Miracle-dz/UniFAR-FTUs huggingface dataset:
Expansion of Invasive Cardiac Services in the United States

Background— The number of hospitals offering invasive cardiac services (diagnostic angiography, percutaneous coronary intervention, and coronary artery bypass grafting) has expanded, yet national patterns of service diffusion and their effect on geographic access to care are unknown. Methods and Results— This is a retrospective cohort study of all hospitals in fee-for-service Medicare, 1996 to 2008. Logistic regression identified the relationship between cardiac service adoption and the proportion of neighboring hospitals within 40 miles already offering the service. From 1996 to 2008, 397 hospitals began offering diagnostic angiography, 387 percutaneous coronary intervention, and 298 coronary artery bypass grafting (increasing the proportion with services by 3%, 11%, and 4%, respectively). This capacity increase led to little new geographic access to care; the population increase in geographic access to diagnostic angiography was 1 percentage point; percutaneous coronary intervention 5 percentage points, and coronary artery bypass grafting 4 percentage points. Controlling for hospital and market characteristics, a 10 percentage point increase in the proportion of nearby hospitals already offering the service increased the odds by 10% that a hospital would add diagnostic angiography (odds ratio, 1.102; 95% confidence interval, 1.018–1.193), increased the odds by 79% that it would add percutaneous coronary intervention (odds ratio, 1.794; 95% confidence interval, 1.288–2.498), and had no significant effect on adding coronary artery bypass grafting (odds ratio, 0.929; 95% confidence interval, 0.608–1.420). Conclusions— Hospitals are most likely to introduce new invasive cardiac services when neighboring hospitals already offer such services. Increases in the number of hospitals offering invasive cardiac services have not led to corresponding increases in geographic access.
Can Additional Homeopathic Treatment Save Costs? A Retrospective Cost-Analysis Based on 44500 Insured Persons

Objectives The aim of this study was to compare the health care costs for patients using additional homeopathic treatment (homeopathy group) with the costs for those receiving usual care (control group). Methods Cost data provided by a large German statutory health insurance company were retrospectively analysed from the societal perspective (primary outcome) and from the statutory health insurance perspective. Patients in both groups were matched using a propensity score matching procedure based on socio-demographic variables as well as costs, number of hospital stays and sick leave days in the previous 12 months. Total cumulative costs over 18 months were compared between the groups with an analysis of covariance (adjusted for baseline costs) across diagnoses and for six specific diagnoses (depression, migraine, allergic rhinitis, asthma, atopic dermatitis, and headache). Results Data from 44,550 patients (67.3% females) were available for analysis. From the societal perspective, total costs after 18 months were higher in the homeopathy group (adj. mean: EUR 7,207.72 [95% CI 7,001.14–7,414.29]) than in the control group (EUR 5,857.56 [5,650.98–6,064.13]; p<0.0001) with the largest differences between groups for productivity loss (homeopathy EUR 3,698.00 [3,586.48–3,809.53] vs. control EUR 3,092.84 [2,981.31–3,204.37]) and outpatient care costs (homeopathy EUR 1,088.25 [1,073.90–1,102.59] vs. control EUR 867.87 [853.52–882.21]). Group differences decreased over time. For all diagnoses, costs were higher in the homeopathy group than in the control group, although this difference was not always statistically significant. Conclusion Compared with usual care, additional homeopathic treatment was associated with significantly higher costs. These analyses did not confirm previously observed cost savings resulting from the use of homeopathy in the health care system.
Fast Appearance Based Object Recognition: A Hybrid Approach

Visual object recognition is a useful skill for robots to possess. However, present approaches to the problem do not scale to large numbers of objects (few manage more than 10) and require too much computation for real-time tasks on a robot. This paper presents a hybrid decision tree/support vector machine approach to recognition which is fast, with recognition times under one second. A new test dataset is also presented, consisting of over 100,000 images of Lego bricks, acquired by repeatedly dropping the bricks. The proposed method achieves 96% accuracy on the set of 89 different types of Lego bricks, demonstrating its applicability for large-scale real-time visual object recognition.
THE 1994 AT&T ATIS CHRONUS RECOGNIZER

The two main components of the AT&T spoken language system, called CHRONUS, are the speech recognizer and the natural language (NL) understanding component. We report about the speech recognition results obtained by the CHRONUS recognizer in the December 1994 ARPA ATIS SPREC evaluations. We also report about the progress made in 1994 at AT&T Bell Laboratories, in spontaneous speech recognition using the ARPA ATIS Corpus. Since the December 1993 ATIS evaluations, we have improved all the recognizer components, including the acoustic frontend, the acoustic phone Hidden Markov Models, the language model, and the lexicon. Therefore, in the December 1994 ATIS evaluations (preadjudication), we have obtained a word error rate of 3.6%, that is a three-fold reduction of the 10.2% error rate of December 1993.
Privacy Leakage in Mobile Computing: Tools, Methods, and Characteristics

