Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical response and risk for reported suicidal ideation and suicide attempts in pediatric antidepressant treatment: a meta-analysis of randomized controlled trials.

CONTEXT The US Food and Drug Administration (FDA) has issued warnings that use of antidepressant medications poses a small but significantly increased risk of suicidal ideation/suicide attempt for children and adolescents. OBJECTIVE To assess the efficacy and risk of reported suicidal ideation/suicide attempt of antidepressants for treatment of pediatric major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and non-OCD anxiety disorders. DATA SOURCES AND STUDY SELECTION PubMed (1988 to July 2006), relevant US and British regulatory agency reports, published abstracts of important scientific meetings (1998-2006), clinical trial registries, and information from authors. Studies were published and unpublished randomized, placebo-controlled, parallel-group trials of second-generation antidepressants (selective serotonin reuptake inhibitors, nefazodone, venlafaxine, and mirtazapine) in participants younger than 19 years with MDD, OCD, or non-OCD anxiety disorders. DATA EXTRACTION Information was extracted on study characteristics, efficacy outcomes, and spontaneously reported suicidal ideation/suicide attempt. DATA SYNTHESIS Twenty-seven trials of pediatric MDD (n = 15), OCD (n = 6), and non-OCD anxiety disorders (n = 6) were selected, and risk differences for response and for suicidal ideation/suicide attempt estimated by random-effects methods. Pooled risk differences in rates of primary study-defined measures of responder status significantly favored antidepressants for MDD (11.0%; [95% confidence interval {CI}, 7.1% to 14.9%]), OCD (19.8% [95% CI, 13.0% to 26.6%), and non-OCD anxiety disorders (37.1% [22.5% to 51.7%]), corresponding to a number needed to treat (NNT) of 10 (95% CI, 7 to 15), 6 (4 to 8), and 3 (2 to 5), respectively. While there was increased risk difference of suicidal ideation/suicide attempt across all trials and indications for drug vs placebo (0.7%; 95% CI, 0.1% to 1.3%) (number needed to harm, 143 [95% CI, 77 to 1000]), the pooled risk differences within each indication were not statistically significant: 0.9% (95% CI, -0.1% to 1.9%) for MDD, 0.5% (-1.2% to 2.2%) for OCD, and 0.7% (-0.4% to 1.8%) for non-OCD anxiety disorders. There were no completed suicides. Age-stratified analyses showed that for children younger than 12 years with MDD, only fluoxetine showed benefit over placebo. In MDD trials, efficacy was moderated by age, duration of depression, and number of sites in the treatment trial. CONCLUSIONS Relative to placebo, antidepressants are efficacious for pediatric MDD, OCD, and non-OCD anxiety disorders, although the effects are strongest in non-OCD anxiety disorders, intermediate in OCD, and more modest in MDD. Benefits of antidepressants appear to be much greater than risks from suicidal ideation/suicide attempt across indications, although comparison of benefit to risk varies as a function of indication, age, chronicity, and study conditions.
A neural-network-based local inverse mapping technique for building statistical DMOS models

This paper presents a methodology to circumvent the time consuming standard approach for statistical model development. The methodology is a two step process. The first part defines the relationship between electrical device parameters and model device parameters by means of training a neural network. The second stage uses the neural network to create worst-case model parameter sets. In order to select an appropriate set of worst-case electrical parameters, a multivariate statistical analysis is performed, such that correlations between device parameters are taken into account. The neural network approach also enables a Monte-Carlo model to be generated. The advantages of the proposed methodology are its speed improvement and accuracy.
Antenna Concepts for Millimeter-Wave Automotive Radar Sensors

Automotive radars are on the market since 1999, both in the frequency range around 24 GHz as well as 76.5 GHz, with a new frequency band ranging from 77 to 81 GHz intended for medium and short-range sensors. The choice and design of the respective sensor antennas are determined by the requirement for high gain and low loss combined with small size and depth for vehicle integration, the challenges by the millimeter-wave frequency range, and a great cost pressure for this commercial application. Consequently, planar antennas are dominating in the lower frequency range, while lens and reflector antennas had been the first choice at 76.5 GHz, partly in folded configurations. With increasing requirements towards a much more detailed observation of the scenery in front or around the vehicle, multibeam antennas or scanning antennas have been designed, and solutions based on (digital) beamforming with a number of integrated antennas are in use or under development. General antenna concepts, partly including some system aspects, as well as three realized antenna configurations will be described in detail in this contribution.
Speech-based Information Retrieval System with Clarification Dialogue Strategy

