Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous monitoring of the boundary-layer top with lidar

Continuous lidar observations of the top height of the boundary layer (BL top) have been performed at Leipzig (51.3° N, 12.4° E), Germany, since August 2005. The results of measurements taken with a compact, automated Raman lidar over a one–year period (February 2006 to January 2007) are presented. Main goals of the study are (a) to demonstrate that BL top monitoring with lidar throughout the year is possible, (b) to present the required data analysis method that permits an automated, robust retrieval of BL top at all weather situations, and (c) to use this opportunity to compare the lidar-derived BL top data with respective BL tops hourly predicted by the regional weather forecast model COSMO. Four different lidar methods for the determination of the BL top are discussed. The wavelet covariance algorithm is modified so that an automated retrieval of BL depths from lidar data is possible. Three case studies of simultaneous observations with the Raman lidar, a vertical-wind Doppler lidar, and accompanying radiosonde profiling of temperature and humidity are presented to compare the potential and the limits of the four lidar techniques. The statistical analysis of the one-year data set reveals that the seasonal mean of the daytime (about 08:00–20:00 Local Time, LT) maximum BL top is 1400 m in spring, 1800 m in summer, 1200 m in autumn, and 800 m in winter at the continental, central European site. BL top typically increases by 100–300 m per hour in the morning of convective days. The comparison between the lidar-derived BL top heights and the predictions of COSMO yields a general underestimation of the BL top by about 20% by the model.
Building Roof Plane Extraction from LIDAR Data

This paper presents a new segmentation technique to use LIDAR point cloud data for automatic extraction of building roof planes. The raw LIDAR points are first classified into two major groups: ground and non-ground points. The ground points are used to generate a 'building mask' in which the black areas represent the ground where there are no laser returns below a certain height. The non-ground points are segmented to extract the planar roof segments. First, the building mask is divided into small grid cells. The cells containing the black pixels are clustered such that each cluster represents an individual building or tree. Second, the non-ground points within a cluster are segmented based on their coplanarity and neighbourhood relations. Third, the planar segments are refined using a rule-based procedure that assigns the common points among the planar segments to the appropriate segments. Finally, another rule-based procedure is applied to remove tree planes which are generally small in size and randomly oriented. Experimental results on three Australian sites have shown that the proposed method offers high building detection and roof plane extraction rates.
Young's Modulus and Degree of Conversion of Different Combination of Light-Cure Dental Resins

Objectives: To evaluate Young's modulus and degree of conversion of several combinations of bisGMA, UEDMA, TEGDMA light-cure dental resin. Methods: Young's modulus and DC% were studied for 21 different resin combinations of bisGMA, TEGDMA and UEDMA. Small universal testing machine and photo-calorimetry were used for the tests. The results were evaluated using ANOVA and Duncan's multiple range tests and regular t-test. Results: Young's modulus varied between 2.37±0.2 GPa (100% TEGDMA) and 4.15±0.2 GPa (100% bisGMA). By adding TEGDMA to bisGMA or UEDMA, the Young's modulus decreased significantly (p<0.05). Degree of conversion was significantly (p<0.05) higher when the wt% of TEGDMA was high in the mixtures than for highly concentrated bis-GMA (resin mixtures with TEGDMA in comparison to mixture with bisGMA had higher degree of conversion). DC% was significantly higher (p<0.05) for binary mixtures of UEDMA and TEGDMA, and significantly lower for 100 wt% bis-GMA (p<0.05). The DC% values were between 53.1%±0.9% (100% bisGMA) and 85.6%±1% (80% UEDMA-20% TEGDMA). The concentration of bisGMA, in the monomer mixture, affected DC% and Young's modulus oppositely. Conclusions: The differences in the values for DC% were mostly justified by the differences in the molecular structures of the different monomers. It was also revealed that higher DC% does not always result in a higher Young's modulus, because molecular and network structural parameters play major roles in the final physical properties of the mixtures.
Runtime Model Recommendation for Exemplar-based Object Detection

