Miracle-dz/UniFAR-FTUs huggingface dataset:
"Compressive neural representation of sparse, high-dimensional probabilities"

This paper shows how sparse, high-dimensional probability distributions could be represented by neurons with exponential compression. The representation is a novel application of compressive sensing to sparse probability distributions rather than to the usual sparse signals. The compressive measurements correspond to expected values of nonlinear functions of the probabilistically distributed variables. When these expected values are estimated by sampling, the quality of the compressed representation is limited only by the quality of sampling. Since the compression preserves the geometric structure of the space of sparse probability distributions, probabilistic computation can be performed in the compressed domain. Interestingly, functions satisfying the requirements of compressive sensing can be implemented as simple perceptrons. If we use perceptrons as a simple model of feedforward computation by neurons, these results show that the mean activity of a relatively small number of neurons can accurately represent a high-dimensional joint distribution implicitly, even without accounting for any noise correlations. This comprises a novel hypothesis for how neurons could encode probabilities in the brain.
Performance Analysis of One-bit Group-sparse Signal Reconstruction

We consider the reconstruction of group-sparse vectors from sign measurements of random projections. In particular, we establish conditions on the number of measurements under which such signal ensembles can be recovered up to a prescribed accuracy. The results rely on a mixed restricted isometry property as first employed by Foucart in the context of 1-bit compressed sensing, as well as certain results on random hyperplane tessellations. The paper fills a gap in the literature by establishing that group-sparse signals can be estimated from 1-bit observations with the same number of measurements as required for the reconstruction of block-sparse signals from unquantized measurements. We confirm the correct behavior of the recovery schemes in a series of numerical experiments.
Nonlinear Support Vector Machines Can Systematically Identify Stocks with High and Low Future Returns

This paper investigates the profitability of a trading strategy based on training a model to identify stocks with high or low predicted returns. A tail set is defined to be a group of stocks whose volatility-adjusted price change is in the highest or lowest quantile, for example the highest or lowest 5%. Each stock is represented by a set of technical and fundamental features computed using CRSP and Compustat data. A classifier is trained on historical tail sets and tested on future data. The classifier is chosen to be a nonlinear support vector machine (SVM) due to its simplicity and effectiveness. The SVM is trained once per month, in order to adjust to changing market conditions. Portfolios are formed by ranking stocks using the classifier output. The highest ranked stocks are used for long positions and the lowest ranked ones for short sales. The Global Industry Classification Standard is used to build a model for each sector such that a total of 8 long-short portfolios for Energy, Materials, Industrials, Consumer Discretionary, Consumer Staples, Health Care, Financials, and Information Technology are formed. The data range from 1981 to 2010. Without measuring trading costs, but using 91 day holding periods to minimize these, the strategy leads to annual excess returns (Jensen alpha) of 15% with volatilities under 8% using the top 25% of the stocks of the distribution for training long positions and the bottom 25% for the short ones.
Adaptive, cricket-inspired artificial hair sensor arrays

A method and system for providing computer-network related information about a calling party. First, the called party receives a telephone number of a calling party. The called party's customer premises equipment (CPE) or elements in a telephone network then use the telephone number to index a database, which contains combinations of telephone numbers and computer-network addresses. Once the calling party's computer-network address is retrieved, calling-party-customized information present at the computer-network location specified by the computer-network address can be sent to and displayed on the called party's CPE. Also, the calling party's telephone number can be sent to an application in the computer network, causing the calling-party-customized information to be automatically displayed on the called party's CPE.
Find me opinion sources in blogosphere: a unified framework for opinionated blog feed retrieval

