Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of high molecular weight compounds in urban atmospheric particles

Abstract. The chemical nature of a large mass fraction of ambient organic aerosol particles is not known. High molecular weight compounds (often named humic-like substances) have recently been detected by several authors and these compounds seem to account for a significant fraction of the total organic aerosol mass. Due to the unknown chemical structure of these compounds quantification as well as a determination of their molecular weight is difficult. In this paper we investigate water soluble humic-like substances in ambient urban aerosol using size exclusion chromatography-UV spectroscopy and laser desorption/ionization mass spectrometry (LDI-MS). LDI-MS was used for the first time to investigate HULIS from atmospheric aerosols. A careful evaluation of the two method shows that both methods complement each other and that both are needed to learn more about the molecular weight distribution and the concentration of humic-like substances. An upper molecular weight limit of humic-like substances of about 700 Da and a concentration of 0.3-1.6 µg/m3 air can be estimated, corresponding to 9-30% of the total organic carbon for an urban background site.
Semen quality of 1346 healthy men, results from the Chongqing area of southwest China.

BACKGROUND Large studies on semen quality of the general healthy population from China are rare. METHODS A cross-sectional study was performed to evaluate the semen quality of 1346 healthy men residing in Chongqing area of southwest China in 2007. The semen parameters were measured and compared with the World Health Organization (WHO) criteria. A linear regression model was used to examine the determinants of semen quality. RESULTS The medians were 2.3 ml for semen volume, 77.8 x 10(6) per ml for semen concentration, 167.7 x 10(6) for total sperm count, 33% for sperm rapid progressive motility, 52.6% for sperm progressive motility and 70.9% for total motility. According to WHO criteria, 61.1% of healthy males had at least one semen parameter below normal threshold values. Season and abstinence duration were found to be significantly associated with semen quality (P < 0.001). Age, smoking, alcohol use and BMI had little or no effect on semen parameters. CONCLUSIONS A high proportion of healthy males in Chongqing area of southwest China had abnormal semen parameters values according to WHO criteria. The semen parameters in the study population were markedly different from those reported for the other Chinese, USA and European populations. The differences remain unexplained and may be due to demographic characteristics, lifestyle, environmental factors or genetic variation.
Software Fault Prediction Model for Embedded Systems : A Novel finding

Software testing plays a vital role in software development especially when the software developed is mission, safety and business critical applications. Software testing is the most time consuming and costly phase. Prediction of a modules info fault-prone and non fault prone prior to testing is one of the cost effective technique. Predicting a safe module as faulty increases the cost of projects by more cautious and better-test resources allocation for those modules, whereas prediction of faulty code as fault free code end up in under-preparation and may leave modules untested this may cause accidental failure and lead towards massive loss . In this research, we present a novel fault prediction technique that reduces the probability of false alarm (pf) and increases the precision for detection of faulty modules. The general expectation from a predictor is to get very high probability of false alarm (pf) to get more reliable and quality software product. We have taken embedded systems software for this study and the goal is to predict as many faulty modules as possible. In this paper we apply a supervised discretization for pre-processing and clustering based classification for prediction of a modules info fault-prone (fp) and non faultprone (nfp) modules. To evaluate this approach we perform an extensive comparative experimental study for the effectiveness of our method with benchmark results for the same embedded software’s. Our fault prediction model produces better results than the standard and benchmark approaches for software fault prediction. Results from our proposed model significantly decreases probability of false alarm (pf) down to 9% while increasing precision and balance rates at 68% and 79% respectively.
Novel two-stage algorithm for non-parametric cast shadow recognition

Environment perception and scene understanding is an important issue for modern driver assistance systems. However, adverse weather situations and disadvantageous illumination conditions like cast shadows have a negative effect on the proper operation of these systems. In this paper, we propose a novel approach for cast shadow recognition in monoscopic color images. In a first step, shadow edge candidates are extracted evaluating binarized channels in the color-opponent and perceptually uniform CIE L*a*b* space. False detections are rejected in a second verification step, using SVM classification and a combination of meaningful color features. We introduce a non-parametric representation for complex shadow edge geometries that enables utilizing shadow edge information for improving downstream vision-based driver assistance systems. A quantitative evaluation of the classification performance as well as results on multiple real-world traffic scenes show a reliable cast shadow recognition with only a few false detections.
Finding Alternative Shortest Paths in Spatial Networks

