Miracle-dz/UniFAR-FTUs huggingface dataset:
Activation of Group I Metabotropic Glutamate Receptors on Main Olfactory Bulb Granule Cells and Periglomerular Cells Enhances Synaptic Inhibition of Mitral Cells

Granule and periglomerular cells in the main olfactory bulb express group I metabotropic glutamate receptors (mGluRs). The group I mGluR agonist 3,4-dihydroxyphenylglycine (DHPG) increases GABAergic spontaneous IPSCs (sIPSCs) in mitral cells, yet the presynaptic mechanism(s) involved and source(s) of the IPSCs are unknown. We investigated the actions of DHPG on sIPSCs and TTX-insensitive miniature IPSCs (mIPSCs) recorded in mitral and external tufted cells in rat olfactory bulb slices. DHPG, acting at mGluR1 and mGluR5, increased the rate but not amplitude of sIPSCs and mIPSCs in both cell types. The increase in mIPSCs depended on voltage-gated Ca2+ channels but persisted when ionotropic glutamate receptors and sodium spikes were blocked. Focal DHPG puffs onto granule cells or bath application after glomerular layer (GL) excision failed to increase mIPSCs in mitral cells. Additionally, GL excision reduced sIPSCs in mitral cells by 50%, suggesting that periglomerular cells exert strong tonic GABAergic inhibition of mitral cells. In contrast, GL DHPG puffs readily increased mIPSCs. These findings indicate that DHPG-evoked GABA release from granule cells requires spikes, whereas in the GL, DHPG facilitates periglomerular cell GABA release via both spike-dependent and spike-independent presynaptic mechanisms. We speculate that mGluRs amplify spike-driven lateral inhibition through the mitral-to-granule cell circuit, whereas GL mGluRs may play a more important role in amplifying intraglomerular inhibition after subthreshold input.
Estimating noise in RF systems

Predicting the noise performance of RF systems is much more complex than for linear ones. The common practice of retrofitting linear noise concepts often leads to wrong answers. For a proper understanding of RF noise, nonlinearities and synchronization, i.e. phase noise in oscillators, have to be accounted for correctly, using stochastic processes. In this tutorial, we outline how to do so for non-oscillatory and oscillatory RF systems. We emphasize basic concepts and important results, while providing sufficient details to maintain rigour. Our presentation covers: basic stochastic concepts for noise analysis; nonstationarity, cyclostationarity and frequency correlation of noise; mixing noise in driven (non-oscillatory) systems; phase noise in oscillators; and computational techniques. Our goal is to enable designers and CAD engineers to understand the basic flow of RF noise analysis and the current literature.
Fitting C 2 Continuous Parametric Surfaces to Frontiers Delimiting Physiologic Structures

We present a technique to fit C 2 continuous parametric surfaces to scattered geometric data points forming frontiers delimiting physiologic structures in segmented images. Such mathematical representation is interesting because it facilitates a large number of operations in modeling. While the fitting of C 2 continuous parametric curves to scattered geometric data points is quite trivial, the fitting of C 2 continuous parametric surfaces is not. The difficulty comes from the fact that each scattered data point should be assigned a unique parametric coordinate, and the fit is quite sensitive to their distribution on the parametric plane. We present a new approach where a polygonal (quadrilateral or triangular) surface is extracted from the segmented image. This surface is subsequently projected onto a parametric plane in a manner to ensure a one-to-one mapping. The resulting polygonal mesh is then regularized for area and edge length. Finally, from this point, surface fitting is relatively trivial. The novelty of our approach lies in the regularization of the polygonal mesh. Process performance is assessed with the reconstruction of a geometric model of mouse heart ventricles from a computerized tomography scan. Our results show an excellent reproduction of the geometric data with surfaces that are C 2 continuous.
"We gotta get out of this place": A qualitative study on the effects of leisure travel on the lives of gay men living in a small community

