Miracle-dz/UniFAR-FTUs huggingface dataset:
A Link-directionality-based Dual Channel MAC Protocol for IEEE 802 . 11 Ad-hoc Networks

In this paper, we propose a link-directionality-based dual channel MAC protocol in an attempt to double the capacities of networks using the single-channel 802.11 protocol. Simulations show that the proposed scheme can achieve more than 78% of our targeted capacities. We believe this is a first paper in the literature to propose a MAC protocol to transmit RTS/DATA and CTS/ACK of a link in different channels. This yields a large potential for multiplying the network capacities of ad-hoc networks by using only two channels.
A Multi-Camera Tracking System That Can always Select A Better View to Perform Tracking

In this paper, we propose a new multiple-camera people tracking system that is equipped with the following functions: (1) can handle long-term occlusions, complete o cclusions, and unpredictable motions; (2) can detect arbitrarysized foreground objects; (3) can detect objects with much faster speed. The main contribution of our method is twofold: 1) An Mto-one relationship with only point homography matching for occlusion detection can achieve efficiency; 2) A view-hoppi ng technique based on object motion probability (OMP) is proposed to automatically select an appropriate observation view for tracking a human subject.
Efficient HRTF Interpolation in 3 D Moving Sound EFFICIENT HRTF INTERPOLATION IN 3 D MOVING SOUND

This paper addresses efficient interpolation of Head-Related Transfer Functions (HRTFs) for binaural generation of moving sound. Aiming at computational complexity reduction, the authors have recently proposed a new method for HRTF interpolation based on auxiliary Inter-positional Transfer Functions (IPTFs). The present paper reviews this IPTF-based method and focuses on IPTF design, which employs tools such as balanced model reduction and spectral smoothing to compute a complete set of reduced-order IPTFs. The interpolation scheme based on these reduced-order IPTFs is computationally more efficient and yields results perceptually comparable to those attainable by the bilinear method, which uses the HRTFs directly. Therefore, the proposed method is promising for real-time generation of spatial sound.
Compact antenna arrays for MIMO applications

We use antenna-antenna interactions to reduce spatial correlations among antenna elements. which allows for closely packed arrays for MIMO applications in small portable devices. The reduction in spatial correlations is a result of the modification of the antennas' radiation pattern when the elements are brought close to each other. We show how a particular dielectric antenna element can be manipulated so that closely placed elements have either nearly isotropic radiation patterns or more anisotropic ones. Accordingly, we find that in a multiple-scattering environment the correlation between antennas with isotropic pattern has an oscillatory behavior with period /spl sim//spl lambda/ expected for a 3D Rayleigh fading environment. On the other hand, antennas with an anisotropic pattern show a low degree of spatial correlation of /spl sim/0.2 independent of the antenna separation. Electromagnetic simulations confirm our experimental observation and provide a path for a systematic design and optimization of compact antenna arrays.
The molecular basis for Mucosal-Associated Invariant T cell recognition of MR1 proteins