This paper aims to find blog feeds having a principal inclination towards making opinionated comments on the given topic, so that we can subscribe to them to track influential and interesting opinions in the blogosphere. One major challenge is assigning topic-related opinion scores to blog feeds, which is embodied in two aspects. Firstly, we should identify whether the blog feed has a principal on-topic opinionated inclination. This inclination should be collectively revealed by all posts of the feed. We should fully consider evidences from all the posts of the feed to identify salient information among many posts of the feed. Secondly, we should capture topic-related opinions in the blog feed while ignoring irrelevant opinions. In this paper, we propose a unified framework for opinionated blog feed retrieval, which combines topic relevance and opinion scores with a generative model. Furthermore, we propose a language modeling approach to estimating opinion scores that is seamlessly integrated into the framework, where two language models, Topic-specific Opinion Model (TOM) and Topic-biased Feed Model (TFM), work collectively to reflect whether the blog feed shows a principal on-topic opinionated inclination. To estimate TFM, we propose a topic-biased random walk to exploit both content and structural information to capture topic-biased salient information in the feed. As for TOM estimation, we propose to use a generative mixture model with prior guidance to effectively capture topic-specific opinion expressing language usage. The conducted experiments in the context of the TREC 2009-2010 Blog Track show the effectiveness of our proposed approaches.
Universal or Multi-mode Adhesives: Why and How?

A new generation of one-bottle dental adhesives is currently being used. The literature refers to them as universal or multi-mode adhesives (UA). UA are indicated as either self-etching (SE) or etch-and-rinse (ER) adhesives. Additionally, manufacturers also recommend an alternative “selective enamel etching” technique. Some UA contain 10-MDP (methacryloyloxydecyl dihydrogen phosphate), which has been shown to bond ionically to hydroxyapatite through nanolayering.18 Taking into account that MDP-mediated nanolayering may be responsible for the clinical success of the two-step SE adhesive Clearfil SE Bond (Kuraray) at 8 years,11 expectations exist regarding the clinical success of MDP-containing UA. Nevertheless, etching dentin with phosphoric acid removes calcium, leaving behind a 2to 5-μm-thick area of denuded collagen fibers. It is not clear at this point if (and how) MDP-containing adhesives are able to bond ionically to calcium-deprived etched dentin through nanolayering. Clinical studies and laboratory evaluations have, in fact, demonstrated that some UA may perform at the same level of previous materials.1,3,5,10 However, enamel etching with phosphoric acid is still recommended for UA. The enamel μTBS values obtained with Scotchbond Universal (3M ESPE) were 28.7 MPa (self-etching) and 40.1 MPa (etched enamel). 9 Even when UA are applied with a rubbing Fig 1 UA bond strengths by application protocol. ABU: All-Bond Universal; GBP: G-Bond Plus/G-aenial Bond; SBU: Scotchbond Universal; Fut-U: FuturaBond U. SE-passive: self-etching, passive application; SE-active: self-etching, active application; ER: etch-and-rinse.
A user-pairing based resource allocation scheme for a large number of devices in M2M communications

Machine-to-machine (M2M) communications exhibit quite different characteristics, compared with human-to-human (H2H) communications. Since the number of M2M devices is much larger than that of users for H2H communications, it may cause a shortage problem of radio resources if we do not consider an efficient radio resource management scheme. In this paper, we propose an efficient resource allocation scheme to support a large number of M2M devices in the network. First, we investigate the tradeoff relationship between a non-orthogonal resource allocation scheme based on user-pairing and an orthogonal resource allocation scheme by considering pilot overhead in resource usage. Second, we set up an optimization problem for minimizing the amount of allocated resources for a large number of devices in the network. Finally, we propose a user-pairing based resource allocation algorithm. When the number of devices is 500 and the average SNR is set to 10 dB, our proposed suboptimal minimum resource allocation (SMRA) scheme reduces the total required number of resource blocks by 29% and 28%, compared with the orthogonal resource allocation (ORA) scheme and the random user-pairing based resource allocation (RUPRA) scheme, respectively.
Targeted gene expression in transgenic Xenopus using the binary Gal4-UAS system