We present an approach for object instance detection that uses model recommendation to predict a subset of relevant exemplar models for object detection based on an testing image at runtime. An initial subset of randomly selected exemplar models, the probe set, is first applied to the testing image, and its responses are used, in conjunction with a rating matrix, to predict the responses of all the exemplar models. The subset of exemplar models predicted to score the highest is then applied to the testing image to generate the final detections. This method enables scaling up the number of exemplar models to capture large object appearance variability, while maintaining computational efficiency. We present a novel max-selection scheme that allows us to build the rating matrix in a weakly-supervised fashion, allowing us to leverage large amounts of data easily. In addition to computational efficiency, we present experimental results which demonstrate that this model recommendation approach can outperform a baseline in which all the exemplar models are evaluated on the testing image.
ScreenStealer: Addressing Screenshot attacks on Android devices

Smartphones are ubiquitous in today's world. With the enhanced and advanced functionalities, smartphones carry a large amount of user's private and confidential data. There are numerous risks, threats, and the rise in powerfulness and effectiveness of malware attacks make smartphones more prone and vulnerable. Due to the rapid increase in Android smartphones users, demands based on new and advanced features as well as the usage ease have been lavished on developers. The Android application developers are working hard to develop innovative applications for millions of Android users around the world. In this struggle of advancement, they are seeking permissions to critical system resources, not directly offered by Android. One of the most projecting way is through ADB (Android Debug Bridge) that has been granted permissions to use critical system resources. There are many applications on Google Play Store that utilize ADB proxy to provide users with unconventional and smart features on smartphones. This paper reviews the ADB capabilities and how Internet access and ADB together allow applications to expose sensitive data of an Android smartphone device. Furthermore, a malicious Android application, `ScreenStealer', has been developed and its effects on Android-based smartphones are studied.
Public school secretaries: hearts of gold, voices of reason

Social scientists have referred to secretaries as invisible and government agencies have described the job classification as non-regulated. One segment of this job classification, public school secretary, could very well be described as nonexistent. However, anyone who has ever visited a public school in the state of Iowa has probably met the school secretary. She has been described as the woman in the principal's office and frequently she has been indirectly, and sometimes directly, assigned to manage the school. Yet, as a group, these public school employees have been ignored by the leaders in educational research and policy study. Fortunately, these women have been missing in an abstract sense. If the public school secretary was suddenly eliminated in reality, public school administrators would protest in the streets. In this study I have reached out to the school secretaries of Iowa and offered them an opportunity to discuss their views regarding their roles in our public schools. I have reported demographic information and the personal perceptions of 147 public school secretaries. These women have represented the smallest and largest school districts in the state. I provided members of this large group with an opportunity to raise their voices. I interviewed and corresponded with eighteen volunteers and of that group, I focused more closely on six women who work in settings that represent a majority of the schools in Iowa. Through their stories and personal narratives, a picture of this woman, the public school secretary, has emerged.
Applying statistical rock physics and seismic inversions to map lithofacies and pore fluid probabilities in a North Sea reservoir.

