Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroform EZ Stenting for Symptomatic Intracranial Artery Stenosis: 30 Days Outcomes in a High-Volume Stroke Center

Objective: To test whether Neuroform EZ stent placement combined with the modified techniques in symptomatic severe intracranial stenosis (ICAS) would result in lower rates of peri-procedural complications of intracranial stenting. Methods: We retrospectively reviewed the clinical data from 71 consecutive patients who underwent Neuroform EZ stent placement combined with the modified techniques for symptomatic severe ICAS at our institute between January 2016 and October 2017. The primary outcomes were ipsi-lateral ischemic stroke, intra-cerebral hemorrhage, or death within 30 days after stenting. The secondary outcome was technical success. Results: The technical success rate was 100%. The mean pre and post-stent stenoses were 84.2% ± 9.1% (median 85%, IQR75% to 90%) and 16.9% ± 10.2 % (median 15%, IQR 10% to 25%). The frequency of ipsi-lateral stroke, intra-cerebral hemorrhage, or death within 30 days was 0%. Conclusions: The combined use of Neuroform EZ stent placement and the modified techniques for symptomatic severe ICAS is technically feasible and safe, with very low peri-procedural complications. Further studies are required to assess the long-term results of this approach.
A unified magnetic resonance imaging pharmacokinetic theory: Intravascular and extracellular contrast reagents

A fundamental reworking of pharmacokinetic theory for the use of contrast reagents (CRs) in T1‐weighted MRI studies is presented. Unlike the standard model in common use, this derivation starts with the quantities measured, the intravascular, interstitial, and intracellular 1H2O signals. The time dependences of CR concentrations are introduced as perturbations of the T1 values of these. Since there is an explicit accounting for the equilibrium exchange of water molecules between tissue compartments, the approach here is a new (second) generation of the shutter‐speed model (S2M). When the first‐order rate constant measuring CR extravasation (Ktrans) is of sufficient magnitude, simulations presented here confirm that neglect of plasma CR, a feature of the first generation of S2M, is a valid approximation. The second S2M generation (S2M2) also automatically accommodates excursions of either or both of the two major equilibrium water exchange systems (transendothelial and transcytolemmal) into any or all possible exchange conditions, from their fast‐exchange limits to their slow‐exchange limits. This can happen not because the exchange kinetics themselves vary during the isothermal CR passage, but because the MR shutter speeds for these processes can vary. When Ktrans is sufficiently small, the S2M2 also naturally accounts for the hyperfine blood agent level dependent (BALD) effect that is easily detectable at high magnetic field. This can be seen for virtually all CRs in normal brain tissue and for virtually all tissues with sufficiently intravascular CRs. Thus, S2M2 represents a unified pharmacokinetic theory for intravascular and extracellular T1 contrast reagents. Magn Reson Med, 2005. © 2005 Wiley‐Liss, Inc.
Longitudinal Assessment of Cortical Excitability in Children and Adolescents With Mild Traumatic Brain Injury and Persistent Post-concussive Symptoms

Introduction: Symptoms following a mild traumatic brain injury (mTBI) usually resolve quickly but may persist past 3 months in up to 15% of children. Mechanisms of mTBI recovery are poorly understood, but may involve alterations in cortical neurophysiology. Transcranial Magnetic Stimulation (TMS) can non-invasively investigate such mechanisms, but the time course of neurophysiological changes in mTBI are unknown. Objective/Hypothesis: To determine the relationship between persistent post-concussive symptoms (PPCS) and altered motor cortex neurophysiology over time. Methods: This was a prospective, longitudinal, controlled cohort study comparing children (8–18 years) with mTBI (symptomatic vs. asymptomatic) groups to controls. Cortical excitability was measured using TMS paradigms at 1 and 2 months post injury. The primary outcome was the cortical silent period (cSP). Secondary outcomes included short interval intracortical inhibition (SICI) and facilitation (SICF), and long-interval cortical inhibition (LICI). Generalized linear mixed model analyses were used to evaluate the effect of group and time on neurophysiological parameters. Results: One hundred seven participants (median age 15.1, 57% female) including 78 (73%) with symptomatic PPCS and 29 with asymptomatic mTBI, were compared to 26 controls. Cortical inhibition (cSP and SICI) was reduced in the symptomatic group compared to asymptomatic group and tended to increase over time. Measures of cortical facilitation (SICF and ICF) were increased in the asymptomatic group and decreased over time. TMS was well tolerated with no serious adverse events. Conclusions: TMS-assessed cortical excitability is altered in children following mild TBI and is dependent on recovery trajectory. Our findings support delayed return to contact sports in children even where clinical symptoms have resolved.
Roles of Phosphorus Sources in Microbial Community Assembly for the Removal of Organic Matters and Ammonia in Activated Sludge

