Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-term cost-effectiveness of collaborative care (vs usual care) for people with depression and comorbid diabetes or cardiovascular disease: a Markov model informed by the COINCIDE randomised controlled trial

Objectives To evaluate the long-term cost-effectiveness of collaborative care (vs usual care) for treating depression in patients with diabetes and/or coronary heart disease (CHD). Setting 36 primary care general practices in North West England. Participants 387 participants completed baseline assessment (collaborative care: 191; usual care: 196) and full or partial 4-month follow-up data were captured for 350 (collaborative care: 170; usual care: 180). 62% of participants were male, 14% were non-white. Participants were aged ≥18 years, listed on a Quality and Outcomes Framework register for CHD and/or type 1 or 2 diabetes mellitus, with persistent depressive symptoms. Patients with psychosis or type I/II bipolar disorder, actively suicidal, in receipt of services for substance misuse, or already in receipt of psychological therapy for depression were excluded. Intervention Collaborative care consisted of evidence-based low-intensity psychological treatments, delivered over 3 months and case management by a practice nurse and a Psychological Well Being Practitioner. Outcome measures As planned, the primary measure of cost-effectiveness was the incremental cost-effectiveness ratio (cost per quality-adjusted life year (QALY)). A Markov model was constructed to extrapolate the trial results from short-term to long-term (24 months). Results The mean cost per participant of collaborative care was £317 (95% CI 284 to 350). Over 24 months, it was estimated that collaborative care was associated with greater healthcare usage costs (net cost £674 (95% CI −30 953 to 38 853)) and QALYs (net QALY gain 0.04 (95% CI −0.46 to 0.54)) than usual care, resulting in a cost per QALY gained of £16 123, and a likelihood of being cost-effective of 0.54 (willingness to pay threshold of £20 000). Conclusions Collaborative care is a potentially cost-effective long-term treatment for depression in patients with comorbid physical and mental illness. The estimated cost per QALY gained was below the threshold recommended by English decision-makers. Further, long-term primary research is needed to address uncertainty associated with estimates of cost-effectiveness. Trial registration number ISRCTN80309252; Post-results.
Pronominal Reference and Pragmatic Enrichment: A Bayesian Account

A standard assumption in linguistic, psycholinguistic, and computational research on pronoun use is that production and interpretation are guided by the same set of contextual factors. Kehler et al. (2008) and Kehler & Rohde (2013) have argued instead for a Bayesian model, one in which pronoun production is insensitive to a class of semanticallyand pragmaticallydriven contextual biases that have been shown to influence pronoun interpretation. Here we evaluate the model using a passage completion study that employs a subtle contextual manipulation to which traditional analyses are insensitive, specifically by varying whether or not a relative clause that modifies the direct object in the context sentence invites the inference of a cause of the event that the sentence denotes. The results support the claim that pronoun interpretation biases, but not production biases, are sensitive to this pragmatic enrichment, revealing precisely the asymmetry predicted by the Bayesian analysis. A correlation analysis further establishes that the model provides better estimates of measured pronoun interpretation biases than two competing models from the literature.
Reconstruction of Cellular Signal Transduction Networks Using Perturbation Assays and Linear Programming

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4+ T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.
Sparse Recovery of Fusion Frame Structured Signals

Fusion frames are collection of subspaces which provide a redundant representation of signal spaces. They generalize classical frames by replacing frame vectors with frame subspaces. This paper considers the sparse recovery of a signal from a fusion frame. We use a block sparsity model for fusion frames and then show that sparse signals under this model can be compressively sampled and reconstructed in ways similar to standard Compressed Sensing (CS). In particular we invoke a mixed l1/l2 norm minimization in order to reconstruct sparse signals. In our work, we show that assuming a certain incoherence property of the subspaces and the apriori knowledge of it allows us to improve recovery when compared to the usual block sparsity case.
t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data

Microarray data analysis typically consists in identifying a list of differentially expressed genes (DEG), i.e., the genes that are differentially expressed between two experimental conditions. Variance shrinkage methods have been considered a better choice than the standard t-test for selecting the DEG because they correct the dependence of the error with the expression level. This dependence is mainly caused by errors in background correction, which more severely affects genes with low expression values. Here, we propose a new method for identifying the DEG that overcomes this issue and does not require background correction or variance shrinkage. Unlike current methods, our methodology is easy to understand and implement. It consists of applying the standard t-test directly on the normalized intensity data, which is possible because the probe intensity is proportional to the gene expression level and because the t-test is scale- and location-invariant. This methodology considerably improves the sensitivity and robustness of the list of DEG when compared with the t-test applied to preprocessed data and to the most widely used shrinkage methods, Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA). Our approach is useful especially when the genes of interest have small differences in expression and therefore get ignored by standard variance shrinkage methods.
Structural Integrity Assessment Using In-Situ Acoustic Emission Monitoring

