Miracle-dz/UniFAR-FTUs huggingface dataset:
Adjusted Drug Treatment Is Superior to Renal Sympathetic Denervation in Patients With True Treatment-Resistant Hypertension

&NA; We aimed to investigate for the first time the blood pressure (BP)–lowering effect of renal sympathetic denervation (RDN) versus clinically adjusted drug treatment in true treatment-resistant hypertension (TRH) after excluding patients with confounding poor drug adherence. Patients with apparent TRH (n=65) were referred for RDN, and those with secondary and spurious hypertension (n=26) were excluded. TRH was defined as office systolic BP (SBP) >140 mm Hg, despite maximally tolerated doses of ≥3 antihypertensive drugs including a diuretic. In addition, ambulatory daytime SBP >135 mm Hg after witnessed intake of antihypertensive drugs was required, after which 20 patients had normalized BP and were excluded. Patients with true TRH were randomized and underwent RDN (n=9) performed with Symplicity Catheter System versus clinically adjusted drug treatment (n=10). The study was stopped early for ethical reasons because RDN had uncertain BP-lowering effect. Office SBP and diastolic BP in the drug-adjusted group changed from 160±14/88±13 mm Hg (±SD) at baseline to 132±10/77±8 mm Hg at 6 months (P<0.0005 and P=0.02, SBP and diastolic BP, respectively) and in the RDN group from 156±13/91±15 to 148±7/89±8 mm Hg (P=0.42 and P=0.48, SBP and diastolic BP, respectively). SBP and diastolic BP were significantly lower in the drug-adjusted group at 6 months (P=0.002 and P=0.004, respectively), and absolute changes in SBP were larger in the drug-adjusted group (P=0.008). Ambulatory BPs changed in parallel to office BPs. Our data suggest that adjusted drug treatment has superior BP lowering effects compared with RDN in patients with true TRH. Clinical Trial Registration— URL: http://www.clinicaltrials. gov. Unique identifier: NCT01673516
Historical, psychopathological, neurological, and neuropsychological aspects of deficit schizophrenia: a multicenter study.

OBJECTIVE This multicenter study aimed to verify whether the historical and psychopathological characteristics of a large group of patients with deficit schizophrenia were consistent with those reported in previous studies. The authors also tested the hypothesis that neurological and neuropsychological indices sensitive to frontoparietal dysfunction, but not those sensitive to temporal lobe dysfunction, are more impaired in patients with deficit schizophrenia than in those with non-deficit schizophrenia. METHOD For each patient with deficit schizophrenia enrolled in the study, a matched subject with non-deficit schizophrenia was recruited. Historical, psychopathological, neurological, and neuropsychological evaluations were carried out for all patients. RESULTS Patients with deficit schizophrenia, compared with patients with non-deficit schizophrenia, had a similar severity of positive symptoms and disorganization and less hostility. They had poorer premorbid adjustment during childhood and early adolescence and exhibited more impairment in general cognitive abilities. The deficit state was associated with impairment in sequencing of complex motor acts, which suggests frontoparietal dysfunction. CONCLUSIONS Previous reports of differences in historical, psychopathological, and neuropsychological characteristics between patients with deficit schizophrenia and those with non-deficit schizophrenia were mostly supported by the present findings. Neurological findings suggest that frontoparietal functioning is more impaired in patients with deficit schizophrenia. Deficit schizophrenia might represent a neurodevelopmental subtype of schizophrenia in which significant behavioral and cognitive impairment since childhood compromises the development of basic capacities relevant to subsequent cognitive and social functioning.
SenseCode: Network coding for reliable sensor networks