Various phosphorus sources are utilized by microbes in WWTPs, eventually affecting microbial assembly and functions. This study identified the effects of phosphorus source on microbial communities and functions in the activated sludge. By cultivation with 59 phosphorus sources, including inorganic phosphates (IP), nucleoside-monophosphates (NMP), cyclic-nucleoside-monophosphates (cNMP), and other organophosphates (OP), we evaluated the change in removal efficiencies of total organic carbon (TOC) and ammonia, microbial biomass, alkaline phosphatase (AKP) activity, microbial community structure, and AKP-associated genes. TOC and ammonia removal efficiency was highest in IP (64.8%) and cNMP (52.3%) treatments. Microbial community structure changed significantly across phosphorus sources that IP and cNMP encouraged Enterobacter and Aeromonas, respectively. The abundance of phoA and phoU genes was higher in IP treatments, whereas phoD and phoX genes dominated OP treatments. Our findings suggested that the performance of WWTPs was dependent on phosphorus sources and provided new insights into effective WWTP management.
Coupled Electromagnetic-Thermal Optimization of a Separate-Stator Modular Machine With Biased Flux

A separate-stator modular machine with biased flux is proposed in this paper. In this machine, the windings and the permanent magnets are located in two separate parts of the stator, which favors the heat dissipation and magnetic saturation reduction of the machine. With the specially designed stator structure, a biased flux can be introduced to flexibly regulate the excitation field by injecting a zero-sequence current into the phase windings, so that a wide operation speed range can be achieved. Moreover, a modular structure is adopted to simplify the automated manufacture assembly. In this paper, the machine configuration and the working principle are first illustrated. The effect of the design parameters on its torque capability is then investigated. A coupled electromagnetic-thermal optimization method based on the genetic algorithm and finite-element method is proposed to improve the torque performance of the machine.
Efficacy and Safety of ABT-126 in Subjects with Mild-to-Moderate Alzheimer's Disease on Stable Doses of Acetylcholinesterase Inhibitors: A Randomized, Double-Blind, Placebo-Controlled Study.

BACKGROUND ABT-126 is a potent, selective α7 nicotinic acetylcholine receptor agonist with putative procognitive effects as a monotherapy in treating Alzheimer's disease (AD). OBJECTIVE This randomized, double-blind, placebo-controlled multicenter study (NCT01549834) investigated the efficacy and safety of ABT-126 in subjects with mild-to-moderate AD who were taking stable doses of acetylcholinesterase inhibitors (AChEIs). METHODS Subjects received 25 mg ABT-126 (n = 143), 75 mg ABT-126 (n = 145), or placebo (n = 146) once daily for 24 weeks. Subjects who completed the 24-week double-blind study were eligible to enroll in a 28-week open-label extension study (NCT01690195) and received 75 mg ABT-126 daily. The primary efficacy endpoint was the change from baseline to week 24 in the 11-item total score of the Alzheimer's Disease Assessment Scale- Cognitive Subscale (ADAS-Cog). RESULTS Neither dose of ABT-126 demonstrated significant improvement compared with placebo in the primary efficacy endpoint. However, 25 mg ABT-126 demonstrated significant improvement compared with placebo in ADAS-Cog scores at week 4 (least squares mean difference, -1.21; standard error, 0.51; p < 0.010, one-sided); 75 mg ABT-126 did not demonstrate significant improvements in ADAS-Cog scores compared with placebo at any time point. A treatment effect was not observed for any secondary efficacy measures of cognition, function, or global improvement. ABT-126 was generally well tolerated; the most common adverse events were agitation, constipation, diarrhea, fall, and headache. CONCLUSIONS Overall, the efficacy profile of ABT-126 did not warrant further development as add-on therapy to AChEIs to treat mild-to-moderate AD.
Cell Variability Impact on the One-Selector One-Resistor Cross-Point Array Performance