This paper addresses a dialogue strategy to clarify and constrain the queries for speech-driven document retrieval systems. In spoken dialogue interfaces, users often make utterances before the query is completely generated in their mind; thus input queries are often vague or fragmental. As a result, usually many items are matched. We propose an efficient dialogue framework, where the system dynamically selects an optimal question based on information gain (IG), which represents reduction of matched items. A set of possible questions is prepared using various knowledge sources. As a bottom-up knowledge source, we extract a list of words that can take a number of objects and potentially causes ambiguity, using a dependency structure analysis of the document texts. This is complemented by top-down knowledge sources of metadata and hand-crafted questions. An experimental evaluation showed that the method significantly improved the success rate of retrieval, and all categories of the prepared questions contributed to the improvement.
Wakefulness Affects Synaptic and Network Activity by Increasing Extracellular Astrocyte-Derived Adenosine

Loss of sleep causes an increase in sleep drive and deficits in hippocampal-dependent memory. Both of these responses are thought to require activation of adenosine A1 receptors (adorA1Rs) and release of transmitter molecules including ATP, which is rapidly converted to adenosine in the extracellular space, from astrocytes in a process termed gliotransmission. Although it is increasingly clear that astrocyte-derived adenosine plays an important role in driving the homeostatic sleep response and the effects of sleep loss on memory (Halassa et al., 2009; Florian et al., 2011), previous studies have not determined whether the concentration of this signaling molecule increases in response to wakefulness. Here, we show that the level of adorA1R activation increases in response to wakefulness in mice (Mus musculus). We found that this increase affected synaptic transmission in the hippocampus and modulated network activity in the cortex. Direct biosensor-based measurement of adenosine showed that the net extracellular concentration of this transmitter increased in response to normal wakefulness and sleep deprivation. Genetic inhibition of gliotransmission prevented this increase and attenuated the wakefulness-dependent changes in synaptic and network regulation by adorA1R. Consequently, we conclude that wakefulness increases the level of extracellular adenosine in the hippocampus and that this increase requires the release of transmitters from astroctyes.
Using RTL statespace information and state encoding for induction based property checking

This paper focuses on checking safety properties of sequential circuits specified on the RT-level. We study how different state encodings can be used to create a gate-level representation of the circuit that facilitates the computation of effective invariants for induction-based property checking. Our experiments show the strong impact of state encoding on the efficiency of the induction process.
ANALOGIES : CREATING NEW MUSIC FROM AN EXISTING PERFORMANCE BY CONCATENATIVE SYNTHESIS

This paper describes a method for creating new music by concatenative synthesis. Given a MIDI score and an audio recording of an example piece of monophonic music, our method synthesizes audio to correspond with a new MIDI score. The algorithm we use is based on concatenative synthesis, commonly used for generating speech. Two versions of our algorithm are explored, one in which individual notes from the example piece are concatenated, and one in which pairs of adjacent notes from the example piece are concatenated. We examine the range of example pieces and target scores for which each version of our algorithm yields good results. Our underlying framework remains general enough to be applicable to other problems, such as rendering a stylized version of the target score, and other types of sound analogies.
Non-linear techniques for video de-interlacing

De-interlacing is the ability to estimate one field in a video image using the other field and is a form of interpolation. Such a task is required in many video applications, such as standards conversion. Unfortunately the performance of de-interlacers based on linear filters is unsatisfactory. An alternative is to use non-linear interpolation. Two non-linear techniques are discussed for this problem: Volterra methods and radial basis function networks. Results illustrating the performance of both non-linear methods are presented along with results for linear techniques. The results are judged bearing in mind that a major consideration in the implementation of such nonlinear systems is their computational complexity.
The Effect of Short Fibers in a Cotton on its Processing Efficiency and Product Quality

The conclusions reached by means of miniature spinning techniques with very small samples of cotton were similar to those obtained in Part I : changes in short fiber con tent do not affect the twist required for maximum strength hut do lower strength some what more than 1% for each 1% increase in short fiber content. These samples covered an exceptionally wide range of short fiber contents, from less than 1% to almost 20% by weight of fibers 3 in. and shorter. The very low short fiber content cottons were produced hy careful hand ginning techniques while the re mainder were obtained by differential ginning techniques.
Sintering optimisation and solution annealing of high nitrogen nickel free austenitic stainless steels prepared by PIM

The effects of various sintering parameters (temperature, time and nitrogen pressure) on the density, nitrogen content and the mechanical properties of high nitrogen nickel free austenitic stainless steel (0Cr–17Mn–11Mo–3N) prepared by powder injection moulding were investigated, and the influence of solution annealing on the microstructure and mechanical properties was also discussed. The results show that the optimal sintering conditions are as follows: sintering temperature 1300°C, sintering time 2 h and nitrogen pressure 0·1 MPa, under which a favourable combination of the relative density of 99·1% and the nitrogen content of 0·78 wt-% can be obtained. After solution annealing at 1150°C for 90 min, the yield strength and ultimate tensile strength can reach 580 and 885 MPa respectively, which are about 2·9 and 1·7 times greater than those of 316L Metal Injection Molding (MIM) stainless steel. Before solution annealing, the sintered specimens mainly consist of γ-austenite, α-ferrite and network of Cr2N phase, while after solution annealing, they reveals a fully austenitic structure without any intergranular nitrides.
A Survey of the Eighth National Conference on Artificial Intelligence: Pulling Together or Pulling Apart?

