Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of cancer pain guidelines by acute care nurse practitioners using an audit and feedback strategy

Purpose: Despite the availability of clinical practice guidelines (CPGs) for cancer pain, consistent integration of these principles into practice has not been achieved. The optimal method for implementing CPGs and the impact of guidelines on healthcare outcomes remain uncertain. This study evaluated the effect of an audit and feedback (A/F) intervention on nurse practitioner (NP) implementation of cancer pain CPGs and on hospitalized patients' self‐report of pain and satisfaction with pain relief. Data sources: Eight NPs and two groups of 96 patients were the sources of data. Eligible patients in both groups completed the Brief Pain Inventory‐Short Form (BPI‐SF) within 24 h of admission and every 48 h until discharge. During A/F, NPs received weekly feedback on pain scores and guideline adherence. Conclusions: Nurse practitioner adherence to CPGs increased during A/F. Pain intensity did not significantly differ between groups. Intervention group patients reported significantly less overall pain interference (p < .0001), interference with general activity (p = .0003), and sleep (p = .006). Satisfaction with pain relief increased from 68.4% to 95.1% during A/F (p < .0001). Implications for practice: A/F is an effective strategy to promote CPG use. Improved functional status in the absence of decreased pain severity underscores the need to consider symptom clusters when studying pain.
Palladium Nanoparticles by Electrospinning from Poly(acrylonitrile-co-acrylic acid)-PdCl2 Solutions. Relations between Preparation Conditions, Particle Size, and Catalytic Activity

Catalytic palladium (Pd) nanoparticles on electrospun copolymers of acrylonitrile and acrylic acid (PAN-AA) mats were produced via reduction of PdCl2 with hydrazine. Fiber mats were electrospun from homogeneous solutions of PAN-AA and PdCl2 in dimethylformamide (DMF). Pd cations were reduced to Pd metals when fiber mats were treated in an aqueous hydrazine solution at room temperature. Pd atoms nucleate and form small crystallites whose sizes were estimated from the peak broadening of X-ray diffraction peaks. Two to four crystallites adhere together and form agglomerates. Agglomerate sizes and fiber diameters were determined by scanning and transmission electron microscopy. Spherical Pd nanoparticles were dispersed homogeneously on the electrospun nanofibers. The effects of copolymer composition and amount of PdCl2 on particle size were investigated. Pd particle size mainly depends on the amount of acrylic acid functional groups and PdCl2 concentration in the spinning solution. Increasing acrylic acid concentration on polymer chains leads to larger Pd nanoparticles. In addition, Pd particle size becomes larger with increasing PdCl2 concentration in the spinning solution. Hence, it is possible to tune the number density and the size of metal nanoparticles. The catalytic activity of the Pd nanoparticles in electrospun mats was determined by selective hydrogenation of dehydrolinalool (3,7-dimethyloct-6- ene-1-yne-3-ol, DHL) in toluene at 90 °C. Electrospun fibers with Pd particles have 4.5 times higher catalytic activity than the current Pd/Al2O3 catalyst.
The Dual Theory of Choice under Risk

This paper investigates the consequences of the following modification of Expected Utility theory: instead of requiring independence with respect to probability mixtures of risky prospects, require independence with respect to direct mixing of payments o f risky prospects. A new theory of choice under risk- a so-called Dual theory-is obtained. Within this new theory, the following questions are considered: (1) numerical representation of preferences; (2) properties of the utility function; ( 3) the possibility for resolving the "paradoxes" of Expected Utilit y theory; ( 4) the characterization of risk aversion; and (5) comparative statics. The paper ends with a discussion of other non-Expected Utility theories proposed recently. Copyright 1987 by The Econometric Society.
Identification of Proteins That Interact with Podocin Using the Yeast 2-Hybrid System