Shortest path query is one of the most fundamental queries in spatial network databases. There exist algorithms that can process shortest path queries in real time. However, many complex applications require more than just the calculation of a single shortest path. For example, one of the common ways to determine the importance (or price) of a vertex or an edge in spatial network is to use Vickrey pricing, which intuitively values the vertex <i>v</i> (or edge <i>e</i>) based on how much harder for travelling from the sources to the destinations without using <i>v</i> (or <i>e</i>). In such cases, the <i>alternative shortest paths</i> without using <i>v</i> (or <i>e</i>) are required. In this article, we propose using a precomputation based approach for both single pair alternative shortest path and all pairs shortest paths processing. To compute the alternative shortest path between a source and a destination efficiently, a naïive way is to precompute and store all alternative shortest paths between every pair of vertices avoiding every possible vertex (or edge), which requires <i>O</i>(<i>n</i><sup>4</sup>) space. Currently, the state of the art approach for reducing the storage cost is to choose a subset of the vertices as center points, and only store the single-source alternative shortest paths from those center points. Such approach has the space complexity of <i>O</i>(<i>n</i><sup>2</sup> log <i>n</i>). We propose a storage scheme termed <i>iSPQF</i>, which utilizes shortest path quadtrees by observing the relationships between each avoiding vertex and its corresponding alternative shortest paths. We have reduced the space complexity from the naïive <i>O</i>(<i>n</i><sup>4</sup>) (or the state of the art <i>O</i>(<i>n</i><sup>4</sup> log <i>n</i>)) to <i>O</i>(min(<i>γ, L</i>)<i>n</i><sup>1.5</sup>) with comparable query performance of <i>O</i>(<i>K</i>), where <i>K</i> is the number of vertices in the returned paths, <i>L</i> is the diameter of the spatial network, and <i>γ</i> is a value that depends on the structure of the spatial network, which is empirically estimated to be 40 for real road networks. Experiments on real road networks have shown that the space cost of the proposed iSPQF is scalable, and both the algorithms based on iSPQF are efficient.
Sequences of Homologous β-Lactamases from Clinical Isolates of Serratia marcescens with Different Substrate Specificities

ABSTRACT Genes for two group 1 β-lactamases, SRT-1 and SST-1, were sequenced. These β-lactamases were produced by clinical isolates ofSerratia marcescens, isolates GN16694 and GN19450, respectively. The resulting enzymes were 96% identical. SRT-1 hydrolyzed oxyimino cephalosporins, but SST-1 hardly hydrolyzed them. At residue 213 in the third motif, which is conserved among group 1 β-lactamases, SRT-1 and SST-1 had Lys and Glu, respectively. By site-directed mutagenesis, the substitution of Glu by Lys at residue 213 in SST-1 resulted in an enzyme that hydrolyzed oxyimino cephalosporins.
SIP server security with TLS: Relative performance evaluation

VoIP (Voice over Internet) provides delivery of voice information over unsecured IP-based networks like the Internet. VoIP data, signaling and voice, needs to be secured in such an environment. Security mechanisms take their toll on VoIP system performance. SIP is dominant signaling protocol for VoIP. This paper measures relative decrease in VoIP performance of system with secured SIP signaling over one without it. It compares SIP with authentication enabled over three transport protocols: UDP, TCP and TLS. Peak throughput of concurrent calls, registration request delay, session request delay, SIP server CPU and RAM usage are measured. Testbed environment consists of Asterisk IP private branch exchange (PBX) as a part of Elastix server, several SIP user agents and SIPp traffic generator. Test results show that performance of SIP over TLS based signaling is four times lower than the SIP signaling over UDP in most metrics.
A retrospective clinical study of 98 adult idiopathic primary intraventricular hemorrhage cases

AbstractThe aim of the study is to define the clinical features, risk factors, treatment and prognosis of idiopathic primary intraventricular hemorrhage (IPIVH). We retrospectively collected the data of consecutively admitted patients who were diagnosed and treated for IPIVH in our hospital from January 2010 to December 2014. The clinical information, treatment, and prognosis at the 6-month follow-up were analyzed.Among the 3798 cases of spontaneous intracranial hemorrhage (ICH), 98 IPIVH (2.58%) patients were recruited for the study. The study population consisted of 60 males and 38 females, with an average age (± standard deviation, SD) of 51.20 ± 15.48 years. The initial symptoms were headache (75 cases) and impaired consciousness (23 cases). The surgical treatments included hematoma evacuation under a microscope or an endoscope in 8 cases (8.16%), external ventricular drainage (EVD) in 11 cases (11.22%), lumbar drainage (LD) in 10 cases (10.20%), and a combination of EVD and LD in 11 cases (11.22%). In total, 4 patients died in the hospital (4.08%). At the 6-month follow-up, 73 patients (74.49%) had an improved outcome (modified Rankin scale [mRS] < 3), and 21 patients (21.43%) had a poor outcome (mRS ≥ 3 points) at the end of the 6-month follow-up.IPIVH is rare in clinical practice, and hypertension is the most common risk factor. Furthermore, the treatment of IPIVH is still controversial. Hematoma evacuation under a microscope or an endoscope, EVD, LD and a combination of EVD and LD could be surgical options for the treatment of IPIVH patients. The outcomes for IPIVH patients could be relatively favorable with individualized treatment.
Low Rates of Repeat HIV Testing Despite Increased Availability of Antiretroviral Therapy in Rural Tanzania: Findings from 2003–2010

