Miracle-dz/UniFAR-FTUs huggingface dataset:
A Reduction Ordering for Higher-Order Terms

We investigate one of the classical problems of the theory ofterm rewriting, namely termination. We present an ordering for compar-ing higher-order terms that can be utilized for testing termination anddecreasingness of higher-order conditional term rewriting systems. Theordering relies on a first-order interpretation of higher-order terms anda suitable extension of the RPO.
ONLINE APPROXIMATORS FOR THE ACTUATORS FDI OF A SMALL COMMERCIAL AIRCRAFT

Abstract In this paper the problem of detecting and isolating faults on the actuators of a small commercial aircraft using online approximators is dealt with. In particular the capabilities of radial basis neural networks to approximate faults on the engines and elevators of an AP-68 Vulcanair commercial aircraft are investigated also in the presence of model uncertainties and external disturbances. The structure of the aircraft and of the fault models appears to be well suited for this kind of application. Although some effort has to be spent in tuning a certain number of parameters, the numerical results obtained on a full nonlinear Matlab-Simulink simulator of the aircraft seem to be encouraging.
Maximizing Network Utilization for SDN Based on WiseAnt Colony Optimization

Software-Defined Network (SDN) allows a centralized controller to globally plan packets forwarding according to the operator's objectives. It may require more forwarding rules, and multi-path routing which is allowed in SDN to improve network utilization and throughput means more forwarding rules. However, the forwarding table in TCAM-based SDN switch is an important but limited resource. With this limitation, to satisfy global network objective, such as maximum flow, we formulate this problem as the Bounded Forwarding-Rules Maximum Flow (BFR-MF) problem which is NP-hard. We maintain fairness among flows to guarantee the performance of individual flows and a certain level of QoS. We improve the Ant Colony Optimization algorithm, such as adding heuristic information based on forwarding table size, and propose the WiseAnt Colony Optimization (WACO) algorithm to solve the BFR-MF problem. We use normalized maximum flow to evaluate the performance of WACO algorithm. Extensive simulations show that WACO algorithm performs better in network utilization on the premise of a certain level of QoS, especially for the data center network.
Appearance of TSH Receptor Antibody and Associated with Metastatic Thyroid Cancer Thyroidectomy Hyperthyroidism after Total JAEDUK

We report here on a patient who was diagnosed with follicular carcinoma in 1985, and who was treated with total thyroidectomy. Two years later, when metastasis was found in his neck lesion, lung, pelvis and right femur, the patient received 131I treatment. Six years after receiving 131I treatment, the patient presented with hyperthyroidism. Whole-body scan with 131I revealed functioning metastasis in his right femur and pelvis. There was no hot spot in the neck region, confirming that no thyroid tissue remained. Blood panels revealed an increase in both TSH binding inhibitory immunoglobulin (TBII. 36.2%; normal. -10-10%) and thyroid stimulating antibody (TSAb, 176%; normal, less than 145%). Treatment with antithyroid drugs, dexamethasone and radioisotope therapy rapidly resolved his hyperthyroidism. Thyrotoxicosis and positive TRAb occurred in the absence of thyroid tissue, and many years after the completion of Rl therapy. The overproduction of thyroid hormone can therefore only be attributed to some mechanism of activity in the metastatic tumor tissue. Key wor ds: Follicular carcinoma, Hyperthyroi dism, Thyrotoxicosis, TSH receptor antibody (Endocrine Journal 44: 855-859,1997) NEARLY 45 cases of thyrotoxicosis associated with thyroid carcinoma have been reported [1-20]. The occurrence of thyrotoxicosis is usually attributed to the overproduction of thyroid hormone in the thyroid tissue. In a few patients with metastatic disease, TSH binding inhibitory immunoglobulin (TBII) has been detected and resulted in thyrotoxicosis [6, 11, 20]. In all these patients, normal thyroid tissue remained, making it possible that the TSH receptor in this normal tissue served as an antigen. The RI therapy used to destroy the metastatic tissue might also have initiated an autoimmune response. This is the only case reported in which no normal thyroid tissue remained as a site for TSH receptors, and in which Received: February 25, 1997 Accepted: September 18, 1997 Correspondence to: Dr. Jaeduk YOSHIMURA NOH, Ito Hospital, 4-3-6 Jingumae, Shibuya-ku, Tokyo 150, Japan RI treatment had occurred so many years in the past that it was unlikely to have contributed to the disease.
Heterogeneous and runtime parameterizable Star-Wheels Network-on-Chip

