Miracle-dz/UniFAR-FTUs huggingface dataset:
Ethanol Enhances Neurosteroidogenesis in Hippocampal Pyramidal Neurons by Paradoxical NMDA Receptor Activation

Using an antibody against 5α-reduced neurosteroids, predominantly allopregnanolone, we found that immunostaining in the CA1 region of rat hippocampal slices was confined to pyramidal neurons. This neurosteroid staining was increased following 15 min administration of 60 mm but not 20 mm ethanol, and the enhancement was blocked by finasteride and dutasteride, selective inhibitors of 5α-reductase, a key enzyme required for allopregnanolone synthesis. Consistent with a prior report indicating that N-methyl-d-aspartate (NMDA) receptor (NMDAR) activation can promote steroid production, we observed that d-2-amino-5-phosphonovalerate (APV), a competitive NMDAR antagonist, blocked the effects of 60 mm ethanol on staining. We previously reported that 60 mm ethanol inhibits the induction of long-term potentiation (LTP), a cellular model for memory formation, in the CA1 region. In the present study, LTP inhibition by 60 mm ethanol was also overcome by both the 5α-reductase inhibitors and by APV. Furthermore, the effects of ethanol on neurosteroid production and LTP were mimicked by a low concentration of NMDA (1 μm), and the ability of NMDA to inhibit LTP and to enhance neurosteroid staining was reversed by finasteride and dutasteride, as well as by APV. These results indicate that ethanol paradoxically enhances GABAergic neurosteroid production by activation of unblocked NMDARs and that acute LTP inhibition by ethanol represents a form of NMDAR-mediated metaplasticity.
Comparison of cognitive functions in bipolar disorder patients with and without comorbid borderline personality disorder

ABSTRACT Objective: The aim of this study was to compare patients with bipolar disorder type I (BD) with and without comorbid borderline personality disorder (BPD), in euthymic period, in terms of cognitive functions. The main hypotesis of this study was that cognitive functions would be more impaired in patients with BD with comorbid BPD (BD + BPD). Methods: The structured clinical interviews for diagnostic and statistical manual of mental disorders-IV axis I disorders (SCID-I and SCID-II) were administered to 105 patients and the patients were separated into two groups as 79 BD patients and 26 BD plus BPD patients. Young Mania Rating Scale, Hamilton Depression Rating Scale, California verbal learning test, Wisconsin card sorting test, trail-making test (TMT), and stroop test were administered to the both groups. Results: BD with comorbid BPD group showed statistically significantly lower performance in the average scores of TMT-A seconds and errors, and TMT-B seconds scores than the BD group (respectively t = −3.449, p = .001; t = −3.431, p = .001; t = −2.331, p = .022). Conclusions: The processing speed, set shifting, and selective attention in BD with comorbid BPD group is more disturbed than the BD group. We suggest that when evaluating the cognitive functions, evaluation of comorbid psychiatric diagnosis, especially BPD, is crucial in BD.
Using Multiscale Kernel Models to Reconstruct Multivariate Functions from Scattered Data

This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing kernels in Hilbert spaces. But it adopts techniques from wavelet theory and shift-invariant spaces to construct a new class of kernels as multiscale superpositions of shifts and scales of a single compactly supported function. This means that the advantages of scaled regular grids are used to construct the kernels, while the advantages of unrestricted scattered data interpolation are maintained after the kernels are constructed. Using such a multiscale kernel, the reconstruction method interpolates at given scattered data. No manipulations of the data are needed. Then, the multiscale structure of the kernel allows to represent the interpolant on regular grids on all scales involved, with cheap evaluation due to the compact support of the function, and with a recursive evaluation technique in support vector regression. Numerical comparisons are given in two dimensions which show competitive results with the single-variable two-variable function, the new model not only can reconstruct linear and the non-linear combination functions very well, but also performs better in multivariate functions reconstruction. The results indicate that the proposed method has effectiveness in terms of both objective measurements and visual evaluation.
UNDERSTAND CUSTOMER BEHAVIOR USING SOCIAL MEDIA IN RECOMMENDATION SYSTEM

