Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular mechanisms of resistance to antibiotics in Bartonella bacilliformis.

OBJECTIVES Bartonella bacilliformis is the aetiological agent of Carrion's disease. Although ciprofloxacin, rifampicin and erythromycin have been successfully used in the treatment of the disease, failures and relapses have been reported. The objective of our study was to select in vitro mutants resistant to antibiotics in order to determine the frequency of mutations and to characterize the mechanism of resistance at the molecular level. METHODS Antibiotic-resistant mutants were selected by serial passages of bacteria on blood agar plates containing antibiotics. Candidate genes involved in resistance were amplified and sequenced and compared in order to look at mutations associated with antibiotic resistance. RESULTS Ciprofloxacin-, rifampicin- and erythromycin-resistant mutants were obtained after five, three and four passages, respectively. Conversely, no mutant was obtained with either gentamicin or doxycycline even after 16 passages. The ciprofloxacin mutant contained an amino acid change at position 87 (Asp --> Asn) in its quinolone resistance-determining region of the DNA gyrase protein, whereas the rifampicin-resistant strain had an amino acid change at position 531 (Ser --> Phe) in the rifampicin resistance-determining region of the rpoB gene. Similarly, the erythromycin-resistant mutant showed an A2058G mutation in the 23S rRNA gene. CONCLUSIONS According with the current knowledge on the treatment of human bartonellosis, we believe that doxycycline in association with gentamicin may be the preferred regimen for the treatment of the acute and eruptive stages of Carrion's disease, but clinical trials are warranted to support our findings.
Human Activity Recognition Using Tag-Based Radio Frequency Localization

ABSTRACT This article provides a comparative study on the different techniques of classifying human activities using tag-based radio-frequency (RF) localization. A publicly available dataset is used where the position data of multiple RF tags worn on different parts of the human body are acquired asynchronously and nonuniformly. In this study, curves fitted to the data are resampled uniformly and then segmented. We investigate the effect on system accuracy of varying the relevant system parameters. We compare various curve-fitting, segmentation, and classification techniques and present the combination resulting in the best performance. The classifiers are validated using 5-fold and subject-based leave-one-out cross validation, and for the complete classification problem with 11 classes, the proposed system demonstrates an average classification error of 8.67% and 21.30%, respectively. When the number of classes is reduced to five by omitting the transition classes, these errors become 1.12% and 6.52%, respectively. The results indicate that the system demonstrates acceptable classification performance despite that tag-based RF localization does not provide very accurate position measurements.
A 1.0–4.0-Gb/s All-Digital CDR With 1.0-ps Period Resolution DCO and Adaptive Proportional Gain Control

This paper describes the design and implementation of an all-digital clock and data recovery circuit (ADCDR) for multigigabit/s operation. The proposed digitally-controlled oscillator (DCO) incorporating a supply-controlled ring oscillator with a digitally-controlled resistor (DCR) generates wide-frequency-range multiphase clocks with fine resolution. With an adaptive proportional gain controller (APGC) which continuously adjusts a proportional gain, the proposed ADCDR recovers data with a low-jitter clock and tracks large input jitter rapidly, resulting in enhanced jitter performance. A digital frequency-acquisition loop with a proportional control greatly reduces acquisition time. Fabricated in a 0.13-μm CMOS process with a 1.2-V supply, the ADCDR occupies 0.074 mm2 and operates from 1.0 Gb/s to 4.0 Gb/s with a bit error rate of less than 10-14. At a 3.0-Gb/s 231 - 1 PRBS, the measured jitter in the recovered clock is 3.59 psrms and 29.4 pspp, and the power consumption is 11.4 mW.
Learning dictionaries of spatial and temporal EEG primitives for brain-computer interfaces