The work presented in this paper is focused on monitoring fatigue crack growth in metallic structures using acoustic emission (AE) technology. Three different methods are proposed to utilize the information obtained from in-situ monitoring for structural health management. Fatigue crack growth tests with real-time acoustic emissions monitoring are conducted on CT specimens made of 7075 aluminum. Proper filtration of the resulting AE signals reveals a log-linear relationship between fracture parameters ( da dN ⁄ and ΔK ) and select AE features; a flexible statistical model is developed to describe the relationship between these parameters. Bayesian inference is used to estimate the model parameters from experimental data. The model is then used to calculate two important quantities that can be used for structural health management: (a) an AE-based instantaneous damage severity index, and (b) an AE-based estimate of the crack size distribution at a given point in time, assuming a known initial crack size distribution. Finally, recursive Bayesian estimation is used for online integration of the structural health assessment information obtained from AE monitoring with crack size estimates obtained from empirical crack growth model. The evidence used in Bayesian updating includes observed crack sizes and/or crack growth rate observations.
Mental ill-health in adults with intellectual disabilities: prevalence and associated factors

Background Reported prevalence of mental ill-health among adults with intellectual disabilities ranges from 7 to 97%, owing to methodological limitations. Little is known about associations. Aims To determine the prevalence of mental ill-health in adults with intellectual disabilities and to investigate factors independently associated with it. Method Population-based study (n=1023) with comprehensive individual assessments modelled using regression analyses. Results Point prevalence of mental ill-health was 40.9% (clinical diagnoses), 35.2%(DC–LD), 16.6% (ICD–10–DCR) and 15.7% (DSM–IV–TR). The most prevalent type was problem behaviours. Mental ill-health was associated with more life events, female gender, type of support, lower ability, more consultations, smoking, incontinence, not having severe physical disabilities and not having immobility; it was not associated with deprived areas, no occupation, communication impairment, epilepsy, hearing impairment or previous institutional residence. Conclusions This investigation informs further longitudinal study, and development of appropriate interventions, public health strategy and policy. ICD–10–DCR and DSM–IV–TR undercount mental ill-health in this population compared with DC–LD.
Next-generation sequencing: advances and applications in cancer diagnosis

Technological advances have led to the introduction of next-generation sequencing (NGS) platforms in cancer investigation. NGS allows massive parallel sequencing that affords maximal tumor genomic assessment. NGS approaches are different, and concern DNA and RNA analysis. DNA sequencing includes whole-genome, whole-exome, and targeted sequencing, which focuses on a selection of genes of interest for a specific disease. RNA sequencing facilitates the detection of alternative gene-spliced transcripts, posttranscriptional modifications, gene fusion, mutations/single-nucleotide polymorphisms, small and long noncoding RNAs, and changes in gene expression. Most applications are in the cancer research field, but lately NGS technology has been revolutionizing cancer molecular diagnostics, due to the many advantages it offers compared to traditional methods. There is greater knowledge on solid cancer diagnostics, and recent interest has been shown also in the field of hematologic cancer. In this review, we report the latest data on NGS diagnostic/predictive clinical applications in solid and hematologic cancers. Moreover, since the amount of NGS data produced is very large and their interpretation is very complex, we briefly discuss two bioinformatic aspects, variant-calling accuracy and copy-number variation detection, which are gaining a lot of importance in cancer-diagnostic assessment.
Genetic and Environmental Etiology of Infant Hemodynamic Response to Speech Stimuli: A Near-Infrared Spectroscopy Study of Twins

For adults and children, genetic and environmental factors are known to affect brain structure and neural activity necessary for conducting various cognitive tasks. However, little is known regarding genetic and environmental contributions to individual differences in neural activity during the first two years of life. Concentrations of oxygenated and deoxygenated hemoglobin were measured bilaterally over temporal areas of 7 monozygotic and 17 dizygotic twin pairs using near-infrared spectroscopy. Results showed that environmental influences on the concentration of hemoglobin were larger than for genetic influences. Significant genetic and environmental influences were detected in different temporal areas. We discuss the genetic and environmental influences on the hemodynamic response to speech stimuli during the first two years of life.
Sedimentary and particulate organic matter : mixed sources for cockle Cerastoderma glaucum in a shallow pond, Western Mediterranean

