Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality factor estimation of JPEG compressed images

The goal of the paper is to present a new approach to estimate the quality factor value for a JPEG image. This approach is based on the statistical model of variance of blocks 8 × 8 for JPEG images. The variance model follows Gamma distribution, characterized by two parameters which are used to calculate a distance between the first and the second compressions. The distance in case of compressing images twice with the same value of quality factor is exploited as characterized fingerprint for quality factor identification of a JPEG image. Experiments with simulated and real images highlight the relevance of the proposed approach.
Research Paper: Using Computerized Data to Identify Adverse Drug Events in Outpatients

OBJECTIVE To evaluate the use of a computer program to identify adverse drug events (ADEs) in the ambulatory setting and to evaluate the relative contribution of four computer search methods for identifying ADEs, including diagnosis codes, allergy rules, computer event monitoring rules, and text searching. DESIGN Retrospective analysis of one year of data from an electronic medical record, including records for 23,064 patients with a primary care physician, of whom 15,665 actually came for care. MEASUREMENT Presence of an ADE; sensitivity and specificity of computer searches for ADE. RESULTS The computer program identified 25,056 incidents, which were associated with an estimated 864 (95 percent confidence interval [CI], 750-978) ADES. Thus, the ADE rate was 5.5 (CI, 5.2-5.9) per 100 patients coming for care. Furthermore, in 79 (CI, 68-89) ADEs, the patient required hospitalization, resulting in an estimated rate of 3.4 (CI, 2.7-4.3) admissions per 1,000 patients. The sensitivity of the search methods for identifying ADEs was estimated to be 58 (CI, 18-98) percent, and the estimated specificity was 88 (CI, 87-88) percent. The positive predictive value was 7.5 (CI, 6.5-8.5) percent, and the negative predictive value was 99.2 (CI, 95.5-99.98) percent. Compared with age and gender-matched controls with no positive screen, patients with ADEs had twice as many outpatient visits and were taking nearly three times as many drugs. Antihypertensives, ACE-inhibitors, antibiotics, and diuretics were associated with 56 (CI, 47-65) percent of ADES. Among ADEs, 23 (CI, 16-32) percent were life-threatening or serious, and 38 (CI, 29-47) percent were judged preventable. CONCLUSION Computerized search programs can detect ADEs, and free-text searches were especially useful. Adverse drug events were frequent, and admissions were not rare, although most hospitals today do not identify them. Thus, such detection programs demonstrate "value-added" for the electronic record and may be useful for directing and assessing the impact of quality improvement efforts.
Joint decoding of tandem and hybrid systems for improved keyword spotting on low resource languages

Copyright © 2015 ISCA. Keyword spotting (KWS) for low-resource languages has drawn increasing attention in recent years. The state-of-the-art KWS systems are based on lattices or Confusion Networks (CN) generated by Automatic Speech Recognition (ASR) systems. It has been shown that considerable KWS gains can be obtained by combining the keyword detection results from different forms of ASR systems, e.g., Tandem and Hybrid systems. This paper investigates an alternative combination scheme for KWS using joint decoding. This scheme treats a Tandem system and a Hybrid system as two separate streams, and makes a linear combination of individual acoustic model log-likelihoods. Joint decoding is more efficient as it requires just a single pass of decoding and a single pass of keyword search. Experiments on six Babel OP2 development languages show that joint decoding is capable of providing consistent gains over each individual system. Moreover, it is possible to efficiently rescore the joint decoding lattices with Tandem or Hybrid acoustic models, and further KWS gains can be obtained by merging the detection posting lists from the joint decoding lattices and rescored lattices.
Cytotoxicity of sulfonamide reactive metabolites: apoptosis and selective toxicity of CD8+ cells by the hydroxylamine of sulfamethoxazole