Sparse methods are widely used in image and audio processing for denoising and classification, but there have been few previous applications to neural signals for brain-computer interfaces (BCIs). We used the dictionary- learning algorithm K-SVD, coupled with Orthogonal Matching Pursuit, to learn dictionaries of spatial and temporal EEG primitives. We applied these to P300 and ErrP data to denoise the EEG and better estimate the underlying P300 and ErrP signals. This methodology improved single-trial classification performance across 13 of 14 subjects, indicating that some of the background noise in EEG signals, presumably from neural or muscular sources, is highly structured. Furthermore, this structure can be captured via dictionary learning and sparse coding algorithms, and exploited to improve BCIs.
Radiofrequency Ablation is Better Than Surgical Resection in Patients With Hepatocellular Carcinoma Within the Milan Criteria and Preserved Liver Function: A Retrospective Study Using Propensity Score Analyses

Goals/Background: Radiofrequency ablation (RFA) and surgical resection (SR) are effective therapies for hepatocellular carcinoma (HCC) within the Milan criteria. We aimed to compare the treatment efficacy according to the liver functional reserve using propensity score analysis. Study: There were 330 and 369 HCC patients within the Milan criteria undergoing SR and RFA, respectively. A total of 147 and 48 pairs of patients with Child-Turcotte-Pugh (CTP) scores=5 and >5, respectively, were matched for analyses. Results: Overall, the 3- and the 5-year survivals were 88% and 76% in the SR group and 80% and 66% in the RFA group, respectively (P=0.006). The SR group had significantly younger patients, a higher male-to-female ratio and hepatitis B infection rate, with a better liver functional reserve and performance status, and a larger tumor burden. In patients with a CTP score of 5, no survival difference was noted between the SR and the RFA groups (P=0.564). In patients with CTP score >5, the SR group had a better long-term survival than the RFA group (P=0.016). After propensity score analysis, the RFA group had a better long-term survival than the SR group in patients with CTP score=5 in the univariate (P=0.024) and the Cox proportional hazards models (hazard ratio: 0.47, P=0.031). Comparable survival results were noted between SR and RFA in patients with CTP score >5 (P=0.15). Conclusions: RFA is a safe procedure with better treatment efficacy than SR in patients with small HCC and a CTP score of 5, and provides effects comparable to SR in patients with CTP score >5. The baseline liver functional reserve may enhance treatment selection for outcome prediction.
Beyond the Coral Triangle: high genetic diversity and near panmixia in Singapore's populations of the broadcast spawning sea star Protoreaster nodosus

The Coral Triangle is widely considered the most important centre of marine biodiversity in Asia while areas on its periphery such as the South China Sea, have received much less interest. Here, we demonstrate that a small population of the knobbly sea star Protoreaster nodosus in Singapore has similarly high levels of genetic diversity as comparable Indonesian populations from the Coral Triangle. The high genetic diversity of this population is remarkable because it is maintained despite decades of continued anthropogenic disturbance. We postulate that it is probably due to broadcast spawning which is likely to maintain high levels of population connectivity. To test this, we analysed 6140 genome-wide single nucleotide polymorphism (SNP) loci for Singapore's populations and demonstrate a pattern of near panmixia. We here document a second case of high genetic diversity and low genetic structure for a broadcast spawner in Singapore, which suggests that such species have high resilience against anthropogenic disturbances. The study demonstrates the feasibility and power of using genome-wide SNPs for connectivity studies of marine invertebrates without a sequenced genome.
Search for an optimal rapid charging pattern for lithium-ion batteries using ant colony system algorithm

Commercial lithium-ion batteries are playing important roles as supplies for mobile phones, laptop computers, and other electronics. In order to maximize the performance of lithium-ion batteries, an advanced rapid charging pattern is required. In this paper, an Ant-Colony-System (ACS)-based algorithm is presented. The proposed ACS-based algorithm can be integrated into a commercially available battery tester to search for the optimal rapid charging pattern. Experimental results show that the obtained rapid charging pattern is capable of charging the lithium-ion batteries to 70% capacity in 30 min. The obtained pattern also provides 25% more cycle life than the conventional constant current-constant voltage method.
Association of Lifestyle Factors With Abdominal Subcutaneous and Visceral Adiposity