With the proliferation of electronic commerce and knowledge economy environment, organizations generate and consume a large amount of online information. Because of large amount of product information on internet, customer has to face difficulty in selection of items. This difficulty can be reduced by recommendation systems [RS]. Many websites such as youtube, e-Bay and amazon have their own versions of recommendation systems, which are having some drawbacks like insufficient data, changing data, changing user preferences and uncertain items. In this paper we do literature review of collaborative filtering, content based filtering and hybrid recommendation algorithms which address issues such as insufficiency of data and change in user preference problem in e-commerce domain. In this paper we have proposed recommendation system which is integrated with social network trust. In this paper, at first a trust score is calculating using social interaction between users. Then trust based recommendation model is proposed.
A new approach based on compressive sensing for solving monostatic scattering from 3D conducting bodies modeled by NURBS surface

A new approach conjugating the compressive sensing (CS) and the Method of Moments (MoM) is proposed and validated in this paper for fast analyzing the monostatic scattering problems. The nonuniform rational B-spline (NURBS) is introduced to MoM for the purpose of reducing the unknowns in the electric field integral equation (EFIE). Meanwhile, the CS theory is utilized to decrease the sampling rate of the incident angles in wide-angle scattering problems. The accuracy and efficiency of the proposed approach are shown by comparing with the traditional MoM using Rao-Wilton-Glisson (RWG) basis function.
The Effects of a Peer-Tutoring Intervention on the Text Production of Students with Learning and Speech Problems: A Case Report.

The purpose of this single-case study was to evaluate the effects of a peertutoring intervention on the text production skills of three third graders with severe learning and speech difficulties. All tutees were initially able to produce only very short stories. During the course of the treatment, higher performing classmates taught them how to apply a graphic organizing strategy (story mapping) to help them plan their texts more systematically. The intervention, which was comprised of between five and seven 45-minute sessions, led to dramatic increases in the number of words that the tutees wrote while producing short stories. Study results provide clear evidence of the effectiveness of teaching students with learning and speech disabilities the use of story maps through peer tutoring. The article ends with a discussion of the limitations of the study as well as suggestions for future research.
Hydrodynamic Helical Orientations of Nanofibers in a Vortex

In this review article, I report our recent studies on spectroscopic visualizations of macroscopic helical alignments of nanofibers in vortex flows. Our designed supramolecular nanofibers, formed through self-assemblies of dye molecules, helically align in torsional flows of a vortex generated by mechanical rotary stirring of the sample solutions. The nanofiber, formed through bundling of linear supramolecular polymers, aligns equally in right- and left-handed vortex flows. However, in contrast, a one-handedly twisted nanofiber, formed through helical bundling of the supramolecular polymers, shows unequal helical alignments in these torsional flows. When the helical handedness of the nanofiber matches that of the vortex flow, the nanofiber aligns more efficiently in the flowing fluid. Such phenomena are observed not only with the artificial helical supramolecular nanofibers but also with biological nanofibers such as double-stranded DNA.
Crisis-Ridden Space, Politics, and the Social Imaginary: The Case of Athens

This paper aims at deconstructing the nature of crisis. It goes beyond the wide- spread negative understanding of the concept as a trauma and reveals its limit- less transformative potential, while elaborating on its spatio-political dimension. Crisis is fundamentally interrelated with productions of knowledge, “normalities,” “rationalities,” “truths,” subject formation, and government a la Foucault. Thus, the lens of crisis is used to analyze and question the current urban transforma- tions in Athens: the nature of the production and management of the city and its space. We wished to narrate the story of Athens differently than the dominant rhetoric and to show how similar values that gave birth to the crisis before the of- cial “crisis” in 2008, are not only still considered “truths” but have also worked as the basis upon which new rationalities have emerged. Our narratives aimed to provide evidence of the components that emerged from deconstructing the crisis, as well as the effects of those components on social and political structures. “Cri- sis” gradually educates us to live with the loss of the city’s contested nature, thus creating a new social imaginary.
Rapid Transition towards the Division of Labor via Evolution of Developmental Plasticity

