Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust channel estimation for OFDM systems with rapid dispersive fading channels

Orthogonal frequency division multiplexing (OFDM) modulation is a promising technique for achieving the high-bit-rates required for a wireless multimedia service. Without channel estimation and tracking, OFDM systems have to use differential phase-shift keying (DPSK), which has a 3 dB signal-to-noise ratio (SNR) loss compared with coherent phase-shift keying (PSK). To improve the performance of OFDM systems by using coherent PSK, we investigate robust channel estimation for OFDM systems. We derive a minimum mean-square-error (MSE) channel estimator, which makes full use of the time- and frequency-domain correlations of the frequency response of time-varying dispersive fading channels. Since the channel statistics are usually unknown, we also analyze the mismatch of the estimator to channel statistics and propose a robust channel estimator that is insensitive to the channel statistics. The robust channel estimator can significantly improve the performance of OFDM systems in a rapid dispersive fading channel.
THE POLITICAL ECONOMY OF INTERNATIONAL MONETARY RELATIONS

■ Abstract The structure of international monetary relations has gained increasing prominence over the past two decades. Both national exchange rate policy and the character of the international monetary system require explanation. At the national level, the choice of exchange rate regime and the desired level of the exchange rate involve distributionally relevant tradeoffs. Interest group and partisan pressures, the structure of political institutions, and the electoral incentives of politicians therefore influence exchange rate regime and level decisions. At the international level, the character of the international monetary system depends on strategic interaction among governments, driven by their national concerns and constrained by the international environment. A global or regional fixed-rate currency regime, in particular, requires at least coordination and often explicit cooperation among national governments.
Optimal motion control for multi-robot system by multilayer network operator

We are addressing the problem of designing an autonomous feedback control for a group of robots moving in the environment with obstacles and avoiding collisions. A robotic team with full information is considered. We propose a two-stage numerical approach for control synthesis. On the first stage a stabilizing control about some point in the state space is produced. On the second stage optimal trajectories are constructed as a set of stabilizing points. We apply a multilayer network operator for numerical search of control functions. Computational experiment is performed for control synthesis for a group of three mobile robots parking in the constrained space.
Research Grant Renewal Proposal Reinforcement Learning and Artificial Intelligence chair :

The RLAI research program pursues an approach to artificial intelligence and engineering problems in which they are formulated as large optimal control problems and approximately solved using reinforcement learning methods. Reinforcement learning is a new body of theory and techniques for optimal control that has been developed in the last twenty years primarily within the machine learning and operations research communities, and which have separately become important in psychology and neuroscience. Reinforcement learning researchers have developed novel methods to approximate solutions to optimal control problems that are too large or too ill-defined for classical solution methods such as dynamic programming. For example, reinforcement learning methods have obtained the best known solutions in such diverse automation applications as helicopter flying, elevator scheduling, playing backgammon, and resource-constrained scheduling. The objectives of the RLAI research program are to create new methods for reinforcement learning that remove some of the limitations on its widespread application and to develop reinforcement learning as a model of intelligence that could approach human abilities.
The Role of Chatting in Online Shopping

Our project sought to understand the behaviors within an integrated instant-messaging and e-commerce network, with the larger goal of understanding social influences on consumer behavior. We tackled this problem in three parts: – Statistics: In the first part of our analysis, we aimed to gain a broad understanding of these networks by retrieving network statistics, such as the wealth distribution; node statistics, such as the relationship between chatting and shopping behavior for individual users; and community statistics, such as trade density within differently sized communities. For individuals, the amount of chatting was negatively correlated with purchasing activity but positively correlated with sales activity. Within communities, denser contact networks and greater messaging activity were correlated with higher trade volume. – Building Trust: An important element on online sales is trust, since the possibility of deception is so much higher than for brick-and-mortar stores. We studied the phenomenon of “stickiness” (the tendency towards repeat business for individual users) as well as propagating trust through buyer-buyer interactions. For the latter, we isolated triads consisting of two buyers, each of whom had made purchases from the same seller, and investigated their messaging behavior. We found that buyers are very likely to purchase again from the same sellers, but sparsity of data on event triads did not give a strong signal on buyers propagating trust. – Signals Predicting Trade Likelihood: To understand what different social influences affect trade likelihood, we performed a feature ablation study involving 30 different features, evaluating the metrics of average precision and area under the ROC curve. Among others, two of the most important signals were the total count of the buyer’s outgoing messages, and the total count of the seller’s previous transactions.
UML Activity Diagram-Based Automatic Test Case Generation For Java Programs

