Miracle-dz/UniFAR-FTUs huggingface dataset:
QuantiFERON-TB predicts tuberculin skin test boosting in U.S. foreign-born.

SETTING Santa Clara County, Northern California. OBJECTIVE To characterize agreement of tuberculin skin test (TST) and QuantiFERON-TB (QFT) with repeated testing. DESIGN Fifty-two subjects participating in an ongoing prospective study of infectious disease transmission were tested by TST and QFT at two home visits 3 months apart. Boosting was defined as reclassification of TST from negative to positive. Agreement and reproducibility of TST and QFT were assessed using kappa and McNemar statistics. RESULTS Of 48 individuals completing all tests, 75% were foreign-born (92% Latin America) and 58% were BCG-vaccinated. Initial TST and QFT were positive in 13 (27%) and 21 (44%), respectively, with an overall agreement of 67% (K = 0.29). Ten (29%) of 35 initial TST-negative reactions boosted, nine of whom were BCG-vaccinated subjects. Boosting occurred in eight (67%) of 12 subjects who were initially QFT-positive/TST-negative. Compared to the second TST, initial QFT had a relative post-test probability of 76% (95% CI 0.58-0.95); boosting accounted for 8/16 (50%) of initial testing discordances. CONCLUSION Positive QFT in the setting of negative TST frequently anticipates a TST boost. This finding helps explain discordance between the two tests and may provide an alternative to serial TST testing.
A Low Resource Consumption Image Region Extraction Algorithm for Mobile Devices

Although the camera phone market has experienced exponential growth in recent years, the applications of built-in camera on the mobile phone still have not progressed as anticipated. One of the main reasons is the low resource on the mobile phone that hinder the deployment of many time consuming image processing tasks. In this paper, a fundamental image processing problem namely image segmentation has been revisited for adapting to a low resource computing device, and a novel image region extraction scheme is proposed. The region extraction algorithm takes into account the constraints exhibited in the mobile phone captured images and the low computing resource made available for applications, and can achieve reasonable result in both performance and speed in our experiments.
The Application of Spatial Analysis Methods in the Real Estate Market in South‑Eastern Poland

The aim of the article is to apply the method of spatial analysis to research the real estate property market in south‑eastern Poland. The methods of spatial statistics will be used to model the space differences of prices per one square metre of dwelling surface located in districts of south‑eastern Poland and to investigate spatial autocorrelation. The databases will be presented in a graphical form. The results may be used to set the spatial regularities and relations. The methods presented may be applied while making strategic decisions.
Raised serum APRIL levels in patients with systemic lupus erythematosus

Objective: To determine whether serum levels of a proliferation-inducing ligand (APRIL) are raised in patients with systemic lupus erythematosus (SLE) and correlate with autoantibody titres or disease activity, or both. Methods: Serum samples from 48 patients with SLE, 41 normal healthy subjects, and 21 patients with rheumatoid arthritis (RA) were assayed for APRIL by enzyme linked immunosorbent assay. Medical charts were retrospectively reviewed for autoantibody titres and immunoglobulin levels. Disease activity was assessed using the British Isles Lupus Assessment Group (BILAG) index. Results: The APRIL levels in the serum samples from patients with SLE were significantly higher than in those from healthy controls and those from patients with RA. Serum APRIL levels did not correlate with serum IgG and IgM levels, but had a tendency to correlate with anti-double stranded DNA antibody titres. Moreover, serum APRIL levels correlated significantly with musculoskeletal manifestations among patients with SLE when assessed by the BILAG index. Conclusion: APRIL may be an important factor in raised autoantibody titres and musculoskeletal disease in patients with SLE. Patients with raised serum APRIL levels may be ideal candidates for therapeutic targeting of APRIL.
Fetal and Neonatal Endocrine Disruptors