Background HIV counselling and testing (HCT) services can play an important role in HIV prevention by encouraging safe sexual behaviours and linking HIV-infected clients to antiretroviral therapy (ART). However, regular repeat testing by high-risk HIV-negative individuals is important for timely initiation of ART as part of the ‘treatment as prevention’ approach. Aim To investigate HCT use during a round of HIV serological surveillance in northwest Tanzania in 2010, and to explore rates of repeat testing between 2003 and 2010. Methods HCT services were provided during the fourth, fifth and sixth rounds of serological surveillance in 2003–2004 (Sero-4), 2006–2007 (Sero-5) and 2010 (Sero-6). HCT services have also been available at a government-run health centre and at other clinics in the study area since 2005. Questionnaires administered during sero-surveys collected information on socio-demographic characteristics, sexual behaviour and reported previous use of HCT services. Results The proportion of participants using HCT increased from 9.4% at Sero-4 to 16.6% at Sero-5 and 25.5% at Sero-6. Among participants attending all three sero-survey rounds (n = 2,010), the proportions using HCT twice or more were low, with 11.1% using the HCT service offered at sero-surveys twice or more, and 25.3% having tested twice or more if reported use of HCT outside of sero-surveys was taken into account. In multivariable analyses, individuals testing HIV-positive were less likely to repeat test than individuals testing HIV-negative (aOR 0.17, 95% CI 0.006–0.52). Discussion/Conclusions Although HCT service use increased over time, it was disappointing that the proportions ever testing and ever repeat-testing were not even larger, considering the increasing availability of HCT and ART in the study area. There was some evidence that HIV-negative people with higher risk sexual behaviours were most likely to repeat test, which was encouraging in terms of the potential to pick-up those at greatest risk of HIV-infection.
Vehicle pose detection using region based convolutional neural network

In recent years, category-level object detection has gained a lot of attention. In addition to object localization, estimation of the object pose has practical applications in intelligent transportation, autonomous driving and robotics. Parts based models have been used for pose estimation in recent years, but these models depend on manual supervision or require a complex algorithm to locate the object parts. In this work, we have used Convolutional Neural Network for the pose estimation of vehicle in an image. The advantage of multiple classifications of objects at the same time motivates us to choose the convolutional neural network. We make use of state-of-the-art implementation of convolution neural network named the Region Based Convolutional Neural Network(FASTER-RCNN) for estimating the pose of vehicle. We annotate the comprehensive cars dataset of Stanford, required for training the model and upon testing we have achieved good results with good accuracy.
Exact Relaxation for Classes of Minimization Problems with Binary Constraints

Relying on the co-area formula, an exact relaxation framework for minimizing objectives involving the total variation of a binary valued function (of bounded variation) is presented. The underlying problem class covers many important applications ranging from binary image restoration, segmentation, minimal compliance topology optimization to the optimal design of composite membranes and many more. The relaxation approach turns the binary constraint into a box constraint. It is shown that thresholding a solution of the relaxed problem almost surely yields a solution of the original binary-valued problem. Furthermore, stability of solutions under data perturbations is studied, and, for applications such as structure optimization, the inclusion of volume constraints is considered. For the efficient numerical solution of the relaxed problem, a locally superlinearly convergent algorithm is proposed which is based on an exact penalization technique, Fenchel duality, and a semismooth Newton approach. The paper ends by a report on numerical results for several applications in particular in mathematical image processing.
The effect of radiative cooling on the X-ray properties of galaxy clusters

ABSTRA C T In this paper, we investigate the effect of cooling on the X-ray properties of galaxy clusters. We have performed N-body, hydrodynamical simulations both with and without the effects of radiative cooling, but neglecting the effects of star formation and feedback. We show that radiative cooling produces an inflow of high-entropy gas from the outer parts of the cluster, thus raising the cluster temperature and decreasing the X-ray luminosity. With radiative cooling clusters are on average from three to five times less luminous in X-rays than the same clusters simulated without cooling. However, we do not produce a large constantdensity core in either the gas or the dark matter distributions. Our results contradict previous work in which cooling raises the X-ray luminosity and deposits an unreasonably large amount of mass in the central cluster galaxy. We achieve this by selecting our numerical resolution in such a way that a reasonable fraction of the baryonic material cools and by decoupling the hot and cold gas in our simulations, a first step towards modelling multiphase gas. We emphasize that globally cooling a sensible amount of material is vital and the presence or absence of massive central concentrations of cold baryonic material has a dramatic effect upon the resultant X-ray properties of the clusters.
Modelling of nitrate and ammonium-containing aerosols in presence of sea salt