Treatment with sulfonamide antibiotics in HIV‐infected patients is associated with a high incidence (> 40%) of adverse drug events, including severe hypersensitivity reactions. Sulfonamide reactive metabolites have been implicated in the pathogenesis of these adverse reactions. Sulfamethoxazole hydroxylamine (SMX‐HA) induces lymphocyte toxicity and suppression of proliferation in vitro; the mechanism(s) of these immunomodulatory effects remain unknown. We investigated the cytotoxicity of SMX‐HA via apoptosis on human peripheral blood mononuclear cells and purified cell subpopulations in vitro. CD19+, CD4+, and CD8+ cells were isolated from human peripheral blood by positive selection of cell surface molecules by magnetic bead separation. SMX‐HA induced significant CD8+ cell death (67 ± 7%) at 100 µM SMX‐HA, with only minimal CD4+ cell death (8 ± 4%). No significant subpopulation toxicity was shown when incubated with parent drug (SMX). Flow cytometry measuring phosphatidylserine externalization 24 h after treatment with 100 µM and 400 µM SMX‐HA revealed 14.1 ± 0.7% and 25.6 ± 4.2% annexin‐positive cells, respectively, compared to 3.7 ± 1.2% in control PBMCs treated with 400 µM SMX. Internucleosomal DNA fragmentation was observed in quiescent and stimulated PBMCs 48 h after incubation with SMX‐HA. Our data show that CD8+ cells are highly susceptible to the toxic effects of SMX‐HA through enhanced cell death by apoptosis. —Hess, D. A. , Sisson, M. E. , Suria, H. , Wijsman, J., Puvanesasingham, R. , Madrenas, J., Rieder, M. J. Cytotoxicity of sulfonamide reactive metabolites: apoptosis and selective toxicity of CD8+ cells by the hydroxylamine of sulfamethoxazole. FASEB J. 13, 1688–1698 (1999)
Linkage Relationships Among Multiple QTL for Horticultural Traits and Late Blight (P. infestans) Resistance on Chromosome 5 Introgressed from Wild Tomato Solanum habrochaites

When the allele of a wild species at a quantitative trait locus (QTL) conferring a desirable trait is introduced into cultivated species, undesirable effects on other traits may occur. These negative phenotypic effects may result from the presence of wild alleles at other closely linked loci that are transferred along with the desired QTL allele (i.e., linkage drag) and/or from pleiotropic effects of the desired allele. Previously, a QTL for resistance to Phytophthora infestans on chromosome 5 of Solanum habrochaites was mapped and introgressed into cultivated tomato (S. lycopersicum). Near-isogenic lines (NILs) were generated and used for fine-mapping of this resistance QTL, which revealed coincident or linked QTL with undesirable effects on yield, maturity, fruit size, and plant architecture traits. Subsequent higher-resolution mapping with chromosome 5 sub-NILs revealed the presence of multiple P. infestans resistance QTL within this 12.3 cM region. In our present study, these sub-NILs were also evaluated for 17 horticultural traits, including yield, maturity, fruit size and shape, fruit quality, and plant architecture traits in replicated field experiments over the course of two years. Each previously detected single horticultural trait QTL fractionated into two or more QTL. A total of 41 QTL were detected across all traits, with ∼30% exhibiting significant QTL × environment interactions. Colocation of QTL for multiple traits suggests either pleiotropy or tightly linked genes control these traits. The complex genetic architecture of horticultural and P. infestans resistance trait QTL within this S. habrochaites region of chromosome 5 presents challenges and opportunities for breeding efforts in cultivated tomato.
Functional Characteristics of a Highly Specific Integrase Encoded by an LTR-Retrotransposon

Background The retroviral Integrase protein catalyzes the insertion of linear viral DNA into host cell DNA. Although different retroviruses have been shown to target distinctive chromosomal regions, few of them display a site-specific integration. ZAM, a retroelement from Drosophila melanogaster very similar in structure and replication cycle to mammalian retroviruses is highly site-specific. Indeed, ZAM copies target the genomic 5′-CGCGCg-3′ consensus-sequences. To enlighten the determinants of this high integration specificity, we investigated the functional properties of its integrase protein denoted ZAM-IN. Principal Findings Here we show that ZAM-IN displays the property to nick DNA molecules in vitro. This endonuclease activity targets specific sequences that are present in a 388 bp fragment taken from the white locus and known to be a genomic ZAM integration site in vivo. Furthermore, ZAM-IN displays the unusual property to directly bind specific genomic DNA sequences. Two specific and independent sites are recognized within the 388 bp fragment of the white locus: the CGCGCg sequence and a closely apposed site different in sequence. Conclusion This study strongly argues that the intrinsic properties of ZAM-IN, ie its binding properties and its endonuclease activity, play an important part in ZAM integration specificity. Its ability to select two binding sites and to nick the DNA molecule reminds the strategy used by some site-specific recombination enzymes and forms the basis for site-specific integration strategies potentially useful in a broad range of genetic engineering applications.
Towards Adoption of DNSSEC: Availability and Security Challenges