Endocrine disruptors are substances commonly encountered in every setting and condition in the modern world. It is virtually impossible to avoid the contact with these chemical compounds in our daily life. Molecules defined as endocrine disruptors constitute an extremely heterogeneous group and include synthetic chemicals used as industrial solvents/lubricants and their by-products. Natural chemicals found in human and animal food (phytoestrogens) also act as endocrine disruptors. Different from adults, children are not exposed only to chemical toxins in the environment but may also be exposed during their intrauterine life. Hundreds of toxic substances, which include neuro-immune and endocrine toxic chemical components that may influence the critical steps of hormonal, neurological and immunological development, may affect the fetus via the placental cord and these substances may be excreted in the meconium. Children and especially newborns are more sensitive to environmental toxins compared to adults. Metabolic pathways are immature, especially in the first months of life. The ability of the newborn to metabolize, detoxify and eliminate many toxins is different from that of the adults. Although exposures occur during fetal or neonatal period, their effects may sometimes be observed in later years. Further studies are needed to clarify the effects of these substances on the endocrine system and to provide evidence for preventive measures. Conflict of interest:None declared.
Novel Atmospheric Pressure Plasma Utilizing Symmetric Dielectric Barrier Discharge for Mass Spectrometry Applications

This paper develops a novel symmetric dielectric barrier discharge (DBD) plasma as an ion source for environmental mass spectrometry (MS) applications. The conventional linear-type DBD plasma generator suffers the drawback of floating voltage at the plasma outlet. This paper develops an innovative symmetric T-shaped DBD plasma generator to produce atmospheric plasma with zero-floating potential for high-sensitivity MS analysis. By changing the geometric configuration and the drive phase of the symmetric T-shaped DBD plasma generator, the resulting symmetric structural design can fully cancel the floating potential and noise signal. Therefore, the main objective of this paper is to compare the differences between traditional linear-type DBD and the symmetric T-shaped DBD designs using MS, spectroscopy, and some basic electrical measurements. The most suitable parameters are determined by changing the electrode design, voltage, temperature, gas flow rate, diameter, and other parameters of the plasma tube. The symmetric T-shaped design generator produces the zero-potential plasma that generates fewer ambient gas molecules to form ozone, NOx, water clusters, and other strong oxidizing molecules such that less damage to the MS samples occurs. This in turn results in a less fragmented ion signal and higher sensing performance for rapid MS applications. In addition, the proposed system can directly ionize gas, liquid, and solid samples at more than $10^{7}$ -cm$^{-3}$ ion concentration. Results show that more information-rich spectra can be obtained with the developed symmetric T-shaped DBD plasma generator compared with the typical linear-type DBD generator.
From Time Petri Nets to Timed Automata

In this paper, we consider Time Petri Nets (TPN) where time is associated with transitions. We give a formal semantics for TPNs in terms of Timed Transition Systems. Then, we propose a translation from TPNs to Timed Automata (TA) that preserves the behavioural semantics (timed bisimilarity) of the TPNs. For the theory of TPNs this result is two-fold: i) reachability problems and more generally TCTL model-checking are decidable for bounded TPNs; ii) allowing strict time constraints on transitions for TPNs preserves the results described in i). The practical applications of the translation are: i) one can specify a system using both TPNs and Timed Automata and a precise semantics is given to the composition; ii) one can use existing tools for analysing timed automata (like KRONOS or UPPAAL or CMC) to analyse TPNs.
Chronic Pain as an Outcome of Surgery: A Review of Predictive Factors