Significance Mucosal-associated invariant T (MAIT) cells are a highly conserved lineage of αβ T cells found in most mammals. These cells express a T-cell receptor of low diversity that recognizes vitamin metabolites presented by the MHC-related protein, MR1. Despite the evolutionary divergence of MR1 from other MHC proteins, we have found that MAIT T-cell receptors recognize MR1 using similar molecular strategies as that of the highly diverse, conventional αβ T cells, which recognize classical MHC molecules presenting peptide fragments. Our results also shed light onto how MR1-presented antigens can modulate the MAIT–T-cell receptor affinity and MAIT cell stimulation. Mucosal-associated invariant T (MAIT) cells are an evolutionarily conserved αβ T-cell lineage that express a semi-invariant T-cell receptor (TCR) restricted to the MHC related-1 (MR1) protein. MAIT cells are dependent upon MR1 expression and exposure to microbes for their development and stimulation, yet these cells can exhibit microbial-independent stimulation when responding to MR1 from different species. We have used this microbial-independent, cross-species reactivity of MAIT cells to define the molecular basis of MAIT-TCR/MR1 engagement and present here a 2.85 Å complex structure of a human MAIT-TCR bound to bovine MR1. The MR1 binding groove is similar in backbone structure to classical peptide-presenting MHC class I molecules (MHCp), yet is partially occluded by large aromatic residues that form cavities suitable for small ligand presentation. The docking of the MAIT-TCR on MR1 is perpendicular to the MR1 surface and straddles the MR1 α1 and α2 helices, similar to classical αβ TCR engagement of MHCp. However, the MAIT-TCR contacts are dominated by the α-chain, focused on the MR1 α2 helix. TCR β-chain contacts are mostly through the variable CDR3β loop that is positioned proximal to the CDR3α loop directly over the MR1 open groove. The elucidation of the MAIT TCR/MR1 complex structure explains how the semi-invariant MAIT-TCR engages the nonpolymorphic MR1 protein, and sheds light onto ligand discrimination by this cell type. Importantly, this structure also provides a critical link in our understanding of the evolution of αβ T-cell recognition of MHC and MHC-like ligands.
Resisting Dynamic Strategies in Gradually Evolving Worlds

We study the online linear optimization problem, in which a player has to make repeated online decisions with linear loss functions and hopes to achieve a small regret. We consider a natural restriction of this problem in which the loss functions have a small deviation, measured by the sum of the distances between every two consecutive loss functions. At the same time, we also consider a natural generalization, in which the regret is measured against a dynamic offline algorithm which can play different strategies in different rounds, but under the constraint that their deviation is small. We show that in this new setting, an online algorithm modified from the gradient descent algorithm can still achieve a small regret, which can be characterized in terms of the deviation of loss functions and the deviation of the offline algorithm. For the closely related online decision problem, we show that an online algorithm modified from the Hedge algorithm can also achieve a small regret in this new setting.
An Empirical Comparison of Histogram-Like Techniques for Query Optimization

We consider the problem of Query Optimization which consists of a database system choosing, among many diierent Query Evaluation Plans (QEP), the most economical one for a given query. Since the number of QEPs increases exponentially with the number of relations involving the query, query optimization is a very complex problem. Many estimation techniques have been developed in order to approximate the cost of a QEP, including the Equi-width 1, 2], the Equi-Depth 3, 4], the Rectangular Attribute Cardinality Map (R-ACM) 5, 6], and the Trapezoidal Attribute Cardinality Map (T-ACM) 5]. For our analysis we have developed a formal, rigorous prototype model used to analyze these methods on random databases. We show that as the error of an estimation technique increases, the probability of choosing the optimal QEP decreases. We also formally show how the estimates can be obtained in joined relations. The research also contains a detailed description of the rigorous prototype model and its implementation, and an empirical comparison of these histogram schemes.
An Overview of NTCIR-5 QAC3

This paper provides an overview of NTCIR-5 QAC3 (Question Answering Challenge 3). QAC is a series of challenges for evaluating question answering technologies in Japanese. QAC3 follows the same course as QAC based on the success of the previous two workshops, with its task limited to that corresponding to QAC2 Subtask 3 aiming at the convergence of research resources for novel subjects. This task assumes interactive use of QA systems and evaluates, among other things, the abilities needed under such circumstances, i.e. proper interpretation of questions under a given dialogue context; in other words, context processing abilities such as anaphora resolution and ellipses handling (hereafter we refer to the task as the IAD task, where IAD stands for Information Access Dialogue, and to the whole workshop as QAC3). The IAD task in QAC3 is based on QAC2 Subtask 3 with several improvements, including elaboration of the scope of questions and answers and introduction of multi-grade evaluation and the concept of a correct answer set. In addition, a new WoZ method was devised and applied in the QAC3 test set construction. QAC3 had as many participants as QAC2 Subtask 3, and new trials and advances in existing methods were observed from the submission results.
Gender and its effects on psychopathology