“We Gotta Get Out of This Place”: The Effects of Leisure Travel in the Lives of Gay Men Living in a Small Community. (December 2003) Sergio Lino Herrera, B.S., Texas A&M University Chair of Advisory Committee: Dr. David Scott A feminist point of view is used in this study of gay men living in a small, collegiate community who use leisure travel as a negotiation strategy to achieve freedom of expression. Feminism is concerned with equality, empowerment, social change, the elimination of invisibility and the distortion of situated experiences. Feminist research is no more defined by the sex of the researcher than by the sex of the researched. Several in-depth interviews were conducted with key informants who revealed the complex nature of how many gay men pursue leisure experiences that are affirming to their gay self-identities in “Soledad. ” While gay meeting places and people exist in this small community, they remain mostly covert and invisible. Leisure travel to larger cities was a major negotiation strategy used to escape the stifling, hetero-normative community in which they lived. Escaping perceived hostilities was essential for gay men to feel comfortable exploring their homosexuality in a positive, affirming manner.
Does Campaign Spending Work?

This article reports the results of several field experiments designed to measure campaign effects in partisan contests. The findings suggest incumbent campaigns failed to increase incumbent vote share, whereas the challenger campaign was effective. To understand these and other results, the incumbent’s optimal spending strategy was analyzed theoretically. The analysis reveals that if incumbents maximize their probability of victory rather than vote share, campaigns by typical incumbents are expected to produce only minimal improvement in incumbent vote share. The analysis also explains how returns to campaign spending vary with the competitiveness of the election, how incumbent spending can improve the incumbent’s probability of victory yet have only minimal effect on incumbent vote share, and why rational spending plans might decrease the sponsor’s expected vote. This article demonstrates the wide scope of application for field experiments and provides an example of how experimental findings can serve as a catalyst for generating theories.
A Variational Method in Image Recovery

This paper is concerned with a classical denoising and deblurring problem in image recovery. Our approach is based on a variational method. By using the Legendre--Fenchel transform, we show how the nonquadratic criterion to be minimized can be split into a sequence of half-quadratic problems easier to solve numerically. First we prove an existence and uniqueness result, and then we describe the algorithm for computing the solution and we give a proof of convergence. Finally, we present some experimental results for synthetic and real images.
Consumer energy portal and home energy management system for smart grid applications

This paper presents a web-based consumer energy portal (CEP) and home energy management system (HEMS) developed in Laboratory for Clean Energy Research (LaCER), School of Electrical & Electronic Engineering in Nanyang Technological University (NTU). The CEP developed will be deployed in NTU campus to provide home users at staff quarters with improved energy services such as electricity billing, outage detection and notification, metering information and energy analysis via websites, distributed generation (DG) aggregation for market participation, home energy management system (HEMS), Time of Use (ToU) pricing scheme selection and demand response management (DRM). A ZigBee based HEMS has been developed with NI-LabVIEW software to take advantage of the CEP. With the CEP and HEMS, home users can manage their energy consumption wisely based on ToU pricing and increase in energy efficiency with the help of the DRM function. Simulation studies were done with the historical data collected from the smart meters installed at staff quarters to show the impact of implementing load shifting technique and incorporating distributed energy resources (DERs) such as Solar Photovoltaic (PV) system and battery storage system (BESS) for noncontestable consumers in NTU.
High density optical interconnects integrated with lasers, optical modulators and photodetectors on a single silicon chip

Silicon optical interposers for inter-chip interconnects, integrated with lasers, an optical splitter, optical modulators and germanium photodetectors on a single silicon substrate were demonstrated. A 12.5-Gbps error-free data transmission and 6.6-Tbps/cm2 transmission density were achieved.
Components for face recognition

We present a method for automatically learning a set of discriminatory facial components for face recognition. The algorithm performs an iterative growing of components starting with small initial components located around pre-selected points in the face. The direction of growing is determined by the gradient of the cross-validation error of the component classifiers. In experiments we analyze how the shape of the components and their discriminatory power changes across different individuals and views.
Crystal structure of hypothetical protein TTHB192 from Thermus thermophilus HB8 reveals a new protein family with an RNA recognition motif‐like domain