A crucial step in several major evolutionary transitions is the division of labor between components of the emerging higher-level evolutionary unit. Examples include the separation of germ and soma in simple multicellular organisms, appearance of multiple cell types and organs in more complex organisms, and emergence of casts in eusocial insects. How the division of labor was achieved in the face of selfishness of lower-level units is controversial. I present a simple mathematical model describing the evolutionary emergence of the division of labor via developmental plasticity starting with a colony of undifferentiated cells and ending with completely differentiated multicellular organisms. I explore how the plausibility and the dynamics of the division of labor depend on its fitness advantage, mutation rate, costs of developmental plasticity, and the colony size. The model shows that the transition to differentiated multicellularity, which has happened many times in the history of life, can be achieved relatively easily. My approach is expandable in a number of directions including the emergence of multiple cell types, complex organs, or casts of eusocial insects.
Distributed Online Learning for Latent Dirichlet Allocation

A major obstacle in using Latent Dirichlet Allocation (LDA) is the amount of time it takes for inference, especially for a dataset that starts out large and expands quickly, such as a corpus of blog posts or online news articles. Recent developments in distributed inference algorithms for LDA, as well as minibatchbased online learning algorithms have offered partial solutions for problem. In this paper, we propose a distributed online learning algorithm for LDA for dealing with both aspects of this problem at once. We apply our learning algorithm to a corpus of Twitter conversations and show that it achieves the same model fit within a much shorter learning time.
A computation method for video segmentation utilizing the pleasure-arousal-dominance emotional information

Extracting video structures is important for video indexing and navigation in large digital video archives. It is usually achieved by video segmentation algorithms. Little research efforts has been invested on segmentation solutions that utilize the video's emotional content. These solutions not only have the potential of providing better performances than existing segmentation methods, but are also able to provide a more natural video segmentation with which viewers can associate with. The development of an affect-based segmentation solution faces many challenges, such as the dynamic and time evolving nature of a video's emotional content. This paper introduces a novel computation method for affect-based video segmentation. It is designed based on the Pleasure-Arousal-Dominance (P-A-D) emotion model[18], which in principle can represent a large number of emotions. This method consists of a P-A-D estimation stage and a segmentation stage. A P-A-D estimator based on the Dynamic Bayesian Networks (DBNs) is proposed for the first stage. A clustering-based algorithm that utilizes the video's P-A-D information is proposed for the second stage. Experimental results demonstrate the feasibility of the method.
Veteran identity as a protective factor: A grounded theory comparison of perceptions of self, illness, and treatment among veterans and non-veterans with schizophrenia

ABSTRACT For individuals with severe mental illness, relatively little is known about the impact of a veteran role identity. Consequently, this article investigates whether veterans (n = 20) and non-veterans (n = 26) with schizophrenia differ in their perceptions of self, illness, or treatment. Participants completed an audiotaped, semistructured interview that was transcribed and coded using modified grounded theory. Veterans were more likely than non-veterans to discuss the following themes: (1) wanting to be “normal,” (2) having a military mindset, (3) being optimistic toward the future, (4) resisting stigma, and (5) having active treatment attitudes. Findings support the theory that identifying as a veteran has several protective factors that might help shape self-perception and thereby responses to stigma, attitudes toward treatment, and hope for the future.
Entry and Spectrum Sharing Scheme Selection in Femtocell Markets