ONE potential adverse outcome from surgery is chronic pain. Analysis of predictive and pathologic factors is important to develop rational strategies to prevent this problem. Additionally, the natural history of patients with and without persistent pain after surgery provides an opportunity to improve the understanding of the physiology and psychology of chronic pain. Ideally, studies of chronic postoperative pain should include (1) sufficient preoperative data (assessment of pain, physiologic and psychologic risk factors for chronic pain); (2) detailed descriptions of the operative approaches used (location and length of incisions, handling of nerves and muscles); (3) the intensity and character of acute postoperative pain and its management; and (4) follow-up at intervals to 1 yr or more. In addition, there would be information about postoperative interventions that may influence pain, such as radiation therapy or chemotherapy. At long-term follow-up visits, patient function, physical signs, and symptoms would be evaluated using a standardized algorithm, including quantitative and descriptive pain assessments. We found no studies that contain all of these data. For this review, we specifically sought population data that reflect the incidence of chronic postoperative pain or predictors (medical, physiologic, and psychologic) of chronic pain. We selected five groups of surgeries (limb amputations, breast surgery, gallbladder surgery, lung surgery, and inguinal hernia surgery). These surgeries were selected because the incidence of pain is known to be high, thus improving the probability of detecting predictive factors. They also represent a range of major surgical procedures.
Projection Based M-Estimators

Random Sample Consensus (RANSAC) is the most widely used robust regression algorithm in computer vision. However, RANSAC has a few drawbacks which make it difficult to use for practical applications. Some of these problems have been addressed through improved sampling algorithms or better cost functions, but an important difficulty still remains. The algorithm is not user independent, and requires knowledge of the scale of the inlier noise. We propose a new robust regression algorithm, the projection based M-estimator (pbM). The pbM algorithm is derived by building a connection to the theory of kernel density estimation and this leads to an improved cost function, which gives better performance. Furthermore, pbM is user independent and does not require any knowledge of the scale of noise corrupting the inliers. We propose a general framework for the pbM algorithm which can handle heteroscedastic data and multiple linear constraints on each data point through the use of Grassmann manifold theory. The performance of pbM is compared with RANSAC and M-Estimator Sample Consensus (MSAC) on various real problems. It is shown that pbM gives better results than RANSAC and MSAC in spite of being user independent.
Analysis of Photovoltaic Cell Performance with Varying Temperature: the Case of South India

2 Abstract: Solar energy is one of the important renewable energy available. The efficient usage of solar energy can yield better power output which can be used as an alternate fuel for conventional energy sources. The Photovoltaic cells are used to generate power from solar energy. In this paper we have dealt with the modelling and analysis of photovoltaic cells with varying temperature values of different cities in south India. The photovoltaic cell is modelled and analysed for its performance using MATLAB/Simulink. The mathematical modelling of photovoltaic cell is done by simulating the equivalent circuit design. The generalized photovoltaic model is used for the analysis. The current and voltage curve are generated as a result of simulation. The south Indian cities taken for comparison are Coimbatore, Bangalore, Erode and Vellore. The temperature values of the above mentioned places were used in the form of monthly averaged basis.
A neutron tomography study of the Seymchan pallasite

The internal structure of an olivine‐rich fragment of the Seymchan meteorite was studied using neutron tomography. The differences in the neutron attenuation coefficients of constituent elements of the studied pallasite and the application of modern mathematical algorithms for a three‐dimensional (3‐D) imaging data analysis allow us to obtain a spatial distribution of different meteorite components. The heterogeneous distribution of the nickel in the metal phase was observed. In addition to the resulting 3‐D model of the Seymchan meteorite, the distributions of the volumes, average sizes, and shape‐related parameters of the FeNi metal component and olivine grains were obtained.
Dynamic Properties of Firoozkooh Sand-Silt Mixtures

A series of undrained resonant column, monotonic and cyclic triaxial tests was performed to investigate the effects of non-plastic fines on the dynamic properties of Firoozkooh sand. Specimens of sand-silt mixtures were prepared at different densities, and tested under various confining pressures. Test results revealed that shear modulus decreases with fines, and increases with relative density and confining pressure. Normalized shear modulus is not affected by fines, relative density and confining pressure, while damping ratio is affected by fines and confining pressure. Finally, field cyclic resistance ratios versus normalized shear wave velocity values are developed on the basis of cyclic triaxial and resonant column tests.
Pattern-based segmentation of digital documents: model and implementation