A thermodynamical model for treatment of gas/aerosol partitioning of semi volatile inorganic aerosols has been implemented in a global chemistry and aerosol transport model (Oslo CTM2). The sulphur cycle and sea salt particles have been implemented earlier in the Oslo CTM2 and the focus of this study is on nitrate partitioning to the aerosol phase and if particulate nitrate is expected to form in fine or coarse mode aerosols. Modelling of the formation of fine mode nitrate particles is complicated since it depends on other aerosol components and aerosol precursors as well as meteorological condition. The surface concentrations from the model are compared to observed surface concentrations at around 20 sites around Europe for nitrate and ammonium. The agreement for nitrate is good but the modelled values are somewhat underestimated compared to observations at high concentrations, whereas for ammonium the agreement is very good. However, we underscore that such a comparison is not of large importance for the aerosol optical depth of particulate nitrate since the vertical profile of aerosol components and their precursors are so important. Fine mode nitrate formation depends on vertical profiles of both ammonia/ammonium and sulphate. The model results show that fine mode particulate nitrate play a non-negligible role in the total aerosol composition in certain industrialized regions and therefore have a significant local radiative forcing. On a global scale the aerosol optical depth of fine mode nitrate is relatively small due to limited availability of ammonia and loss to larger sea salt particles. Inclusion of sea salt in the calculations reduces the aerosol optical depth and burden of fine mode nitrate by 25% on a global scale but with large regional variations.
Efficient use of signal-free samples for DOA estimation and detection in colored noise

In a typical array processing scenario, noise acting on the array can not be assumed spatially white. It is in many cases necessary to use quiet periods, when only noise is received, to estimate the noise covariance. If estimation of the signal parameters, such as directions of arrivals (DOAs), and noise covariance is performed jointly, performance can be improved. This is especially true when stationarity considerations limit the amount of available, valid noise-only data. This is shown in an earlier work, together with the introduction of an optimal weighting for weighted subspace fitting (WSF), when based on whitened data. An asymptotically valid approximative maximum likelihood method (AML) for the DOA estimation problem is derived in this paper. The resulting criterion can be concentrated with respect to the signal parameters. In numerical experiments, AML shows very promising small-sample performance compared to earlier methods. The associated criterion function is well suited for numerical optimization and allows for the development of a novel, MODE-like, non-iterative estimation procedure if the array belongs to the important class of uniform linear arrays. This non-iterative resulting procedure retains the asymptotic properties of maximum likelihood, and numerical simulations indicate superior threshold performance when compared to an optimally weighted WSF formulation of MODE. For the detection problem, no method has been presented that takes the unknown noise covariance into account. Here, a well known detection scheme for WSF is extended to work in this scenario as well. The derivations of this scheme further stress the importance of correctly weighting WSF when the noise covariance is unknown. It is also shown that the minimum value of the criterion function associated with AML can be used for the detection purpose. Numerical experiments indicate promising performance for the AML-detection scheme
Race, gender, and class in entrepreneurship: intersectional counterframes and black business owners

ABSTRACT Entrepreneurship is often touted as an economic opportunity that embodies American ideals of individualism and financial gain. Yet social scientists have long noted divergent entrepreneurial outcomes among various groups. In this paper, we consider how race informs entrepreneurship for minority business owners. In particular, we focus on the ways black entrepreneurs use racial counterframes as a means of defining various aspects of the entrepreneurial experience. Furthermore, we introduce the concept of intersectional counterframes to show how black entrepreneurs understand business ownership as a response to categories that interact with not only to race, but other social group categories as well, such as gender. We argue here that these business owners use both counterframes to construct entrepreneurship not simply as a potential pathway to economic stability, but perhaps more importantly, as a response to existing inequality.
Non-linear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation

We explore and compare the performances of two non-linear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM (CDM: cold dark matter) cosmologies. The first model is the well known Q model, first applied in the analysis of Two-degree Field Galaxy Redshift Survey data. The second, the P model, is inspired by the halo model, in which non-linear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while the two models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalization, a technique sometimes used in the marginalization of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended non-linear correction model also because of its physical transparency.