A survey of 150 papers from the Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90) shows that AI research follows two methodologies, each incomplete with respect to the goals of designing and analyzing AI systems but with complementary strengths. I propose a mixed methodology and illustrate it with examples from the Proceedings.
Integrating remote sensing, spatial analysis and certainty factor model for waste dumping risk assessment

Waste dumping is one of the main pollution causing land deterioration and resource depletion. To help manage the environmental protection resource, this study proposed the risk assessment integrating remote sensing and geographic information system (GIS) to predict and map potential waste dumping area. Factors relative to waste dumping were generated with spatial analysis, which quantifies the spatial correlation between waste dumping areas and other land use. The suspected waste dumping mapping with FORMOSAT-2 imagery and hybrid classification was used as the other factor. All factors were then combined with certainty factor (CF) model to generate waste dumping risk map. Validating the result with the 45 waste dumping cases, CF model predicts 75.56% of the waste dumping cases in the very high potential area. The result demonstrated that integrating remote sensing, spatial analysis and CF model for waste dumping risk assessment could be reliable. Future applications include helping inspectors to concentrate the patrol areas, which could save manpower significantly.
Break temperatures of mould fluxes and their relevance to continuous casting

Abstract The break temperatures of mould fluxes are important since they help to control the horizontal heat transfer and lubrication between the steel shell and the mould, and consequently affect occurrences of longitudinal cracking and sticker breakout in continuous casting. Break temperatures T br have been determined for both steady state and dynamic measurement of the viscosity, and equations relating T br to chemical composition have been obtained for both cases. It has been found that T br can be affected by (i) cooling rates and (ii) fluorine losses during the measurements.
Survival and detection of rotaviruses on environmental surfaces in day care centers

Previously, we demonstrated that children in day care centers commonly experience diarrhea due to rotavirus, giardia, and bacterial pathogens. Multiple agents frequently coexist, and the environment is heavily contaminated with enteric bacteria during outbreaks. A study of environmental surface contamination with rotavirus was performed during three non-outbreak periods. Of 25 samples collected from environmental surfaces and teachers hands at a day care center, 4 (16%) were positive for rotavirus antigen when a fluorescence assay was used. We also examined the survival of two animal viruses, rotavirus SA-11 and poliovirus type 1, and bacteriophage 12 on similar environmental surfaces in a laboratory. Poliovirus type 1 and bacteriophage f2 were more resistant to drying than rotavirus SA-11 and could be recovered after a 90-min exposure on a dry surface. Rotavirus SA-11 could be detected for 30 min. All three viruses survived longer when they were suspended in fecal material than when they were suspended in distilled water. These data suggest that several agents, including rotavirus, can remain viable on contaminated surfaces long enough to be transmitted to susceptible children. This finding helps explain why rotavirus shows a mode of spread like that of parasitic and bacterial agents within day care center settings.
Feedback-bus oscillation ring: A general architecture for delay characterization and test of interconnects

In this paper we propose a flexible delay characterization and test architecture, called Feedback-Bus Oscillation Ring (FB-OR), for die-to-die interconnects in a 3D IC. As compared to previous works, it is unique in its ability to streamline the characterization/test operations for a set of arbitrary interconnects with multiple pins sprawling multiple dies. During the Design-for-Testability stage, one common feedback-bus (connected to all dies in the IC under characterization/test) is inserted. Through this feedback-bus, an oscillation ring can be formed dynamically and the Variable-Output-Threshold (VOT) technique can be applied to characterize the delay of one interconnect segment at a time. Experimental results indicate that this method is not only flexible and scalable, but requiring only a small area overhead.
Automatic reconstruction of surfaces and scalar fields from 3D scans

We present an efficient and uniform approach for the automatic reconstruction of surfaces of CAD (computer aided design) models and scalar fields defined on them, from an unorganized collection of scanned point data. A possible application is the rapid computer model reconstruction of an existing part or prototype from a three dimensional (3D) points scan of its surface. Color, texture or some scalar material property of the physical part, define natural scalar fields over the surface of the CAD model. Our reconstruction algorithm does not impose any convexity or differentiability restrictions on the surface of the original physical part or the scalar field function, except that it assumes that there is a sufficient sampling of the input point data to unambiguously reconstruct the CAD model. Compared to earlier methods our algorithm has the advantages of simplicity, efficiency and uniformity (both CAD model and scalar field reconstruction). The simplicity and efficiency of our approach is based on several novel uses of appropriate sub-structures (alpha shapes) of a three-dimensional Delaunay Triangulation, its dual the three-dimensional Voronoi diagram, and dual uses of trivariate Bernstein-Bezier forms. The boundary of the CAD model is modeled using implicit cubic Bernstein-Bezier patches, while the scalar field is reconstructed with functional cubic Bernstein-Bezier patches. CR
A Role for Both Conformational Selection and Induced Fit in Ligand Binding by the LAO Protein