Multiprocessor Systems-on-Chip (MPSoCs) are a promising solution to fulfill the requirements of high performance computing applications, such as image processing or bioinformatics. Many different MPSoC architectures are introduced by industry and academics, such as Intel's Single Cloud Computer (SCC) or IBM's Cell. To achieve a high efficiency on such MPSoCs a high computing performance in the processing elements (PE) is not the only parameter. The bandwidth of the memory and especially the on-chip communication infrastructure are extremely important to achieve the requirements of the applications. Furthermore, for embedded System-on-Chip solutions, flexibility is extremely important for providing a good tradeoff between performance and power consumption. Especially, for general purpose MPSoCs, designed for a wide range of applications with different communication demands, this flexibility is essential for a good energy efficiency. A simple bus or Network-on-Chip (NoC) with fixed bandwidth and communication paradigm is not sufficient in this varying application scenario and its design space. In this paper novel features for the heterogeneous and runtime adaptive Star-Wheels Network-on-Chip are presented. This Network-on-Chip is used within a runtime adaptive MPSoC, which enables to tailor processors and accelerators to the requirements of the applications. For optimizing the Star-Wheels Network-on-Chip and its communication protocol at runtime to the application requirement the following novel features have been added: the combination of the circuit- and the packet-switched communication paradigm and an algorithm-based placement of the processing elements within the NoC. The integration of the novel algorithm into the design methodology and the exploitation of the novel features within the special purpose runtime operating system of a runtime adaptive MPSoC are also introduced.
Using Genetic Algorithms with Small Populations

Most reported (serial) implementations of genetic algorithms have assumed population sizes of at least 30, and often very much larger. The general question of population sizing has been considered from several aspects, with somewhat connicting conclusions , and then only for populations of binary strings. In this paper we consider applications where it is important to use as small a population as possible, where the number of tness evaluations is limited, and where non-binary representations are important. First, we approach the question of specifying a minimum size by asking what characteristics of an initial population are likely to lead to poor performance, and calculate population sizes which will almost certainly avoid such features, on the assumption that initial populations are chosen in a random fashion. It will be shown that rather small populations suuce for binary strings, but that populations need to be considerably larger for the more general case where string alleles are de-ned over q-ary alphabets. This also gives an interesting sidelight on the debate in respect of the general desirability of using higher-cardinality alphabets. We then consider whether we should choose initial populations other than randomly, and make some connections with work in the elds of error-detecting codes and experimental design. Finally, we report some computational comparisons which suggest that using a structured initial population may be helpful .
Propagation in a Model of Goods, Labor and Financial Market Frictions !

Investigating mechanisms of propagation has been central to the business cycle research agenda since its inception. Recent search models of the labor market fail in generating both the size and the persistence of their of central variables to productivity shocks, as does the RBC model in the case of output. Building a model with three imperfect markets - goods, labor and credit -, we find that goods market frictions drastically change the qualitative and quantitative dynamics of labor market variables, leading to significant improvements in bridging the gap with the data both in terms of persistence and volatility. Two factors affecting the expected path of the value to hiring a worker generate persistence: first, the expected dynamics of congestion on goods market, which depends on consumers' search for goods and the entry of new products; and second, the expected dynamics of prices, which alter future profit flows. In the absence of these frictions, there is no persistence in the growth rates, and little amplification, of labor market variables.
Cortactin, an 80/85-kilodalton pp60src substrate, is a filamentous actin-binding protein enriched in the cell cortex

Two related cellular proteins, p80 and p85 (cortactin), become phosphorylated on tyrosine in pp60src-transformed cells and in cells stimulated with certain growth factors. The amino-terminal half of cortactin is comprised of multiple copies of an internal, tandem 37- amino acid repeat. The carboxyl-terminal half contains a distal SH3 domain. We report that cortactin is an F-actin-binding protein. The binding to F-actin is specific and saturable. The amino-terminal repeat region appears to be both necessary and sufficient to mediate actin binding, whereas the SH3 domain had no apparent effect on the actin- binding activity. Cortactin, present in several different cell types, is enriched in cortical structures such as membrane ruffles and lamellipodia. The properties of cortactin indicate that it may be important for microfilament-membrane interactions as well as transducing signals from the cell surface to the cytoskeleton. We suggest the name cortactin, reflecting the cortical subcellular localization and its actin-binding activity.
ITSPOKE: An Intelligent Tutoring Spoken Dialogue System

ITSPOKE is a spoken dialogue system that uses the Why2-Atlas text-based tutoring system as its "back-end". A student first types a natural language answer to a qualitative physics problem. ITSPOKE then engages the student in a spoken dialogue to provide feedback and correct misconceptions, and to elicit more complete explanations. We are using ITSPOKE to generate an empirically-based understanding of the ramifications of adding spoken language capabilities to text-based dialogue tutors.
Convergence Analysis of Perturbed Feasible Descent Methods

We develop a general approach to convergence analysis of feasible descent methods in the presence of perturbations. The important novel feature of our analysis is that perturbations need not tend to zero in the limit. In that case, standard convergence analysis techniques are not applicable. Therefore a new approach is needed. We show that, in the presence of perturbations, a certain "-approximate solution can be obtained, where " depends on the level of perturbations linearly. Applications to the gradient projection, proximal minimization, extragradient and incremental gradient algorithms are described.
Virtual fusion for speaker recognition