The number of smartphones, tablets, sensors, and connected wearable devices are rapidly increasing. Today, in many parts of the globe, the penetration of mobile computers has overtaken the number of traditional personal computers. This trend and the always-on nature of these devices have resulted in increasing concerns over the intrusive nature of these devices and the privacy risks that they impose on users or those associated with them. In this paper, we survey the current state of the art on mobile computing research, focusing on privacy risks and data leakage effects. We then discuss a number of methods, recommendations, and ongoing research in limiting the privacy leakages and associated risks by mobile computing.
Clustering for music search results

Clustering for better representation of the diversity of text or image search results has been studied extensively. In this paper, we extend this methodology to the novel domain of music search. We conduct empirical evaluation of different clustering algorithms, audio feature representations, and the incorporation of lyrics for music clustering. Our evaluation shows the fusion of audio and text features yields the best clustering accuracy.
Bounds on the Information Rate for Sparse Channels with Long Memory and i.u.d. Inputs

In this paper we propose new bounds on the achievable information rate for discrete-time Gaussian channels with intersymbol interference (ISI) and independent and uniformly distributed (i.u.d.) channel input symbols drawn from finite-order modulation alphabets. Specifically, we are interested in developing new bounds on the achievable rates for sparse channels with long memory. We obtain a lower bound which can be achieved by practical receivers, based on MMSE channel shortening and suboptimal symbol detection for a reduced-state channel. An upper bound is given in the form of a semi-analytical solution derived using basic information theoretic inequalities, by a grouping of the channel taps into several clusters resulting in a newly defined single-input multiple-output (SIMO) channel. We show that the so obtained time-dispersive SIMO channel can be represented by an equivalent single-input single-output (SISO) channel with a significantly shorter channel memory. The reduced computational complexity allows the use of the BCJR algorithm for the newly defined channel. The proposed bounds are illustrated through several sparse channel examples and i.u. d. input symbols, showing that the upper bound significantly outperforms existing bounds. Performance of our lower bound strongly depends on the channel structure, showing best results for minimum-phase and maximum-phase systems.
Fast RTP Retransmission for IPTV - Implementation and Evaluation

With the deployment of IPTV reliability for multicast is becoming an important research topic again. Even though it has been intensively investigated before, there is now an understanding of the deployment scenario and the application requirements that allows solutions to be evaluated in detail. We describe how to design a fast retransmission cache based on recent extensions of RTP. We have implemented a prototype intended for deployment in an access node and explain the necessary trade-offs in the design. The paper also contains a performance evaluation which shows the efficiency of the retransmission functionality to handle losses and its performance in congested networks.
Control of porcine reproductive and respiratory syndrome (PRRS) through genetic improvements in disease resistance and tolerance

Infections caused by porcine reproductive and respiratory syndrome virus (PRRSV) have a severe economic impact on pig production in North America, Europe, and Asia. The emergence and eventual predominance of PRRS in the 1990s are the likely result of changes in the pork industry initiated in the late 1970s, which allowed the virus to occupy a unique niche within a modern commercial production system. PRRSV infection is responsible for severe clinical disease, but can maintain a life-long subclinical infection, as well as participate in several polymicrobial syndromes. Current vaccines lessen clinical signs, but are of limited use for disease control and elimination. The relatively poor protective immunity following vaccination is a function of the virus's capacity to generate a large degree of genetic diversity, combined with several strategies to evade innate and adaptive immune responses. In 2007, the PRRS Host Genetics consortium (PHGC) was established to explore the role of host genetics as an avenue for PRRS control. The PHGC model for PRRS incorporates the experimental infection of large numbers of growing pigs and has created the opportunity to study experimental PRRSV infection at the population level. The results show that pigs can be placed into distinct phenotypic groups, including pigs that show resistance (i.e., low virus load) or pigs that exhibit “tolerance” to infection. Tolerance was illustrated by pigs that gain weight normally in the face of a relatively high virus load. Genome-wide association analysis has identified a region on chromosome 4 (SSC4) correlated with resistance; i.e., lower cumulative virus load within the first 42 days of infection. The genomic region is near a family of genes involved in innate immunity. The region is also associated with higher weight gain in challenged pigs, suggesting that pigs with the resistance alleles don't seem to simultaneously experience reduction in growth, i.e., that resistance and tolerance are not antagonistically related. These results create the opportunity to develop breeding programs that will produce pigs with increased resistance to PRRS and simultaneously high growth rate. The identification of genomic markers involved in actual tolerance will likely prove more difficult, primarily because tolerance is difficult to quantify and because tolerance mechanism are still poorly understood. Another avenue of study includes the identification of genomic markers related to improved response following vaccination.
A Principle-Based System for Syntactic Analysis