We have determined the crystal structure of hypothetical protein TTHB192 from Thermus thermophilus HB8 at 1.9 Å resolution. This protein is a member of the Escherichia coli ygcH sequence family, which contains ∼15 sequence homologs of bacterial origin. These homologs have a high isoelectric point. The crystal structure reveals that TTHB192 consists of two independently folded domains, and that each domain exhibits a ferredoxin‐like fold with a four‐stranded antiparallel β‐sheet packed on one side by α‐helices. These two tandem domains face each other to generate a β‐sheet platform. TTHB192 displays overall structural similarity to Sex‐lethal protein and poly(A)‐binding protein fragments. These proteins have RNA binding activity which is supported by a β‐sheet platform formed by two tandem repeats of an RNA recognition motif domain with signature sequence motifs on the β‐sheet surface. Although TTHB192 does not have the same signature sequence motif as the RNA recognition motif domain, the presence of an evolutionarily conserved basic patch on the β‐sheet platform could be functionally relevant for nucleic acid‐binding. This report shows that TTHB192 and its sequence homologs adopt an RNA recognition motif‐like domain and provides the first testable functional hypothesis for this protein family.
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction Tasks

Research in social media analysis is experiencing a recent surge with a large number of works applying representation learning models to solve high-level syntactico-semantic tasks such as sentiment analysis, semantic textual similarity computation, hashtag prediction and so on. Although the performance of the representation learning models are better than the traditional baselines for the tasks, little is known about the core properties of a tweet encoded within the representations. Understanding these core properties would empower us in making generalizable conclusions about the quality of representations. Our work presented here constitutes the first step in opening the black-box of vector embedding for social media posts, with emphasis on tweets in particular. In order to understand the core properties encoded in a tweet representation, we evaluate the representations to estimate the extent to which it can model each of those properties such as tweet length, presence of words, hashtags, mentions, capitalization, and so on. This is done with the help of multiple classifiers which take the representation as input. Essentially, each classifier evaluates one of the syntactic or social properties which are arguably salient for a tweet. This is also the first holistic study on extensively analysing the ability to encode these properties for a wide variety of tweet representation models including the traditional unsupervised methods (BOW, LDA), unsupervised representation learning methods (Siamese CBOW, Tweet2Vec) as well as supervised methods (CNN, BLSTM).
Building the Architecture of A Statistics-Based Query Optimization Solution for Heterogeneous Mediators

Access to different and remote sources with heterogeneous formats is one of the most important challenges in Enterprise Information Integration. Even though there exists an increasing number of solutions which obtain information from structured and semistructured sources such as web sites, lack of Quality of Service in HTTP connections makes it very difficult to measure the mediated query performance. Different solutions based on relational and hierarchical optimization techniques have been proposed to improve query’s results, mainly in terms of time and space. This article proposes the utilization of some of these techniques in an integrated way, adding some concepts which help improve their functioning, all by using a specialized cost repository; some of them are the differentiation between positive and negative query capabilities or the use of search method’s utilization ranking in the cost repository. Besides, the article defines and explains how physical layer optimization by means of a configurable pool of browsers can help improve query’s result time in a non-despicable way.
An Experience with Building Digital Open Access Repository DML-CZ

A succesfully built institutional or community repository (e.g. set of workflows) needs a \emph{coordinated effort of librarians, IT specialists and representatives of users -- content specialists}. We will explain and discuss \emph{design, technical a political decisions} behind building the Czech Digital Mathematics Library DML-CZ (\url{http://dml.cz}) in the context of other succesfull thematical community projects (PubMed Central, ADS, SCOAP3 and planned EuDML). A framework developed for handling different types of mathematical publications is presented. It integrates workflow for the articles scanned from a paper, for documents from retro-born digital period (data were available in some type of electronic form) and for born-digital papers (newly published data from publishers). Experience gained, lessons learned and tools prepared during development of the Czech Digital Mathematics Library DML-CZ are described. We describe problems of \emph{migration of existing workflows (born-digital, retro-digital) into the repository'}. negotiations with Google Scholar towards better visibility, indexing and search, and problems of copyright and sustainability issues we have faced.
The Distribution of Charged Amino Acid Residues and the Ca2+ Permeability of Nicotinic Acetylcholine Receptors: A Predictive Model