This paper presents a simplified post-classification framework for enhancing the performance of a given speaker recognition classifier by means of other “auxiliary” classifiers. We call it Virtual Fusion, since the assisting classifiers are used only for training the post-classifier and are not necessary in operating mode. Experiments performed using Nist’04 and ’05 evaluations suggest that the proposed technique is able to consistently improve the EER of a typical GMM-cepstrum classifier by up to 15%.
Timestamp removal for panorama video surveillance

This paper presents a fast algorithm to locate and remove overlaid video timestamps for panorama video surveillance. The timestamp removal for panorama video surveillance is a challenge research problem because it allows a very short processing time and it requires to recovery the covered objects. And the existing general object localization methods cannot localize the timestamp reliably and the existing object removal methods cannot remove timestamps with high visual scene consistence. For the timestamp localization, this paper customizes the existing method of localizing digital video clocks. For timestamp removal this paper proposes a fast and novel procedure. Its fast speed is because it employs a fast image registration method mainly by fusing the PTZ camera motion estimation and global histogram-based image matching. Then it recoveries the pixels covered by timestamps by using a temporal-neighbor pixel recovery method. The extensive experimental results show that the proposed algorithm can remove a timestamp within 2 seconds and the recovered frames are visually consistent with the real scene.
Dependence balance outer bounds for the discrete memoryless two-way multiple access broadcast channel

We present an outer bound for the discrete memo-ryless two-way multiple access broadcast channel (TW-MAC/BC) using the dependence balance idea. The cut-set outer bound for multi-user channels allows arbitrarily correlated input distributions while the dependence balance idea limits the set of arbitrarily correlated input distributions to those satisfying a specific constraint known as dependence balance bound, which is particularly useful in channels with feedback or adaptation, as in two-way channels. We obtain a general dependence-balance-based outer bound for the discrete memoryless TW-MAC/BC, and a parallel channel extension for the single-output channel. We then show that for the single-output binary additive noisy TW-MAC/BC Y = X1 + X2 + X3 + Z (Z Bernoulli(0.5)), an outer bound to the symmetric sum-rate of our outer bound is strictly smaller than that of the cut-set outer bound. This is shown using the composite function technique introduced by Willems and used by Tandon and Ulukus in the context of multiple-access channels with feedback.
When Do States Say Uncle? Network Dependence and Sanction Compliance

ABSTRACT In this article we address the long-debated question of when and why states comply with sanctions. While the literature remains indeterminate as to whether the key mechanisms driving sanction compliance are tied to interstate relations, intrastate constraints, or a dynamic combination of the two, our theoretical framework and methodological approach provide a novel perspective that incorporates insights drawn from network theory to explain the time until countries comply. Specifically, we argue that reciprocity, a concept with deep roots in both network theory and international relations, has largely been overlooked in the study of sanction compliance. Though often ignored, this concept captures an essential aspect of how cooperation is fostered in the international system and allows us to better analyze the strategic environment underlying sanctioning behavior. Given the theoretical importance of reciprocity in understanding interstate relations, we provide an approach that integrates estimations of this type of network interdependency into extant frameworks for modeling the time until countries comply with sanctions. Our results highlight that reciprocity not only has a substantive effect in explaining the duration of sanctions but that models excluding this concept from their specifications do notably worse in terms of their predictive performance.
Improving Real-Time Software Quality by Direct Specification of Timing Requirements

In real-time programming, correct timing is as important as correct computational results. However, most real-time programming languages focus on concurrency rather than timing, leaving timing as an indirect result of task priorities and process synchronization. The resulting systems often have high complexity and tend to obfuscate the intentions of the programmer when it comes to timing. In this paper it is demonstrated how the integration of a timing construct into a programming language can improve on this when supported by synchronous communication and an earliest deadline first scheduler. It is argued that the scheduler should be lazy, and not execute statements without deadlines even if they are ready and the system is otherwise idle. This leads to a heightened awareness of the timing requirements associated with the different functionality in the system, and ultimately to the potential use of timing responsibilities as a new way of structuring a program.
Design space exploration of a software speculative parallelization scheme

