Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple antimicrobial resistance of pneumococci in children with otitis media, bacteremia, and meningitis in Slovakia.

Penicillin-resistant pneumococci have been isolated from middle ear fluid, blood, cerebrospinal fluid, and nasopharyngeal secretions of several hundred children in Slovakia since 1985; 116 of these isolates were serotyped and tested for susceptibility to antimicrobial drugs at the Centers for Disease Control and Prevention. To define the prevalence of drug-resistant pneumococci and identify risk factors for infection, laboratory and medical records were reviewed. Nearly all (96%) of the resistant strains tested were serotype 14. Of these, all were resistant to penicillin (MIC, 4-16 micrograms/mL); most were resistant to cefaclor, erythromycin, tetracycline, and chloramphenicol; and many had decreased susceptibility to trimethoprim-sulfamethoxazole and ceftriaxone. Frequent antibiotic use, prior hospitalization, and length of hospital stay (P < .001 for all 3) were associated with infection with resistant strains. These findings suggest the need for routine screening of pneumococcal isolates for penicillin resistance and highlight the importance of controlling globally the spread of resistant pneumococci.
Detecting and characterizing social spam campaigns

Online social networks (OSNs) are exceptionally useful collaboration and communication tools for millions of users and their friends. Unfortunately, in the wrong hands, they are also extremely effective tools for executing spam campaigns and spreading malware. In this poster, we present an initial study to detect and quantitatively analyze the coordinated spam campaigns on online social networks in the wild. Our system detected about 200K malicious wall posts with embedded URLs, traced back to roughly 57K accounts. We find that more than 70% of all malicious wall posts are advertising phishing sites
The Impacts of the Climate Change Levy on Business: Evidence from Microdata

We estimate the impacts of the Climate Change Levy (CCL) on manufacturing plants using panel data from the UK production census. Our identification strategy builds on the comparison of outcomes between plants subject to the CCL and plants that were granted an 80% discount on the levy after joining a Climate Change Agreement (CCA). Exploiting exogenous variation in eligibility for CCA participation, we find that the CCL had a strong negative impact on energy intensity and electricity use. We cannot reject the hypothesis that the tax had no detrimental effects on economic performance and on plant exit.
Exploiting Parallel Texts for Word Sense Disambiguation: An Empirical Study

A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automatically acquire sense-tagged training data from English-Chinese parallel corpora, which are then used for disambiguating the nouns in the SENSEVAL-2 English lexical sample task. Our investigation reveals that this method of acquiring sense-tagged data is promising. On a subset of the most difficult SENSEVAL-2 nouns, the accuracy difference between the two approaches is only 14.0%, and the difference could narrow further to 6.5% if we disregard the advantage that manually sense-tagged data have in their sense coverage. Our analysis also highlights the importance of the issue of domain dependence in evaluating WSD programs.
Human outer dense fiber gene, ODF2, localizes to chromosome 9q34

We have isolated the human homolog of the rat Odf2 gene. In rat, Odf2, the 84-kDa major outer dense fiber protein, interacts strongly and specifically with Odf1, the 27-kDa major outer dense fiber protein. The interaction is mediated by leucine zippers during ODF assembly along the sperm axoneme. We compared homology and genomic structure to rat and mouse Odf2 genes. Using fluorescence in situ hybridization, we mapped the human Odf2 gene (ODF2) to chromosome 9q34.
Measuring and Optimizing Distributed Array Programs

Nowadays, there is a rising trend of building array-based distributed computing frameworks, which are suitable for implementing many machine learning and data mining algorithms. However, most of these frameworks only execute each primitive in an isolated manner and in the exact order defined by programmers, which implies a huge space for optimization. In this paper, we propose a novel array-based programming model, named Kasen, which distinguishes itself from models in the existing literature by defining a strict computation and communication model. This model makes it easy to analyze programs' behavior and measure their performance, with which we design a corresponding optimizer that can automatically apply high-level optimizations to the original programs written by programmers. According to our evaluation, the optimizer of Kasen can achieve a significant reduction on memory read/write, buffer allocation and network traffic, which leads to a speedup up to 5.82x.
Cyclostationary detection from sub-Nyquist samples for Cognitive Radios: Model reconciliation

Cognitive Radio (CR) challenges spectrum sensing into dealing with wideband signals in an efficient and reliable way. CR receivers traditionally deal with signals with high Nyquist rates and low Signal to Noise Ratios (SNRs). On the one hand, sub-Nyquist sampling of such signals alleviates the burden both on the analog and the digital side. On the other hand, cyclostationary detection ensures better robustness to noise. Cyclostationary detection from sub-Nyquist samples has been considered via two main signal models that seem inherently different. In this paper, we show that those two models can lead to similar relations between the cyclic spectrum we wish to recover and the correlation between the sub-Nyquist samples. We show that we can then derive the minimal sampling rate allowing for perfect reconstruction of the signal's cyclic spectrum in a noise-free environment for both models in a unified way. We consider both sparse and non sparse signals as well as blind and non blind detection in the sparse case. Simulations show that our detector outperforms energy detection at low SNRs.
A UML Profile for Core Components and their Transformation to XSD