Angelo Di Iorio received a PhD in Computer Science from the University of Bologna, Italy. The title of his thesis is "Pattern-based Segmentation of Digital Documents: Model and Implementation". His research cover markup-languages, collaborative authoring, document versioning, content analysis and (re-)formatting, e-learning, and semantic web technologies. His interests have recently been extended towards layout languages and algorithms.
The Importance of Worker Reputation Information in Microtask-Based Crowd Work Systems

This paper presents the first systematic investigation of the potential performance gains for crowd work systems, deriving from available information at the requester about individual worker reputation. In particular, we first formalize the optimal task assignment problem when workers’ reputation estimates are available, as the maximization of a monotone (submodular) function subject to Matroid constraints. Then, being the optimal problem NP-hard, we propose a simple but efficient greedy heuristic task allocation algorithm. We also propose a simple “maximum a-posteriori” decision rule and a decision algorithm based on message passing. Finally, we test and compare different solutions, showing that system performance can greatly benefit from information about workers’ reputation. Our main findings are that: i) even largely inaccurate estimates of workers’ reputation can be effectively exploited in the task assignment to greatly improve system performance; ii) the performance of the maximum a-posteriori decision rule quickly degrades as worker reputation estimates become inaccurate; iii) when workers’ reputation estimates are significantly inaccurate, the best performance can be obtained by combining our proposed task assignment algorithm with the message-passing decision algorithm.
Vascular Endothelial Function Related to Cardiac Surgery

regulating vascular tone, preventing platelet aggregation, anti-proliferation etc. All these functions are important in physiological and pathophysiological status. The regulation of vascular tone – the endothelium-dependent relaxation is mediated by three endothelium-derived relaxing factors (EDRFs) – nitric oxide (NO), prostacyclin (PGI 2 ), and an unidentifi ed endotheliumderived hyperpolarizing factor (EDHF).
How fast is fisheries-induced evolution? Quantitative analysis of modelling and empirical studies

A number of theoretical models, experimental studies and time‐series studies of wild fish have explored the presence and magnitude of fisheries‐induced evolution (FIE). While most studies agree that FIE is likely to be happening in many fished stocks, there are disagreements about its rates and implications for stock viability. To address these disagreements in a quantitative manner, we conducted a meta‐analysis of FIE rates reported in theoretical and empirical studies. We discovered that rates of phenotypic change observed in wild fish are about four times higher than the evolutionary rates reported in modelling studies, but correlation between the rate of change and instantaneous fishing mortality (F) was very similar in the two types of studies. Mixed‐model analyses showed that in the modelling studies traits associated with reproductive investment and growth evolved slower than rates related to maturation. In empirical observations age‐at‐maturation was changing faster than other life‐history traits. We also found that, despite different assumption and modelling approaches, rates of evolution for a given F value reported in 10 of 13 modelling studies were not significantly different.
Cell-Share: Opportunistic Use of Cellular Uplink to Augment Rural WiFi Mesh Networks

The Internet has revolutionized communication, ed- ucation, commerce and information access for its users world- wide. Unfortunately, the lack of copper/fiber infrastructure in the rural areas of the developing world has prevented a large majority of the human population from reaping the benefits of the Internet. While the number of mobile subscribers in the developing world has more than quadrupled in the last five years, the adoption of the Internet has shown a slow growth pattern. Recently, there has been a growing interest in providing Internet access to rural areas by means of inexpensive long distance WiFi mesh networks. However, the expensive Internet uplink and the difficulty in troubleshooting of WiFi mesh networks has hindered their large scale deployment. In this paper, we propose Cell- Share - an architecture that leverages the explosive growth in cellular network penetration in the developing world to provide rural WiFi mesh networks with an on-demand scalable Internet uplink and troubleshooting back-channel using a collaborative mobile phone framework. We implement Cell-Share on Windows Mobile and Android platforms to demonstrate the feasibility of using the infrastructure of cellular data networks to provide a back-channel for network troubleshooting as well as capacity enhancement for rural mesh networks. I. INTRODUCTION The information and communication infrastructure of any region plays a pivotal role in its socio-economic development and can be regarded as one of its greatest assets. With rapid advances in the field of communication technology and infor- mation access over the past few decades, the world has entered the communications age. The growth of the Internet has played an integral role in this information revolution. Unfortunately, this revolution contributed in the development of only a small portion of the human population, confined to the contemporary developed economies of the world and the urban areas of the developing nations, resulting in a "digital divide". A vast majority of the people living in the rural areas of developing and under-developed nations have yet to take advantage of the Internet revolution. Figure 1 highlights the disparity in the availability of electricity, fixed-telephone service and some form of public Internet facility in the village communities of the world, as estimated by the International Telecommunica- tion Union (ITU) - a United Nations agency for Information and Communication Technology (ICT) issues (11).
Analysing patient factors and treatment impact on diabetic foot ulcers in South Africa