Nicotinic acetylcholine receptors (nAChRs) are cation-selective ligand-gated ion channels exhibiting variable Ca2+ permeability depending on their subunit composition. The Ca2+ permeability is a crucial functional parameter to understand the physiological role of nAChRs, in particular considering their ability to modulate Ca2+-dependent processes such as neurotransmitter release. The rings of extracellular and intracellular charged amino acid residues adjacent to the pore-lining TM2 transmembrane segment have been shown to play a key role in the cation selectivity of these receptor channels, but to date a quantitative relationship between these structural determinants and the Ca2+ permeability of nAChRs is lacking. In the last years the Ca2+ permeability of several nAChR subtypes has been experimentally evaluated, in terms of fractional Ca2+ current (Pf, i.e., the percentage of the total current carried by Ca2+ ions). In the present study, the available Pf-values of nAChRs are used to build a simplified modular model describing the contribution of the charged residues in defined regions flanking TM2 to the selectivity filter controlling Ca2+ influx. This model allows to predict the currently unknown Pf-values of existing nAChRs, as well as the hypothetical Ca2+ permeability of subunit combinations not able to assemble into functional receptors. In particular, basing on the amino acid sequences, a Pf > 50% would be associated with homomeric nAChRs composed by different α subunits, excluding α7, α9, and α10. Furthermore, according to the model, human α7β2 receptors should have Pf-values ranging from 3.6% (4:1 ratio) to 0.1% (1:4 ratio), much lower than the 11.4% of homomeric α7 nAChR. These results help to understand the evolution and the function of the large diversity of the nicotinic receptor family.
StreamingBandit: Developing Adaptive Persuasive Systems

This paper introduces StreamingBandit, a (back-end) solution for developing adaptive and personalized persuasive systems. Creating successful persuasive applications requires a combination of design, social science, and technology. StreamingBandit contributes to the required technology by providing a platform that can be used to adapt persuasive technologies in real-time and at large scales. We first introduce the design philosophy of StreamingBandit using a running example and highlight how a large number of adaptive persuasive systems can be regarded as solutions to (contextual) multi-armed bandit problems: a type of problem that StreamingBandit was built to address. Subsequently, we detail several scenarios of the use of StreamingBandit to create adaptive persuasive systems and detail its future developments.
The Role of Innate Immunity in Promoting SaeR/S-Mediated Virulence in Staphylococcus aureus

The ability of Staphylococcus aureus to infect tissues is dependent on precise control of virulence through gene-regulatory systems. While the SaeR/S two-component system has been shown to be a major regulator of S. aureus virulence, the influence of the host environment on SaeR/S-regulated genes (saeR/S targets) remains incompletely defined. Using QuantiGene 2.0 transcriptional assays, we examined expression of genes with the SaeR binding site in USA300 exposed to human and mouse neutrophils and host-derived peptides and during subcutaneous skin infection. We found that only some of the saeR/S targets, as opposed to the entire SaeR/S virulon, were activated within 5 and 10 min of interacting with human neutrophils as well as α-defensin. Furthermore, mouse neutrophils promoted transcription of saeR/S targets despite lacking α-defensin, and the murine skin environment elicited a distinctive expression profile of saeR/S targets. These findings indicate that saeR/S-mediated transcription is unique to and dependent on specific host stimuli. By using isogenic USA300ΔsaeR/S and USA300Δagr knockout strains, we also determined that SaeR/S is the major regulator of virulence factors, while Agr, a quorum-sensing two-component system, has moderate influence on transcription of the saeR/S targets under the tested physiological conditions.
Towards Unsupervised Learning of Constructions From Text

