Miracle-dz/UniFAR-FTUs huggingface dataset:
A new adaptive equalizer for carrierless amplitude and phase (CAP) receivers

In carrierless amplitude and phase (CAP) modulation systems, receivers with adaptive linear equalizers generally use an equalizer structure consisting of two parallel arms of fractionally-spaced, tapped-delay-line filters for channel equalization. In this paper, we proposed a new adaptive equalizer based on the existing structure. For infinite number of taps, both equalizers with optimum weights provide the same level of mean-square error (MSE) performance. In comparison with the existing equalizer using the standard least mean square (LMS) algorithm, the new equalizer with a modified LMS algorithm has less than half the misadjustment for the same convergence rate. Alternatively, for the same misadjustment, the weights of the new adaptive equalizer converge faster than the existing equalizer.
Supervising interest rate risk management

This Economic Letter reviews the Basel Capital Accord's stated principles on interest rate risk. In brief, the principles strongly support the idea that banks' internal risk assessments should, whenever possible, form the basis for supervisory oversight of their interest rate risk profiles. The principles suggest supervisory guidelines for assessing the adequacy of interest rate risk management systems, such as focusing on banks' internal control functions and stress-testing results.
A simple method of enhancing magnetic filter efficiency

In filtered vacuum arc deposition, the plasma produced by spots is passed through a curved duct by means of a magnetic field, in order to remove macroparticles which would otherwise contaminate the deposition. In this paper, it is suggested that the plasma throughput efficiency in such a magnetic filter may be enhanced by locating the plasma source (e.g. the vacuum arc cathode) in the free-passage zone at the duct entrance.
Chitosan–chondroitin sulphate nanoparticles for controlled delivery of platelet lysates in bone regenerative medicine

In this study, a new formulation of nanoparticles (NPs) based on the electrostatic interaction between chitosan and chondroitin sulphate (CH–CS NPs) is proposed for the controlled release of proteins and growth factors (GFs), specifically platelet lysates (PLs). These nanoparticulate carriers are particularly promising for protein entrapment because the interactions between the polysaccharides and the entrapped proteins mimic the interactions between chondroitin sulphate and proteins in the native extracellular matrix (ECM). Spherical non‐cytotoxic NPs were successfully produced, exhibiting high encapsulation efficiency for physiological levels of GFs and a controlled protein release profile for > 1 month. Moreover, it was also observed that these NPs can be uptaken by human adipose‐derived stem cells (hASCs), depending on the concentration of NPs in the culture medium and incubation time. This shows the versatility of the developed NPs, which, besides acting as a protein delivery system, can also be used in the future as intracellular carriers for bioactive agents, such as nucleotides. When the PL‐loaded NPs were used as a replacement of bovine serum for in vitro hASCs culture, the viability and proliferation of hASCs was not compromised. The release of PLs from CH–CS NPs also proved to be effective for the enhancement of in vitro osteogenic differentiation of hASCs, as shown by the increased levels of mineralization, suggesting not only the effective role of the delivery system but also the role of PLs as an osteogenic supplement for bone tissue engineering and regenerative medicine applications. Copyright © 2012 John Wiley & Sons, Ltd.
Processing Efficiency of Divided Spatial Attention Mechanisms in Human Visual Cortex

Many visual tasks require deployment of attention to multiple objects or locations. We used functional magnetic resonance imaging and behavioral experiments to investigate the relative processing efficiency of two putative attentional mechanisms for performing such tasks: the “zoom lens” and “multiple spotlights. ” Two key questions were investigated: (1) does splitting the spotlight into multiple foci incur an overhead cost that diminishes the efficacy of attention compared with the zoom lens, and (2) does splitting the spotlight provide a benefit relative to the zoom lens by conserving attention resources that otherwise would be directed to task irrelevant stimuli? For both mechanisms, attending to multiple object locations decreased processing efficiency at a single location, resulting in both decreased behavioral performance and decreased blood oxygenation level-dependent (BOLD) signal attentional modulation. When the two mechanisms attended to multiple objects across the same spatial extent, the multiple spotlight mechanism, which ignores intervening stimuli, yielded better performance and higher BOLD signal. When the two mechanisms processed the same number of stimuli, splitting the spotlight neither impaired performance nor diminished BOLD signal in occipital cortex. The surprising efficiency of the multiple spotlight mechanism supports the emerging view that spatial attention is easily deployed in a diverse range of spatial configurations.
ESL/EFL Instructors' Perceptions of the Efficacy of Online Reading Instruction