DNSSEC deployment is long overdue; however, it seems to be finally taking off. Recent cache poisoning attacks motivate protecting DNS, with strong cryptography, rather than with challenge-response ‘defenses’. Our goal is to motivate and help correct DNSSEC deployment. We discuss the state of DNSSEC deployment, obstacles to adoption and potential ways to increase adoption. We then present a comprehensive overview of challenges and potential pitfalls of DNSSEC, well known and less known, including: • Vulnerable configurations: we present several DNSSEC configurations, which are natural and, based on the limited deployment so far, expected to be popular, yet are vulnerable to attack. This includes NSEC3 opt-out records and interdomain referrals (in NS, MX and CNAME records). • Incremental Deployment: we discuss potential for increased vulnerability due to popular practices of incremental deployment, and recommend secure practice. • Super-sized Response Challenges: DNSSEC responses include cryptographic keys and hence are relatively long; we explain how this extra-long responses cause interoperability challenges, and can be abused for DoS and even DNS poisoning. We discuss potential solutions.
Radiometric Model of the Sea Surface in the Presence of Currents

A consistent radiometric model of the ocean is an important part of the interpretation of passive microwave radiometric data. Empirical relations between measured brightness temperature and environmental parameters such as wind, surface temperature, salinity, etc., are often used for processing satellite and airborne data. There are some difficulties when using these approaches when a nonstationary environment is being studied, such as wind and/or surface currents that vary in time and space. In this case, a consistent model based on physical parameters of the sea surface and atmosphere is needed. We consider a radiometric model of the ocean based on a wave-action balance equation. Following Kudryavtsev and Makin, we modified the source term to account for parasitic ripples. Along with surface roughness, the model provides wave-breaking statistics and foam coverage, which is especially important for the microwave radiometry due to high foam emissivity. Comparison between the model prediction and the experimental observations shows a good agreement.
Personalized Reputation Model in Cooperative Distributed Systems

Reputation systems provide a promising way to build trust relationships between users in distributed cooperation systems, such as file sharing, streaming, distributed computing and social network, through which a user can distinguish good services or users from malicious ones and cooperate with them. However, most reputation models mainly focus on evaluating the quality of services in one dimension, but care less about the preferences of different users. This paper proposes a personalized reputation model which provides each user a personalized trust view on others according to his preferences. In our approach, we aggregate the usersâ€™ preferences with collaborative filtering method and qualify it with user similarity which is integrated into the computing of reputation value. The experimental results suggest that our model can resist possible kinds of malicious behaviors efficiently.
An approximation algorithm for finding skeletal points for density based clustering approaches

Clustering is the problem of finding relations in a data set in an supervised manner. These relations can be extracted using the density of a data set, where density of a data point is defined as the number of data points around it. To find the number of data points around another point, region queries are adopted. Region queries are the most expensive construct in density based algorithm, so it should be optimized to enhance the performance of density based clustering algorithms specially on large data sets. Finding the optimum set of region queries to cover all the data points has been proven to be NP-complete. This optimum set is called the skeletal points of a data set. In this paper, we proposed a generic algorithms which fires region queries at most 6 times the optimum number of region queries (has 6 as approximation factor). Also, we have extend this generic algorithm to create a DBSCAN (the most wellknown density based algorithm) derivative, named ADBSCAN. Presented experimental results show that ADBSCAN has a better approximation to DBSCAN than the DBRS-H (the most well-known randomized density based algorithm) in terms of performance and quality of clustering, specially for large data sets.
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data