Test case generation based on design specifications is an important part of testing processes. In this paper, Unified Modeling Language activity diagrams are used as design specifications. By setting up several test adequacy criteria with respect to activity diagrams, an automatic approach is presented to generate test cases for Java programs. Instead of directly deriving test cases from activity diagrams, this approach selects test cases from a set of randomly generated ones according to a given test adequacy criterion. In the approach, we first instrument a Java program under testing according to its activity diagram model, and randomly generate abundant test cases for the program. Then, by running the instrumented program we obtain the corresponding program execution traces. Finally, by matching these traces with the behavior of the activity diagram, a reduced set of test cases are selected according to the given test adequacy criterion. This approach can also be used to check the consistency between the program execution traces and the behavior of activity diagrams.
Mitochondrial DNA Activates the NLRP3 Inflammasome and Predisposes to Type 1 Diabetes in Murine Model

Although a correlation between polymorphisms of NOD-like receptor family-pyrin domain containing 3 (NLRP3) and predisposition to type 1 diabetes (T1D) has been identified, the potential function and activation of the NLRP3 inflammasome in T1D have not been clarified. The present study shows that non-obese diabetic mice exhibited increased NLRP3, and pro-IL-1β gene expression in pancreatic lymph nodes (PLNs). Similar increases in gene expression of NLRP3, apoptosis associated speck like protein (ASC) and pro-IL-1β were induced by multiple low doses of streptozotocin (STZ) in C57BL/6 mice. In addition, diabetic C57BL/6 mice also exhibited increased IL-1β protein expression in the pancreatic tissue at day 7, which remained elevated until day 15. Diabetic mice also showed increased positive caspase-1 macrophages in the PLNs, which were decreased in NLRP3−/− mice, but not in ASC−/− mice, after STZ treatment. NLRP3- and IL-1R-deficient mice, but not ASC-deficient mice, showed reduced incidence of diabetes, less insulitis, lower hyperglycemia, and normal insulin levels compared to wild-type (WT) diabetic mice. Notably, these mice also displayed a decrease in IL-17-producing CD4 and CD8 T cells (Th17 and Tc17) and IFN-γ-producing CD4 and CD8 T cells (Th1 and Tc1) in the PLNs. Following STZ treatment to induce T1D, NLRP3-deficient mice also exhibited an increase in myeloid-derived suppressor cell and mast cell numbers in the PLNs along with a significant increase in IL-6, IL-10, and IL-4 expression in the pancreatic tissue. Interestingly, diabetic mice revealed increased circulating expression of genes related to mitochondrial DNA, such as cytochrome b and cytochrome c, but not NADH dehydrogenase subunit 6 (NADH). Mitochondrial DNA (mDNA) from diabetic mice, but not from non-diabetic mice, induced significant IL-1β production and caspase-1 activation by WT macrophages, which was reduced in NLRP3−/− macrophages. Finally, mDNA administration in vivo increased Th17/Tc17/Th1/Tc1 cells in the PLNs and precipitated T1D onset, which was abolished in NLRP3−/− mice. Overall, our results demonstrate that mDNA-mediated NLRP3 activation triggers caspase-1-dependent IL-1β production and contributes to pathogenic cellular responses during the development of STZ-induced T1D.
An EPG study of initial clusters in varying prosodic conditions

Articulatory strengthening as a function of prosodic variation has so far been largely investigated for singleton consonants and vowels only. The aim of this study is to analyze effects of prosodic variation on the word intial cluster /kl/ by varying lexical word stress, accent and prosodic boundary levels. Therefore, three subjects were recorded by means of Electropalatography. Derived temporal parameters provide evidence corroborating the assumption that /k/ - which was closer to the boundary - was more affected by boundary strength than the more distal segment /l/, while /l/ tended to be stronger influenced by lexical stress than /k/. At lower prosodic boundaries, the consonants overlapped to a greater degree as compared to higher prosodic boundaries.
Simultaneous adaptive wire adjustment and local topology modification for tuning a bounded-skew clock tree

The need for incremental algorithms to implement engineering changes (ECs) in clock trees (CTs) is critical in the system-on-a-chip (SoC) design cycle. An algorithm, called adaptive wire adjustment (AWA), is proposed to minimize the clock skew iteratively to any given bound. In order to speed up AWA's convergence, a local topology-modification (LTM) technique is incorporated into AWA. Moreover, LTM incorporation into AWA results in total wire-length reduction as well. Also, the incorporation of the LTM technique into the deferred-merge embedding (DME) algorithm and Greedy-DME (GDME) helps reduce the total wire length by around 7.8% and 9.8%, respectively. Additionally, applying LTM to GDME reduces wire elongations and the standard deviation of the path lengths (SDPL) between clock pins by 96.4% and 51.5%, respectively.
Diagnostic Quality of Compressed Medical Images: Objective and Subjective Evaluation