Seasonal changes in feeding habits and diet of the cockle Cerastoderma glaucum (Mollusca, Bivalvia) were analysed using carbon (δ 13 C) and nitrogen (δ 15 N) stable isotopes. I aimed to investigate the role of benthic and pelagic sources in the diet of this dominant infaunal bivalve on a western Mediterranean sandy bottomed pond. Adult C. glaucum and all potential organic sources (particulate and sedimentary organic matter, seagrass, macroalgae, het- erotrophic detritus) were collected and analysed for δ 13 Ca ndδ 15 N. In total 5 dominant organic sources were found, ranging between -21.0 and -8.0%� for δ 13 C and from 3.0 to about 7.0%� for δ 15 N. C. glaucum assimilated fraction ranged between -14.0/-15.0%� and 6.0/9.0%� respectively, for carbon and nitrogen, while its estimated fractionation seasonally varied between 1 and 1.5 for carbon and was about 3 for nitrogen. C. glaucum reflected the isotopic com- position of its food while maintaining, throughout the year, a fairly constant isotopic composition in its assimilated fraction, despite the high variability in isotopic composition of available sources.
Distance Computation and Routing with Small Messages

We consider shortest paths computation and related tasks from the viewpoint of network algorithms, where the n-node input graph is also the computational system: nodes represent processors and edges represent communication links, which can in each time step carry an O(log n)-bit message. We identify several basic distributed distance computation tasks that are highly useful in the design of more sophisticated algorithms and provide efficient solutions. We showcase the utility of these tools by means of several applications. keywords: CONGEST model, source detection, skeleton spanner, compact routing, all-pairs shortest paths, single-souce shortest paths This article is based on preliminary results appearing at conferences [32,34,35]. This work has been supported by the Swiss National Science Foundation (SNSF), the Swiss Society of Friends of the Weizmann Institute of Science, the Deutsche Forschungsgemeinschaft (DFG, reference number Le 3107/1-1), the Israel Science Foundation (grants 894/09 and 1444/14), the United States-Israel Binational Science Foundation (grant 2008348), the Israel Ministry of Science and Technology (infrastructures grant), the Citi Foundation, and the I-CORE program of the Israel PBC and ISF (grant 4/11). Christoph Lenzen MPI for Informatics Campus E1.4, 66123 Saarbrücken, Germany email: clenzen@mpi-inf.mpg. de phone: 0049 681 9325 1008 fax: 0049 681 9325 199 Boaz Patt-Shamir School of Electrical Engineering Tel Aviv University, Tel Aviv 69978, Israel David Peleg Faculty of Mathematics and Computer Science Weizmann Institute of Science, Rehovot 76100, Israel
Development of a UPLC-TQ/MS Approach for the Determination of Eleven Bioactive Components in Haizao Yuhu Decoction Plus-Minus Haizao and Gancao Drug Combination after Oral Administration in a Rat Model of Hypothyroidism

Haizao Yuhu Decoction (HYD) has been used for approximately 500 years and is well-known in Traditional Chinese Medicine for its efficacy in the treatment of thyroid-related diseases. In this study, a rapid liquid chromatography-tandem mass spectrometry method was developed for the determination of liquiritin, naringin, hesperidin, peimine, liquiritigenin, glycyrrhizic acid, bergapten, nobiletin, osthole, and glycyrrhetinic acid in rat plasma to investigate the pharmacokinetic profile of different HYD prescriptions in a rat model of hypothyroidism. The differences in pharmacokinetic parameters among the groups were compared by Student’s t-test. The pharmacokinetic profile of liquiritin, naringin, hesperidin, peimine, liquiritigenin, glycyrrhizic acid, bergapten, nobiletin, osthole, and glycyrrhetinic acid showed significant differences between Haizao and Gancao anti-drug combination and other herbs in HYD. These results may contribute to the rational clinical use of HYD and reveal the compatibility profile of the Haizao and Gancao anti-drug combination.
Role of correlation in the operation of quantum-dot cellular automata