The transgenic technique in Xenopus allows one to misexpress genes in a temporally and spatially controlled manner. However, this system suffers from two experimental limitations. First, the restriction enzyme-mediated integration procedure relies on chromosomal damage, resulting in a percentage of embryos failing to develop normally. Second, every transgenic embryo has unique sites of integration and unique transgene copy number, resulting in variable transgene expression levels and variable phenotypes. For these reasons, we have adapted the Gal4-UAS method for targeted gene expression to Xenopus. This technique relies on the generation of transgenic lines that carry “activator” or “effector” constructs. Activator lines express the yeast transcription factor, Gal4, under the control of a desired promoter, whereas effector lines contain DNA-binding motifs for Gal4-(UAS) linked to the gene of interest. We show that on intercrossing of these lines, the effector gene is transcribed in the temporal and spatial manner of the activator's promoter. Furthermore, we use the Gal4-UAS system to misexpress Xvent-2, a transcriptional target of bone morphogenetic protein 4 (BMP4) signaling during early embryogenesis. Embryos inheriting both the Gal4 activator and Xvent-2 effector transgenes display a consistent microcephalic phenotype. Finally, we exploit this system to characterize the neural and mesodermal defects obtained from early misexpression of Xvent-2. These results emphasize the potential of this system for the controlled analyses of gene function in Xenopus.
ICE: An Expressive Iterative Combinatorial Exchange

We present the design and analysis of the first fully expressive, iterative combinatorial exchange (ICE). The exchange incorporates a tree-based bidding language (TBBL) that is concise and expressive for CEs. Bidders specify lower and upper bounds in TBBL on their value for different trades and refine these bounds across rounds. These bounds allow price discovery and useful preference elicitation in early rounds, and allow termination with an efficient trade despite partial information on bidder valuations. All computation in the exchange is carefully optimized to exploit the structure of the bid-trees and to avoid enumerating trades. A proxied interpretation of a revealed-preference activity rule, coupled with simple linear prices, ensures progress across rounds. The exchange is fully implemented, and we give results demonstrating several aspects of its scalability and economic properties with simulated bidding strategies.
Robust economic model predictive control based on a periodicity constraint

This paper proposes robust economic model predictive control based on a periodicity constraint for linear systems subject to unknown‐but‐bounded additive disturbances. In this economic MPC design, a periodic steady‐state trajectory is not required and thus assumed unknown, which precludes the use of enforcing terminal state constraints as in other standard economic formulations. Instead, based on the desired periodicity of system operation, we optimize the economic performance over a set of periodic trajectories that include the current state. To achieve robust constraint satisfaction, we use a tube‐based technique in the economic MPC formulation. The mismatches between the nominal model and the closed‐loop system with perturbations are limited using a local control law. With the proposed robust tube‐based strategy, recursive feasibility is guaranteed. Moreover, under a convexity assumption, the closed‐loop convergence of the closed‐loop system is analyzed, and an optimality certificate is provided to check if the closed‐loop trajectory reaches a neighborhood of the optimal nominal periodic steady trajectory using Karush‐Kuhn‐Tucker optimality conditions. Finally, through numerical examples, we show the effectiveness of the proposed approach.
Innate Invariant NKT Cell Recognition of HIV-1–Infected Dendritic Cells Is an Early Detection Mechanism Targeted by Viral Immune Evasion

Invariant NKT (iNKT) cells are innate-like T cells that respond rapidly with a broad range of effector functions upon recognition of glycolipid Ags presented by CD1d. HIV-1 carries Nef- and Vpu-dependent mechanisms to interfere with CD1d surface expression, indirectly suggesting a role for iNKT cells in control of HIV-1 infection. In this study, we investigated whether iNKT cells can participate in the innate cell–mediated immune response to HIV-1. Infection of dendritic cells (DCs) with Nef- and Vpu-deficient HIV-1 induced upregulation of CD1d in a TLR7-dependent manner. Infection of DCs caused modulation of enzymes in the sphingolipid pathway and enhanced expression of the endogenous glucosylceramide Ag. Importantly, iNKT cells responded specifically to rare DCs productively infected with Nef- and Vpu-defective HIV-1. Transmitted founder viral isolates differed in their CD1d downregulation capacity, suggesting that diverse strains may be differentially successful in inhibiting this pathway. Furthermore, both iNKT cells and DCs expressing CD1d and HIV receptors resided in the female genital mucosa, a site where HIV-1 transmission occurs. Taken together, these findings suggest that innate iNKT cell sensing of HIV-1 infection in DCs is an early immune detection mechanism, which is independent of priming and adaptive recognition of viral Ag, and is actively targeted by Nef- and Vpu-dependent viral immune evasion mechanisms.
Overexpression of an Apocynum venetum DEAD-Box Helicase Gene (AvDH1) in Cotton Confers Salinity Tolerance and Increases Yield in a Saline Field

