amount of continuous frames of such object. An enhanced local feature descriptor is used to represent detected objects in our smart camera network. We select stable and distinctive SIFT features from an object as well as maintain the viewpoint relations existing amongst different features. The matching algorithm takes into consideration not only the appearance of SIFT features but also those viewpoint relations. Such descriptors are constructed in in‐camera scenarios with the support from tracking algorithms, and can provide useful information about the object matching when solving tracking in cross‐camera scenarios. 1. Project Introduction This project aims to provide the searching functionality to our smart camera network so that the user can query by example. Therefore, we need to figure out the effective way to represent detected objects in our network and do object matching, which will also help get better results in cross‐camera tracking. There are three local features being used in object matching in our platform: location, color histogram, and SIFT feature [1, 2]. Location and color histogram are very effective to match objects in single camera scenario, but due to the variance in factors such as the illumination and view angle amongst different cameras, these two features are less useful when it comes to match object that are captured from different cameras. Contrasted with the location and color histogram, SIFT features are robust to changes in image scale, noise and illumination, so we try to represent objects by using SIFT features, which make objects from different cameras comparable. 2. Related Work Detecting distinctive local image features is a noticeable progress occurred in computer vision. The local SIFT features has been applied in image retrieval, object recognition, and autonomous vehicle navigation tasks. In [3], indexing descriptors are extracted from local regions to retrieve the right CD‐covers from a database of 40000 images of popular music CD's. In [4], local features are used in vehicle navigation to estimate the global uncertainty of epipolar geometry. The Locality Sensitive Hashing algorithm [5, 6] aims at searching for the nearest points in a high dimensional space, so it is also used in some image retrieval applications such as [7]. In our project, both the local SIFT feature and the LSH algorithm are used to find an effective way to do
Specific heat, internal energy, and thermodynamic Casimir force in the neighborhood of the λ transition

We discuss the relation of the excess specific heat, the excess energy per area, and the thermodynamic Casimir force in thin films. A priori these quantities depend on the reduced temperature $t$ and the thickness ${L}_{0}$ of the film. However finite-size scaling theory predicts that the scaling functions ${h}^{\ensuremath{''}}(x)$, ${h}^{\ensuremath{'}}(x)$, and $\ensuremath{\theta}(x)$ of these quantities depend only on the combination $x=t{[{L}_{0}/{\ensuremath{\xi}}_{0}]}^{1/\ensuremath{\nu}}$, where $\ensuremath{\nu}$ is the critical exponent and ${\ensuremath{\xi}}_{0}$ the amplitude of the correlation length. Furthermore, the finite-size scaling function $\ensuremath{\theta}(x)$ of the thermodynamic Casimir force per area can be expressed in terms of the scaling functions ${h}^{\ensuremath{'}}(x)$ and $h(x)$ of the excess energy per area and the excess free energy per area. Here we study this relation at the example of thin films of the improved two-component ${\ensuremath{\phi}}^{4}$ model on the simple cubic lattice. Note that this model undergoes a second-order phase transition that belongs to the three-dimensional XY universality class. First we simulate films with periodic boundary conditions in the short direction and a thickness up to ${L}_{0}=13$ lattice spacings. We find that even for these rather thin films, the predictions of finite-size scaling are well satisfied. We repeat the analysis for films with free boundary conditions. To this end we use Monte Carlo data for the energy per area obtained in previous work. It turns our that corrections to scaling caused by the boundary conditions are very prominent in this case. Only by taking into account these corrections we are able to obtain $\ensuremath{\theta}(x)$ from the excess energy. Finally we repeat this exercise using experimental data for the excess specific heat of $^{4}\text{H}\text{e}$ films near the $\ensuremath{\lambda}$ transition. The finite-size scaling behavior of the excess specific heat is governed by ${h}^{\ensuremath{''}}(x)$, which is proportional to the scaling function ${f}_{2}$ discussed in the literature.