OBJECTIVE— The purpose of this study was to assess the relationship between lifestyle factors and abdominal subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in a community-based setting. RESEARCH DESIGN AND METHODS— Cross-sectional associations between lifestyle factors (dietary quality, physical activity, smoking, and alcohol consumption) and SAT and VAT volumes were examined in 2,926 Framingham Heart Study participants (48.6% women, aged 50 ± 10 years). RESULTS— Diets consistent with the 2005 Dietary Guidelines Adherence Index and greater physical activity were inversely associated with SAT and VAT (P < 0.0001–0.002). In men, former smoking was associated with higher SAT (2,743 ± 56 cm3) compared with current smokers (2,629 ± 88 cm3) or those who never smoked (2,538 ± 44 cm3; P = 0.02). Both former and current smoking was associated with higher VAT (P = 0.03 [women]; P = 0.005 [men]). Women with high amounts of alcohol intake (>7 drinks/week) had lower SAT (2,869 ± 106 cm3) than those who consumed less alcohol (3,184 ± 44 cm3, P = 0.006); significant differences in VAT were not observed (P = 0.18). In men, high amounts of alcohol intake (>14 drinks/week) were associated with higher VAT (2,272 ± 59 cm3) compared with intake of ≤14 drinks/week (2,139 ± 25 cm3, P = 0.04), whereas SAT did not differ (P = 0.91). An increasing number of healthy lifestyle factors were associated with lower SAT and VAT volumes (all P < 0.003). CONCLUSIONS— Adherence to recommended dietary guidelines and physical activity are associated with lower SAT and VAT volumes. However, both smoking and high alcohol intake are differentially associated with VAT volumes. Further research to uncover the putative mechanisms is warranted.
Bacterial Capture by Peptide-Mimetic Oligoacyllysine Surfaces

ABSTRACT Most procedures for detecting pathogens in liquid media require an initial concentration step. However, poor recovery efficiencies of conventional methods, such as filtration, often lead to low sensitivity. Here, we describe a strategy for concentrating bacteria using their binding affinity for an oligoacyllysine (OAK), a novel peptide-mimetic antimicrobial compound. We show that the resin-linked OAK (ROAK) efficiently captures a variety of pathogens in different media, upon brief incubation with ROAK beads or after continuous flow through a ROAK-packed column. Using Escherichia coli expressing green fluorescent protein, we show that binding occurs rapidly during incubation and persists after filtration as visualized by confocal microscopy. The high binding affinity of bacteria was confirmed by surface plasmon resonance technology using an OAK-linked chip. ROAK-bound bacteria remained viable and were readily identifiable by real-time PCR after ethanol elution. A single ROAK bead is estimated to capture about 3,000 bacterial cells in culture medium, in contaminated saline or tap water. ROAK beads can be regenerated for multiple uses after brief ethanol treatment. Collectively, the data support the notion that OAK-based coating of polymeric surfaces might represent a useful means for medium filtration as well as for concentration of bacteria.
Video analysis validation of a real-time physical activity detection algorithm based on a single waist mounted tri-axial accelerometer sensor

We have validated a real-time activity classification algorithm based on monitoring by a body worn system which is potentially suitable for low-power applications on a relatively computationally lightweight processing unit. The algorithm output was validated using annotation data generated from video recordings of 20 elderly volunteers performing both a semi-structured protocol and a free-living protocol. The algorithm correctly identified sitting 75.1% of the time, standing 68.8% of the time, lying 50.9% of the time, and walking and other upright locomotion 82.7% of the time. This is one of the most detailed validations of a body worn sensor algorithm to date and offers an insight into the challenges of developing a real-time physical activity classification algorithm for a tri-axial accelerometer based sensor worn at the waist.
Mistake-driven learning with thesaurus for text categorization