Designing a communication protocol for sensor networks often involves obtaining the right trade-off between energy efficiency and end-to-end packet error rate. In this article, we show that network coding provides a means to elegantly balance these two goals. We present the design and implementation of SenseCode, a collection protocol for sensor networks—and, to the best of our knowledge, the first such implemented protocol to employ network coding. SenseCode provides a way to gracefully introduce a configurable amount of redundant information into the network, thereby decreasing end-to-end packet error rate in the face of packet loss. We compare SenseCode to the best (to our knowledge) existing alternative and show that it reduces end-to-end packet error rate in highly dynamic environments, while consuming a comparable amount of network resources. We have implemented SenseCode as a TinyOS module and evaluate it through extensive TOSSIM simulations.
TreeJuxtaposer: scalable tree comparison using Focus+Context with guaranteed visibility

Structural comparison of large trees is a difficult task that is only partially supported by current visualization techniques, which are mainly designed for browsing. We present TreeJuxtaposer, a system designed to support the comparison task for large trees of several hundred thousand nodes. We introduce the idea of "guaranteed visibility", where highlighted areas are treated as landmarks that must remain visually apparent at all times. We propose a new methodology for detailed structural comparison between two trees and provide a new nearly-linear algorithm for computing the best corresponding node from one tree to another. In addition, we present a new rectilinear Focus+Context technique for navigation that is well suited to the dynamic linking of side-by-side views while guaranteeing landmark visibility and constant frame rates. These three contributions result in a system delivering a fluid exploration experience that scales both in the size of the dataset and the number of pixels in the display. We have based the design decisions for our system on the needs of a target audience of biologists who must understand the structural details of many phylogenetic, or evolutionary, trees. Our tool is also useful in many other application domains where tree comparison is needed, ranging from network management to call graph optimization to genealogy.
Bayesian Locality Sensitive Hashing for Fast Similarity Search

Given a collection of objects and an associated similarity measure, the all-pairs similarity search problem asks us to find all pairs of objects with similarity greater than a certain user-specified threshold. Locality-sensitive hashing (LSH) based methods have become a very popular approach for this problem. However, most such methods only use LSH for the first phase of similarity search - i.e. efficient indexing for candidate generation. In this paper, we present BayesLSH, a principled Bayesian algorithm for the subsequent phase of similarity search - performing candidate pruning and similarity estimation using LSH. A simpler variant, BayesLSH-Lite, which calculates similarities exactly, is also presented. Our algorithms are able to quickly prune away a large majority of the false positive candidate pairs, leading to significant speedups over baseline approaches. For BayesLSH, we also provide probabilistic guarantees on the quality of the output, both in terms of accuracy and recall. Finally, the quality of BayesLSH's output can be easily tuned and does not require any manual setting of the number of hashes to use for similarity estimation, unlike standard approaches. For two state-of-the-art candidate generation algorithms, AllPairs and LSH, BayesLSH enables significant speedups, typically in the range 2x-20x for a wide variety of datasets.
Multilayer VLSI layout for interconnection networks

Current VLSI technology allows more than two wiring layers and the number is expected to rise in future. In this paper we show that, by designing VLSI layouts directly for an L-layer model, the layout area for a variety of networks can be reduced by a factor of about (L/2)/sup 2/ compared to the layout area required under a 2-layer model, and the volume and maximum wire length can be reduced by a factor of about L/2, leading to considerably lower cost and/or higher performance. The proposed layouts for k-ary n-cubes, hypercubes, butterfly networks, cube-connected cycles (CCC), folded hypercubes, generalized hypercubes, k-ary n-cube cluster-c, hierarchical hypercube networks, reduced hypercubes, hierarchical swap networks, and indirect swap networks, are the best layouts reported for these networks thus far and are optimal within a small constant factor under both the Thompson model and the multilayer grid model. All of our layouts are optimally scalable in that we can allow each network node to occupy the largest possible area (e.g., o(N/L/sup 2/) for hypercubes) without increasing the leading constant of the layout area, volume, or maximum wire length.
Levothyroxine Treatment in Pregnancy: Indications, Efficacy, and Therapeutic Regimen