Traditional approaches to natural language processing (NLP) can be considered construction-based. That is to say, they employ surface oriented, language specific rules, whether in the form of an Augmented Transition Network (ATN), logic grammar or some other grammar/parsing formalism. The problems of such approaches have always been apparent; they involve large sets of rules, often ad hoc, and their adequacy with respect to the grammar of the language is difficult to ensure.
A Novel Receiver for ACO-OFDM in Visible Light Communication

This letter proposes a novel receiver for asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) system in visible light communication to enhance its performance. In ACO-OFDM, the even subcarriers are distorted by the clipping noise and are simply discarded in the conventional receiver. In this letter we show that the signals on the even subcarriers can be viewed as data-dependent precoded OFDM. A novel receiver based on minimum mean square error criteria is then proposed to exploit the even subcarriers to collect additional diversity and coding gains, leading to improved bit error rate performance. Simulations show that the proposed receiver provides significant signal-to-noise ratio gain (up to 10 dB) over the conventional receiver, especially in non-line-of-sight channels. Moreover, the proposed receiver is also superior to some existing advanced ones.
Enhancing test precision for local Lorentz-symmetry violation with entanglement

A recent proposal for testing Lorentz symmetry violation (LSV) presents a formulation where the effect of violation is described as a local interaction [R. Shaniv, et al, Phys. Rev. Lett. 120, 103202 (2018)]. An entangled ion pair in a decoherence free subspace (DFS) is shown to double the signal to noise ratio (SNR) of one ion, while (even)-N/2 such DFS pairs in a collective entangled state improve SNR by N times, provided the state parity or the even/odd numbers of ions can be measured. It remains to find out, however, how such fiducial entangled states can be prepared at nonexponentially small success rates. This work suggests two types of many particle entangled states for testing LSV: the maximally entangled NOON state, which can achieve Heisenberg limited precision; and the balanced spin-1 Dicke state, which is readily available in deterministic fashion. We show that the latter also lives in a DFS and is immune to stray magnetic fields. It can achieve classical precision limit or the standard quantum limit (SQL) based on collective population measurement without individual atom resolution. Given the high interests in LSV and in entanglement assisted quantum metrology, our observation offers additional incentives for pursuing practical applications of many atom entangled states.
Estimating a Markovian Epidemic Model Using Household Serial Interval Data from the Early Phase of an Epidemic

The clinical serial interval of an infectious disease is the time between date of symptom onset in an index case and the date of symptom onset in one of its secondary cases. It is a quantity which is commonly collected during a pandemic and is of fundamental importance to public health policy and mathematical modelling. In this paper we present a novel method for calculating the serial interval distribution for a Markovian model of household transmission dynamics. This allows the use of Bayesian MCMC methods, with explicit evaluation of the likelihood, to fit to serial interval data and infer parameters of the underlying model. We use simulated and real data to verify the accuracy of our methodology and illustrate the importance of accounting for household size. The output of our approach can be used to produce posterior distributions of population level epidemic characteristics.
Evaluation of commercially available RNA amplification kits for RNA sequencing using very low input amounts of total RNA.

This article includes supplemental data. Please visit http://www.fasebj. org to obtain this information.Multiple recent publications on RNA sequencing (RNA-seq) have demonstrated the power of next-generation sequencing technologies in whole-transcriptome analysis. Vendor-specific protocols used for RNA library construction often require at least 100 ng total RNA. However, under certain conditions, much less RNA is available for library construction. In these cases, effective transcriptome profiling requires amplification of subnanogram amounts of RNA. Several commercial RNA amplification kits are available for amplification prior to library construction for next-generation sequencing, but these kits have not been comprehensively field evaluated for accuracy and performance of RNA-seq for picogram amounts of RNA. To address this, 4 types of amplification kits were tested with 3 different concentrations, from 5 ng to 50 pg, of a commercially available RNA. Kits were tested at multiple sites to assess reproducibility and ease of use. The human total reference RNA used was spiked with a control pool of RNA molecules in order to further evaluate quantitative recovery of input material. Additional control data sets were generated from libraries constructed following polyA selection or ribosomal depletion using established kits and protocols. cDNA was collected from the different sites, and libraries were synthesized at a single site using established protocols. Sequencing runs were carried out on the Illumina platform. Numerous metrics were compared among the kits and dilutions used. Overall, no single kit appeared to meet all the challenges of small input material. However, it is encouraging that excellent data can be recovered with even the 50 pg input total RNA.
The potential role of speakers' vocal tract morphology onto speech perception: preliminary results