With speculative parallelization, code sections that cannot be fully analyzed by the compiler are optimistically executed in parallel. Hardware schemes are fast but expensive and require modifications to the processors and/or memory system. Software schemes require no changes to the hardware of existing shared-memory systems, but can suffer from significant overheads involved with the speculative execution. In fact, the performance of software schemes is highly dependent on application characteristics, the design and implementation of the scheme, and the system configuration and size. This paper explores the design space of a recently proposed software speculative parallelization scheme. In the process, we gain insight into the most beneficial features of software schemes for speculative parallelization, as well as the most influential application characteristics. For instance, experimental results show that, contrary to intuition, checking for data dependence violations on every speculative store, as opposed to at commit time, leads to little performance degradation in the worst case and to significantly better performance with large configurations. Also, scheduling policies based on windows can perform very close to fully dynamic policies with a fraction of the memory overhead. Finally, experimental results show consistent speedups in the execution of loops that cannot be parallelized at compile time, both with and without RAW data dependences, for 4 to 32 processors.
The Influence of Gender-role Socializatioii , Media Use and Sports Participation on Perceptions of Gender-Appropriate Sports

This study seeks to update understanding of how sports in U.S. society are viewed in light ofgender norms. A survey of 340 college students found that even youth who have grown up with Title IXstill rate most sports as masculine, including the newer action sports even though these sports incorporate elements considered generally feminine. The study also examined the relationship between media use, sports participation, and gender role socialization with the typing of sports as masculine or feminine; although these factors seemed to impact typing for some sports by degrees, overall findings suggest that traditional gender-typing of sports is resilient. Using Bandura's (¡986) social learning theory, the authors suggest that until mediated images are more inclusive of women in a variety of sports, rising participation rates by women in sports and fitness activities will do little to change traditional gender-typing.
Chalmers Publication Library Gaussian MAP Filtering Using Kalman Optimization

This paper deals with the update step of Gaussian MAP filtering. In this framework, we seek a Gaussian approximation to the posterior probability density function (PDF) whose mean is given by the maximum a posteriori (MAP) estimator. We propose two novel optimisation algorithms which are quite suitable for finding the MAP estimate although they can also be used to solve general optimisation problems. These are based on the design of a sequence of PDFs that become increasingly concentrated around the MAP estimate. The resulting algorithms are referred to as Kalman optimisation (KO) methods. We also provide the important relations between these KO methods and their conventional optimisation algorithms (COAs) counterparts, i.e., Newton ́s and Levenberg-Marquardt algorithms. Our simulations indicate that KO methods are more robust than their COA equivalents.
Improved PCR Performance Using Template DNA from Formalin-Fixed and Paraffin-Embedded Tissues by Overcoming PCR Inhibition

Formalin-fixed and paraffin-embedded (FFPE) tissues represent a valuable source for biomarker studies and clinical routine diagnostics. However, they suffer from degradation of nucleic acids due to the fixation process. Since genetic and epigenetic studies usually require PCR amplification, this degradation hampers its use significantly, impairing PCR robustness or necessitating short amplicons. In routine laboratory medicine a highly robust PCR performance is mandatory for the clinical utility of genetic and epigenetic biomarkers. Therefore, methods to improve PCR performance using DNA from FFPE tissue are highly desired and of wider interest. The effect of template DNA derived from FFPE tissues on PCR performance was investigated by means of qPCR and conventional PCR using PCR fragments of different sizes. DNA fragmentation was analyzed via agarose gel electrophoresis. This study showed that poor PCR amplification was partly caused by inhibition of the DNA polymerase by fragmented DNA from FFPE tissue and not only due to the absence of intact template molecules of sufficient integrity. This PCR inhibition was successfully minimized by increasing the polymerase concentration, dNTP concentration and PCR elongation time thereby allowing for the robust amplification of larger amplicons. This was shown for genomic template DNA as well as for bisulfite-converted template DNA required for DNA methylation analyses. In conclusion, PCR using DNA from FFPE tissue suffers from inhibition which can be alleviated by adaptation of the PCR conditions, therefore allowing for a significant improvement of PCR performance with regard to variability and the generation of larger amplicons. The presented solutions to overcome this PCR inhibition are of tremendous value for clinical chemistry and laboratory medicine.
Data-aware DRAM refresh to squeeze the margin of retention time in hybrid memory cube

With the increase of storage density, DRAM refresh leads to higher overhead of power and bandwidth, particularly in emerging 3D stacked memory design like Hybrid Memory Cube (HMC). To exploit the hardware resources for a smarter solution, we propose a data-aware refresh control scheme, Trial and Error (Trial-n-Error), which leverages the data-pattern dependence characteristics of the cells' retention time to reduce refresh operations. Trial-n-Error is a systematic approach that employs our proposed Synergy Testing to capture the refresh bottleneck of DRAM memory: “weak” cells that have a relatively shorter retention time. By locating the dominant weak cells sensitized by applications, Trial-n-Error can avoid the worst-case refresh setting, and adjust the refresh rate under the control of our self-tuning algorithm. Thus, Trial-n-Error can gradually approach to the possible lower-bound of refresh rate for less energy and memory bandwidth consumption. In experiments of 3D-stacked DRAMs, we successfully eliminate an average of 28% refresh operations and save 21% refresh energy for a set of pre-profiled synthetic data patterns and real benchmarks.