Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of transform filter for sound field reproduction using microphone array and loudspeaker array

In this paper, we propose a novel method of sound field reproduction using a microphone array and loudspeaker array. Our objective is to obtain the driving signal of a planar or linear loudspeaker array only from the sound pressure distribution acquired by the planar or linear microphone array. In this study, we derive a formulation of the transform from the received signals of the microphone array to the driving signals of the loudspeaker array. The transform is achieved as a mean of a filter in a spatio-temporal frequency domain. Numerical simulation results are presented to compare the proposed method with the method based on the conventional least square algorithm. The reproduction accuracies were found to be almost the same, however, the filter size and amount of calculation required for the proposed method were much smaller than those for the least square algorithm based one.
Hippocampus Shape Analysis and Late-Life Depression

Major depression in the elderly is associated with brain structural changes and vascular lesions. Changes in the subcortical regions of the limbic system have also been noted. Studies examining hippocampus volumetric differences in depression have shown variable results, possibly due to any volume differences being secondary to local shape changes rather than differences in the overall volume. Shape analysis offers the potential to detect such changes. The present study applied spherical harmonic (SPHARM) shape analysis to the left and right hippocampi of 61 elderly subjects with major depression and 43 non-depressed elderly subjects. Statistical models controlling for age, sex, and total cerebral volume showed a significant reduction in depressed compared with control subjects in the left hippocampus (F1,103 = 5.26; p = 0.0240) but not right hippocampus volume (F1,103 = 0.41; p = 0.5213). Shape analysis showed significant differences in the mid-body of the left (but not the right) hippocampus between depressed and controls. When the depressed group was dichotomized into those whose depression was remitted at time of imaging and those who were unremitted, the shape comparison showed remitted subjects to be indistinguishable from controls (both sides) while the unremitted subjects differed in the midbody and the lateral side near the head. Hippocampal volume showed no difference between controls and remitted subjects but nonremitted subjects had significantly smaller left hippocampal volumes with no significant group differences in the right hippocampus. These findings may provide support to other reports of neurogenic effects of antidepressants and their relation to successful treatment for depressive symptoms.
Negative Training Data Can be Harmful to Text Classification

This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Traditional binary classification involves building a classifier using labeled positive and negative training examples. The classifier is then applied to classify test instances into positive and negative classes. A fundamental assumption is that the training and test data are identically distributed. However, this assumption may not hold in practice. In this paper, we study a particular problem where the positive data is identically distributed but the negative data may or may not be so. Many practical text classification and retrieval applications fit this model. We argue that in this setting negative training data should not be used, and that PU learning can be employed to solve the problem. Empirical evaluation has been conducted to support our claim. This result is important as it may fundamentally change the current binary classification paradigm.
Jesus, Hillel and the Man of the Street. Moral and Social Norms in Heterogeneous Populations

This paper presents an idealized model of social interaction, where preferences are private information and individuals cannot condition their behavior on the identity of whom they are interacting with. An optimal decentralized benchmark rule is identified, where each individual imposes some restriction on what people interacting with him cannot do. Social norms arise in the model as a consequence of reciprocating behavior. I show that social norms can always be reversed, as long as there remains a minimal level of diversity in individual choices. Social norms turn out to be less efficient than democracy as a way to obtain homogeneity in individual behavior. However, both mechanisms are welfare-reducing w.r. t. the decentralized benchmark. Moreover, imposing a single behavior by democratic decision is more welfare-reducing the more fragmented society is (thus the larger the “threat” of invasion from a population with adverse preferences). Unfortunately, this is exactly the case when the law has a higher probability of being implemented. Finally, the democratic decision of banning a specific action is analyzed. I found that bans can be both welfare-reducing or welfare-enhancing w.r. t. the decentralized benchmark. However, they are more likely to be welfare-reducing when they hurt more people (for instance the larger the “threat” of invasion from a population with adverse preferences), but this is when they are more likely to be implemented.
Are Evaluation Metrics Identical With Binary Judgements ?

Many information retrieval (IR) metrics are top-heavy, and some even have parameters for adjusting their discount curve. By choosing the right metric and parameters, the experimenter can arrive at a discount curve that is appropriate for their setting. However, in many cases changing the discount curve may not change the outcome of an experiment. This poster considers query-level directional agreement between DCG, AP, P@10, RBP(p = 0.5) and RBP(p = 0.8), in the case of binary relevance judgments. Results show that directional disagreements are rare, for both top-10 and top-1000 rankings. In many cases we considered, a change of discount is likely to have no effect on experimental outcomes.
A Randomized Cutting Plane Method with Probabilistic Geometric Convergence