Introduction. Hormonal basis of mood disorders in women. Gender and dimensions of the self: implications for internalization and externalization behavior. Gender differences in major depression: epidemiological findings. Gender differences in schizophrenia. Gender differences in major depression: the role of anxiety. Gender differences in the epidemiology of substance dependence in the United States. Gender-specific etiologies for antisocial and borderline personality disorders. Pubertal changes and adolescent challenges: why rates of depression rise precipitously for girls between ages 10 and 15 years. Gender and schizophrenia. Gender effects in gene--environment interactions in substance abuse. Gender differences in response to treatments of depression. Anxiety disorders: clinical implications of gender differences. Gender differences in the effects of opiates and cocaine: implications for treatment. Index.
A New Approach to Collaborative Group Formation

This paper implements a tool, referred to as the Automated Group Decomposition Program (AGDP), which divides a class of students into groups, using the k-means algorithm, for the purpose of collaborative learning, and then heterogenizes the groups based on a factor called the degree of heterogeneity (DOH). The tool takes as input two sets of scores and the students‟ roll numbers and outputs the required groups. The first score set scored students on communication skills, fluency in using computers and group work attitude. This score set was used to generate the homogeneous groups. The second score set scored students on their knowledge of the subject and was used to generate the heterogeneous groups. The tool can be used to generate homogeneous clusters, heterogeneous clusters and a mixture of both. This tool can not only be used by teachers but also by instructors with minimal computer experience wishing to form groups to maximize learning.
Classifying Q&A from Teachers' Speech: Moving Toward an Automated System of Dialogic Analysis

Question-answer (Q&A) is fundamental for dialogic instruction, an important pedagogical technique based on the free exchange of ideas and open-ended discussion. Automatically detecting Q&A is key to providing teachers with feedback on appropriate use of dialogic instructional strategies. In line with this, this paper studies the possibility of automatically detecting segments of Q&A in live classrooms based solely on audio recordings of teacher speech. The proposed approach has two steps. First, teacher utterances were automatically detected from the audio stream via an amplitude envelope thresholding-based approach. Second, supervised classifiers were trained on speech-silence patterns derived from the teacher utterances. The best models were able to detect Q&A segments in windows of 90 seconds with an AUC (Area Under the Receiver Operating Characteristic Curve) of 0.78 in a manner that generalizes to new classes. Implications of the findings for automatic coding of classroom discourse are discussed.
Modified Betweenness Centrality for Predicting Traffic Flow

Centrality measures define the relationship between particular structural features of a network. Although network analysis has been utilized to express the most relevant physical, topological and static properties of networks, dynamic and temporal aspects are mostly disregarded. For example, in travel network studies the physical street network is assumed to be static, although it can have relevant dynamic and temporal constraints such as current traffic volume in comparison to capacity or night time closures. Traffic flow can be defined as the process of physical agents moving along an urban travel network (Kazerani and Winter 2009). Since these agents are dynamic and purposeful, they have specific travel demands such as to leave an origin or reach a destination at a specific time. If the agents consider centrality of streets in their route planning, their route planning problem becomes essentially a dynamic one. Furthermore, their time dependent demands contribute to the dynamics of centrality measures. So the research question is how to modify conventional centrality measures by considering the time dependent travel demand. So far, betweenness centrality (Freeman 1977) has been used as one of the prominent centrality measures for analyzing physical street network. In order to consider dynamic and temporal aspects of agents’ travel demand in the street network a modified version of betweenness centrality will be developed to study people’s origins and destinations in three different time periods of the day. The result will be compared to the traditional betweenness centrality of the street network to see the impact including these temporal and dynamic aspects on explaining traffic patterns.
Propose a Framework for Criminal Mining by Web Structure and Content Mining