This paper extends the mistake-driven learner WINNOW to better utilize thesauri for text categorization. In our method not only words but also semantic categories given by the thesaurus are used as features in a classier. New ltering and disambiguation methods are used as pre-processing to solve the problems caused by the use of the thesaurus. In order to verify our methods, we test a large body of tagged Japanese newspaper articles created by RWCP 1 . Experimental results show that WINNOW with thesauri attains high accuracy and that the proposed ltering and disambiguation methods also contribute to the improved accuracy.
A Corpus and Phonetic Dictionary for Tunisian Arabic Speech Recognition

In this paper we describe an effort to create a corpus and phonetic dictionary for Tunisian Arabic Automatic Speech Recognition (ASR). The corpus, named TARIC (Tunisian Arabic Railway Interaction Corpus) has a collection of audio recordings and transcriptions from dialogues in the Tunisian Railway Transport Network. The phonetic (or pronunciation) dictionary is an important ASR component that serves as an intermediary between acoustic models and language models in ASR systems. The method proposed in this paper, to automatically generate a phonetic dictionary, is rule based. For that reason, we define a set of pronunciation rules and a lexicon of exceptions. To determine the performance of our phonetic rules, we chose to evaluate our pronunciation dictionary on two types of corpora. The word error rate of word grapheme-to-phoneme mapping is around 9%.
Spillover Compensation in the Presence of Respiratory Motion Embedded in SPECT Perfusion Data

Spillover from adjacent significant accumulations of extra-cardiac activity decreases diagnostic accuracy of SPECT perfusion imaging in especially the inferior/septal cardiac region. One method of compensating for the spillover at some location outside of a structure is to estimate it as the counts blurred into this location when a template (3D model) of the structure undergoes simulated imaging followed by reconstruction. The objective of this study was to determine what impact uncorrected respiratory motion has on such spillover compensation of extra-cardiac activity in the right coronary artery (RCA) territory, and if it is possible to use manual segmentation to define the extra-cardiac activity template(s) used in spillover correction. Two separate MCAT phantoms (1283 matrices) were simulated to represent the source and attenuation distributions of patients with and without respiratory motion. For each phantom the heart was modeled: 1) with a normal perfusion pattern and 2) with an RCA defect equal to 50% of the normal myocardium count level. After Monte Carlo simulation of 64times64times120 projections with appropriate noise, data were reconstructed using the rescaled block iterative (RBI) algorithm with 30 subsets and 5 iterations with compensation for attenuation, scatter and resolution. A 3D Gaussian post-filter with a sigma of 0.476 cm was used to suppress noise. Manual segmentation of the liver in filtered emission slices was used to create 3D binary templates. The true liver distribution (with and without respiratory motion included) was also used as binary templates. These templates were projected using a ray-driven projector simulating the imaging system with the exclusion of Compton scatter and reconstructed using the same protocol as for the emission data, excluding scatter compensation. Reconstructed templates were scaled using reconstructed emission count levels from the liver, and spillover subtracted outside the template. It was evident from the polar maps that the manually segmented template reconstructions were unable to remove all the spillover originating in the liver from the inferior wall. This was especially noticeable when a perfusion defect is present. Templates based on the true liver distribution appreciably improved spillover correction. Thus the emerging combined SPECT/CT technology may play a vital role in identifying and segmenting extra-cardiac structures more reliably thereby facilitating spillover correction. This study also indicates that compensation for respiratory motion might play an important role in spillover compensation.
SAKE - Secure Authenticated Key Establishment in Sensor Networks