Molecular recognition is determined by the structure and dynamics of both a protein and its ligand, but it is difficult to directly assess the role of each of these players. In this study, we use Markov State Models (MSMs) built from atomistic simulations to elucidate the mechanism by which the Lysine-, Arginine-, Ornithine-binding (LAO) protein binds to its ligand. We show that our model can predict the bound state, binding free energy, and association rate with reasonable accuracy and then use the model to dissect the binding mechanism. In the past, this binding event has often been assumed to occur via an induced fit mechanism because the protein's binding site is completely closed in the bound state, making it impossible for the ligand to enter the binding site after the protein has adopted the closed conformation. More complex mechanisms have also been hypothesized, but these have remained controversial. Here, we are able to directly observe roles for both the conformational selection and induced fit mechanisms in LAO binding. First, the LAO protein tends to form a partially closed encounter complex via conformational selection (that is, the apo protein can sample this state), though the induced fit mechanism can also play a role here. Then, interactions with the ligand can induce a transition to the bound state. Based on these results, we propose that MSMs built from atomistic simulations may be a powerful way of dissecting ligand-binding mechanisms and may eventually facilitate a deeper understanding of allostery as well as the prediction of new protein-ligand interactions, an important step in drug discovery.
An Evaluation of Multiple Imputation for Meta-Analytic Structural Equation Modeling

A simulation study was used to evaluate multiple imputation (MI) to handle MCAR correlations in the first step of meta-analytic structural equation modeling: the synthesis of the correlation matrix and the test of homogeneity. No substantial parameter bias resulted from using MI. Although some SE bias was found for meta-analyses involving smaller numbers of studies, the homogeneity test was never rejected when using MI.
Containment of Partially Specified Tree-Pattern Queries

Nowadays, huge volumes of data, including scientific data, are organized or exported in tree-structured form. Querying capabilities are provided through tree-pattern queries. The need for integrating multiple data sources with different tree structures has driven, recently, the suggestion of query languages that relax the complete specification of a tree pattern. In this paper we adopt a query language with partially specified tree-pattern queries. A central feature of this type of queries is that the structure can be specified fully, partially, or not at all in a query. Important issues in query optimization require solving the query containment problem. We study the containment problem for partially specified tree-pattern queries. To support the evaluation of such queries, we use semantically rich constructs, called dimension graphs, which abstract structural information of the tree-structured data. We address the problem of query containment in the absence (absolute query containment) and in the presence (relative query containment) of dimension graphs, and we provide necessary and sufficient conditions for each type of query containment. We suggest a technique for relative query containment checking based on structural information extracted in advance from the dimension graph. Our approach is implemented and validated, through extensive experimental evaluation
Selenium and Mercury in the Brazilian Amazon: Opposing Influences on Age-Related Cataracts

Background Age-related cataracts (ARCs) are an important cause of blindness in developing countries. Although antioxidants may be part of the body’s defense to prevent ARC, environmental contaminants may contribute to cataractogenesis. In fish-eating populations of the lower Tapajós region, elevated exposure to mercury (Hg) has been reported, and blood levels of selenium (Se) range from normal to very high (> 1,000 μg/L). Objectives We examined ARCs in relation to these elements among adults (≥ 40 years of age) from 12 riverside communities. Methods Participants (n = 211) provided blood samples and underwent an extensive ocular examination. Inductively coupled plasma mass spectrometry was used to assess Hg and Se in blood and plasma. Results One-third (n = 69; 32.7%) of the participants had ARC. Lower plasma Se (P-Se; < 25th percentile, 110 μg/L) and higher blood Hg (B-Hg; ≥ 25th percentile, 25 μg/L) were associated with a higher prevalence odds ratio (POR) of ARC [adjusted POR (95% confidence interval), 2.69 (1.11–6.56) and 4.45 (1.43–13.83), respectively]. Among participants with high P-Se, we observed a positive but nonsignificant association with high B-Hg exposure, whereas among those with low B-Hg, we observed no association for P-Se. However, compared with the optimum situation (high P-Se, low B-Hg), the POR for those with low P-Se and high B-Hg was 16.4 (3.0–87.9). This finding suggests a synergistic effect. Conclusion Our results suggest that persons in this population with elevated Hg, the cataractogenic effects of Hg may be offset by Se. Because of the relatively small sample size and possible confounding by other dietary nutrients, additional studies with sufficient power to assess multiple nutrient and toxic interactions are required to confirm these findings.