This paper investigates the impact of cell variability on the read performance of the one-selector one-resistor (1S1R) cross-point array. A variability-aware array-sizing analysis methodology is introduced, considering three independent variability sources, namely, the data pattern randomness, the selector variability, and the resistive switching element (RSE) variability. By analyzing the impact of each variability factor separately, we show that the data pattern randomness is not an important contributor for the read margin (RM) degradation. While the intrinsic RSE variability reflected in the narrowing of the ON/OFF RSE window degrades the RM, the selector variability adds to this further, mainly affecting the ON-state readout current, and causing extra RM degradation. To accommodate cell variability and guarantee acceptable read performance, additional cell performance margin is required. The 1S1R requirements are extrapolated for 1-Mb array, assuming variability-affected cells. It is found that, with a typical selector variability, a minimal RSE window of 5 and a selector half-bias nonlinearity of ~8000 are required to achieve at least 10% RM.
Negotiation for Data Mining E-services

A keyboard operated electronic musical instrument is disclosed wherein the number of tone generators is less than the number of keyswitches in a keyboard array of keyswitches. If all the available tone generators have been assigned to actuated keyswitches, the actuation of an additional keyswitch causes the oldest tone generator to be assigned to the newest keyswitch. The assignment action does not depend upon the release of any keyswitch. A phase addition means is used to remove the oldest tone generator so that release key clicks are not generated.
Compact Model for Negative Capacitance Enhanced Spintronics Devices

Although spin transfer torque (STT)-based magnetic tunneling junction (MTJ) owns advantages of nonvolatility, nonlimited endurance, and fast write/read, its demand for high current density significantly casts a shadow over its future prospects. Recently, a novel three-terminal MTJ cell that combines voltage-controlled magnetic anisotropy (VCMA) effect and negative capacitance (NC) effect is proposed. Drawing support from the NC amplified VCMA effect and the three-step operation scenario, this novel MTJ cell can dramatically lower the energy consumption to fJ as well as keep high operation speed within nanoseconds. The feasibility of the proposed NC enhanced VCMA spintronics device for memory and logic application is proved by extensive physical simulation in our previous work. However, a SPICE compatible compact model of the proposed NC enhanced VCMA spintronics device is still demanded for circuit and system level evaluation. In this paper, we provide an accurate and fast compact model of NC enhanced VCMA device for both memory and logic applications.
Nephron-sparing surgery for tumors in a solitary kidney

Purpose of review Presence of a tumor in a solitary kidney is an absolute indication for performing nephron-sparing surgery (NSS). In the past two decades, new modalities for treatment of small renal mass have emerged but despite their evolution and promising results, partial nephrectomy remains the cornerstone of surgical treatment in this setting. Herein, we review the literature surrounding NSS in patients with a solitary kidney. Recent findings Data from large retrospective, single and multi-institutional series indicate that open partial nephrectomy in patients with a solitary kidney can achieve oncological control as well as renal function preservation with acceptable complication profile. Available data indicate that employing parenchymal cooling can mitigate the deleterious effects of prolonged clamp time during partial nephrectomy. Introduction of laparoscopic and, more recently, robotic approach have allowed minimally invasive approach in selected patients undergoing partial nephrectomy. Large comparative studies comparing minimally invasive approaches to open technique are lacking. Summary Established and emerging NSS techniques along with our better understating of the factors affecting function after surgery have fostered improvement of delivery of care in the setting of renal tumor(s) in a solitary kidney. Future developments should focus on minimizing the invasiveness of treatments while further improving cancer control and functional preservation.
Code Search Based on Alteration Intent