Master key schemes are a viable solution to establish pairwise shared secret keys in wireless sensor networks. In these schemes, a master key is preconfigured into each sensor node which is then used by each node to generate pairwise shared secret keys. In the literature so far, it is essential for each sensor node to keep master key in its memory during the entire phase of key setup. As soon as key setup completes, each node erases the master key from its memory. Although key setup phase of a node lasts for a small interval of time, it is not impossible for an adversary to compromise a node during this time. In this situation, the presence of master key can be disastrous. So the challenge is to protect a sensor network from compromise of master key during its key setup phase. We propose Secure Authenticated Key Establishment (SAKE) protocol that meets the above challenge by introducing an idea that master key need not to be kept by a sensor node for the entire key setup phase thereby shortening the master key compromise window. With the help of our proposed scheme, other attacks during key setup phase can also be avoided.
Spoken Control of Existing Mobile Interfaces With the Crowd

Recently, a number of mobile crowd-powered assistive technology systems have been made possible due to the advent of real-time crowdsourcing and ubiquitous broadband internet access on phones and other mobile devices. However, until now these systems have typically aided accessibility from the user’s device, not for it. In this paper, we design Legion:Mobile, a system that will allow blind and motor impaired users to control their mobile device using more robust spoken controls than are currently available using automatic systems today. We do this by building on prior work on Legion, which allowed the crowd to control existing desktop interfaces, and Chorus, a conversational assistant powered by the crowd. We discuss the design and architecture that makes Legion:Mobile possible, and address privacy concerns often associated with crowd assistance.
IBM Research Report Analyzing Analytics Part 1: A Survey of Business Analytics Models and Algorithms

Many organizations today are faced with the challenge of processing and distilling information from huge and growing collections of data. We see examples of retailers trying to better serve their customers, telecommunications providers trying to more effectively manage their growing networks, cities trying to provide smarter infrastructure and services for their rapidly growing populations, and many more similar instances across multiple industries. These organizations are facing a deluge of information and are increasingly deploying sophisticated mathematical algorithms to model the behavior of their business processes to discover correlations in the data, to predict trends and ultimately drive decisions to optimize their operations. These techniques, are known collectively as ”analytics”, and draw upon multiple disciplines, including statistics, quantitative analysis, data mining, and machine learning. In this survey paper and the accompanying research report, we identify some of the key techniques employed in analytics both to serve as an introduction for the non-specialist and to explore the opportunity for greater optimization for parallel computer architectures and systems software. We are interested in isolating and documenting repeated patterns in analytical algorithms, data structures and data types, and in understanding how these could be most effectively mapped onto parallel systems. Scalable and efficient parallelism is critically important to enable organizations to apply these techniques to ever larger data sets for reducing the time taken to perform these analyses. To this end, we focus on analytical models (e.g. neural networks, logistic regression or support vector machines) that can be executed using different algorithms. For most major model types, we study implementations of key algorithms to determine common computational and runtime patterns. We then use this information to characterize and recommend suitable parallelization strategies.
Estimating Human Pose in Images

This project attempts to improve the performance of an existing method of estimating the pose of humans in still images. Tasks such as object detection and classification have received much attention already in the literature. However, sometimes we are interested in more detailed aspects of objects like pose. This is a challenging task due to the large variety of poses an object can take in a variety of settings. For human pose estimation, aspects such as clothing, occlusion of body parts, etc. make the task even harder.
Rigidity of Circulating Lymphocytes Is Primarily Conferred by Vimentin Intermediate Filaments

Lymphocytes need rigidity while in circulation, but must abruptly become deformable to undergo transmigration into tissue. Previously, the control of leukocyte deformability has been attributed to microfilaments or microtubules, but the present studies demonstrate the greater importance of vimentin intermediate filaments (IFs). In circulating T lymphocytes, IFs form a distinctive spherical cage that undergoes a rapid condensation into a juxtanuclear aggregate during chemokine-induced polarization. Measurements of the resistance of peripheral blood T lymphocytes to global deformation demonstrate that their rigidity is primarily dependent on intact vimentin filaments. Microtubules, in contrast, are not sufficient to maintain rigidity. Thus, vimentin IFs are a primary source of structural support in circulating human lymphocytes, and their regulated collapse is likely to be an essential element in chemokine-induced transendothelial migration.