Soil salinity is a major environmental stress limiting plant growth and productivity. We have reported previously the isolation of an Apocynum venetum DEAD-box helicase 1 (AvDH1) that is expressed in response to salt exposure. Here, we report that the overexpression of AvDH1 driven by a constitutive cauliflower mosaic virus-35S promoter in cotton plants confers salinity tolerance. Southern and Northern blotting analyses showed that the AvDH1 gene was integrated into the cotton genome and expressed. In this study, the growth of transgenic cotton expressing AvDH1 was evaluated under saline conditions in a growth chamber and in a saline field trial. Transgenic cotton overexpressing AvDH1 was much more resistant to salt than the wild-type plants when grown in a growth chamber. The lower membrane ion leakage, along with increased activity of superoxide dismutase, in AvDH1 transgenic lines suggested that these characteristics may prevent membrane damage, which increases plant survival rates. In a saline field, the transgenic cotton lines expressing AvDH1 showed increased boll numbers, boll weights and seed cotton yields compared with wild-type plants, especially at high soil salinity levels. This study indicates that transgenic cotton expressing AvDH1 is a promising option for increasing crop productivity in saline fields.
Appendix A 4 Guidance on the epidemiological investigation of outbreaks of infection

8 This Appendix is based upon a report prepared by the Public Health Laboratory Service under contract to the Drinking Water Inspectorate. The principal authors were: Dr John de Louvois, Head, PHLS Environmental Surveillance Unit, CDSC, Colindale (since retired) Dr Patricia O’Neill, Consultant Microbiologist/CCDC, Shropshire HA, Shrewsbury Public Health Laboratory Dr James Stuart, Consultant Epidemiologist, CDSC (South and West), Gloucester Public Health Laboratory Dr Tony Swan, Head, PHLS Statistics Unit, Colindale
Perianal Tuberculosis: A Case Report and a Review of the Literature

Extra pulmonary tuberculosis accounts for less than 15% of all cases of tuberculosis whereas the Intestinal one constitutes less than 1% of the extrapulmonary forms of the disease. The lesions of abdominal organs are more common while they rarely occur in the anoperineal area for the spread of the disease to the anus is extremely rare. We report a case of a 37-year-old male patient with large bilateral infected perianal tubercular ulcerations as well as pulmonary and peritoneal tuberculosis. The treatment was both surgical and medical and the therapy lasted for seven months. After six months from the beginning of the treatment, the lesion had totally disappeared and there is still no recurrence after one year of followup. Tuberculosis should generally be taken into consideration in the differential diagnosis of the ulcerative lesions of the anal and perianal regions for these lesions do occur in the said areas despite their rarity. The treatment is usually both surgical and medical so as to get excellent results.
Automated phylogenetic taxonomy: an example in the homobasidiomycetes (mushroom-forming fungi).