In the South African public healthcare sector, 28% of diabetic patients present to primary healthcare clinics with diabetic foot ulcers (DFUs), often presenting in advanced stages of ulcer severity. In this study, we aimed to categorise factors predisposing individuals to developing a DFU and to identify the potential shortcomings in existing treatment plans in the South African healthcare system. In addition, the use of preventative measures in the management of DFUs was examined as well as the influence of past treatment practices. A total minimum sample size of 50 DFUs was required for this study. Participants who were selected for this study had their past records reviewed in order to determine the likelihood of previous DFU infections, as well as to determine the occurrence of co-morbidities. The treatment protocol implemented was recorded. Twelve-month patient records were used to identify the infection frequency and past treatment protocols. A total of 48.9% of patients reported that they did not make use of any preventative measures. The most frequent concurrent medical conditions were hypertension, dyslipidaemia, and peripheral neuropathy. Polypharmacy was prevalent, with 55% of the population prescribed five or more medications. Potential medication interactions were examined and a total of 210 interactions were documented. An analysis of past and current treatment practices revealed that 52.1% of the treatment protocols did not comply with local treatment guidelines. This study highlights the urgent need for updated DFU treatment protocols in relation to the overall management of DFUs, taking into account existing international guidelines.
PSYCHOLOGICAL MEDICINE

D. BROAD BENT, Oxford w. F. BYNUM, London A. CARLSSON, Gothenburg T. j . CROW, Harrow s. GARATTINI , Milan D. GRAHAME-SMITH, Oxford j . A. GRAY, London H. HAFNER, Mannheim R. A. HINDE, Cambridge EDITORIAL BOARD A. JABLENSKY, Sofia A. L. JOHNSON, Cambridge M. LADER, London p. L. LANTOS, London A. LAWSON, London w. A. LISHMAN, London M. MARMOT, London c. D. MARSDEN, London P. R. McHUGH, Baltimore D. PLOOG, Munich L. N. ROBINS, 5/ Louis G. F. RUSSELL, London M. L. RUTTER, London j . R. SMYTHIES, London p. VENABLES, York J. K. WING, London M.WYKE, London
Modeling of Tamper Resistance to Electromagnetic Side-channel Attacks on Voltage-scaled Circuits

The threat of information leakage by Side-Channel Attacks (SCAs) using ElectroMagnetic (EM) leakage is becoming more and more prominent for crypto circuits. This paper models tamper resistance to EM SCAs on voltage-scaled crypto circuits. It is well known that if the supply voltage is donwscaled, attackers need to acquire more EM traces to extract secret key information in crypto circuits. Therefore, crypto circuits can process more data safely. However, their supply voltage dependence is not fully studied. This paper thus firstly models voltage dependence of the strength in the EM emission from crypto circuits. Then, this paper proposes the tamper resistance model which analytically expresses the relationship between the supply voltage and the minimum traces to disclosure based on test vector leakage assessment. This helps consider to optimize the trade-off relationship between encryption performance and tamper resistance to the information leakage. The proposed models are validated by measurement results using an Advanced Encryption Standard (AES) circuit with a 180-nm process technology.