Without image compression, images data would become much larger and consequently retrieval of images will be slow, thus telemedicine would in many situations be impractical. But it is natural to raise the question of how much an image can be compressed and still preserve sufficient information for a given clinical application. Evaluation of the diagnostic quality of compressed medical image still remains an important issue. In this paper, three different medical image modalities have been compressed and decompressed using DWT for different compression ratios and evaluated using objective and subjective testing. The quality of the reconstructed images has been measured using objective measures such as MSE, MAE, SNR, and PSNR. Ten observers have been involved to carry out the subjective evaluation. Based on the quality of the reconstructed images, the PSNR obtained has been between 35.3 dB to 58.0 dB for CT scan images, 38.6 dB to 55.0 dB for MRI and 34.5 dB to 51 MB for X-ray images. For radiology applications, the compression ratio of 30:1 is acceptable for CT images, and a compression ratio of 40:1 is acceptable for MRI, and compression ratio of 20:1 is acceptable for X-ray images.
Intra-query adaptivity for MapReduce query processing systems

MapReduce query processing systems translate a query statement into a query plan, consisting of a set of MapReduce jobs to be executed in distributed machines. During query translation, these query systems uniformly allocate computing resources to each job by delegating the same tuning to the entire query plan. However, jobs may implement their own collection of operators, which lead to different usage of computing resources. In this paper we propose an adaptive tuning mechanism that enables setting specific resources to each job within a query plan. Our adaptive mechanism relies on a data structure that maps jobs to tuning codes by analyzing source code and log files. This adaptive mechanism allows delegating specific resources to the query plan at runtime as the data structure hosts specific pre-computed tuning codes.
Background subtraction based on cooccurrence of image variations

This paper presents a novel background subtraction method for detecting foreground objects in dynamic scenes involving swaying trees and fluttering flags. Most methods proposed so far adjust the permissible range of the background image variations according to the training samples of background images. Thus, the detection sensitivity decreases at those pixels having wide permissible ranges. If we can narrow the ranges by analyzing input images, the detection sensitivity can be improved. For this narrowing, we employ the property that image variations at neighboring image blocks have strong correlation, also known as "cooccurrence". This approach is essentially different from chronological background image updating or morphological postprocessing. Experimental results for real images demonstrate the effectiveness of our method.
Unscheduled Akt-Triggered Activation of Cyclin-Dependent Kinase 2 as a Key Effector Mechanism of Apoptin's Anticancer Toxicity

ABSTRACT Apoptin, a protein from the chicken anemia virus, has attracted attention because it specifically kills tumor cells while leaving normal cells unharmed. The reason for this tumor selectivity is unclear and depends on subcellular localization, as apoptin resides in the cytoplasm of normal cells but in the nuclei of transformed cells. It was shown that nuclear localization and tumor-specific killing crucially require apoptin's phosphorylation by an as yet unknown kinase. Here we elucidate the pathway of apoptin-induced apoptosis and show that it essentially depends on abnormal phosphatidylinositol 3-kinase (PI3-kinase)/Akt activation, resulting in the activation of the cyclin-dependent kinase CDK2. Inhibitors as well as dominant-negative mutants of PI3-kinase and Akt not only inhibited CDK2 activation but also protected cells from apoptin-induced cell death. Akt activated CDK2 by direct phosphorylation as well as by the phosphorylation-induced degradation of the inhibitor p27Kip1. Importantly, we also identified CDK2 as the principal kinase that phosphorylates apoptin and is crucially required for apoptin-induced cell death. Immortalized CDK2-deficient fibroblasts and CDK2 knockdown cells were markedly protected against apoptin. Thus, our results not only decipher the pathway of apoptin-induced cell death but also provide mechanistic insights for the selective killing of tumor cells.
Peripheral Interactions among Single Papilla Inputs to Gustatory Nerve Fibers

Recordings were made from single fibers of the rat chorda tympani nerve while the peripheral receptor fields were mapped using a stimulator developed to stimulate single fungiform papillae which in the rat contain a solitary taste bud. The results indicate that several fungiform papillae may supply input to a single fiber, and the most sensitive papilla of these provided, on the average, about one-half of the response of that fiber to stimulation of the entire tongue. The magnitude of the response to each concentration of stimulus and the shape of the concentration-response curves differ among papillae innervated by the same fiber. If one of the papillae supplying input to the fiber was stimulated individually with NaCl solution, application of this stimulus to the tongue surface surrounding the isolated papilla resulted in enhancement of the fiber response. If the papilla was stimulated with NaCl and potassium benzoate solution was applied to the surround, a depression of the response occurred. The excitatory input of the cationic stimuli and the depressing influence of the anionic stimuli interacted to determine the resultant steady-state impulse frequency of the single afferent fiber. A hypothetical model involving the summation of generator currents along the unmyelinated terminals of the single afferent neuron is presented as a speculative explanation of the integration of inputs from several receptors innervated by the same single fiber.
Design and Implementation of a Simplified Turbo Decoder for 3GPP2