Code search is to retrieve the method according to the user needs. Many people think of the query as the only one to reflect the user needs. So they start with the query and find the synonyms, semantically similar to the query terms, for query expansion. However, they overlook a fact: the retrieved methods still need to be altered because it does not meet the user needs directly. This implies that the alteration made in the retrieved methods also reflects the user needs. In this paper, we start with the alteration intent (the possible alterations after retrieving methods) and propose to predict the alteration intent and use it for query expansion. The experiment results show that our approach outperforms CodeHow, the approach to use APIs for query expansion, by 59.8% with a precision score of 0.815.
Moving Evolution Education Forward: A Systematic Analysis of Literature to Identify Gaps in Collective Knowledge for Teaching

A systematic analysis of the literature undertaken to identify gaps in collective knowledge for teaching undergraduate evolution is reported. A total of 316 peer-reviewed papers were analyzed to determine: evolutionary topics addressed; whether the focus was student thinking, assessment, instructional strategies, or goals; and the type of work. Future research priorities are proposed.
Isothermal compressed air system for internal channel cooling

The objective of the current experimental study is to build a system that can provide a steady state mass flow rate of air and constant temperature which will be used for cooling system of gas turbine blade. The compressed air is used as air supply for jet impingement in a rotating test model. The system is capable to provide 200 l/min of compressed air at constant temperature for a period of 50 minutes at 4 bar pressure. Three different designs have been tested with different tanks arrangements. Three tanks with total volume of 2 m2 where used to produce the compressed air conditions.
Detection and Classification of Brain Hemorrhage Based on Hounsfield Values and Convolution Neural Network Technique

In recent years, brain hemorrhage tends to increase rapidly and is one of the most dangerous for our life. Thus, the automatic detection and classification of brain hemorrhage are essential for doctors to treat. In this paper, we present a new approach using convolution neural network technique and Hounsfield Unit values for analyzing brain hemorrhage from CT/MRI images. The proposed method includes two stages: classification of brain hemorrhage using convolution neural network technique; detection of brain hemorrhage areas and determination of brain hemorrhage time based on Hounsfield Unit values. Our method is effective for doctors in recognizing brain hemorrhage, diagnosing the location, time and severity level of brain hemorrhage for prompt patient treatment.
Improving Transient Stability Assessment by Installing Super Capacitor Energy Storage using Critical Trajectory Method based on Modified Losing Synchronism

Transient Stability Assessment (TSA) in electrical power system is one of the main aspects to achieve continuity and reliability of the system due to the changing of the load and the interconnection of the system become more complex. Meanwhile, the protection system has to be accurate in isolating the disturbance. Critical Clearing Time (CCT) became the main issues to determine the stability of the system after a disturbance happened. Critical Trajectory is a method to obtain CCT which is accurate and has faster calculation than other methods. In addition, Super Capacitor Energy Storage (SCES) is one of the reliable energy storages to store and supply massive electric power simultaneously. It is suitable with the nonlinearity pattern of transient stability. In order to improve the value of CCT, SCES is installed in the system. This proposed method is tested using IEEE 3-machine 9-bus system. The simulation result shows that the proposed method gives higher value of CCT in average range 0.0143s. It means the operation time of protection system is longer and it also has a longer time when a failure in protection system occur. As a result, the system will remain stable after a disturbance happen and it can improve transient stability of the system.
Efficient RCS Evaluation for the Conventional TF/SF Separation Model in the FDTD Technique

A systematic radar cross-section (RCS) evaluation scheme to enhance the total-field/scattered-field (TF/SF) separation scheme is developed in this paper for the nonstandard finite-difference time-domain (NS-FDTD) and FDTD method. Usually, the direct launch of an electromagnetic wave on the TF/SF separation surface generates undesired scattered artifacts. To avoid the influence of these forms in RCS, we introduce an error prediction model via pre-calculated data from vector parasites. It is numerically shown that our technique can improve the reliability of the RCS analysis for aircrafts with electrically large size.
Weak 13 CO in the Cloverleaf quasar: evidence for a young, early generation starburst