We consider learning a distance metric in a weakly supervised setting where bags (or sets) of instances are labeled with bags of labels. A general approach is to formulate the problem as a Multiple Instance Learning (MIL) problem where the metric is learned so that the distances between instances inferred to be similar are smaller than the distances between instances inferred to be dissimilar. Classic approaches alternate the optimization over the learned metric and the assignment of similar instances. In this paper, we propose an efficient method that jointly learns the metric and the assignment of instances. In particular, our model is learned by solving an extension of k-means for MIL problems where instances are assigned to categories depending on annotations provided at bag-level. Our learning algorithm is much faster than existing metric learning methods for MIL problems and obtains state-of-the-art recognition performance in automated image annotation and instance classification for face identification.
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning

Reinforcement learning algorithms for real-world robotic applications must be able to handle complex, unknown dynamical systems while maintaining data-efficient learning. These requirements are handled well by model-free and model-based RL approaches, respectively. In this work, we aim to combine the advantages of these approaches. By focusing on time-varying linear-Gaussian policies, we enable a model-based algorithm based on the linear-quadratic regulator that can be integrated into the model-free framework of path integral policy improvement. We can further combine our method with guided policy search to train arbitrary parameterized policies such as deep neural networks. Our simulation and real-world experiments demonstrate that this method can solve challenging manipulation tasks with comparable or better performance than model-free methods while maintaining the sample efficiency of model-based methods.
Sugar Metabolism in Hummingbirds and Nectar Bats

Hummingbirds and nectar bats coevolved with the plants they visit to feed on floral nectars rich in sugars. The extremely high metabolic costs imposed by small size and hovering flight in combination with reliance upon sugars as their main source of dietary calories resulted in convergent evolution of a suite of structural and functional traits. These allow high rates of aerobic energy metabolism in the flight muscles, fueled almost entirely by the oxidation of dietary sugars, during flight. High intestinal sucrase activities enable high rates of sucrose hydrolysis. Intestinal absorption of glucose and fructose occurs mainly through a paracellular pathway. In the fasted state, energy metabolism during flight relies on the oxidation of fat synthesized from previously-ingested sugar. During repeated bouts of hover-feeding, the enhanced digestive capacities, in combination with high capacities for sugar transport and oxidation in the flight muscles, allow the operation of the “sugar oxidation cascade”, the pathway by which dietary sugars are directly oxidized by flight muscles during exercise. It is suggested that the potentially harmful effects of nectar diets are prevented by locomotory exercise, just as in human hunter-gatherers who consume large quantities of honey.
Utility-based radio resource allocation for QoS traffic in wireless networks

In this paper, we study utility-based resource allocation for soft QoS traffic in infrastructure-based wireless networks. Soft QoS traffic here refers to the traffic which demands certain amount of bandwidth for normal operation but allows some flexibility when the given bandwidth is close to the preferred value. The resource requirement of soft QoS traffic can be described with sigmoid utility function. Our objective is to maximize the total utility of all soft QoS flows without going through a wireless bidding process. We develop essential theorems as the design guidelines for this problem, and then propose a sub-optimal, polynomial time solution based on the developed theorems. We prove that the difference in the performance of our mechanism and the optimal solution is bounded. The performance of the proposed solution is evaluated via simulations. The results show that our solution can adapt to any types of soft QoS flows. Specifically, it acts like a hard QoS system and allocates resource in a fairness-oriented manner when the utility functions of flows are unit-step functions; on the other hand, when the utility functions are concave, it behaves like a best effort system and allocates resource in a throughput-oriented way.
Evidence for Persistent, Occult Infection in Neonatal Macaques following Perinatal Transmission of Simian-Human Immunodeficiency Virus SF162P3