Summary Reliably predicting lithologic and saturation heterogeneities is one of the key problems in reservoir characterization. In this study we show how statistical rock physics techniques combined with seismic information can be used to classify reservoir lithologies and pore fluids. One of the innovations was to use a new seismic impedance attribute (related to VP/VS ratio) that incorporates far-offset data, but at the same time can be practically obtained using normal incidence inversion algorithms. The methods were applied to a North Sea turbidite system. We incorporated well log measurements with calibration from core data to estimate the near and far-offset reflectivity and impedance attributes. Multivariate probability distributions were estimated from the data to identify the attribute clusters and their separability for different facies and fluid saturations. A training data was set up using Monte Carlo simulations based on the well log derived probability distributions. Fluid substitution b y Gassmann’s equation was used to extend the training data, thus accounting for pore fluid conditions not encountered in the well. Seismic inversion of near offset and far offset stacks gave us two 3-D cubes of impedance attributes in the interwell region. The near offset stack approximates a zero offset section giving an estimate of the normal incidence acoustic impedance (rV). The far offset stack gives an estimate of a VP/VS related elastic impedance attribute that is equivalent to the acoustic impedance for non-normal incidence. These impedance attributes obtained from seismic inversion were then used with the training probability distribution functions to predict the probability of occurrence of the different lithofacies in the interwell region. Simple statistical classification techniques, as well as geostatistical indicator simulations were applied on the 3-D seismic data cube. A Markov-Bayes technique was used to update the probabilities obtained from the seismic data by taking into account the spatial correlation as estimated from the facies indicator variograms. The final results are spatial 3-D maps of not only the most likely facies and pore fluids, but also their occurrence probabilities. A key ingredient in this study was the exploitation of physically-based seismic-toreservoir properties transforms optimally combined with statistical techniques.
APPLICATION OF A TAGUCHI-BASED NEURAL NETWORK FOR FORECASTING AND OPTIMIZATION OF THE SURFACE ROUGHNESS IN A WIRE-ELECTRICAL-DISCHARGE MACHINING PROCESS UPORABA TAGUCHIJEVE NEVRONSKE MRE@E ZA NAPOVEDOVANJE IN OPTIMIRANJE POVR(INSKE HRAPAVOSTI PRI POSTOPKU @I^NE EROZIJE

Wire-electrical-discharge machining (WEDM) is a modification of electro-discharge machining (EDM) and has been widely used for a long time for cutting punches and dies, shaped pockets and other machine parts on conductive materials. WEDM erodes workpiece materials by a series of discrete electrical sparks between the workpiece and an electrode flushed or immersed in a dielectric fluid. The WEDM process is particularly suitable for machining hard materials as well as complex shapes. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the surface roughness in a WEDM process. A back-propagation neural network (BPNN) was developed to predict the surface roughness. In the development of a predictive model, machining parameters of open-circuit voltage, pulse duration, wire speed and dielectric flushing pressure were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the surface roughness (Ra). Finally, the Taguchi approach was applied to determine the optimum levels of machining parameters.
Will the German Debt Brake Succeed? Survey Evidence from State Politicians

The present paper analyzes expectations of German politicians about the German debt brake (Schuldenbremse), which became part of the German constitution in 2009. This fiscal rule requires the federal government and the German states to run a (cyclically adjusted) budget deficit of no more than 0.35% of GDP starting in 2016 and zero % starting in 2020, respectively. We use unique survey data from more than 630 politicians at the state level to systematically study the subjective beliefs in the compli-ance and desirability of the debt brake. We find that i) state politicians who belong to the coalition parties of the current federal government coalition believe more strongly in federal government compliance, ii) state politicians who belong to the party of the current state government believe more strongly in the own state s compliance, iii) worse state fiscal conditions and stronger beliefs in lack of credible enforcement of the debt brake lower the perceived likelihood of compliance, iv) there often is a large discrepancy in the assessed probability of compliance between politicians from the own state vs. politicians from other states, v) beliefs into the consequences of non-compliance with the debt brake are quite heterogeneous, and vi) politicians often find the debt brake more desirable than probable.
Factor structures of the Swedish Version of the RFIPC: Investigating the Validity of Measurements of IBD Patients’ Worries and Concerns