Observations of ^(12)CO at high redshift indicate rapid metal enrichment in the nuclear regions of at least some galaxies in the early universe. However, the enrichment may be limited to nuclei that are synthesized by short-lived massive stars, excluding classical “secondary” nuclei like ^(13)C. Testing this idea, we used the IRAM Interferometer to tentatively detect the ^(13)CO J = 3 → 2 line at a level of 0.3 Jy km s^(-1) toward the Cloverleaf quasar at z = 2.5. This is the first observational evidence for ^(13)C at high redshift. The ^(12)CO/^(13)CO J = 3 → 2 luminosity ratio is with 40_(-8)^(+25) much higher than ratios observed in molecular clouds of the Milky Way and in the ultraluminous galaxy Arp 220, but may be similar to that observed toward NGC 6240. Large Velocity Gradient models simulating seven ^(12)CO transitions and the ^(13)CO line yield ^(12)CO/^(13)CO abundance ratios in excess of 100. It is possible that the measured ratio is affected by a strong submillimeter radiation field, which reduces the contrast between the ^(13)CO line and the background. It is more likely, however, that the ratio is caused by a real deficiency of ^(13)CO. This is already apparent in local ultraluminous galaxies and may be even more severe in the Cloverleaf because of its young age (≾ 2.5 Gyr). A potential conflict with optical data, indicating high abundances also for secondary nuclei in quasars of high redshift, may be settled if the bulk of the CO emission is originating sufficiently far from the active galactic nucleus of the Cloverleaf.
Frequent Pattern Discovery in First-Order Logic

In recent years, the usage and size of databases have grown dramatically, due to a constant decrease in the cost of both the collection and the storage of huge amounts of data. The need for tools to exploit the popular Data Warehouse has grown accordingly and has given rise to a rapidly evolving research field at the intersection of statistics, databases, and machine learning: Data Mining and Knowledge Discovery in Databases (KDD). Within KDD, the discovery of recurrent patterns in (potentially huge) data collections has become one of the central topics. In tasks where the goal is to uncover structure in the data and where there is no preset target concept, the discovery of relatively simple but frequently occurring patterns has shown good promise. The motivation for such an application is the potentially high business value of the discovered patterns. At the heart of the task is the problem of determining all combinations of items that occur frequently together, where ‘frequent’ is defined as ‘exceeding a user-specified frequency threshold’. The use of a frequency threshold for filtering out non-interesting patterns is natural for a large number of data mining problems. Patterns that are rare, e.g., that concern only a couple of customers, are probably not reliable nor useful for the user. Frequent pattern discovery has been studied in a variety of settings. In its simplest form, the task is known from association rule mining. A prototypical application example of this basic setting is in market basket analysis: find out which items tend to be sold together. The fundamental task of association rule and frequent set discovery has been extended in various directions, allowing more useful patterns (e.g., sequential patterns or episodes) to be discovered with special purpose algorithms. We present a general formulation of the frequent pattern discovery problem, where both the database and the patterns are represented in some subset of first-order logic, i.e., essentially Prolog. Obviously, when compared to the original, attributevalue based format employed in frequent pattern discovery algorithms, the Prolog database format is more expressive. In relational databases terminology: where traditional techniques assume a single table representation with one row per example, in Prolog an example can be represented by means of a collection of rows drawn from a set of related tables. In this framework, each example as it were corresponds to a (mini-)database. The central type of pattern we consider is that of a Prolog query. Such a query is the first-order logic equivalent of an item set. To verify whether a query matches a particular example we can submit it to the (mini-)database that corresponds to the example. We then conclude the pattern holds w.r. t. the example if and only if the query succeeds. Much like in the case of association rules, we can combine two queries, where one extends the other, into a rule, called a query extension. For instance: