Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary and pharmacologic management to prevent recurrent nephrolithiasis in adults: a clinical practice guideline from the American College of Physicians.

DESCRIPTION The American College of Physicians (ACP) developed this guideline to present the evidence and provide clinical recommendations on the comparative effectiveness and safety of preventive dietary and pharmacologic management of recurrent nephrolithiasis in adults. METHODS This guideline is based on published literature on this topic that was identified using MEDLINE, the Cochrane Database of Systematic Reviews (through March 2014), Google Scholar, ClinicalTrials.gov, and Web of Science. Searches were limited to English-language publications. The clinical outcomes evaluated for this guideline include symptomatic stone recurrence, pain, urinary tract obstruction with acute renal impairment, infection, procedure-related illness, emergency department visits, hospitalizations, quality of life, and end-stage renal disease. This guideline grades the quality of evidence and strength of recommendations using ACP's clinical practice guidelines grading system. The target audience for this guideline is all clinicians, and the target patient population is all adults with recurrent nephrolithiasis (≥1 prior kidney stone episode). RECOMMENDATION 1 ACP recommends management with increased fluid intake spread throughout the day to achieve at least 2 L of urine per day to prevent recurrent nephrolithiasis. (Grade: weak recommendation, low-quality evidence). RECOMMENDATION 2 ACP recommends pharmacologic monotherapy with a thiazide diuretic, citrate, or allopurinol to prevent recurrent nephrolithiasis in patients with active disease in which increased fluid intake fails to reduce the formation of stones. (Grade: weak recommendation, moderate-quality evidence).
Longitudinal Data Analysis

Longitudinal studies are quite common in modern clinical trials and cohort studies. Unlike cross-sectional designs, where observations from study subjects are available only at a single time point, individuals in longitudinal or cohort studies are assessed repeatedly over time. By taking advantages of multiple snapshots of a group over time, data from longitudinal studies captures both between-individual differences and within-individual dynamics, affording the opportunity to study more complicated biological, psychological, and behavioral hypotheses than their crosssectional counterparts. For example, if we want to test whether exposure to some chemical agent can cause some type of cancer, the between-subject difference observed in crosssectional data can only provide evidence of an association or correlation between the exposure and disease. The within-individual dynamics in longitudinal data allows for inference of a causal nature for such a relationship. Longitudinal data presents multiple methodological challenges in study designs and data analyses. The primary problem is the correlation among the repeated responses of the same subject. Classic models for cross-sectional data analysis such as multiple linear and logistic regressions are based on the independence of observations and thus in general do not apply to longitudinal data. For example, in
Sonographic Features of a Spermatic Cord Capillary Hemangioma

Soft tissue hemangiomas are relatively common benign tumors, which may occur anywhere in the body. On histologic examination, these soft tissue hemangiomas may be divided into 5 categories depending on the dominant type of vascular channel identified: capillary, cavernous, arteriovenous, venous, and mixed. 1 There have been only a small number of case reports of spermatic cord hemangiomas, 2-5 and, to our knowledge, the sonographic appearances have not been documented previously. We describe the sonographic appearances of an isolated capillary hemangioma of the spermatic cord confirmed on histologic examination and discuss the possible differential diagnosis.
Hybrid Load-Value Predictors

Load instructions diminish processor performance in two ways. First, due to the continuously widening gap between CPU and memory speed, the relative latency of load instructions grows constantly and the slows program execution. Next, memory reads limit the available instruction-level parallelism as instructions that use the result of a load must wait for the memory access to complete before they can start executing. Load-value predictors alleviate both problems by allowing the CPU to speculatively continue processing without having to wait for load instructions, which can significantly improve the execution speed. In this paper, we investigate the performance of all hybrids that can be built out of a register value, a last value, a stride 2-delta, the last four values, and a finite context method predictor. Our analysis shows that hybrids can deliver 25 percent more speedup than the best single-component predictors. Our hybridization study identified the register value + stride 2-delta predictor as one of the best two-component hybrids. It matches or exceeds the speedup of two-component hybrids from the literature in spite of its substantially smaller and simpler design. Of all the predictors we studied, the register value + stride 2-delta + last four value hybrid performs best.
Vaccination with Dendritic Cells Pulsed with Peptides of Myelin Basic Protein Promotes Functional Recovery from Spinal Cord Injury

Injury-induced self-destructive processes cause significant functional loss after incomplete spinal cord injury (SCI). Cellular elements of both the innate (macrophage) and the adaptive (T-cell) immune response can, if properly activated and controlled, promote post-traumatic regrowth and protection after SCI. Dendritic cells (DCs) trigger activation of effector and regulatory T-cells, providing a link between the functions of the innate and the adaptive immune systems. They also initiate and control the body's response to pathogenic agents and regulate immune responses to both foreign and self-antigens. Here we show that post-injury injection of bone marrow-derived DCs pulsed with encephalitogenic or nonencephalitogenic peptides derived from myelin basic protein, when administered (either systemically or locally by injection into the lesion site) up to 12 d after the injury, led to significant and pronounced recovery from severe incomplete SCI. No significant protection was seen in DC recipients deprived of mature T-cells. Flow cytometry, RT-PCR, and proliferation assays indicated that the DCs prepared and used here were mature and immunogenic. Taken together, the results suggest that the DC-mediated neuroprotection was achieved via the induction of a systemic T-cell-dependent immune response. Better preservation of neural tissue and diminished formation of cysts and scar tissue accompanied the improved functional recovery in DC-treated rats. The use of antigen-specific DCs may represent an effective way to obtain, via transient induction of an autoimmune response, the maximal benefit of immune-mediated repair and maintenance as well as protection against self-destructive compounds.
Image Watermarking Based on Multiple Objective Genetic Algorithm

The Differential Energy Watermarking (DEW)algorithm has been demonstrated as an effective video watermarking algorithm. While in some scenarios, DEW algorithm cannot rovide enough robustness and fidelity. In order to solve this problem, a watermarking algorithm for uncompressed video based on Quantization Index Modulation (QIM) and differential energy is proposed in this paper. The experimental results indicate that the proposed algorithm is more robust than original DEW and modified low-frequency DEW for lossy compression and transcoding, while maintaining high fidelity. Besides, the algorithm can be used in real-time applications for its low computation complexity.
A Mutation in Synaptojanin 2 Causes Progressive Hearing Loss in the ENU-Mutagenised Mouse Strain Mozart

Background Hearing impairment is the most common sensory impairment in humans, affecting 1∶1,000 births. We have identified an ENU generated mouse mutant, Mozart, with recessively inherited, non-syndromic progressive hearing loss caused by a mutation in the synaptojanin 2 (Synj2), a central regulatory enzyme in the phosphoinositide-signaling cascade. Methodology/Principal Findings The hearing loss in Mozart is caused by a p.Asn538Lys mutation in the catalytic domain of the inositol polyphosphate 5-phosphatase synaptojanin 2. Within the cochlea, Synj2 mRNA expression was detected in the inner and outer hair cells but not in the spiral ganglion. Synj2 N538K mutant protein showed loss of lipid phosphatase activity, and was unable to degrade phosphoinositide signaling molecules. Mutant Mozart mice (Synj2 N538K/N538K) exhibited progressive hearing loss and showed signs of hair cell degeneration as early as two weeks of age, with fusion of stereocilia followed by complete loss of hair bundles and ultimately loss of hair cells. No changes in vestibular or neurological function, or other clinical or behavioral manifestations were apparent. Conclusions/Significance Phosphoinositides are membrane associated signaling molecules that regulate many cellular processes including cell death, proliferation, actin polymerization and ion channel activity. These results reveal Synj2 as a critical regulator of hair cell survival that is essential for hair cell maintenance and hearing function.
Effects of vehicle speed and engine load on motor vehicle emissions.

Laboratory studies have provided a foundation of knowledge regarding vehicle emissions, but questions remain regarding the relationship between on-road vehicle emissions and changes in vehicle speed and engine load that occur as driving conditions change. Light-duty vehicle emissions of CO, NOx, and NMHC were quantified as functions of vehicle speed and engine load in a California highway tunnel for downhill and uphill traffic on a _4% grade. Emissions were measured throughout the day; average speed decreased inside the tunnel as traffic volume increased. Emissions of CO were typically 16-34 g L-1 (i.e., grams of CO emitted per liter of gasoline consumed) during downhill driving and ranged from 27 to 75 g L-1 during uphill driving. Downhill driving and moderate-speed uphill driving resulted in similar CO emission factors. The factor of 2 increase in CO emissions observed during higherspeed uphill driving is likely evidence of enriched engine fuel/ air ratios; this was unexpected because uphill driving observed in this study occurred at moderate engine loads within the range experienced during the city driving cycle of the U.S. emissions certification test. Emissions of NOx (as NO2) were typically 1.1-3.3 g L-1 for downhill driving and varied between 3.8 and 5.3 g L-1 for uphill driving. Unlike observations for CO, all uphill driving conditions resulted in higher NOx emission factors as compared to downhill driving. NOx emissions increased with vehicle speed for uphill driving but not as strongly as CO emissions. Emissions of CO and NOx are functions of both vehicle speed and specific power; neither parameter alone captures all the relevant effects on emissions. In contrast to results for CO and NOx reported here and results for NMHC reported previously by Pierson et al. (Atmos. Environ. 1996,30, 2233- 2256), emissions of NMHC per unit of fuel burned for downhill driving were over 3 times greater than NMHC emissions for uphill driving. Emission rates of CO and NOx varied more with driving conditions when expressed per unit distance traveled rather than per unit fuel burned while NMHC emission rates normalized to distance traveled were approximately constant for uphill versus downhill driving during peak traffic periods.
The Materials Science of Eating and Food Breakdown

Most of the process of eating is a learned skill. While an infant readily puts most things in its mouth, the ability to distinguish food from any other material has to be taught, and even then it is several years before the whole range of foods can be consumed efficiently. Yet by the time we are 5–10 years old, our mastery of the complex set of mechanical actions involving tongue, teeth, and swallowing is so complete that we do not consciously note what we are doing or how we do it.
Application of K-Means clustering in hot spot detection for thermal infrared images

K-Means Clustering is one of the method for image segmentation which will subtract the interest area from background. By using K-Means Clustering, thermal image is divided into 2 layers which separates the hotter region from the background image. This will ease the hot spot detection on thermal infrared images. This paper presents work on the implementation of K-Means Clustering onto thermal images. The algorithm for thermal infrared image segmentation using K-Means Clustering was developed and executed using MATLAB R2015a software. It was proven that K-Means Clustering ease the hot spot detection from the thermal images.
Pain‐Related Suppression of Beta Oscillations Facilitates Voluntary Movement

Abstract Increased beta oscillations over sensorimotor cortex are antikinetic. Motor‐ and pain‐related processes separately suppress beta oscillations over sensorimotor cortex leading to the prediction that ongoing pain should facilitate movement. In the current study, we used a paradigm in which voluntary movements were executed during an ongoing pain‐eliciting stimulus to test the hypothesis that a pain‐related suppression of beta oscillations would facilitate the initiation of a subsequent voluntary movement. Using kinematic measures, electromyography, and high‐density electroencephalography, we demonstrate that ongoing pain leads to shorter reaction times without affecting the kinematics or accuracy of movement. Reaction time was positively correlated with beta power prior to movement in contralateral premotor areas. Our findings corroborate the view that beta‐band oscillations are antikinetic and provide new evidence that pain primes the motor system for action. Our observations provide the first evidence that a pain‐related suppression of beta oscillations over contralateral premotor areas leads to shorter reaction times for voluntary movement.
Reservoir computing with signal-mixing cavities