Background Worries and concerns of patients with IBD comprise an important negative factor in their HRQOL. The Rating Form of Inflammatory Bowel Disease Patient Concerns (RFIPC) was developed to describe the nature and degree of the worries and concerns of IBD patients. In the original version, the specific issues of worries are divided into four separate factors. These factors provide useful information about HRQOL and the kind of worries and concerns which are most important to the patient. However, the Swedish version of the RFIPC is often scored using a single sum score, implying that all the specific issues of worries stem from a single general worry factor. The aim of this study was to validate the factor structure of the Swedish version of the RFIPC. Methods A sample consisting of 195 patients with IBD filled out the RFIPC. Confirmatory factor analysis was performed to examine fit of three hypothesized models of factor structure. Spearman’s correlation and Mann-Whitney analysis were used to follow up the results. Results The single-factor model displayed poor fit indices. The four-factor model marked substantive improvement, but still remains inadequate. The final four-factor model permitting correlated error terms between some items displayed the most adequate fit. Conclusions The factorial structure of the RFIPC, as suggested in the original version, was able to be replicated with a slight modification in the Swedish version. The separate factors identified in this structure provide more detailed information about the worries and concerns of IBD patients as these components of worries are different related to HRQOL and general health.
Motivating parents of kids with asthma to quit smoking: the PAQS project.

The Parents of Asthmatics Quit Smoking (PAQS) project contrasts two theory-based smoking cessation interventions for parents of children with asthma, and compares mechanisms of behavior change within and across theoretical perspectives. We hypothesize that enhancing the perception of risk to self and child will motivate smoking cessation more than standard approaches that emphasize building self-efficacy and coping skills for quitting in a population that is largely not motivated to quit smoking. Smokers (n = 288) and their asthmatic children who receive nurse-delivered in-home asthma education (as part of the insurance carrier's standard of care) are randomized into one of two treatment conditions: (1) the Behavioral Action Model (BAM), in which nurses emphasize goal setting and skill building to enhance self-efficacy to quit smoking, or 2) the Precaution Adoption Model (PAM), in which nurses tailor the intervention to the smoker's readiness to quit and incorporate biomarker feedback [i.e. level of carbon monoxide exposure to the smoker and level of environmental tobacco smoke (ETS) exposure to the child] in order to increase risk perception in smokers. In both conditions, smokers who are ready to quit receive the nicotine patch. Analyses will examine (1) quit rates, ETS level and motivation to quit as the primary dependent variables, (2) mediators of behavior change between and within conditions, and (3) relations between parent smoking outcomes and child asthma morbidity (i.e. ER visits and asthma symptoms) post-treatment. Results will help tailor interventions to this population, and identify mechanisms of behavior change that result in adaptive health outcomes for smokers and their children who have asthma.
Compensating Printer Modulation Transfer Function in Spatial and Color Adaptive Rendering Workflows

Experiments have shown that the quality of printed images depends on the capacity of the printing system to accurately re- produce details. We propose to improve the quality by compensat- ing for the Modulation Transfer Function (MTF) of the printing system. The MTF of the printing system is measured using a mod- ified version of the method proposed by Jang and Allebach [1]. Then the MTF is adaptively compensated in the Fourier domain, depending on the frequency and on the local mean value. This compensation is included within our mathematical framework for Spatial and Color Adaptive Gamut Mapping Algorithms. Results of a category judgment experiment show significant improvement as the printed MTF compensated images obtain the best scores.
Dynamics of Two Picophytoplankton Groups in Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a Stochastic Advection-Reaction-Diffusion Model

A stochastic advection-reaction-diffusion model with terms of multiplicative white Gaussian noise, valid for weakly mixed waters, is studied to obtain the vertical stationary spatial distributions of two groups of picophytoplankton, i.e., picoeukaryotes and Prochlorococcus, which account about for 60% of total chlorophyll on average in Mediterranean Sea. By numerically solving the equations of the model, we analyze the one-dimensional spatio-temporal dynamics of the total picophytoplankton biomass and nutrient concentration along the water column at different depths. In particular, we integrate the equations over a time interval long enough, obtaining the steady spatial distributions for the cell concentrations of the two picophytoplankton groups. The results are converted into chlorophyll a and divinil chlorophyll a concentrations and compared with experimental data collected in two different sites of the Sicily Channel (southern Mediterranean Sea). The comparison shows that real distributions are well reproduced by theoretical profiles. Specifically, position, shape and magnitude of the theoretical deep chlorophyll maximum exhibit a good agreement with the experimental values.
Simple Fluorescent Sensors Engineered with Catalytic DNA ‘MgZ’ Based on a Non-Classic Allosteric Design