New technologies offer significant potential for teaching and learning L2 reading skills. Accordingly, this study examined ESL/EFL instructors’ perceptions of the usefulness and effectiveness of online reading in L2 reading instruction. A convenience sample of seventy male and female ESL/EFL instructors was selected, and the respondents completed a 24-item, researcher-constructed questionnaire and responded to open-ended questions. Descriptive and inferential statistical analysis, including means and standard deviations, as well as various statistical tests, such as paired t-tests and bootstrapped p-values, were used to assess the data. Results revealed that the participants held strong beliefs about the usefulness of online reading in improving the quality of L2 reading instruction and developing learners’ reading skills. A thorough discussion of these results is provided. These findings highlight significant practical, technical, and pedagogical implications for online L2 reading classrooms, particularly in terms of teacher training and practices of computer integration.
An impedance control for simplified hydraulic model with Casimir functions

This paper gives a new impedance control of non-mechanical systems whose inputs are not effort (torque) but flow (velocity). First, we illustrate structural properties of such systems using a simeple example. Then, we give a new impledance control for the non-mechanical system with flow-input ports using Casimir functions. The proposed method does not have any canceling action.
Daylight Saving Time Transitions and Road Traffic Accidents

Circadian rhythm disruptions may have harmful impacts on health. Circadian rhythm disruptions caused by jet lag compromise the quality and amount of sleep and may lead to a variety of symptoms such as fatigue, headache, and loss of attention and alertness. Even a minor change in time schedule may cause considerable stress for the body. Transitions into and out of daylight saving time alter the social and environmental timing twice a year. According to earlier studies, this change in time-schedule leads to sleep disruption and fragmentation of the circadian rhythm. Since sleep deprivation decreases motivation, attention, and alertness, transitions into and out of daylight saving time may increase the amount of accidents during the following days after the transition. We studied the amount of road traffic accidents one week before and one week after transitions into and out of daylight saving time during years from 1981 to 2006. Our results demonstrated that transitions into and out of daylight saving time did not increase the number of traffic road accidents.
Role of polysaccharides in food, digestion, and health

ABSTRACT Polysaccharides derived from plant foods are major components of the human diet, with limited contributions of related components from fungal and algal sources. In particular, starch and other storage carbohydrates are the major sources of energy in all diets, while cell wall polysaccharides are the major components of dietary fiber. We review the role of these components in the human diet, including their structure and distribution, their modification during food processing and effects on functional properties, their behavior in the gastrointestinal tract, and their contribution to healthy diets.
Learning-based image representation and method for face recognition

This paper presents a novel method for face recognition. First, we generate the new image representation from the decorrelated hybrid color configurations rather than RGB color space via a learning algorithm. The learning algorithm, Principal Component Analysis (PCA) plus Fisher Linear Discriminant analysis (FLD), is able to derive the desired color transformation to generate a discriminating image representation that is optimal for face recognition. Second, we partition face image into some small patches, each of which can obtain its own color transformation, to reduce the effect of illumination variations. Thus, a patch-based novel image representation method is proposed for face recognition. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 show that the proposed method outperforms gray-scale image and some recent methods in face recognition.
Quantitative Microbial Community Analysis of Three Different Sulfidic Mine Tailing Dumps Generating Acid Mine Drainage

ABSTRACT The microbial communities of three different sulfidic and acidic mine waste tailing dumps located in Botswana, Germany, and Sweden were quantitatively analyzed using quantitative real-time PCR (Q-PCR), fluorescence in situ hybridization (FISH), catalyzed reporter deposition-FISH (CARD-FISH), Sybr green II direct counting, and the most probable number (MPN) cultivation technique. Depth profiles of cell numbers showed that the compositions of the microbial communities are greatly different at the three sites and also strongly varied between zones of oxidized and unoxidized tailings. Maximum cell numbers of up to 109 cells g−1 dry weight were determined in the pyrite or pyrrhotite oxidation zones, whereas cell numbers in unoxidized tailings were significantly lower. Bacteria dominated over Archaea and Eukarya at all tailing sites. The acidophilic Fe(II)- and/or sulfur-oxidizing Acidithiobacillus spp. dominated over the acidophilic Fe(II)-oxidizing Leptospirillum spp. among the Bacteria at two sites. The two genera were equally abundant at the third site. The acidophilic Fe(II)- and sulfur-oxidizing Sulfobacillus spp. were generally less abundant. The acidophilic Fe(III)-reducing Acidiphilium spp. could be found at only one site. The neutrophilic Fe(III)-reducing Geobacteraceae as well as the dsrA gene of sulfate reducers were quantifiable at all three sites. FISH analysis provided reliable data only for tailing zones with high microbial activity, whereas CARD-FISH, Q-PCR, Sybr green II staining, and MPN were suitable methods for a quantitative microbial community analysis of tailings in general.
Changes in worker fatigue after vitamin C administration

