Miracle-dz/UniFAR-FTUs huggingface dataset:
BER and Diversity Order Analysis of Distributed Alamouti's Code with CSI-Assisted Relays

This paper focuses on the average bit error rate (BER) and diversity order analysis of the distributed Alamouti's code in dissimilar cooperative networks with channel state information (CSI)-assisted relays. We first assume that the relays adopt the amplifying coefficient proposed in . Lower and upper bounds of the average BER of the distributed Alamouti's code are derived. Those two bounds tightly bound the exact average BER. Then we show that, surprisingly, the distributed Alamouti's code achieves only diversity order one when the relays use the amplifying coefficient proposed in . To resolve this problem, we propose a new threshold-based amplifying coefficient for the distributed Alamouti's code based on the work in . This new amplifying coefficient makes the distributed Alamouti's code achieve the full diversity order two. Moreover, based on three different CSI assumptions, four amplifying schemes are developed in order to determine the value of the threshold used in the new amplifying coefficient.
DFT for high-quality low cost manufacturing test

The semiconductor industry is capable of building "tester-limited fabs" and definitely needs a more cost-effective solution for the cost of test problem than the one we have today. The solutions are likely, to come from several different sources. While the ATE industry is addressing the cost of test problem by designing new DFT testers, it is the EDA industry that holds the key to providing an embedded test solution that guarantees high-quality, low cost manufacturing test. In this presentation we examine various DFT technologies and their ability to provide high quality low cost manufacturing test.
Flow tiles

We present <i>flow tiles</i>, a novel technique for representing and designing velocity fields. Unlike existing procedural flow generators, tiling offers a natural user interface for field design. Tilings can be constructed to meet a wide variety of external and internal boundary conditions, making them suitable for inclusion in larger environments. Tiles offer memory savings through the re-use of prototypical elements. Each flow tile contains a small field and many tiles can be combined to produce large flows. The corners and edges of tiles are constructed to ensure continuity across boundaries between tiles. In addition, all our tiles and the resulting titing are divergence-free and hence suitable for representing a range of effects. We discuss issues that arise in designing flow tiles, algorithms for creating tilings, and three applications: a crowd on city streets, a river flowing between banks, and swirling fog. The first two applications use stationary fields, while the latter demonstrates a dynamic field.
Hierarchical Superhydrophobic Surfaces Fabricated by Dual‐Scale Electron‐Beam‐Lithography with Well‐Ordered Secondary Nanostructures

Recent studies on superhydrophobic surfaces have revealed the important roles of structural hierarchy in the overall properties of these surfaces. Here, a novel, versatile, and efficient technique is introduced for fabricating macroscopic hierarchical superhydrophobic surfaces with both well‐defined primary microstructures and well‐ordered secondary nanostructures using electron‐beam lithography. With this technique, the engineering capability of controlling the size, shape, and distribution of the secondary‐features is demonstrated, which allows a systematic and quantitative study of the individual effects of these parameters. Superhydrophobic surfaces produced by this new technique exhibit two distinctive wetting behaviors, high and low adhesion. The structural characteristics and structure‐property relations of each of those two regimes are discussed.
Classification of functional near-infrared spectroscopy signals applying reduction of scalp hemodynamic artifact

Functional near-infrared spectroscopy (fNIRS) has been applied to brain-computer interfaces (BCIs) in many studies because of its simplicity of use and portability. However, scalp-hemodynamics creates artifacts that often contaminate fNIRS signals and substantially degrade the signal-to-noise ratio of functional signals. Although some studies have reported methods for reducing these artifacts, no study has investigated their effects on BCIs. Previously, we proposed to remove these artifacts using a method that estimates the global scalp-hemodynamic component from a minimal number of short source-detector distance channels (Short-channels), and removes its influence from standard source-detector distance channels using a general linear model (GLM) that incorporates the scalp-hemodynamics in the design matrix. Here, we investigated the effects of applying scalp-hemodynamic reduction to classify four actions: grasping a ball with the right, left, or both hands, or resting. We used a support vector machine (SVM) and binary-tree multi-classification, and compared five types of ΔOxy-Hb features: time samples of raw data, of data after subtracting out scalp-hemodynamics, and of the estimated scalp-hemodynamics themselves, and GLM β values for the cerebral-hemodynamic component obtained using a standard GLM without the scalp-hemodynamic model and those obtained using our proposed GLM. Results showed that the proposed method successfully improved the signal-to-noise ratio of ΔOxy-Hb signals, and the β values estimated by the proposed method showed the highest accuracy for classification. Thus, reduction of scalp-hemodynamic artifacts using our method may make fNIRS-BCIs more accurate.
Role of Hippocampal Cav1.2 Ca2+ Channels in NMDA Receptor-Independent Synaptic Plasticity and Spatial Memory