In business-to-business e-commerce, traditional electronic data interchange (EDI) approaches such as UN/EDIFACT have been superseded by approaches like web services and ebXML. Nevertheless, a precise and common semantic definition of business documents exchanged is needed. In order to become independent from a transfer syntax, we prefer defining the documents as platform independent models. An approach that follows this idea is the UN/CEFACT's core component standard. Core components are reusable semantic building blocks which can be combined in various ways to create shared libraries of interoperable business documents. In order to use standard UML modeling tools we have developed a UML profile for the core components standard. Furthermore, we adapt the UN/CEFACT naming and design rules for the UML profile in order to derive XML schemas for business document exchanges. The overall approach is demonstrated by using a specific example from the field of e-commerce.
Interruptions to workflow: Their relationship with irritation and satisfaction with performance, and the mediating roles of time pressure and mental demands

Understanding the mechanisms of workflow interruptions is crucial for reducing employee strain and maintaining performance. This study investigates how interruptions affect perceptions of performance and irritation by employing a within-person approach. Such interruptions refer to intruding secondary tasks, such as requests for assistance, which occur within the primary task. Based on empirical evidence and action theory, it is proposed that the occurrence of interruptions is negatively related to satisfaction with one's own performance and positively related to forgetting of intentions and the experience of irritation. Mental demands and time pressure are proposed as mediators. Data were gathered from 133 nurses in German hospitals by means of a five-day diary study (four measurements taken daily; three during a morning work shift and one after work, in the evening). Multilevel analyses showed that workflow interruptions had detrimental effects on satisfaction with one's own performance, the forgetting of intentions, and irritation. The mediation effects of mental demands and time pressure were supported for irritation and (partially) supported for satisfaction with performance. They were not supported for the forgetting of intentions. These findings demonstrate the importance of reducing the time and mental demands associated with interruptions.
Evaluation of the Antiviral Activity of a Green Tea Solution as a Hand-Wash Disinfectant

Based on the broad-spectrum antiviral effect of green tea catechins, we established an experimental skin contact model for influenza virus transmission and evaluated the use of a green tea solution as a first-hand disinfectant. The infectivity of the virus on the skin cell layer became obsolete when washed with the green tea solution. The skin contact model could be applied to develop non-pharmaceutical intervention measures for reducing human transmission of the influenza virus.
Model-based synthesis and optimization of static multi-rate image processing algorithms

High computational effort in modern image processing applications like medical imaging or high-resolution video processing often demands for massively parallel special purpose architectures in form of FPGAs or ASICs. However, their efficient implementation is still a challenge, as the design complexity causes exploding development times and costs. This paper presents a new design flow which permits to specify, analyze, and synthesize complex image processing algorithms. A novel buffer requirement analysis allows exploiting possible tradeoffs between required communication memory and computational logic for multi-rate applications. The derived schedule and buffer results are taken into account for resource optimized synthesis of the required hardware accelerators. Application to a multi-resolution filter shows that buffer analysis is possible in less than one second and that scheduling alternatives influence the required communication memory by up to 24% and the computational resources by up to 16%.
Beyond Ph.D. — What next? Publishing, networking and research trade-offs in relation to planning your career

A Ph.D. in simulation offers many possibilities for a further career. Examples of popular job types for simulation researchers are analyst or researcher in a public or private organization, consultant, entrepreneur, and Post Doc or researcher in a university. During the Ph.D. research, it is very well possible to prepare for the desired career path. The trade-off between applied research and theoretical research can be managed to provide a good starting point for the chosen type of job. The types of publications and research outlets can also be aligned. Independent of the job, methodological soundness, a good theoretical foundation, and validation of concepts and models are key to success. The paper will provide several guidelines for publication strategies adapted to the job type, as well as a networking strategy to help you link to the right people.
Approaching Real-time Network Traffic Classification

Recent research explored the feasibility of using Machine Learning methods to provide accurate network traffic classification. We further believe that these methods can work on real-time Internet traffic with sufficient accuracy for practical applications. In this paper we present ANTc, a framework for quasi-realtime statistical traffic classification. It essentially demultiplexes network flows, collects statistical features of the flows, and then allows classification of the flows into arbitrary traffic classes using a pre-trained Naive Bayes model. ANTc contains a built-in feature collector for the input of Naive Bayes classifier and further provides a modular framework to facilitate further investigations into statistical classification methodologies. It also provides a set of flow sampling parameters which can be tuned, thus is capable of demonstrating the impact on classification accuracy from flow sample size restrictions. Results show that ANTc using Naive Baye model can work in near real-time without obvious decrease in precision.
Sema6B, Sema6C, and Sema6D Expression and Function during Mammalian Retinal Development