Anonymous and suitable information always are provided by criminal web data for Law enforcement agencies. The digital data that are used in forensic analysis comprises of pieces of information which are about the accused social networks. Nevertheless, evaluating these pieces of information is a challenging means an operator has to extract the appropriate information from the text in the website manually, after that it finds a connection between different pieces of information and classify them into a database structure. Then, the set is ready to utilize different criminal network analysis tools for test. Therefore, this manual procedure of arranging data for analysis is not efficient because it affected by many errors. Moreover, the quality of achieving analyzed data is related to the expertise and experience of the investigator so the reliability of the tests is not continuous. Actually, the better result is achieved, the more knowledgeable is an operator. The aim of this study is to report the process of exploring the criminal suspects of forensic data analysis that support the reliability gap by offering a framework by utilizing High-level architecture of a scalable universal crawler.
Neural representation of the sensorimotor speech–action-repository

A speech–action-repository (SAR) or “mental syllabary” has been proposed as a central module for sensorimotor processing of syllables. In this approach, syllables occurring frequently within language are assumed to be stored as holistic sensorimotor patterns, while non-frequent syllables need to be assembled from sub-syllabic units. Thus, frequent syllables are processed efficiently and quickly during production or perception by a direct activation of their sensorimotor patterns. Whereas several behavioral psycholinguistic studies provided evidence in support of the existence of a syllabary, fMRI studies have failed to demonstrate its neural reality. In the present fMRI study a reaction paradigm using homogeneous vs. heterogeneous syllable blocks are used during overt vs. covert speech production and auditory vs. visual presentation modes. Two complementary data analyses were performed: (1) in a logical conjunction, activation for syllable processing independent of input modality and response mode was assessed, in order to support the assumption of existence of a supramodal hub within a SAR. (2) In addition priming effects in the BOLD response in homogeneous vs. heterogeneous blocks were measured in order to identify brain regions, which indicate reduced activity during multiple production/perception repetitions of a specific syllable in order to determine state maps. Auditory-visual conjunction analysis revealed an activation network comprising bilateral precentral gyrus (PrCG) and left inferior frontal gyrus (IFG) (area 44). These results are compatible with the notion of a supramodal hub within the SAR. The main effect of homogeneity priming revealed an activation pattern of areas within frontal, temporal, and parietal lobe. These findings are taken to represent sensorimotor state maps of the SAR. In conclusion, the present study provided preliminary evidence for a SAR.
Cholinergic Pairing with Visual Activation Results in Long-Term Enhancement of Visual Evoked Potentials

Acetylcholine (ACh) contributes to learning processes by modulating cortical plasticity in terms of intensity of neuronal activity and selectivity properties of cortical neurons. However, it is not known if ACh induces long term effects within the primary visual cortex (V1) that could sustain visual learning mechanisms. In the present study we analyzed visual evoked potentials (VEPs) in V1 of rats during a 4–8 h period after coupling visual stimulation to an intracortical injection of ACh analog carbachol or stimulation of basal forebrain. To clarify the action of ACh on VEP activity in V1, we individually pre-injected muscarinic (scopolamine), nicotinic (mecamylamine), α7 (methyllycaconitine), and NMDA (CPP) receptor antagonists before carbachol infusion. Stimulation of the cholinergic system paired with visual stimulation significantly increased VEP amplitude (56%) during a 6 h period. Pre-treatment with scopolamine, mecamylamine and CPP completely abolished this long-term enhancement, while α7 inhibition induced an instant increase of VEP amplitude. This suggests a role of ACh in facilitating visual stimuli responsiveness through mechanisms comparable to LTP which involve nicotinic and muscarinic receptors with an interaction of NMDA transmission in the visual cortex.
A computational complexity-aware model for performance analysis of software servers