Current knowledge about the molecular mechanisms of NMDA receptor (NMDAR)-independent long-term potentiation (LTP) in the hippocampus and its function for memory formation in the behaving animal is limited. NMDAR-independent LTP in the CA1 region is thought to require activity of postsynaptic L-type voltage-dependent Ca2+ channels (Cav1.x), but the underlying channel isoform remains unknown. We evaluated the function of the Cav1.2 L-type Ca2+ channel for spatial learning, synaptic plasticity, and triggering of learning-associated biochemical processes using a mouse line with an inactivation of the CACNA1C (Cav1.2) gene in the hippocampus and neocortex (Cav1.2HCKO). This model shows (1) a selective loss of protein synthesis-dependent NMDAR-independent Schaffer collateral/CA1 late-phase LTP (L-LTP), (2) a severe impairment of hippocampus-dependent spatial memory, and (3) decreased activation of the mitogen-activated protein kinase (MAPK) pathway and reduced cAMP response element (CRE)-dependent transcription in CA1 pyramidal neurons. Our results provide strong evidence for a role of L-type Ca2+ channel-dependent, NMDAR-independent hippocampal L-LTP in the formation of spatial memory in the behaving animal and for a function of the MAPK/CREB (CRE-binding protein) signaling cascade in linking Cav1.2 channel-mediated Ca2+ influx to either process.
Primal-dual entropy-based interior-point algorithms for linear optimization

We propose a family of search directions based on primal-dual entropy in the context of interior-point methods for linear optimization. We show that by using entropy based search directions in the predictor step of a predictor-corrector algorithm together with a homogeneous self-dual embedding, we can achieve the current best iteration complexity bound for linear optimization. Then, we focus on some wide neighborhood algorithms and show that in our family of entropy based search directions, we can find the best search direction and step size combination by performing a plane search at each iteration. For this purpose, we propose a heuristic plane search algorithm as well as an exact one. Finally, we perform computational experiments to study the performance of entropy-based search directions in wide neighborhoods of the central path, with and without utilizing the plane search algorithms.
Transmission Systems IB-DFE receivers with space diversity for CP-assisted DS-CDMA and MC-CDMA systems

Multi-Carrier Code Division Multiple Access (MC-CDMA), currently regarded as a promising multiple access scheme for broadband communications, is known to combine the advantages of an Orthogonal Frequency Division Multiplexing (OFDM)-based, Cyclic Prefix (CP)-assisted block transmission with those of CDMA systems. Recently, it was recognised that DS-CDMA (Direct Sequence) implementations can also take advantage of the benefits of the CP-assisted block transmission approach, therefore enabling an efficient use of Fast Fourier Transform (FFT)-based, chip level Frequency-Domain Equalisation (FDE) techniques. When employing a linear FDE with both MC-CDMA and DS-CDMA, the FDE coefficients can be optimised under the Minimum Mean Squared Error (MMSE) criterion, so as to avoid significant noise enhancement. The residual interference levels can be very high, especially for fully loaded scenarios, since the FDE/MMSE does not perform a perfect channel inversion. This paper deals with CP-assisted DS-CDMA systems and MC-CDMA systems with frequency-domain spreading. We consider the use of Iterative Block Decision Feedback Equalisation (IB-DFE) FDE techniques as an alternative to conventional, linear FDE techniques, and derive the appropriate IB-DFE parameters in a receiver diversity context. Our performance results show that IB-DFE techniques with moderate complexity allow significant performance gains in both systems, with bit error rate (BER) that can be close to the single-code matched filter bound (MFB) (especially for the CP-assisted DS-CDMA alternative), even with full code usage. Copyright © 2007 John Wiley & Sons. Ltd.
BUFFEST: Predicting Buffer Conditions and Real-time Requirements of HTTP(S) Adaptive Streaming Clients