Abstract Objective : In recent research, the role of oxidative stress has been an important factor in fatigue. The principal objective of this study was to evaluate changes in fatigue in workers after vitamin C administration. Methods : We consecutively examined 44 workers who work regularly. They were orally administered 6 g of vitamin C daily for 2 weeks. We then investigated the demographic data and assessed any changes in the patients’ fatigue scale (VAS, FSS) and blood tests (vitamin C, HgA1c, CRP, AST, ALT, r-GTP, cortisol). Results: In fatigue, both VAS and FSS improved after vitamin C administration (p<0.005). In blood tests, AST, ALT, r-GTP, HgA1c, CRP, and cortisol were reduced after vitamin C administration (p<0.005). Conclusions : Vitamin C administration reduced fatigue symptoms and improved blood tests with fatigue in workers.
Gastric Inhibitory Polypeptide (GIP) Is Selectively Decreased in the Roux-Limb of Dietary Obese Mice after RYGB Surgery

Gastric inhibitory polypeptide (GIP, glucose-dependent insulinotropic polypeptide) is expressed by intestinal K cells to regulate glucose-induced insulin secretion. The impact of Roux-en Y bypass (RYGB) surgery on blood GIP is highly contraversial. This study was conducted to address the mechanism of controversy. GIP mRNA was examined in the intestine, and serum GIP was determined using Luminex and ELISA in diet-induced obese (DIO) mice. The assays were conducted in RYGB mice in fasting and fed conditions. Food preference, weight loss and insulin sensitivity were monitored in RYGB mice. In DIO mice, GIP mRNA was increased by 80% in all sections of the small intestine over the lean control. The increase was observed in both fasting and fed conditions. After RYGB surgery, the food-induced GIP expression was selectively reduced in the Roux-limb, but not in the biliopancreatic and common limbs of intestine in fed condition. Lack of stimulation by glucose or cholesterol contributed to the reduction. Jejunal mucosa of Roux-limb exhibited hypertrophy, but villous surface was decreased by the undigested food. Serum GIP (total) was significantly higher in the fasting condition, but not in the fed condition due to attenuated GIP response to food intake in RYGB mice. The GIP alteration was associated with chow diet preference, sustained weight loss and insulin sensitization in RYGB mice. RYGB increased serum GIP in the fasting, but not in the fed conditions. The loss of food-induced GIP response in Roux-limb of intestine likely contributes to the attenuated serum GIP response to feeding.
Speech enhancement using excitation source information

This paper proposes an approach for processing speech from multiple microphones to enhance speech degraded by noise and reverberation. The approach is based on exploiting the features of the excitation source in speech production. In particular, the characteristics of voiced speech can be used to derive a coherently added signal from the linear prediction (LP) residuals of the degraded speech data from different microphones. A weight function is derived from the coherently added signal. For coherent addition the time-delay between a pair of microphones is estimated using the knowledge of the source information present in the LP residual. The enhanced speech is generated by exciting the time varying all-pole filter with the weighted LP residual.
Logical Induction

We present a computable algorithm that assigns probabilities to every logical statement in a given formal language, and refines those probabilities over time. For instance, if the language is Peano arithmetic, it assigns probabilities to all arithmetical statements, including claims about the twin prime conjecture, the outputs of long-running computations, and its own probabilities. We show that our algorithm, an instance of what we call a logical inductor, satisfies a number of intuitive desiderata, including: (1) it learns to predict patterns of truth and falsehood in logical statements, often long before having the resources to evaluate the statements, so long as the patterns can be written down in polynomial time; (2) it learns to use appropriate statistical summaries to predict sequences of statements whose truth values appear pseudorandom; and (3) it learns to have accurate beliefs about its own current beliefs, in a manner that avoids the standard paradoxes of self-reference. For example, if a given computer program only ever produces outputs in a certain range, a logical inductor learns this fact in a timely manner; and if late digits in the decimal expansion of π are difficult to predict, then a logical inductor learns to assign ≈ 10% probability to “the nth digit of π is a 7” for large n. Logical inductors also learn to trust their future beliefs more than their current beliefs, and their beliefs are coherent in the limit (whenever φ → ψ, P∞(φ) ≤ P∞(ψ), and so on); and logical inductors strictly dominate the universal semimeasure in the limit. These properties and many others all follow from a single logical induction criterion, which is motivated by a series of stock trading analogies. Roughly speaking, each logical sentence φ is associated with a stock that is worth $1 per share if φ is true and nothing otherwise, and we interpret the belief-state of a logically uncertain reasoner as a set of market prices, where Pn(φ) = 50% means that on day n, shares of φ may be bought or sold from the reasoner for 50¢. The logical induction criterion says (very roughly) that there should not be any polynomial-time computable trading strategy with finite risk tolerance that earns unbounded profits in that market over time. This criterion bears strong resemblance to the “no Dutch book” criteria that support both expected utility theory (von Neumann and Morgenstern 1944) and Bayesian probability theory (Ramsey 1931; de Finetti 1937).
Towards a Decentralized Algorithm for Mapping Network and Computational Resources for Distributed Data-Flow Computations