ABSTRACT To model human immunodeficiency virus (HIV) perinatal transmission, we studied infection of simian-human immunodeficiency virus (SHIV) SF162P3 in 10 pregnant Macaca nemestrina females and their offspring. Four of nine infants born to and suckled by these dams had evidence of infection, a transmission rate of 44.4% (95% confidence interval, 13.7% to 78.8%). We quantified transplacentally acquired and de novo Env-specific immunoglobulin G (IgG), IgM, and neutralizing antibodies in newborns. Transmission of escape variants was confirmed. In utero infection (n = 1) resulted in high viremia, depletion of peripheral CD4+ T cells, and rapid evolution of env in blood and tissues. Peripartum or postpartum SHIV infection (n = 3) resulted in postacute viral control that was undetectable by very sensitive multiplex PCR, despite increasing antibodies. Seropositive infants with highly controlled viremia had homogeneous peripheral blood env sequences, and their tissues had <3 copies per million cells. A high incidence of seropositive virus-low or -negative SHIV infection in infant macaques has implications for HIV type 1 perinatal transmission and detection.
Bangla phoneme recognition for ASR using multilayer neural network

This paper presents a Bangla phoneme recognition method for Automatic Speech Recognition (ASR). The method consists of two stages: i) a multilayer neural network (MLN), which converts acoustic features, mel frequency cepstral coefficients (MFCCs), into phoneme probabilities and ii) the phoneme probabilities obtained from the first stage and corresponding Δ and ΔΔ parameters calculated by linear regression (LR) are inserted into a hidden Markov model (HMM) based classifier to obtain more accurate phoneme strings. From the experiments on Bangla speech corpus prepared by us, it is observed that the proposed method provides higher phoneme recognition performance than the existing method. Moreover, it requires a fewer mixture components in the HMMs.
The FASB - AcSEC Relationship: Cooperation or Conflict?

The following is adapted from a speech by Dennis R. Beresford, chairman of the Financial Accounting Standards Board and past chairman of the American Institute of CPAs accounting standards executive committee, concerning the cooperation that is the cornerstone of the FASB-AcSEC relationship. The speech was delivered at the AICPA 18th National Conference on SEC Developments and appeared in its entirely in the January 23, 1992, issue of the FASB Status Report. Concern about the FASB-AcSEC relationship first heated up in 1977 and 1978. The AICPA issued several statements of position, causing * Some AcSEC members to become concerned about SOPs' uncertain authoritative status. * The Financial Executives Institute, among others, to protest that AcSEC was becoming a competing standard setter. * The FASB to become concerned the AICPA wanted to regain some of the authority it had granted the FASB. * The Securities and Exchange Commission to report to Congress that the FASB should deal with specialized industry problems. These factors all contributed to FASB's plan to (1) rewrite in FASB format all SOPs, AICPA industry accounting guides and accounting portions of its industry audit guides and (2) issue them as standards after public comment. I now believe the FASB wasted a lot of time and effort issuing statements that merely extracted AICPA literature. A any rate, the extraction process ran out of steam and came to a halt in 1982 - before it was complete. Because AcSEC was discouraged from issuing SOPs in most cases, the Institute began devoting more of its attention to issues papers, identifying problems for the board rather than trying to fix them directly. Issues papers, intended as neutral documents, soon included advisory conclusions (AcSEC votes on the various issues). Some considered issues papers with advisory conclusions another form of generally accepted accounting principles - perhaps only slightly less authoritative than SOPs. Just about the time I joined the FASB in 1987, AcSEC completed an issues paper on accounting for options. As was the usual procedure, AcSEC sent us that paper and urged us to add a project on options to our agenda. But even before sending us the document, the Institute had published it and sold copies. Also, a summary article appeared in the Journal of Accountancy. We sensed the AICPA was attempting to established GAAP in at least an indirect way. The board reviewed the options issues paper at a public meeting in February 1987, deciding to deal with accounting for options as part of the financial instruments project. We also believed some advisory conclusions conflicted with FASB-established GAAP, so we reiterated that existing authoritative standards had to be followed. The board,which agreed advisory conclusions could create confusion among practitioners, urged AcSEC to delete them in the future. However, we also acknowledged the FASB probably could not keep up with the need for specialized industry guidance and in a significant change from our 1970s position, encouraged AcSEC to consider SOPS when appropriate. …