We propose a randomized method for general convex optimization problems; namely, the minimization of a linear function over a convex body. The idea is to generate $N$ random points inside the body, choose the best one, and cut the part of the body defined by the linear constraint. We analyze the convergence properties of the algorithm from a theoretical viewpoint, i.e., under the rather standard assumption that an algorithm for uniform generation of random points in the convex body is available. Under this assumption, the expected rate of convergence for such method is proved to be geometric. This analysis is based on new results on the statistical properties of the empirical minimum over a convex body that we obtained in this paper. Moreover, explicit sample size results on convergence are derived. In particular, we compute the minimum number of random points that should be generated at each step in order to guarantee that, in a probabilistic sense, the method performs better than the deterministic center-of-gravity algorithm. From a practical viewpoint, we show how the method can be implemented using hit-and-run versions of Markov-chain Monte Carlo algorithms and exemplify the performance of this implementable modification via a number of illustrative problems. A crucial notion for the hit-and-run implementation is that of boundary oracle, which is available for most optimization problems including linear matrix inequalities and many other kinds of constraints. Preliminary numerical results for semidefinite programs are presented confirming that the randomized approach might be competitive to modern deterministic convex optimization methods.
Compensation Approaches for Far-field Speaker Identification

While speaker identification performance has improved dramatically over the past years, the presence of interfering noise and the variety of channel conditions pose a major obstacle. Particularly the mismatch between training and test condition leads to severe performance degradations. In this paper we explored several approaches to compensation for the effects of reverberation including compensation using linear post-filtering and frame-base score competition.
Comparison of heart rhythm and morphological ECG features in recognition of sleep apnea from the ECG

This study addresses the problem of sleep apnea recognition on a minute-by-minute basis from single-lead ECGs recorded overnight. Analysis of heart rate fluctuations, quantified by the series of RR-intervals, is compared to analysis of ECG morphology variations, assessed using signal vectors from the QRS- and the T-wave region and projecting them onto their first principal component. The resulting series of scalar Karhunen-Loeve coefficients (KLCs) were used as descriptors of morphology. From the derived series, we calculated a measure of similarity and a spectral index in temporal segments of 5 min, and assessed their diagnostic accuracy by ROC-analysis. Although the performance for the RR-series and the similarity feature was 81%/84% sens . /spec. , better results up to 87%/87% were obtained from the T-wave KLCs. It is concluded that the effects of sleep apnea on the ECG are reflected more uniformly in morphology variations of the ECG compared to heart rhythm.
An accurate and extensible mobile IPv6 (xMIPV6) simulation model for OMNeT++

MIPv6 is the IPv6 based mobility management protocol and it is expected to become the mobility management protocol of choice for the Next Generation Wireless Access Networks. In order to develop the understanding of the protocol’s behavior, its suitability for deploying in a wireless environment and in order to be able to propose and develop appropriate improvements and optimizations, it is imperative to have an accurate, reliable and scalable simulation model for the MIPv6 protocol which is fully compliant to the IETF standards and specifications. This paper presents the logic, design and performance results of an extensible MIPv6 (xMIPv6) simulation model integrated into the INET20061020 framework for the OMNeT++ discrete event simulator.
Backup and process migration mechanisms in process support systems

Availability in Process Support Systems (PSS) can be achieved by using standby mechanisms that allow a backup server to take over in case a primary server fails. These mechanisms, resembling the process pair approach used in operating systems, require the primary to send information about state changes to the backup on a regular basis. In PSS where all relevant state information is stored in a database, there are two principal strategies for synchronizing a primary–backup pair. One is to use the replication mechanisms provided by the DBMS. Another is to implement a message mechanism to exchange state information between servers above the database level. For both approaches, several variants exist that allow to trade run-time performance for failover time. This paper discusses the possible strategies and evaluates their performance based on an implementation within the OPERA process support kernel. Moreover, it is shown how the mechanisms can be used as the basis for implementing process migration in a distributed setting.
T Foxp3 Alloantigen-Specific Peripheral Development of Lymph Node Occupancy Is Required for the

We previously demonstrated that L-selectin (CD62L)-dependent T cell homing to lymph nodes (LN) is required for tolerance induction to alloantigen. To explore the mechanisms of this observation, we analyzed the development and distribution of regulatory T cells (Treg), which play an important protective role against allograft rejection in transplantation tolerance. Alloantigen-speciﬁc tolerance was induced using either anti-CD2 plus anti-CD3 mAbs, or anti-CD40L mAbs plus donor-speciﬁc transfusion, in fully mismatched (BALB/c donor, C57BL/6 recipient) vascularized cardiac allografts. An expansion of CD4 (cid:1) CD25 (cid:1) CD62L high T cells was observed speciﬁcally within the LN of tolerant animals, but not in other anatomic sites or under nontolerizing conditions. These cells exhibited a substantial up-regulation of Foxp3 expression as measured by real-time PCR and by ﬂuorescent immunohistochemistry, and possessed alloantigen-speciﬁc suppressor activity. Neither LN nor other lymphoid cells expressed the regulatory phenotype if recipients were treated with anti-CD62L mAbs, which both prevented LN homing and caused early allograft rejection. However, administration of FTY720, a sphingosine 1-phosphate receptor modulator that induces CD62L-independent T cell accumulation in the LNs, restored CD4 (cid:1) CD25 (cid:1) Treg in the LNs along with graft survival. These data suggest that alloantigen-speciﬁc Foxp3
Profiling per-packet and per-byte energy consumption in the NetFPGA Gigabit router