Most NAE (nucleic acid enzyme) sensors are composed of an RNA-cleaving catalytic motif and an aptameric receptor. They operate by activating or repressing the catalytic activity of a relevant NAE through the conformational change in the aptamer upon target binding. To transduce a molecular recognition event to a fluorescence signal, a fluorophore-quencher pair is attached to opposite ends of the RNA substrate such that when the NAE cleaves the substrate, an increased level of fluorescence can be generated. However, almost all NAE sensors to date harbor either NAEs that cannot accommodate a fluorophore-quencher pair near the cleavage site or those that can accept such a modification but require divalent transition metal ions for catalysis. Therefore, the signaling magnitude and the versatility of current NAE sensors might not suffice for analytical and biological applications. Here we report an RNA-cleaving DNA enzyme, termed ‘MgZ’, which depends on Mg2+ for its activity and can accommodate bulky dye moieties next to the cleavage site. MgZ was created by in vitro selection. The selection scheme entailed acidic buffering and ethanol-based reaction stoppage to remove selfish DNAs. Characterization of MgZ revealed a three-way junction structure, a cleavage rate of 1 min−1, and 26-fold fluorescence enhancement. Two ligand-responsive NAE sensors were rationally designed by linking an aptamer sequence to the substrate of MgZ. In the absence of the target, the aptamer-linked substrate is locked into a conformation that prohibits MgZ from accessing the substrate. In the presence of the target, the aptamer releases the substrate, which induces MgZ-mediated RNA cleavage. The discovery of MgZ and the introduction of the above NAE sensor design strategy should facilitate future efforts in sensor engineering.
Mycobacterium tuberculosis Bacteremia in a Cohort of HIV-Infected Patients Hospitalized with Severe Sepsis in Uganda–High Frequency, Low Clinical Sand Derivation of a Clinical Prediction Score

Background When manifested as Mycobacterium tuberculosis (MTB) bacteremia, disseminated MTB infection clinically mimics other serious blood stream infections often hindering early diagnosis and initiation of potentially life-saving anti-tuberculosis therapy. In a cohort of hospitalized HIV-infected Ugandan patients with severe sepsis, we report the frequency, management and outcomes of patients with MTB bacteremia and propose a risk score based on clinical predictors of MTB bacteremia. Methods We prospectively enrolled adult patients with severe sepsis at two Ugandan hospitals and obtained blood cultures for MTB identification. Multivariable logistic regression modeling was used to determine predictors of MTB bacteremia and to inform the stratification of patients into MTB bacteremia risk categories based on relevant patient characteristics. Results Among 368 HIV-infected patients with a syndrome of severe sepsis, eighty-six (23%) had MTB bacteremia. Patients with MTB bacteremia had a significantly lower median CD4 count (17 vs 64 lymphocytes/mm3, p<0.001) and a higher 30-day mortality (53% vs 32%, p = 0.001) than patients without MTB bacteremia. A minority of patients with MTB bacteremia underwent standard MTB diagnostic testing (24%) or received empiric anti-tuberculosis therapy (15%). Independent factors associated with MTB bacteremia included male sex, increased heart rate, low CD4 count, absence of highly active anti-retroviral therapy, chief complaint of fever, low serum sodium and low hemoglobin. A risk score derived from a model containing these independent predictors had good predictive accuracy [area under the curve = 0.85, 95% CI 0.80–0.89]. Conclusions Nearly 1 in 4 adult HIV-infected patients hospitalized with severe sepsis in 2 Ugandan hospitals had MTB bacteremia. Among patients in whom MTB was suspected, standard tests for diagnosing pulmonary MTB were inaccurate for correctly classifying patients with or without bloodstream MTB infection. A MTB bacteremia risk score can improve early diagnosis of MTB bacteremia particularly in settings with increased HIV and MTB co-infection.