The prevalence of overt and subclinical hypothyroidism during pregnancy is estimated to be 0.3–0.5% and 2–3%, respectively. Thyroid autoantibodies are found in 5–18% of women in the childbearing age. The aim of this review is to underscore the clinical significance of these findings on the health of both the mother and her offspring. Methods of evaluation of thyroid function tests (TFTs) during pregnancy are described as are the threshold values for the diagnosis of overt and subclinical hypothyroidism or hypothyroxinemia. Anticipated differences in TFTs in iodine-sufficient and iodine-deficient areas are discussed and data are provided on potential complications of hypothyroidism/hypothyroxinemia and autoimmune thyroid disease during pregnancy and adverse effects for the offspring. The beneficial effects of levothyroxine therapy on pregnancy outcomes and offspring development are discussed with a proposed treatment regimen and follow up strategy.
Research on a Direct-Drive Wave Energy Converter Using an Outer-PM Linear Tubular Generator

An outer-permanent magnet tubular linear generator has been designed to increase the power density and distance of relative movement. The design of the two buoys has been completed. This paper describes the detailed design process of the proposed generator. The magnetic network model of the proposed generator is implemented to analyze the performance. Considering the cogging force and voltage, the linear generator has been optimized and the final parameters have been determined. Based on the design results, the integrated wave converter system has been manufactured and put into China’s Yellow Sea. The measured voltage is highly consistent with the simulation data. All of results show that the proposed generator is well suitable for wave energy conversion.
Towards Dynamical Seasonal Forecast of Extratropical Transition in the North Atlantic

Extratropical transition can extend the threat of tropical cyclones into the midlatitudes and modify it through expansion of rainfall and wind fields. Despite the scientific and socioeconomic interest, the seasonal forecast of extratropical transition has received little attention. The GFDL High‐Resolution Forecast‐Oriented Low Ocean Resolution (FLOR) model (HiFLOR) shows skill in seasonal forecasts of tropical cyclone frequency as well as major hurricanes. A July‐initialized 12‐member ensemble retrospective seasonal forecast experiment with HiFLOR in the North Atlantic is conducted, representing one of the very first attempts to predict the extratropical transition activity months in advance. HiFLOR exhibits retrospective skill in seasonal forecasts of basin‐wide and regional ET activity relative to best track and reanalysis data. In contrast, the skill of HiFLOR in predictions of non‐ET activity is limited. Future work targeted at improved predictions of non‐ET storms provides a path for enhanced TC activity forecasting.
Compilation of LTL Goal Formulas into PDDL

Temporally extended goals are used in planning to express safety and maintenance conditions. Linear temporal logic is the language often used to express temporally extended goals. We present a method for compiling LTL goal formulas into Planning Domain Definition Language (PDDL), which is handled by many AI planners. The compilation process first constructs a finite state machine representing all reachable progressions of the goal formula, then modifies the planning domain and problem definition so that the state of the FSM is tracked.
AirSWOT InSAR Mapping of Surface Water Elevations and Hydraulic Gradients Across the Yukon Flats Basin, Alaska

AirSWOT, an experimental airborne Ka‐band interferometric synthetic aperture radar, was developed for hydrologic research and validation of the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission (to be launched in 2021). AirSWOT and SWOT aim to improve understanding of surface water processes by mapping water surface elevation (WSE) and water surface slope (WSS) in rivers, lakes, and wetlands. However, the utility of AirSWOT for these purposes remains largely unexamined. We present the first investigation of AirSWOT WSE and WSS surveys over complex, low‐relief, wetland‐river hydrologic environments, including (1) a field‐validated assessment of AirSWOT WSE and WSS precisions for lakes and rivers in the Yukon Flats Basin, an Arctic‐Boreal wetland complex in eastern interior Alaska; (2) improved scientific understanding of surface water flow gradients and the influence of subsurface permafrost; and (3) recommendations for improving AirSWOT precisions in future scientific and SWOT validation campaigns. AirSWOT quantifies WSE with an RMSE of 8 and 15 cm in 1 and 0.0625 km2 river reaches, respectively, and 21 cm in lakes. This indicates good utility for studying hydrologic flux, WSS, geomorphic processes, and coupled surface/subsurface hydrology in permafrost environments. This also suggests that AirSWOT supplies sufficient precision for validating SWOT WSE and WSS over rivers, but not lakes. However, improvements in sensor calibration and flight experiment design may improve precisions in future deployments as may modifications to data processing. We conclude that AirSWOT is a useful tool for bridging the gap between field observations and forthcoming global SWOT satellite products.
TriAL-QL: Distributed Processing of Navigational Queries