Improving energy efficiency of Internet equipment is becoming an increasingly important research topic, motivated by the need to reduce energy costs (and Carbon footprint) for Internet Service Providers, as well as increase power density to achieve more switching capacity per-rack. While recent research has profiled the power consumption of commercial routing equipment, these profiles are coarse-grained (i.e., at the granularity of per line-card or per port), and moreover such platforms are inflexible for experimentation with new energy-saving mechanisms. In this paper we therefore consider the NetFPGA platform, which is becoming an increasingly popular routing platform for networking research due to its versatility and low-cost. Using a precise hardware-based traffic generator and high-fidelity energy probe, we conduct several experiments that allow us to decompose the energy consumption of the NetFPGA routing card into fine-grained per-packet and per-byte components with reasonable accuracy. Our quantification of energy consumption on this platform opens the doors for estimating network-wide energy footprints at the granularity of traffic sessions and applications (e.g., due to TCP file transfers), and provides a benchmark against which energy improvements arising from new architectures and protocols can be evaluated.
High-density genetic map construction and identification of a locus controlling weeping trait in an ornamental woody plant (Prunus mume Sieb. et Zucc)

High-density genetic map is a valuable tool for fine mapping locus controlling a specific trait especially for perennial woody plants. In this study, we firstly constructed a high-density genetic map of mei (Prunus mume) using SLAF markers, developed by specific locus amplified fragment sequencing (SLAF-seq). The linkage map contains 8,007 markers, with a mean marker distance of 0.195 cM, making it the densest genetic map for the genus Prunus. Though weeping trees are used worldwide as landscape plants, little is known about weeping controlling gene(s) (Pl). To test the utility of the high-density genetic map, we did fine-scale mapping of this important ornamental trait. In total, three statistic methods were performed progressively based on the result of inheritance analysis. Quantitative trait loci (QTL) analysis initially revealed that a locus on linkage group 7 was strongly responsible for weeping trait. Mutmap-like strategy and extreme linkage analysis were then applied to fine map this locus within 1.14 cM. Bioinformatics analysis of the locus identified some candidate genes. The successful localization of weeping trait strongly indicates that the high-density map constructed using SLAF markers is a worthy reference for mapping important traits for woody plants.
Extracting fuzzy classi cation rules with gene expression programming

In essence, data mining consists of extracting knowledge from data. This paper proposes an evolutionary system for discovering fuzzy classi cation rules. Fuzzy logic is useful for data mining especially in the case for performing classi cation task. Three methods were used to extract fuzzy classi cation rules using Evolutionary Algorithms: (1) genetic selection small number of large number of fuzzy candidate rules, (2) genetic reduction of genetic space, selection fuzzy rules from large the candidate rules, (3) genetic learning of fuzzy classi cation rules. In this paper, we propose a new gene expression programming (GEP) algorithm for discovering logical fuzzy classi cation rules, the proposed method has been tested and the results are comparable with other techniques include Genetic Programming (GP).
Chronic Intermittent Ethanol Exposure Alters Stress Effects on (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP) Immunolabeling of Amygdala Neurons in C57BL/6J Mice

The GABAergic neuroactive steroid (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP, allopregnanolone) is decreased in various brain regions of C57BL/6J mice following exposure to an acute stressor or chronic intermittent ethanol (CIE) exposure and withdrawal. It is well established that there are complex interactions between stress and ethanol drinking, with mixed literature regarding the effects of stress on ethanol intake. However, there is little research examining how chronic ethanol exposure alters stress responses. The present work examined the impact of CIE exposure and withdrawal on changes in brain levels of 3α,5α-THP, as well as hormonal and behavioral responses to forced swim stress (FSS). Adult male C57BL/6J mice were exposed to four cycles of CIE to induce ethanol dependence. Following 8 h or 72 h withdrawal, mice were subjected to FSS for 10 min, and 50 min later brains were collected for immunohistochemical analysis of cellular 3α,5α-THP. Behavioral and circulating corticosterone responses to FSS were quantified. Following 8 h withdrawal, ethanol exposure potentiated the corticosterone response to FSS. Following 72 h withdrawal, this difference was no longer observed. Following 8 h withdrawal, stress-exposed mice showed no differences in immobility, swimming or struggling behavior. However, following 72 h withdrawal, ethanol-exposed mice showed less immobility and greater swimming behavior compared to air-exposed mice. Interestingly, cellular 3α,5α-THP levels were increased in the lateral amygdala 8 h and 72 h post-withdrawal in stressed ethanol-exposed mice compared to ethanol-exposed/non-stressed mice. In the paraventricular nucleus of the hypothalamus, stress exposure decreased 3α,5α-THP levels compared to controls following 72 h withdrawal, but no differences were observed 8 h post-withdrawal. There were no differences in cellular 3α,5α-THP levels in the nucleus accumbens shell at either withdrawal time point. These data suggest that there are different mechanisms mediating hormonal, behavioral, and brain responses to stress following CIE exposure. The lateral amygdala appears to be an extremely sensitive brain region exhibiting changes in cellular 3α,5α-THP levels following CIE and exposure to swim stress. It is likely that these changes in cellular 3α,5α-THP levels in the lateral amygdala contribute to the behavioral effects observed following 72 h withdrawal.
Modeling full-length VBR video using Markov-renewal-modulated TES models