Stalls during video playback are perhaps the most important indicator of a client's viewing experience. To provide the best possible service, a proactive network operator may therefore want to know the buffer conditions of streaming clients and use this information to help avoid stalls due to empty buffers. However, estimation of clients' buffer conditions is complicated by most streaming services being rate-adaptive, and many of them also encrypted. Rate adaptation reduces the correlation between network throughput and client buffer conditions. Usage of HTTPS prevents operators from observing information related to video chunk requests, such as indications of rate adaptation or other HTTP-level information. This paper presents BUFFEST, a novel classification framework that can be used to classify and predict streaming clients' buffer conditions from both HTTP and HTTPS traffic. To illustrate the tradeoffs between prediction accuracy and the available information used by classifiers, we design and evaluate classifiers of different complexity. At the core of BUFFEST is an event-based buffer emulator module for detailed analysis of clients' buffer levels throughout a streaming session, as well as for automated training and evaluation of online packet-level classifiers. We then present example results using simple threshold-based classifiers and machine learning classifiers that only use TCP/IP packet-level information. Our results are encouraging and show that BUFFEST can distinguish streaming clients with low buffer conditions from clients with significant buffer margin during a session even when HTTPS is used.
Cognitively inspired task design to improve user performance on crowdsourcing platforms

Recent research in human computation has focused on improving the quality of work done by crowd workers on crowdsourcing platforms. Multiple approaches have been adopted like filtering crowd workers through qualification tasks, and aggregating responses from multiple crowd workers to obtain consensus. We investigate here how improving the presentation of the task itself by using cognitively inspired features affects the performance of crowd workers. We illustrate this with a case-study for the task of extracting text from scanned images. We generated six task-presentation designs by modifying two parameters - visual saliency of the target fields and working memory requirements - and conducted experiments on Amazon Mechanical Turk (AMT) and with an eye-tracker in the lab setting. Our results identify which task-design parameters (e.g. highlighting target fields) result in improved performance, and which ones do not (e.g. reducing the number of distractors). In conclusion, we claim that the use of cognitively inspired features for task design is a powerful technique for maximizing the performance of crowd workers.
RADIATION PROTECTION IN PEDIATRIC INTERVENTIONAL CARDIOLOGY: AN IAEA PILOT PROGRAM IN LATIN AMERICA

The aim of this work is to present a methodology and some initial results for a pilot program on radiation protection (RP) in pediatric interventional cardiology under the auspices of the International Atomic Energy Agency. The starting point of the program was a workshop involving several pediatric cardiologists leading this specialty in 11 Latin American countries. The workshop included a pilot RP training course and additional sessions during which the objectives of the program and the methodology to collect and process data on patient and staff radiation doses were discussed. Special attention was dedicated to agree on a common quality control (QC) protocol for the x-ray and imaging systems used in the different catheterization laboratories. The preliminary data showed that only 64% of the cardiologists used their personal dosimeters regularly and that only 36% were aware of their personal dose values. The data on pediatric interventional activity were collected from 10 centers from nine different countries. A total of 2,429 procedures (50% diagnostic and 50% therapeutic) were carried out during 2009 in these centers. Patient dose data were available in only a few centers and were not analyzed on a regular basis in any of the catheterization laboratories involved. Plans were developed for a basic QC protocol of the x-ray systems and construction of a Latin American database on pediatric cardiology with patient and staff dose values with the idea in mind of obtaining distributions of these dose values before promoting several optimization strategies.
Ant Colony Based Routing Algorithm for Multi-sink Networks