Quantum-dot cellular automata (QCA) may offer a viable alternative of traditional transistor-based technology at the nanoscale. When modeling a QCA circuit, the number of degrees of freedom necessary to describe the quantum mechanical state increases exponentially making modeling even modest size cell arrays difficult. The intercellular Hartree approximation largely reduces the number of state variables and still gives good results especially when the system remains near ground state. This suggests that a large part of the correlation degrees of freedom are not essential from the point of view of the dynamics. In certain cases, however, such as, for example, the majority gate with unequal input legs, the Hartree approximation gives qualitatively wrong results. An intermediate model is constructed between the Hartree approximation and the exact model, based on the coherence vector formalism. By including correlation effects to a desired degree, it improves the results of the Hartree method and gives the ap.
Preliminary Study of Characterization of Nanoparticles from Coconut Shell as Filler Agent in Composites Materials

Agricultural wastes which include shell of coconut dry fruits (CS) can be used to prepare filler in polymer composite for commercial use. The raw CS was converted into nanoparticle in 4 steps, namely, grinding, refining, sieving and high energy ball mill. The CSNs was extracted by n-hexane for oil removal process. The presence of the oil was studied by Transmission Electron Microscopy (TEM) and Energy Dispersive X-ray analysis (EDX) to identify the existence of the oil within the nanoparticle. The decomposition temperature of the nanoparticle was studied by thermal gravimetric analysis (TGA). The nanoparticle size obtained from TEM, X-ray Diffraction (XRD) analysis and particle size analyzer was found to be 10-30 nm, 21.61- 44.46 nm and 50.75-91.28 nm (with nano size distribution intensity of 75.30%) respectively. The nanoparticle CS exhibits lower degree of crystallinity, or higher of amorphous area. The nanoparticle CS shape and surface was found to be smaller with angular, irregular and crushed shapes after been ball milling process.
A Clipper-free Algorithm for Efficient HW-Implementation of Local Dimming LED-Backlight

In this paper, we present algorithms for the calculation of local dimming LED-Backlight. They assure clipper-free results and can be implemented at low HW- costs. The power saving is in average 38.7% compared to global dimming. For a XGA display 72K (RGB) logic gates are needed to implement this algorithm on chip.
New method of analysis of polymer modified bitumen microstructure

The paper presents a new method of assessment of polymer modified bitumen microstructure. Properties of microstructure of polymer modified bitumen and factors influencing propertes of polymer-bitumen system are discussed. Two methods of evaluations of microstructure are presented: the qualitative method based on the model images and the quantitative method based on the mathematical description of polymer particle dispersed in bitumen matrix. Morphological operations performed on captured images in order to separate polymer phase dispersed in bitumen are described. In this study images obtained from fluorescent microscope are analysed with computer image analysis program. The computer image analysis method enables automation of the processing of large number of images and allows an exclusion of human suggestion factor.
Remaining Life Prognostics for an Army Ground Vehicle System

Reliability is a key parameter for the development of safe and effective military vehicles with a reasonable life cycle cost. One innovative technology that is being promoted in the Department of Defense is the use of Health and Usage Monitoring Systems and remaining life prognostics to improve reliability and availability. The feasibility of using data collected from a limited set of existing and simple add-on sensors to make fatigue damage estimations on a complexly loaded component within a military wheeled vehicle system was investigated. Methods for identifying the critical inputs for fatigue estimation are evaluated and compared. A baseline physics of failure analysis was performed on an example component to evaluate the proposed HUMS algorithms and demonstrate the accuracy of resulting fatigue predictions.
Effect of addition amount and fineness of phosphorus slag on physical performance of moderate heat Portland cement

The effect of fineness of phosphorus slag and content on performance of phosphorus slag moderate heat Portland cement was studied.The result showed that the setting time of phosphorus slag cement prolonged with the slag content increased and fineness increased,and decreased before increased with the fineness of slag incresed,while the soundness of the cement was qualified.In order to satisfy the demands of construction and mechanical without activator,it was necessary to reduce the content of phosphorus slag to about 20% or less.With the increasing of fineness,the ratio of dry shrinkage of phosphorus slag cement at 7d,14d and 28d showed a "V" trend,and after 14d the dry shrinkage became constant.Also the retardation mechanism and strength of phosphorus slag moderate heat Portland cement were studied by XRD,SEM and the research on grindability of phosphorus slag.
Design and Implementation of a YARP Device Driver Interface: The Depth-Sensor Case

This work illustrates the design phases leading to the development of a new YARP device interface along with its client/server implementation. In order to obtain a smoother integration and a more reliable software usability, while avoiding common errors during the design phases, a new interface is created in the YARP network when a new family of devices is introduced.