In order to investigate the influence of vocal tract morphology, i.e. different palate shapes, on the acoustic output and its perceptual consequences, we simulated /kVk/-sequences by means of a 2D biomechanical tongue model. Three palate shapes (normal, flat and dome shaped) differing in the coronal and mid-sagittal plane were implemented in the model. We assumed that small articulatory changes have a large impact on the area function and hence on the acoustics for subjects with a flat palate shape in comparison to normal or dome shaped palates. The results for the variability of the estimated area functions at the minimal constriction location and for the formant patterns clearly show vowel specific effects with respect to the three different palate shapes. KVk-sequences with the high front vowel /i/ were influenced to a greater extent than /kak/ and /kuk/-sequences.
Neuronal activity (c-Fos) delineating interactions of the cerebral cortex and basal ganglia

The cerebral cortex and basal ganglia (BG) form a neural circuit that is disrupted in disorders such as Parkinson’s disease. We found that neuronal activity (c-Fos) in the BG followed cortical activity, i.e., high in arousal state and low in sleep state. To determine if cortical activity is necessary for BG activity, we administered atropine to rats to induce a dissociative state resulting in slow-wave electroencephalography but hyperactive motor behaviors. Atropine blocked c-Fos expression in the cortex and BG, despite high c-Fos expression in the sub-cortical arousal neuronal groups and thalamus, indicating that cortical activity is required for BG activation. To identify which glutamate receptors in the BG that mediate cortical inputs, we injected ketamine [N-methyl-d-aspartate (NMDA) receptor antagonist] and 6-cyano-nitroquinoxaline-2, 3-dione (CNQX, a non-NMDA receptor antagonist). Systemic ketamine and CNQX administration revealed that NMDA receptors mediated subthalamic nucleus (STN) input to internal globus pallidus (GPi) and substantia nigra pars reticulata (SNr), while non-NMDA receptor mediated cortical input to the STN. Both types of glutamate receptors were involved in mediating cortical input to the striatum. Dorsal striatal (caudoputamen, CPu) dopamine depletion by 6-hydroxydopamine resulted in reduced activity of the CPu, globus pallidus externa (GPe), and STN but increased activity of the GPi, SNr, and putative layer V neurons in the motor cortex. Our results reveal that the cortical activity is necessary for BG activity and clarifies the pathways and properties of the BG-cortical network and their putative role in the pathophysiology of BG disorders.
Contribution of Risk Factors to Extremely, Very and Moderately Preterm Births – Register-Based Analysis of 1,390,742 Singleton Births

Background Preterm birth, defined as birth occurring before 37 weeks gestation, is one of the most significant contributors to neonatal mortality and morbidity, with long-term adverse consequences for health, and cognitive outcome. Objective The aim of the present study was to identify risk factors of preterm birth (≤36+6 weeks gestation) among singleton births and to quantify the contribution of risk factors to socioeconomic disparities in preterm birth. Methods A retrospective population–based case-control study using data derived from the Finnish Medical Birth Register. A total population of singleton births in Finland from 1987−2010 (n = 1,390,742) was reviewed. Results Among all singleton births (n = 1,390,742), 4.6% (n = 63,340) were preterm (<37 weeks), of which 0.3% (n = 4,452) were classed as extremely preterm, 0.4% (n = 6,213) very preterm and 3.8% (n = 54,177) moderately preterm. Smoking alone explained up to 33% of the variation in extremely, very and moderately preterm birth incidence between high and the low socioeconomic status (SES) groups. Reproductive risk factors (placental abruption, placenta previa, major congenital anomaly, amniocentesis, chorionic villus biopsy, anemia, stillbirth, small for gestational age (SGA) and fetal sex) altogether explained 7.7−25.0% of the variation in preterm birth between SES groups. Conclusions Smoking explained about one third of the variation in preterm birth groups between SES groups whereas the contribution of reproductive risk factors including placental abruption, placenta previa, major congenital anomaly, amniocentesis, chorionic villus biopsy, anemia, stillbirth, SGA and fetal sex was up to one fourth.
Accurate Prediction of Protein Functional Class From Sequence in the Mycobacterium Tuberculosis and Escherichia Coli Genomes Using Data Mining

The analysis of genomics data needs to become as automated as its generation. Here we present a novel data‐mining approach to predicting protein functional class from sequence. This method is based on a combination of inductive logic programming clustering and rule learning. We demonstrate the effectiveness of this approach on the M. tuberculosis and E. coli genomes, and identify biologically interpretable rules which predict protein functional class from information only available from the sequence. These rules predict 65% of the ORFs with no assigned function in M. tuberculosis and 24% of those in E. coli, with an estimated accuracy of 60–80% (depending on the level of functional assignment). The rules are founded on a combination of detection of remote homology, convergent evolution and horizontal gene transfer. We identify rules that predict protein functional class even in the absence of detectable sequence or structural homology. These rules give insight into the evolutionary history of M. tuberculosis and E. coli. Copyright © 2000 John Wiley & Sons, Ltd.