Routing algorithm is a key component of wireless sensor networks. The researchers applied a lot of routing algorithm to satisfy the needs of various wireless sensor networks. In this paper we analyzed the topologies of multi-sink node wireless sensor networks and achieved a multi-direction routing algorithm based on Meet Ant Colony optimization for multi-sink node wireless sensor networks. The simulation proved that this routing algorithm can transfer the data to different sink in different directions. Its efficiency and convergence are extremely superior to GEM and GBR.
Optimization Fusion Approach for Image Segmentation using K-Means Algorithm

This paper presents a new, simple and Efficient segmentation approach,based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable,accurate and a non-overlapped image result.The main objective of the paper is to get a non-overlapping and a reliable output by using k-means and genetic algorithm. The different colorspaces are to be fused in our application by the simple (K-means based) clustering technique on an input image. The optimized range for k-means clustering values is obtained by performing genetic algorithm. Image segmentation for six color spaces are performed by kmeans. The k-means algorithm is an iterative technique that is used to partition an image into K clusters. The obtained output remains simple to implement, fast, general enough to be applied to various computer vision applications (e.g., motion detection and segmentation). The result aims at developing an accurate and more reliable image which can be used in locating tumors, measure tissue volume, face recognition, finger print recognition and in locating an object clearly from a satellite image and in more.
Inhibition of epibranchial placode‐derived ganglia in the developing rat by bisdiamine

Although bisdiamine has been shown to affect the development of mammals, its effect on the nervous system has gone largely unrecognized. In the present study, rats were given bisdiamine by gavage on days 9 and 10 of pregnancy. They were sacrificed at intervals and the fetuses were prepared for study of serial sections stained with hematoxylin and eosin, or by immunohistochemical reaction with HNK‐1 monoclonal antibody. HNK‐1 reacted strongly with the nervous system, allowing precise analysis of the components and their relationships. Controls receiving no bisdiamine were prepared and studied in parallel with the experimental fetuses. Administration of bisdiamine inhibited development of the petrosal and nodose ganglia, altered associations of the glossopharyngeal, vagus, and hypoglossal nerves, and inhibited contributions of vagal nerve fibers to the developing enteric system. The proximal ganglia of the glossopharyngeal and vagus nerves developed normally. It is concluded that bisdiamine affects, directly or indirectly, the differentiation of nervous components derived from the epibranchial placodes. It seems likely that these placode‐derived components serve as pioneer neurons in establishing the pathway for the posteriorly extending trunks of the glossopharyngeal and vagus nerves. The early changes in congenital conditions such as the DiGeorge syndrome may not be limited to alterations in neural crest derivatives. It may be worthwhile to investigate more closely whether there are alterations in the nervous system associated with these syndromes. © 1992 Wiley‐Liss, Inc.
Building a comprehensive ontology to refine video concept detection

Recent research has discovered that leveraging ontology is an effective way to facilitate semantic video concept detection. As an explicit knowledge representation, a formal ontology definition usually consists of a lexicon, properties, and relations. In this paper, we present a comprehensive representation scheme for video semantic ontology in which all the three components are well studied. Specifically, we leverage LSCOM to construct the concept lexicon, describe concept property as the weights of different modalities which are obtained manually or by data-driven approach, and model two types of concept relations (i.e., pairwise concept correlation and hierarchical relation). In contrast with most existing ontologies which are only focused on one or two components for domain-specific videos, the proposed ontology is more comprehensive and general. To validate the effectiveness of this ontology, we further apply it to video concept detection. The experiments on TRECVID 2005 corpus have demonstrated a superior performance compared to existing key approaches to video concept detection.
Min-Rep instances with large supergirth and the hardness of approximating basic spanners