Systematists confront a truly formidable task, which is to construct a comprehensive, phylogenetically accurate classification for all of life. Progress toward this goal has accelerated in recent years through analyses of DNA and protein sequences. The dramatic growth of molecular phylogenetics prompts us to ask whether established taxonomic practices are equipped to deal with the rapidly accumulating data. Here, we consider the current status of phylogenetics and classification in the homobasidiomycetes (mushroom-forming fungi), which includes roughly 17,000 described species (Kirk et al., 2001). We find that the available data are not being integrated, and that there is a significant gap between current taxonomy and understanding of phylogenetic relationships. To close this gap, we suggest that there is a need for new approaches that use the tools of bioinformatics to automate the process of phylogenetic analysis and classification, and we describe a prototype software package that we have developed for this purpose. The tools that we have created are applied to homobasidiomycetes, but can be adapted for use in any group of organisms.
Deep Polyphonic ADSR Piano Note Transcription

We investigate a late-fusion approach to piano transcription, combined with a strong temporal prior in the form of a handcrafted Hidden Markov Model (HMM). The network architecture under consideration is compact in terms of its number of parameters and easy to train with gradient descent. The network outputs are fused over time in the final stage to obtain note segmentations, with an HMM whose transition probabilities are chosen based on a model of attack, decay, sustain, release (ADSR) envelopes, commonly used for sound synthesis. The note segments are then subject to a final binary decision rule to reject too weak note segment hypotheses. We obtain state-of-the-art results on the MAPS dataset, and are able to outperform other approaches by a large margin, when predicting complete note regions from onsets to offsets.
Modelling Periodic Data Dissemination in Wireless Sensor Networks

Epidemic-based communications, or 'gossiping', provides a robust and scalable method for maintaining a knowledge base in a sensor network faced with an unpredictable network environment. Since sensed information is often periodic in time, protocols should be able to manage multiple messages in an efficient way. We describe a mathematical model of gossiping dealing with multiple messages. We present simulation results that suggest the model can provide insights into the design and optimisation of sensor networks in the case of dissemination of periodically generated data. We show that it is possible to control data freshness without increasing overhead, and quantify the importance of topology in achieving timely dissemination.
Direct haplotyping of chromosomal segments from multiple heterozygotes via allele-specific PCR amplification.

Alele specfic amplcation (ASA) of a DNA segmet [11 Is possible Ifthe polymorphism defining the aleleI b at the 3' end of one of the two prime required for polymerase chain reacon (PCR) [2]. The preseae or absnce of product after amplcaton with a given allele-speciflc primer and an Invariant primer annenag distall tpes the polymorphic priming site. Beyond Its discrimination at the polymorphic site, we hypothesized that ASA would sectively amplf the segment encompassed between primers in either the paternal or maternal chromosome of a heterozygote. Hence, it should be possible to haplotype directly all polymorpbbms nested between PCR primers. We chadncterlzed a pedigree (Fig la) at two polymorphic lod in the -globin ciuster [31. One locus wu typed I1p acording to presene or absee of a 630 bp product after ASA with allele-specific primers GR1/GR3 and Invariant primer GRS (Fig lb). The second locus, nested within the PCR segmet, was typed +/- for a TaqI site using a restriction fragtmt length polymorphsm (RFLP) on product amplifedwith GRS and primer 'GR=I "GR = anueals Indiscriminately to the GR1/GR3 site. Homozygote 'A' sets the phase of one chromosome In 'B' as 1,-; the other chromosome Is 3,+, which Is inherited by 'I' (homozygous 3,+) throagh 'G'. Theefore, the haplotypes are 1,- and 3,+. We all ASA
Using Land Surface Phenology for Spatio-temporal Mining of Image Time Series : A Manifesto

PROLEGOMENA: We are in an age of intensive earth observation. Critically needed are tools that will enable efficient and accurate characterization of land surface dynamics by analyzing and extracting the spatio-temporal patterns contained in image time series. As domain scientists, rather than computational scientists, we approach the data with some ideas about what constitutes interestingness in our data. One recurrent interesting theme is the distinction between change from a baseline and variation about a baseline. Baseline characterization is a foundational step in scientifically informed data mining. We seek first to incorporate our domain knowledge in the form of expectations of land surface dynamics, so that we can subsequently identify significant deviations from those expectations (de Beurs and Henebry 2004). Indeed, the motivation of extending occasional observation into intensive monitoring is to detect change, quantify disturbance, and enable prediction. The first NASA workshop on earth science data mining identified anomaly detection as a key characteristic of scientific data mining (Behnke et al. 2000).