Navigational queries are among the most natural query patterns for RDF data, but yet most existing RDF query languages fail to cover all the varieties inherent to its triple-based model, including SPARQL 1.1 and its derivatives. As a consequence, the development of more expressive RDF languages is of general interest. With TriAL* [14], there exists an expressive algebra which subsumes many previous approaches, while adding novel features that are not expressible in most other RDF query languages based on the standard graph model. However, its algebraic notation is inappropriate for practical usage and it is not supported by any existing RDF triple store. In this paper, we propose TriAL-QL, an easy to write and grasp language for TriAL*, preserving its compositional algebraic structure. We present an implementation based on Impala, a massive parallel SQL query engine on Hadoop, using an optimized semi-naive evaluation for the recursive fragments of TriAL*. This way, we support both data-intensive ETL-like workloads and explorative ad-hoc style queries. To demonstrate the scalability and expressiveness of our approach, we conducted experiments on generated social networks with up to 1.8 billion triples and compared different execution strategies to a Hive-based solution.
Mining Operational Preconditions

A procedure’s client must satisfy its precondition— that is, reach a state in which the procedure may be called. Preconditions describe the state that needs to be reached, but not how to reach it. We use static analysis to infer the sequence of operations a variable goes through before being used as a parameter: “In parseProperties(String xml), the parameter xml normally stems from getProperties(). ” Such operational preconditions can be learned from code examples and checked to detect anomalies. Applied to AJ, our OP-M prototype found 288 violations of operational preconditions, uncovering 9 unique defects and 48 unique code smells.
Hydros Soil Moisture Retrieval Algorithms: Status and Relevance to Future Missions

In 2002 the Hydrosphere State Mission (Hydros) was selected by NASA as the alternate mission for a flight opportunity under its Earth System Science Pathfinder program. The Hydros mission objective was to collect the first global scale measurements of the Earth's soil moisture and land surface freeze/thaw conditions, using a combined L band radiometer and radar system operating at 1.41 and 1.26 GHz, respectively. Although NASA cancelled the Hydros mission in December 2005 due to insufficient funding and its reversion back to alternate mission status, the development of accurate soil moisture retrieval algorithms and associated error analyses begun under the Hydros project are still relevant to SMOS and to other potential future soil moisture missions.
A new crossover technique for Cartesian genetic programming

Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped to create the offspring. Later Miller and Thomson introduced Cartesian Genetic Programming, which uses directed graphs as a representation to replace the tree structures originally introduced by Koza. Cartesian Genetic Programming has been shown to perform better than the traditional Genetic Programming; but it does not use crossover to create offspring, it is implemented using mutation only. In this paper a new crossover method in Genetic Programming is introduced. The new technique is based on an adaptation of the Cartesian Genetic Programming representation and is tested on two simple regression problems. It is shown that by implementing the new crossover technique, convergence is faster than that of using mutation only in the Cartesian Genetic Programming method.
Effect of Speed and Torque on Statistical Parameters in Tapered Bearing Fault Detection