In an age where we get swamped by big data, new machine learning techniques for efficient high-speed data processing become more important than ever. One of these techniques, known as reservoir computing, is specifically designed for processing time-dependent data. We propose some new ideas for implementing such a reservoir computer on a silicon photonics chip for low-power and high-bandwidth optical communication applications. Our simulations show that this photonic reservoir can for example be used in pattern recognition tasks such as header recognition.
Beyond bevacizumab: new anti-VEGF strategies in colorectal cancer

Introduction: Treatment of colorectal cancer (CRC) has changed dramatically over the past decade, mainly due to the advent of molecularly targeted agents. In particular, an improved understanding of the role of the angiogenesis pathway in CRC has led to advancements in treatment. Bevacizumab has been shown to improve the progression-free survival and overall survival when combined with cytotoxic chemotherapy in patients with metastatic CRC (mCRC) and at present is the only antiangiogenesis agent approved for the treatment of this cancer. Areas covered: In this review, the authors outline the most recent data on the VEGF signaling pathway and on new therapeutic reagents that target it, provide insight into their mechanisms, and describe results from recent clinical trials. Expert opinion: In the new decade of ‘modern therapy', an increasing number of antiangiogenic agents for the treatment of mCRC are being tested in preclinical models, and dozens of studies on these drugs are ongoing. Presently, eight novel antiangiogenic agents are in Phase III trials and a wide range of other candidates are being tested in Phase I/II trials. Given the preliminary positive results of two recent Phase III trials, aflibercept and regorafenib, probably, will be new-targeted agents approved for the treatment of mCRC. Furthermore, the list of potentially approved agents seems to increase in the next years and to maximize their potential clinical impact, is critically important to introduce efficient molecular diagnostic methodologies into the drug development process to indentify the subset of patients who would benefit most from their use.
Immediate and long-term effect of balloon angioplasty or stent implantation on the absolute and relative coronary blood flow velocity reserve.

BACKGROUND There is controversy regarding the immediate and long-term effects of PTCA on the coronary flow reserve. METHODS AND RESULTS A total of 54 patients with 1-vessel disease and normal left ventricular function were studied after balloon angioplasty (n=34) or stent implantation (n=20). Distal coronary blood flow velocity reserve (CFR) was defined as the ratio of adenosine-induced hyperemic versus baseline blood flow velocity with a 0.014-in Doppler guidewire. The relative CFR was defined as the ratio of the distal CFR and the reference CFR measured in the normal adjacent coronary artery. Hemodynamic and angiographic measurements were performed before and directly after balloon angioplasty or stent implantation and at 6-month follow-up. CFR after PTCA </=2.5 was defined as an impaired CFR. Immediately after PTCA, CFR improved toward the range of the reference artery CFR. In both the balloon-treated and the stent-treated groups, initial high CFR values decreased and impaired CFR values increased at follow-up toward the values of the reference CFR in patients without restenosis. Impaired CFR after balloon angioplasty (33%) or stent implantation (58%) in patients without restenosis was related to an increased baseline flow velocity that normalized at follow-up. Patients with an increase of CFR after stenting were characterized by an unaltered baseline flow velocity and an increased adenosine-induced hyperemic flow velocity. CONCLUSIONS An impaired CFR (</=2.5) is a frequent finding after balloon angioplasty or stent implantation as a result of a high baseline flow velocity. Normalization of impaired CFR at follow-up in patients without restenosis was associated with a decline of the baseline flow velocity after both balloon angioplasty and stent implantation, supporting the contention that this phenomenon relates to a slow recovery of autoregulation of the microvascular bed.
Challenges in Perception and Decision Making for Intelligent Automotive Vehicles: A Case Study

This paper overviews challenges in perception and decision making for intelligent, or highly automated, automotive vehicles. We illustrate our development of a complete perception and decision making system which addresses various challenges and propose an action planning method for highly automated vehicles which can merge into a roundabout. We use learning from demonstration to construct a classifier for high-level decision making, and develop a novel set of formulations that is suited to this challenging situation: multiple agents in a highly dynamic environment with interdependencies between agents, partial observability, and a limited amount of training data. Having limited amount of labeled training data is highly constraining, but a very real issue in real-world applications. We believe that our formulations are also well suited to other automated driving scenarios.
Task Scheduling for Heterogeneous Computing Based on Learning Classifier System

Task scheduling still remains one of the most challenging problems to achieve high performance in heterogeneous computing environments in spite of numerous efforts. This paper presents a novel scheduling algorithm based on learning classifier system for heterogeneous computing environment. In the presented algorithm, XCS classifier system is used to find the optimal task assignment on different processors, and the execution sequence of tasks on the same processor is set by the heuristic used in list scheduling approach. Empirical studies on benchmark task graphs show that the proposed algorithm is able to produce higher speedup compared with the related algorithms. Further experiments also indicate that the proposed algorithm maintains almost the same performance with different parameter settings.
Iterative learning control algorithms based on complex stochastic distribution systems

In this paper, a new generalized iterative learning algorithm is first proposed based on complex non-Gaussion stochastic control systems. Following designed neural networks are used to approximate the output PDF of the stochastic system in the repetitive processes or the batch processes, the tracking control to PDF is transformed into a parameter adaptive tuning problem in NN basis function. Under this framework, we study a new model free iterative learning control problem and propose a convex optimization algorithm based on a set of designed LMIs and L1 performance index. Such an algorithm has the advantage of the improvement of the closed-loop output PDF tracking performance and robustness. Simulation results are given to demonstrate the effectiveness of the proposed approach.
A study of phenotypic variation of Staphylococcus epidermidis using Congo red agar

SUMMARY This study examines a series of phenotypic variants of Staphylococcus epidermidis that were generated from a pair of parent variants, isolated from valvular tissue of a patient with prosthetic valve endocarditis. The variants were initially classified by examining their colonial morphology on Congo red agar. In addition to differences in Congo red binding and colonial morphology, they differed in the expression of several surface components and enzymes. Despite these phenotypic differences, all variants had the same restriction endonuclease profile of plasmid DNA. Examination of a collection of clinical isolates demonstrated that phenotypic variation is a common property of S. epidermidis. The ability to express different combinations of surface components and enzymes could contribute to the virulence of S. epidermidis strains by enabling these organisms to colonize a range of diverse environments.
On the intrinsic temperature dependence of the stacking-fault energy in copper-aluminium alloys

Abstract The temperature variation of the separation of Shockley partials of single dissociated dislocations in Cu-6·44 at. % Al and Cu-13·43 at. % Al has been measured by means of in situ thermal cycling experiments in a high-voltage electron microscope; a weak-beam high-resolution imaging technique was used for the observations. The variations of the partial separation on changing the temperature was analysed by taking into account such factors as temperature dependence of shear modulus, the solute impedance effect, the Suzuki effect and short-range order which may give rise to the variation of partial separation, in addition to the intrinsic temperature dependence of the stacking-fault energy γ. The intrinsic temperature dependence of γ was determined in the range 77 K to 1020 K for Cu-13-43 at. % Al and in the range 120 K to 723 K for Cu-6·44 at. % Al. The nature of the intrinsic temperature dependence of γ is discussed.
Deciding the Twins Property for Weighted Tree Automata over Extremal Semifields

It has remained an open question whether the twins property for weighted tree automata is decidable. This property is crucial for determinizing such an automaton, and it has been argued that determinization improves the output of parsers and translation systems. We show that the twins property for weighted tree automata over extremal semifields is decidable.