We study the Min-rep with large supergirth problem. We show that if the supergirth in the Min-Rep graph is some k, 0 < k ≤ log1−2ǫ n, the problem is roughly 2log 1−ǫ n/k hard to approximate. A similar theorem was claimed by the paper [19] from ICALP 2000. However their paper contains an error. We use the new proof to show inapproximability for the min-size k-spanner problem which is the simplest spanners problem. Assuming NP 6⊆ BPTIME(2polylog(n)), we show that it is hard to approximate the minimum size k-spanner for every k ≥ 3, within a factor better than min{2(1/2c) log n, 15(log1/(1+ǫ) n)/(2k)/ log n}. For k in the above range the inapproximability equals nΘ(1/k) and this matches the upper bound [1] up to the constant that multiplies in the exponent 1/k. In [19], a similar hardness for the minimum size spanner problem is claimed, however, the error in the previous claim carried over and made this second claim incorrect as well. Thus for the problem of Min-Rep with large supergirth we give the first non-trivial lower bound. For the basic k-spanner problem we improve the previous best lower bound of Ω(log n)/k from [27].
A highly parallelized MIMO detector for vector-based reconfigurable architectures

This paper presents a highly parallelized MIMO signal detection algorithm targeting vector-based reconfigurable architectures. The detector achieves high data-level parallelism and near-ML performance by adopting a vector-architecture-friendly technique - parallel node perturbation. To further reduce the computational complexity, imbalanced node and successive partial node expansion schemes in conjunction with sorted QR decomposition are applied. The effectiveness of the proposed algorithm is evaluated by simulations performed on a simplified 4×4 MIMO LTE-A testbed and operation analysis. Compared to the K-Best detector and fixed-complexity sphere decoder (FSD), the number of visited nodes in the proposed algorithm is reduced by 15 and 1.9 times respectively, with less than 1dB performance degradation. Benefiting from the fully deterministic non-iterative dataflow structure, reconfiguration rate is 95% less than that of the K-Best detector and 17% less than the case of FSD.
Rendered Path: Range-Free Localization in Anisotropic Sensor Networks With Holes

Sensor positioning is a crucial part of many location-dependent applications that utilize wireless sensor networks (WSNs). Current localization approaches can be divided into two groups: range-based and range-free. Due to the high costs and critical assumptions, the range-based schemes are often impractical for WSNs. The existing range-free schemes, on the other hand, suffer from poor accuracy and low scalability. Without the help of a large number of uniformly deployed seed nodes, those schemes fail in anisotropic WSNs with possible holes. To address this issue, we propose the rendered path (REP) protocol. To the best of our knowledge, REP is the only range-free protocol for locating sensors with constant number of seeds in anisotropic sensor networks.
Serum C3 Enhances Complement Receptor 3-Mediated Phagocytosis of Borrelia burgdorferi

Complement receptor (CR) 3 is a bona fide phagocytic receptor for Borrelia burgdorferi, the causative agent of Lyme borreliosis 1, 2. CR3 is also the receptor for the opsonin iC3b, a final degradation product of the complement component C3 3, 4. The transit of B. burgdorferi through the blood during the dissemination phase exposes the spirochete to serum components, including complement 5. B. burgdorferi contains proteins with anti-complement activities that trigger the inactivation of C3b through the binding of factor H (FH) on the surface of the bacterium 6. This could lead to the accumulation of the opsonin, iC3b, and the enhanced phagocytosis of the spirochete. To test whether the presence of serum would increase the phagocytosis of B. burgdorferi, we incubated bone marrow-derived macrophages (BMMs), generated as described 1, with heat-inactivated (HI; 56 oC, 30 min) or active normal mouse sera (NMS). Phagocytosis protocols were followed according to published reports 1, 2. The presence of 10% HI serum resulted in phagocytosis levels comparable to those in the absence of serum (Fig. ​(Fig.1A,B). 1A,B). However, the presence of 10 % NMS enhanced the capacity of macrophages to internalize B. burgdorferi (Fig. ​(Fig.1A). 1A). The same effect was observed on RAW264.7 (RAW) cells (Fig. ​(Fig.1C). 1C). Thus, the contact of B. burgdorferi with serum components results in their enhanced phagocytic uptake. Next, we assessed whether the increased phagocytic activity associated with the presence of serum was due to C3-derived opsonin generation. We used sera from C3-deficient mice (C3 KO), in which B. burgdorferi dissemination is enhanced compared to WT mice 5. The presence of C3 KO serum abrogated the increased phagocytosis observed in the presence of NMS, both in BMMs (Fig. ​(Fig.1A,B)1A,B) and RAW cells (Fig. ​(Fig.11C).