Focusing on a femtocell communications market, we study the entrant network service provider's (NSP's) long-term decision: whether to enter the market and which spectrum sharing technology to select to maximize its profit. This long-term decision is closely related to the entrant's pricing strategy and the users' aggregate demand, which we model as medium-term and short-term decisions, respectively. We consider two markets, one with no incumbent and the other with one incumbent. For both markets, we show the existence and uniqueness of an equilibrium point in the user subscription dynamics, and provide a sufficient condition for the convergence of the dynamics. For the market with no incumbent, we derive upper and lower bounds on the optimal price and market share that maximize the entrant's revenue, based on which the entrant selects an available technology to maximize its long-term profit. For the market with one incumbent, we model competition between the two NSPs as a non-cooperative game, in which the incumbent and the entrant choose their market shares independently, and provide a sufficient condition that guarantees the existence of at least one pure Nash equilibrium. Finally, we formalize the problem of entry and spectrum sharing scheme selection for the entrant and provide numerical results to complement our analysis.
Improving Musical Genre Classification with RBF Networks

We explore the automatic classification of audio tracks into music genres using radial basis function (RBF) networks. We explore unsupervised and supervised methods for initializing the parameter of the radial basis functions. Using gradient descent during training of the networks, we find that we can significantly improve classification accuracy. We also develop three feature ranking algorithm that are useful for feature subset selection. Using subsets of features, we can maintain (and improve) classification accuracy while greatly reducing the amount of computation required for training a network. Combining multiple methods for initialization, using gradient descent, and using a subset of features, we create an RBF network that matches the musical classification performance to that of humans in an equivalent test.
A Study on the Presence of Ferritin-binding Proteins in Fetal Horse Plasma

In mammal circulation, ferritin-binding proteins (FBPs) are thought to be involved in clearance of circulating ferritin after complex formation with it through receptor-mediated uptake. However, there is no report on fetal FBP in fetal circulation. Although iron concentrations of fetal horse plasma were higher than those of adult horse plasma, plasma ferritin concentrations and ferritin-binding activities were found to be significantly lower in fetus than in adult. FBPs were purified from fetal or adult horse plasma on horse spleen ferritin-Sepharose 4B affinity column. Partially affinity-purified fetal horse plasma FBPs were mainly separated into 65 and 41 kDa bands in addition to minor bands with higher molecular masses ranged from 102 to 140 kDa on SDS-PAGE under reducing condition. The adult horse plasma FBPs were separated into 74, 54 and 28 kDa bands, and the 74 and 54 kDa bands reacted with antibodies specific for horse IgM and IgG heavy chains, respectively, by immunoblotting analyses. On the other hand, no antibodies to horse immunoglobulin classes detected any bands in fetal horse plasma FBPs. The affinity-purified adult and fetal horse plasma FBPs did not contain fibrinogen as a plasma specific FBP, probably due to its lower affinity to the ligand ferritin. These results demonstrate the presence of FBPs which are different from adult horse plasma FBPs including anti-ferritin autoantibodies in fetal plasma.
Implementing IPsec in Wireless Sensor Networks

There is an increasing need for wireless sensor networks (WSNs) to be more tightly integrated with the Internet. Several real world deployment of stand-alone wireless sensor networks exists. A number of solutions have been proposed to address the security threats in these WSNs. However, integrating WSNs with the Internet in such a way as to ensure a secure End-to-End (E2E) communication path between IPv6 enabled sensor networks and the Internet remains an open research issue. In this paper, the 6LoWPAN adaptation layer was extended to support both IPsec's Authentication Header (AH) and Encapsulation Security Payload (ESP). Thus, the communication endpoints in WSNs are able to communicate securely using encryption and authentication. The proposed AH and ESP compressed headers performance are evaluated via test-bed implementation in 6LoWPAN for IPv6 communications on IEEE 802.15. 4 networks. The results confirm the possibility of implementing E2E security in IPv6 enabled WSNs to create a smooth transition between WSNs and the Internet. This can potentially play a big role in the emerging "Internet of Things" paradigm.
Non-linear n-best List Reranking with Few Features