In the vertebrate retina, the formation of neural circuits within discrete laminae is critical for the establishment of retinal visual function. Precise formation of retinal circuits requires the coordinated actions of adhesive and repulsive molecules, including repulsive transmembrane semaphorins (Sema6A, Sema5A, and Sema5B). These semaphorins signal through different Plexin A (PlexA) receptors, thereby regulating distinct aspects of retinal circuit assembly. Here, we investigate the physiological roles of three Class 6 transmembrane semaphorins (Sema6B, Sema6C, and Sema6D), previously identified as PlexA receptor ligands in non-retinal tissues, in mammalian retinal development. We performed expression analysis and also phenotypic analyses of mice that carry null mutations in each of genes encoding these proteins using a broad range of inner and outer retinal markers. We find that these Class 6 semaphorins are uniquely expressed throughout postnatal retinal development in specific domains and cell types of the developing retina. However, we do not observe defects in stereotypical lamina-specific neurite stratification of retinal neuron subtypes in Sema6B−/− or Sema6C−/−; Sema6D−/− retinas. These findings indicate these Class 6 transmembrane semaphorins are unlikely to serve as major PlexA receptor ligands for the assembly of murine retinal circuit laminar organization.
Comparison of Attitude Estimation Techniques for Low-cost Unmanned Aerial Vehicles

Attitude estimation for small, low-cost unmanned aerial vehicles is often achieved using a relatively simple complementary filter that combines onboard accelerometers, gyroscopes, and magnetometer sensing. This paper explores the limits of performance of such attitude estimation, with a focus on performance in highly dynamic maneuvers. The complementary filter is derived along with the extended Kalman filter and unscented Kalman filter to evaluate the potential performance gains when using a more sophisticated estimator. Simulations are presented that compare performance across a range of test cases, many where ground truth was generated from manually controlled flights in a flight simulator. Estimator scenarios that are generic across the different estimator types (such as the way sensor information is processed, and the use of dynamically changing gains) are compared across the test cases. An appendix is included as a quick reference for the common attitude representations and their kinematic expressions.
Differential and antagonistic effects of 9- cis -retinoic acid and vitamin D analogues on pancreatic cancer cells in vitro

Retinoids and vitamin D are known to exert important anti-tumour effects in a variety of cell types. In this study the effects of 9-cis-retinoic acid (9cRA) the vitamin D analogues EB1089 and CB1093 on three pancreatic adenocarcinoma cell lines were investigated. All compounds caused inhibition of in vitro growth but the vitamin D analogues were generally the more potent growth inhibitors. They were also more effective on their own than in combination with 9cRA. Growth arrest correlated with an increased proportion of cells in the G0/G1 phase. Apoptosis was induced in the three cell lines by 9cRA, whereas neither EB1089 nor CB1093 had this effect. Furthermore, addition of EB1089 or CB1093 together with 9cRA resulted in significantly reduced apoptosis. Our results show that retinoic acids as well as vitamin D analogues have inhibitory effects on pancreatic tumour cells but different and antagonistic mechanisms seem to be employed. © 2000 Cancer Research Campaign
Entity-Relationship Models of Information Artefacts

Data modelling reveals the internal structure of an information system, abstracting away from details of the physical representation. We show that entity-relationship modelling, a well-tried example of a data-modelling technique, can be applied to both interactive and non-interactive information artefacts in the domain of HCI. By extending the conventional ER notation slightly (to give ERMIA, Entity-Relationship Modelling for Information Artefacts) it can be used to describe differences between different representations of the same information, differences between user’s conceptual models of the same device, and the structure and update requirements of distributed information in a worksystem. It also yields symbolic-level estimates of Card et al.’s (1994) index of ‘cost-of-knowledge’ in an information structure, plus a novel index, the ‘cost-of-update’; these symbolic estimates offer a useful complement to the highly detailed analyses of time costs obtainable from GOMS-like models. We conclude that, as a cheap, coarse-grained, and easy-to-learn modelling technique, ERMIA usefully fills a gap in the range of available HCI analysis techniques. NOTE TO EDITOR AND REFEREES: The figures will be supplied separately for printing. Figure 20, the Spiral Calendar, will be improved (we have asked the authors to be allowed to use the original artwork).
Molecular components of signal amplification in olfactory sensory cilia