Several high-throughput distributed data-processing applications require multi-hop processing of streams of data. These applications include continual processing on data streams originating from a network of sensors, composing a multimedia stream through embedding several component streams originating from different locations, etc. These data-flow computing applications require multiple processing nodes interconnected according to the data-flow topology of the application, for on-stream processing of the data. Since the applications usually sustain for a long period, it is important to optimally map the component computations and communications on the nodes and links in the network, fulfilling the capacity constraints and optimizing some quality metric such as end-to-end latency. The mapping problem is unfortunately NP-complete and heuristics have been previously proposed to compute the approximate solution in a centralized way. However, because of the dynamicity of the network, it is practically impossible to aggregate the correct state of the whole network in a single node. In this paper, we present a distributed algorithm for optimal mapping of the components of the data flow applications. We propose several heuristics to minimize the message complexity of the algorithm while maintaining the quality of the solution.
Improving the Convergence of Backpropagation by Opposite Transfer Functions

The backpropagation algorithm is a very popular approach to learning in feed-forward multi-layer perceptron networks. However, in many scenarios the time required to adequately learn the task is considerable. Many existing approaches have improved the convergence rate by altering the learning algorithm. We present a simple alternative approach inspired by opposition-based learning that simultaneously considers each network transfer function and its opposite. The effect is an improvement in convergence rate and over traditional backpropagation learning with momentum. We use four common benchmark problems to illustrate the improvement in convergence time.
KnowSense: A Semantically-enabled Pervasive Framework to Assist Clinical Autonomy Assessment

The KnowSense framework, presented in this work, supports monitoring behavioral aspects of individuals in goal-oriented scenarios, within controlled, pervasive environments. Semantic Web technologies, such as OWL 2, are extensively employed in KnowSense to represent sensor observations and application domain specifics as well as to implement hybrid activity recognition and problem detection solutions. Although the framework can be beneficial in a variety of domains that require multi-sensing and goal-oriented data analytics such as smart homes, it is currently applied in the eminent field of healthcare. In this proof-of-concept health application, it provides the semantic models and intelligent detection of Instrumental Activities of Daily Living (IADLs) to assist in the clinical assessment of autonomy at different stages of dementia.
Low Complexity SNR Estimation for Transmissions Over Time-Varying Flat-Fading Channels

In this paper we present two algorithms for SNR estimation for transmissions over flat-fading time-varying channels. The first method exploits a polynomial approximation of the time-varying channel to derive a joint maximum likelihood estimator of the signal power and noise variance. The second technique is based on a subspace decomposition approach and exploits the inherent properties of the signal correlation matrix. Both algorithms can be implemented with affordable complexity and exhibit excellent performance.
Automated tuning of gain-scheduled control systems

This paper describes an application of nonsmooth optimization to the tuning of fixed-structure gain-scheduled controllers. The gain schedule is tuned over the entire operating range subject to standard frequency-domain requirements at each design point. The result is a smooth, compact scheduling formula that can be either implemented directly or turned into a lookup table. The effectiveness of this approach is illustrated on a gain-scheduled three-loop autopilot for the pitch axis of an airframe.
Comparing and combining unimodal methods for multimodal recognition

Multimodal recognition has recently become more attractive and common method in multimedia information retrieval. In many cases it shows better recognition results than using only unimodal methods. Most of current multimodal recognition methods still depend on unimodal recognition results. Therefore, in order to get better recognition performance, it is important to choose suitable features and classification models for each unimodal recognition task. In this paper, we research several unimodal recognition methods, features for them and their combination techniques, in the application setup of concept detection in image-text data. For image features, we use GoogLeNet deep convolutional neural network (DCNN) activation features and semantic concept vectors. For text features, we use simple binary vectors for tags and word2vec vectors. As the concept detection model, we apply the Multimodal Deep Boltzmann Machine (DBM) model and the Support Vector Machine (SVM) with the linear homogeneous kernel map and the non-linear radial basis function (RBF) kernel. The experimental results with the MIRFLICKR-1M data set show that the Multimodal DBM or the non-linear SVM approaches produce equally good results within the margins of statistical variation.
Allocation of processing resources between right and left spatial attention

Researches in Visual Evoked Potentials (VEPs) showed that spatial attention exerted an amplitude modulation of the attended inputs in primary visual cortex during the interval 80–200 ms following stimulus onset. VEPs data of a classical left or right visual field selective attention experiment were analyzed by the method of spatial principal component analysis (PCA) and statistical analysis. The results indicated that allocation of processing resources in humans had differences between right and left spatial attention when stimuli appeared in unattended position. Transferring attention from right to left demanded more energy than shifting attention from left to right. It implied that right-handed subjects might have an advantage in right spatial attention.