Statistical learning methods offer a route for identifying linguistic constructions. Phrasal constructions are interesting both from the viewpoint of cognitive modeling and for improving NLP applications such as machine translation. In this article, an initial model structure and search algorithm for attempting to learn constructions from plain text is described. An information-theoretic optimization criteria, namely the Minimum Description Length principle, is utilized. The method is applied to a Finnish corpus consisting of stories told by children.
Mirror Symmetry

We prove mirror symmetry for supersymmetric sigma models on Kahler manifolds in 1+1 dimensions. The proof involves establishing the equivalence of the gauged linear sigma model, embedded in a theory with an enlarged gauge symmetry, with a Landau-Ginzburg theory of Toda type. Standard R ->1/R duality and dynamical generation of superpotential by vortices are crucial in the derivation. This provides not only a proof of mirror symmetry in the case of (local and global) Calabi-Yau manifolds, but also for sigma models on manifolds with positive first Chern class, including deformations of the action by holomorphic isometries.
Comparison of Lupus Nephritis Induction Treatments in a Hispanic Population: A Single-center Cohort Analysis

Objective. To evaluate response rates in an adult lupus nephritis (LN) cohort in Mexico City, Mexico. Methods. We analyzed 165 patients with biopsy-proven LN histological International Society of Nephrology/Renal Pathology Society classes III, IV, or V, distributed by treatment drug in 3 groups: mycophenolate mofetil (MMF; dosage > 2 g/day per 6 mos, n = 63), intravenous cyclophosphamide (IVC; 0.7 g/m2 body surface area monthly per 6 pulses, n = 66), or azathioprine (AZA; dosage > 1.5 mg/kg/day per 6 mos, n = 36). Median followup was 31 ± 18 months. The primary endpoint was the proportion of patients achieving complete renal response (CR). Secondary endpoints included the proportion of patients achieving renal response (complete or partial), renal flare–free survival, doubling of serum creatinine, and progression to endstage renal disease (ESRD). Results. MMF induction was superior to IVC (HR 2.00, 95% CI 1.23–3.25, p = 0.005) and AZA (HR 2.12, 95% CI 1.23–3.66, p = 0.007) in the primary endpoint. Censored CR rates at 6, 12, 24, and 36 months were 32.6%, 56.1%, 76.6%, and 94.1% for MMF; 24.2%, 34.4%, 57.9%, and 62.1% for IVC; and 8.4%, 39.8%, 49.7%, and 49.7% for AZA. MMF was also superior in renal response to treatment and renal flare–free survival outcomes. There were no differences between groups in doubling of serum creatinine or progression to ESRD. The induction treatment with MMF (HR 2.04, 95% CI 1.25–3.33, p = 0.005) and absence of vascular lesions on renal biopsy (HR 2.05, 95% CI 1.25–3.37, p = 0.004) were associated with CR, whereas proteinuria at the time of presentation was negatively associated with CR (HR 0.91, 95% CI 0.84–0.98, p = 0.013). Conclusion. MMF induction therapy is superior to IVC and AZA in patients with LN of Mexican-mestizo race.
Arnold: Declarative Crowd-Machine Data Integration

The availability of rich data from sources such as the World Wide Web, social media, and sensor streams is giving rise to a range of applications that rely on a clean, consistent, and integrated database built over these sources. Human input, or crowd-sourcing, is an eective tool to help produce such high-quality data. It is infeasible, however, to involve humans at every step of the data cleaning process for all data. We have developed a declarative approach to data cleaning and integration that balances when and where to apply crowd-sourcing and machine computation using a new type of data independence that we term Labor Independence. Labor Independence divides the logical operations that should be performed on each record from the physical implementations of those operations. Using this layer of independence, the data cleaning process can choose the physical operator for each logical operation that yields the highest quality for the lowest cost. We introduce Arnold, a data cleaning and integration architecture that utilizes Labor Independence to eciently clean and integrate large amounts of data.