In this paper a VLSI architecture for a configurable turbo decoder, compliant with the 3GPP2 standard is presented. A simple modification of the conventional iterative structure of a turbo decoder is presented, where one of the constituent interleavers can be eliminated, allowing an important reduction in the overall complexity of the turbo decoder with no performance degradations. Performance analysis is highlighted vis \`a vis a fixed point reference model. In addition, results of the overall architecture with the sliding window approach and implemented on an Alter a device is shown.
A Proposed Fuzzy based Framework for Calculating Success Metrics of Agile Software Projects

Agile development methodologies are considered the most important guarantor for the success of software development project as they depend on the best practices in the development process rather than on the theatrical concepts. But, because of the unclear and ambiguous indicators within agility evaluation, most metrics are described in a form of human-like language by linguistic terms which are described by ambiguity and multi-possibility, so that such metrics cannot be effectively handled the conventional evaluation approaches. However, fuzzy logic provides useful techniques for dealing with decisions in such environments which contain imprecise and vague values. Accordingly, using of fuzzy logic techniques will be a good choice. Thus, this paper proposes a framework for calculating Success Metrics (SM) of agile software projects based on fuzzy logic to address the ambiguity in agility assessment. The paper presents the details of the proposed framework and an illustrative example.
Sperm stratification and paternity success in red flour beetles

Abstract. When females are inseminated by multiple males, male paternity success (sperm precedence) is determined by the underlying processes of sperm storage and sperm utilization. Although informative for many questions, two‐male sperm competition experiments may offer limited insight into natural mating scenarios when females are likely to mate with several males. In this study, genetic markers in Tribolium castaneum are used to trace paternity for multiple sires, and to determine whether displacement of stored sperm that occurs after a third mating equally affects both previous mates, or if fertilizations are disproportionately lost by the female's most recent mate. For 20 days after triple‐matings, first males retain significantly higher paternity success (relative to first male paternity in double‐matings) compared with second males. These results demonstrate that when females remate before sperm mixing occurs, sperm stratification results in differential loss of sperm from the most recent mate. This study provides insight into the mechanisms underlying sperm precedence in a promiscuous mating system, and suggests that T. castaneum females could limit paternity success of particular mates by remating with more highly preferred males.
Resistance Training for Diabetes Prevention and Therapy: Experimental Findings and Molecular Mechanisms

Type 2 diabetes mellitus (T2D) is characterized by insulin resistance, impaired glycogen synthesis, lipid accumulation, and impaired mitochondrial function. Exercise training has received increasing recognition as a cornerstone in the prevention and treatment of T2D. Emerging research suggests that resistance training (RT) has the power to combat metabolic dysfunction in patients with T2D and seems to be an effective measure to improve overall metabolic health and reduce metabolic risk factors in diabetic patients. However, there is limited mechanistic insight into how these adaptations occur. This review provides an overview of the intervention data on the impact of RT on glucose metabolism. In addition, the molecular mechanisms that lead to adaptation in skeletal muscle in response to RT and that are associated with possible beneficial metabolic responses are discussed. Some of the beneficial adaptations exerted by RT include increased GLUT4 translocation in skeletal muscle, increased insulin sensitivity and hence restored metabolic flexibility. Increased energy expenditure and excess postexercise oxygen consumption in response to RT may be other beneficial effects. RT is increasingly establishing itself as an effective measure to improve overall metabolic health and reduce metabolic risk factors in diabetic patients.
Language support for incremental integration of independently developed components in Java

The aim of component-based software development is to assembly applications from existing components, writing as little extra code as possible. For programmers, assembly of applications from existing components should increase reuse, thus allowing them to concentrate on value-added tasks and to produce high-quality software within a shorter time. For users, component-based software development promises tailor made functionality from the adaptaion of ready-made components. However, this ideal scenario has not yet become reality: today, many applications are still developed from scratch, and there are still relatively few ready-made components that can be easily reused in new applications. Why is it so? We believe that part of the answer is that current object-oriented programming languages are missing support for non-invasive dynamic adaptation that works at the level of multiple objects simultaneously. Such support would allow unanticipated, incremental modifications of a system's components at runtime. In this paper we propose Lasagne/J an extension of the Java programming language that helps programmers to overcome many of the integration problems that they face when assembling new applications from components developed by independent component vendors.