The mammalian olfactory system detects an unlimited variety of odorants with a limited set of odorant receptors. To cope with the complexity of the odor world, each odorant receptor must detect many different odorants. The demand for low odor selectivity creates problems for the transduction process: the initial transduction step, the synthesis of the second messenger cAMP, operates with low efficiency, mainly because odorants bind only briefly to their receptors. Sensory cilia of olfactory receptor neurons have developed an unusual solution to this problem. They accumulate chloride ions at rest and discharge a chloride current upon odor detection. This chloride current amplifies the receptor potential and promotes electrical excitation. We have studied this amplification process by examining identity, subcellular localization, and regulation of its molecular components. We found that the Na+/K+/2Cl− cotransporter NKCC1 is expressed in the ciliary membrane, where it mediates chloride accumulation into the ciliary lumen. Gene silencing experiments revealed that the activity of this transporter depends on the kinases SPAK and OSR1, which are enriched in the cilia together with their own activating kinases, WNK1 and WNK4. A second Cl− transporter, the Cl−/HCO3− exchanger SLC4A1, is expressed in the cilia and may support Cl− accumulation. The calcium-dependent chloride channel TMEM16B (ANO2) provides a ciliary pathway for the excitatory chloride current. These findings describe a specific set of ciliary proteins involved in anion-based signal amplification. They provide a molecular concept for the unique strategy that allows olfactory sensory neurons to operate as efficient transducers of weak sensory stimuli.
Development of Surface Management System Integrated with CTAS Arrival Tool

The Surface Management System (SMS) is a decision support tool that helps tower traffic coordinators and Ground/Local controllers manage and control airport surface traffic in order to increase capacity, efficiency, and flexibility. SMS provides common situation awareness to personnel at various air traffic control facilities such as air traffic control towers (ATCTs), airline ramp towers, the Terminal Radar Approach Controls (TRACONs), and Air Route Traffic Control Centers. SMS also provides a traffic management tool to assist ATCT traffic management coordinators in making decisions regarding airport configuration and runway load balancing. The Build 1 of the SMS tool was successfully tested at Memphis International Airport. This paper reports the recent development efforts performed to integrate SMS with the Center-TRACON Automation System (CTAS) Traffic Management Advisor (TMA) to improve its prediction accuracy for arrival traffic and robustness under modeling uncertainties. The preliminary analysis results performed on the traffic data at the Dallas/Fort Worth International Airport have shown significant improvements in predicting runway assignment, runway arrival time, and arrival demand.
Basic circuit compilation techniques for an ion-trap quantum machine

We study the problem of compilation of quantum algorithms into optimized physical-level circuits executable in a quantum information processing (QIP) experiment based on trapped atomic ions. We report a complete strategy: starting with an algorithm in the form of a quantum computer program, we compile it into a high-level logical circuit that goes through multiple stages of decomposition into progressively lower-level circuits until we reach the physical execution-level specification. We skip the fault-tolerance layer, as it is not within the scope of this work. The different stages are structured so as to best assist with the overall optimization while taking into account numerous optimization criteria, including minimizing the number of expensive two-qubit gates, minimizing the number of less expensive single-qubit gates, optimizing the runtime, minimizing the overall circuit error, and optimizing classical control sequences. Our approach allows a trade-off between circuit runtime and quantum error, as well as to accommodate future changes in the optimization criteria that may likely arise as a result of the anticipated improvements in the physical-level control of the experiment.
Evaluation of quality of sound source separation algorithms: Human perception vs quantitative metrics

In this paper we look into the test methods to evaluate the quality of audio separation algorithms. Specifically we try to correlate the results of listening tests with state-of-the-art objective measures. To this end, the quality of the harmonic signals obtained with two harmonic-percussive separation algorithms was evaluated with BSS_Eval, PEASS and via listening tests. A correlation analysis was conducted and results show that for harmonic-percussive separation algorithms, neither BSS_Eval nor PEASS show strong correlation with the ratings obtained via listening tests and suggest that existing perceptual objective measures for quality assessment do not generalize well to different separation algorithms.
Simplified active power and reactive power control with MPPT for three-phase grid-connected photovoltaic inverters

This paper presents the simplified active power and reactive power control with the maximum power point tracking (MPPT) for three-phase grid-connected photovoltaic (PV) inverters. With the proposed control strategy, the perturbation and observation method is used for the simple MPPT algorithm and the current command on the rotating reference frame is regulated by the feedback and feedforward controller. In order to guarantee the all maximum power is transferred to the grid, the d-axis current or active power command is calculated from the PV power. Moreover, the design guidelines of phase-locked loop (PLL) and current controller are also presented. Validity of the proposed grid-connected inverters is confirmed by simulation.