This paper describes a general methodology for constructing accurate source models of long sequences (full-length movies) of full-motion compressed VBR (variable bit rate) video, directly from empirical data sets of observed bit rate (frame size) records. The main idea is to first cluster scenes into classes and use TES (transform-expand-sample) processes to carefully model their duration and bit rate processes, and then modulate these scene class models by a Markov-renewal process that governs scene transitions. The resulting model is a Markov-renewal-modulated TES (MRMT) process. The fidelity criteria imposed are relatively stringent in that they call for the simultaneous capture of empirical histograms and autocorrelation functions, as well as the qualitative appearance of the empirical data, including burstiness. To illustrate the methodology, the paper provides a detailed description of the modeling procedure, using a JPEG-like coding trace of the "Star Wars" movie as a working example. The resulting MRMT model was validated by comparing its simulation-based statistics to their empirical counterparts, and by a performance study of the corresponding loss rates for various buffer sizes. The results support the efficacy of the modeling methodology and suggest that suites of realistic and compact source models can be developed for other types of movies under a variety of coding schemes. These may be used to drive realistic Monte Carlo simulations of broadband telecommunications networks.
Development of Molecular Dynamics Simulation System for Large-Scale Supra-Biomolecules, PABIOS (PArallel BIOmolecular Simulator)

The Earth Simulator has the highest power ever achieved to perform molecular dynamics simulation of large-scale supra-molecular systems. Now, we are developing a molecular dynamics simulation system, called PABIOS, which is designed to run a system composed of more than a million particles efficiently on parallel computers. To perform large-scale simulations rapidly and accurately, state-of-the-art algorithms, such as Particle-Particle Particle-Mesh (PPPM) which can compute the long-range Coulomb interaction accurately and efficiently, are implemented. PABIOS uses a domain decomposition method which can achieve high parallelization. To optimize the load balance among the processors, the dynamic load-balancing algo-rithm was developed, and the assignment of subcells in the decomposition method for parallel computations to processors was automatically adjusted during the molecular dynamics simulation. Moreover, to make up for the insufficient parallel efficiency ratio of the PM calculation of PPPM, we have limited the number of processors which deal with the PM calculation and assigned the rest of the processors to other calculations. In order to improve the performance of PABIOS on the Earth Simulator, the algorithm to calculate short-range interactions (PP interactions) was intensively vectorized. A benchmark test was carried out using the system of a RuvA-Holliday junction DNA complex which consisted of 166,177 atoms. At present, PABIOS has achieved a parallelization efficiency ratio of 55.0%, and a vectorization ratio of 97.5% even when 15 nodes (120 processors) are used. As a result, the speed of calculation is about twice as fast as that of last fiscal year.
Further tabulation of the Erdös-Selfridge function

For a positive integer k, the Erdos-Selfridge function is the least integer g(k) > k + 1 such that all prime factors of ( g k (k) ) exceed k. This paper describes a rapid method of tabulating g(k) using VLSI based sieving hardware. We investigate the number of admissible residues for each modulus in the underlying sieving problem and relate this number to the size of g(k). A table of values of g(k) for 135 ≤ k ≤ 200 is provided.
Human-robot interaction design for low cognitive load in cooperative work

This work describes effective interaction design for a cooperative task in which a mobile robot sweeps over a table and a human can help it by picking up an obstacle. For efficient cooperation, we introduce behaviors of a robot to sweep a region under an obstacle when a human picks it up vertically, and designs the robot based on the interaction embedded in a human's operations to achieve a task. This interaction enables a human to easily cooperate with a robot without additional and explicit commands. We made experiments to evaluate the interaction embedded in a task by comparing with other explicit interaction, and the experimental results show that our cooperative sweeping is more efficient than autonomous one and our interaction embedded in a task needs less cognitive load than other explicit interaction such as voice or leading the robot by hand.