In Machine Translation, it is customary to compute the model score of a predicted hypothesis as a linear combination of multiple features, where each feature assesses a particular facet of the hypothesis. The choice of a linear combination is usually justified by the possibility of efficient inference (decoding); yet, the appropriateness of this simple combination scheme to the task at hand is rarely questioned. In this paper, we propose an approach that replaces the linear scoring function with a non-linear scoring function. To investigate the applicability of this approach, we rescore n-best lists generated with a conventional machine translation engine (using a linear scoring function for generating its hypotheses) with a non-linear scoring function learned using the learning-to-rank framework. Moderate, though consistent, gains in BLEU are demonstrated on the WMT’10, WMT’11 and WMT’12 test sets.
The Feldstein-Horioka puzzle and a new measure of international capital mobility

In intertemporal optimization models of current account dynamics, the budget constraint will induce high degrees of positive comovement in the levels of savings and investment and the two variables are likely to be cointegrated. Error correction will then also influence the correlations of the cyclical components which will therefore be uninformative about capital mobility. As an alternative we suggest a new measure of long-run capital mobility based on Johansen's (1988) procedure. We apply our method to historical British and US data and find surprisingly high levels of long-run capital mobility throughout the century.
Heliospheric interstellar H temperature from SOHO/SWAN H cell data

We show a first comparison between selected SOHO/SWAN H cell data recorded in 1996-1997 and a simple classical "hot model" of the interstellar (IS) H flow in the inner heliosphere. Our goal is to obtain some constraints on the interplanetary background Ly-[FORMULA] profiles, for the first time without any assumption on the H cell characteristics. For this purpose the H cell optical thickness and its temperature are free parameters of the study, but we assume that the direction of the flow and the allowed range for the upwind line-of-sight apparent Doppler shift are known from previous studies. We derive apparent temperatures (or line-of-sight (LOS) temperatures) between 11,000 and 20,000 K according to the direction. This implies a significant broadening with respect to the linewidths expected for a flow at the same temperature as the interstellar helium flow (6,000 [FORMULA] 1000 K) in the optically thin approximation. Radiative transfer is probably responsible for a fraction of this effect, and heating at the heliospheric interface for the remaining. The best solutions are found for an upwind velocity of 26 km s-1, in excellent agreement with an independent study by Quemerais et al. (1999), and for very similar H cell absorption width and temporal decrease. The deceleration of interstellar H at heliopause crossing is found to be between 2.5 and 4.5 km s-1. We also use one particular H cell absorption map to derive directly from the data how the LOS temperature (or linewidth) varies with the angle with the wind direction. Interestingly, we measure a temperature minimum between the upwind and crosswind directions, while classical models predict a monotonic increase of the LOS temperature from upwind to downwind. We believe that this behavior is the first evidence for the existence of two distinct populations at different velocities (primary and secondary IS atoms), as predicted by heliosphere-interstellar gas interface models. If confirmed, this should be an extremely good diagnostic of the interface.
Linear Transmit Beamforming Techniques for the Multigroup Multicast Scenario

In the context of next-generation wireless systems, it is expected that services targeted at mass content distribution will become widely popular. Multicast services, such as audio/video streaming and mobile television, have the characteristic that the same information has to be transmitted to a group of recipients, which may include user terminals as well as relay stations, in the case of relaying networks. This paper deals with the problem of multigroup multicast beamforming for multiantenna wireless cellular networks, which assumes that multiple multicast groups can share the same resource. The intergroup interference, which appears due to the resource sharing, needs to be suppressed by the beamforming algorithms. In this paper, new linear transmit beamforming techniques are proposed, which aim to provide a reasonable tradeoff between performance and computational complexity. These techniques correspond to extensions of known algorithms, such as zero forcing (ZF), minimum mean square error (MMSE), and signal-to-interference-plus-noise ratio (SINR) balancing, to the multicast case. Furthermore, new ldquomulticast-awarerdquo techniques that take into account the peculiarities of multicast transmission are proposed to improve performance. To provide the necessary mathematical framework for the analysis, a novel general multigroup multicast system model is proposed as well.