The effect of the rotational speed and axial torque on the diagnostics of tapered rolling element bearing defects was investigated. The accelerometer was mounted on the bearing housing and connected to Sound and Vibration Analyzer (SVAN 958) and was used to measure the accelerations from the bearing housing. The data obtained from the bearing was processed to detect damage of the bearing using statistical tools and the results were subsequently analyzed to see if bearing damage had been captured. From this study it can be seen that damage is more evident when the bearing is loaded. Also, at the incipient stage of damage the crest factor and kurtosis values are high but as time progresses the crest factors and kurtosis values decrease whereas the peak and RMS values are low at the incipient stage but increase with damage. Keywords—crest factor, damage detection, kurtosis, RMS, tapered roller bearing.
An exploration of nurse-physician perceptions of collaborative behaviour

ABSTRACT Interprofessional collaboration is a key element in providing safe, holistic patient care in the acute care setting. Trended data at a community hospital indicated opportunities for improvement in collaboration on micro, meso, and macro levels. The aim of this survey study was to assess the current state of collaboration between frontline nurses and physicians at a non-academic acute care hospital. A convenience sample of participants was recruited with a final respondent sample of 355 nurses and 82 physicians. The results indicated that physicians generally perceived greater collaboration than nurses. Physician ratings did not vary by primary practice area, whereas nurse ratings varied by clinical practice area. Nurse ratings were the lowest in the operating room and the highest in the emergency department. Text-based responses to an open-ended question were analysed by role and coded by two independent research teams. Emergent themes emphasised the importance of rounding, roles, respect, and communication. Despite recognition of the need for improved collaboration and relational behaviours, strategies to improve collaborative practice must be fostered at the meso level by organisational leaders and customised to address micro-level values. At the study site, findings have been used to address and improve collaboration towards the goal of becoming a high reliability organisation.
A Spectral Clustering Approach to Validating Sensors via Their Peers in Distributed Sensor Networks

In a distributed sensor network, the goodness of a sensor may change according to its current device status (e.g. health of hardware) and environment (e.g. wireless reception conditions at the sensor location). As a result, it is often necessary to validate periodically sensors in the field, in order to identify those which no longer work properly and eliminate them from applications' use. In this paper, we describe a spectral clustering approach of using peer sensors to identify these bad sensors. Using a simple model problem, we describe how our sensor validation method works and demonstrate its performance in simulation.
Complement levels and risk of organ involvement in patients with systemic lupus erythematosus

Objective Complement plays a major role in SLE. Complement participation has been linked to disease activity and damage. Our objective was to estimate the association of complement behaviour with clinical manifestations, visceral injury and mortality in patients with SLE. Methods Complement determinations (C3 and C4 levels) were analysed in patients with SLE (fulfilling American College of Rheumatology (ACR) or Systemic Lupus International Collaborating Clinics (SLICC)criteria) seen at a university hospital between 2000 and 2013. Patients were grouped in those with permanent C3 and/or C4 low values (low complement group), those with C3 and C4 constant normal values (normal complement group) and those with fluctuant values (periods of normal and periods of low values: fluctuant group). Clinical characteristics and mortality were analysed and compared between groups. Results 270 patients with SLE were included (242 females, 89.6%), mean age at diagnosis was 34.2 years (SD 15.8). 75 patients had fluctuant levels of complement, 79 patients had persistent low complement levels and 116 had normal complement levels. Lupus glomerulonephritis was more frequent in patients with fluctuant levels (75%, 56% and 49%, respectively, p=0002). The normal complement group had less frequency of haematological involvement and anti-double stranded DNA (dsDNA) antibodies. At the end of the follow-up, 53% of the patients had damage (SLICC/ACR ≥1). In a Cox proportional hazard model age at diagnosis, neurological impairment, thrombocytopaenia and corticosteroids were associated with more damage, while hydroxychloroquine was a protective factor. There were no differences between complements groups on accumulated damage. Ten-year survival rate was 93%, 93.5% and 92% for the normal complement group, the persistently low group and the fluctuant group, respectively. Conclusions Patients with constant normal complement had lower prevalence of haematological involvement and anti-dsDNA, while patients with fluctuant complement had higher renal impairment. Neither the persistent low complement nor the fluctuant complement groups had increased mortality and/or visceral damage.