Queueing models are routinely used to analyze the performance of software systems. However, contrary to common assumptions, the time that a software server takes to complete jobs may depend on the total number of active sessions in the server. We present a queueing model that explicitly takes into account the time, taken by algorithms in the server, that varies with the user population. The model analytically predicts the response time and the "saturation number" of such systems. We validate our model with simulation and further demonstrate its usefulness by suggesting a heuristic technique to "discover" the complexity of algorithms in server software, solely from response time measurement. We applied the discovery technique to a Web-server testbed, and found that we can identify the asymptotic behavior of processing time as a function of the user population with a fair amount of accuracy. The results show that this promises to be one of the many "black-box analysis" techniques, often found necessary in the real world.
The response of L5 pyramidal neurons of the PFC to magnetic stimulation from a micro-coil

Magnetic stimulation of the nervous system, e.g. transcranial magnetic stimulation (TMS), has been used both to unravel basic structure and function of the nervous system as well as to treat neurological diseases, i.e. clinical depression. Despite progress in both areas, ongoing advancements have been limited by a lack of understanding of the mechanism by which magnetic stimulation alters neural activity. Here, we report responses of cortical neurons to magnetic stimulation arising from a sub-millimeter coil. Cell attached patch clamp was used to record neural activity of layer 5/6 pyramidal neurons of the prefrontal cortex (PFC) in the in vitro mouse brain slice preparation. The fields arising from the small coil were quite different from those arising during clinical TMS but nevertheless allowed the responses of cortical neurons to magnetic stimulation to be probed. For example, the focal nature of induced fields allowed the sensitivity of different regions within targeted pyramidal neurons, e.g. apical dendrite, soma and axon hillock, to be compared. We found that PFC pyramidal neurons were not sensitive to single pulses of stimulation regardless of coil location. However, regions of the apical dendrite and proximal axon were both sensitive to repetitive stimulation as long as the orientation of the induced electric field was aligned with the long axis of the neuron. These results suggest that neurons of the PFC are sensitive to weak magnetic fields and further, that this type of approach may be useful for unraveling some of the mechanisms underlying TMS.
Glucagon Receptor–Mediated Extracellular Signal–Regulated Kinase 1/2 Phosphorylation in Rat Mesangial Cells: Role of Protein Kinase A and Phospholipase C

Glucagon, a major insulin counterregulatory hormone, binds to specific Gs protein–coupled receptors to activate glycogenolytic and gluconeogenic pathways, causing blood glucose levels to increase. Inappropriate increases in serum glucagon play a critical role in the development of insulin resistance and target organ damage in type 2 diabetes. We tested the hypotheses that: (1) glucagon induces proliferation of rat glomerular mesangial cells through glucagon receptor–activated phosphorylation of mitogen-activated protein kinase extracellular signal–regulated kinase 1/2 (p-ERK 1/2); and (2) this phosphorylation involves activation of cAMP-dependent protein kinase A (PKA) and phospholipase C (PLC)/[Ca2+]i signaling pathways. In rat mesangial cells, glucagon (1 nM) stimulated [3H]-thymidine incorporation by 96% (P<0.01). This proliferative effect was blocked by the specific glucagon receptor antagonist [Des-His1-Glu9] glucagon (1 &mgr;mol/L; P<0.01), a mitogen-activated protein kinase/ERK kinase inhibitor PD98059 (10 &mgr;mol/L; P<0.01), a PLC inhibitor U73122 (1 &mgr;mol/L; P<0.01), or a PKA inhibitor H-89 (1 &mgr;mol/L; P<0.01). The proliferation was associated with a 2-fold increase in p-ERK 1/2 that peaked 5 minutes after glucagon stimulation (P<0.01) and also was blocked by [Des-His1-Glu9] glucagon. Total ERK 1/2 was not affected by glucagon. Pretreating of mesangial cells with U73122 or H89 significantly attenuated ERK 1/2 phosphorylation induced by glucagon. We believe that these are the first data showing that glucagon activates specific receptors to induce ERK 1/2 phosphorylation and thereby increase mesangial cell proliferation and that this effect of glucagon involves both PLC/[Ca2+]i- and cAMP-dependent PKA-activated signaling cascades.