Purpose As a membrane protein at the insertion site of the slit diaphragm (SD) complex in podocyte foot processes, podocin has been reported to act as a scaffolding protein required to maintain or regulate the structural integrity of the SD. In order to identify proteins that associate or interact with podocin, we screened a mouse kidney complementary DNA (cDNA) library using a yeast 2-hybrid system. Materials and Methods 1) The full-length cDNA of podocin from the mouse kidney was amplified by Polymerase Chain Reaction (PCR), 2) The PCR product was cloned into a pGBKT7 vector, pGBKT7-podocin, 3) After the pGBKT7-podocin was transformed into AH109, the AH109/pGBKT7-podocin product was obtained, 4) The mouse kidney cDNA library was transformed into the AH109/pGBKT7-podocin and screened by selection steps, 5) Next, twelve clones were cultured and isolated, 6) The yeast-purified plasmids were transformed into Escherichia coli (E. coli) by heat shock, and 7) To identify the activation domain (AD)/library inserts, we digested them with Him III, and the fragments were then sequenced. Results 12 positive clones that interacted with podocin were obtained by screening a mouse kidney cDNA library using pGBKT7-podocin. Among them, only 4 clones were found to function at the podocyte where podocin is present. Conclusion Additional studies are needed to clarify the role and interaction with podocin and candidates.
The abelian cosets of the Heisenberg group

In this paper we study the abelian cosets of the H4 WZW model. They coincide or are related to several interesting three-dimensional backgrounds such as the Melvin model, the conical point-particle space-times and the null orbifold. We perform a detailed CFT analysis of all the models and compute the coset characters as well as some typical three-point couplings of coset primaries.
Multi-vendor, multicentre comparison of contrast-enhanced SSFP and T2-STIR CMR for determining myocardium at risk in ST-elevation myocardial infarction

Aims Myocardial salvage, determined by cardiac magnetic resonance imaging (CMR), is used as end point in cardioprotection trials. To calculate myocardial salvage, infarct size is related to myocardium at risk (MaR), which can be assessed by T2-short tau inversion recovery (T2-STIR) and contrast-enhanced steady-state free precession magnetic resonance imaging (CE-SSFP). We aimed to determine how T2-STIR and CE-SSFP perform in determining MaR when applied in multicentre, multi-vendor settings. Methods and results A total of 215 patients from 17 centres were included after percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction. CMR was performed within 1–8 days. These patients participated in the MITOCARE or CHILL-MI cardioprotection trials. Additionally, 8 patients from a previous study, imaged 1 day post-CMR, were included. Late gadolinium enhancement, T2-STIR, and CE-SSFP images were acquired on 1.5T MR scanners (Philips, Siemens, or GE). In 65% of the patients, T2-STIR was of diagnostic quality compared with 97% for CE-SSFP. In diagnostic quality images, there was no difference in MaR by T2-STIR and CE-SSFP (bias: 0.02 ± 6%, P = 0.96, r2 = 0.71, P < 0.001), or between treatment and control arms. No change in size or quality of MaR nor ability to identify culprit artery was seen over the first week after the acute event (P = 0.44). Conclusion In diagnostic quality images, T2-STIR and CE-SSFP provide similar estimates of MaR, were constant over the first week, and were not affected by treatment. CE-SSFP had a higher degree of diagnostic quality images compared with T2 imaging for sequences from two out of three vendors. Therefore, CE-SSFP is currently more suitable for implementation in multicentre, multi-vendor clinical trials.
A Novel Topology for Photovoltaic DC/DC Full-Bridge Converter With Flat Efficiency Under Wide PV Module Voltage and Load Range

In this paper, a novel topology for a photovoltaic (PV) dc/dc converter that can dramatically reduce the power rating and increase the efficiency of a PV system by analyzing PV module characteristics is proposed. Based on the analysis, in the proposed topology, only 30.7% power of the total PV system is needed for a dc/dc converter. Furthermore, the dc/dc converter efficiency curve is flat under wide PV module voltage and all load ranges. In particular, the converter efficiency at the lower duty range is dramatically improved. The total PV system is implemented for a 250-kW PV power conditioning system (PCS). This system has only three dc/dc converters with a 25-kW power rating. It is only one-third of the total PV PCS power. The 25-kW prototype PV dc/dc converter is introduced to experimentally verify the proposed topology. In addition, an experimental result shows that the proposed topology exhibits a good performance.
PWM rectifier with low DC voltage ripple for magnet supply

Control techniques that optimize the behaviour of pulse-width modulation (PWM) rectifiers for magnet supplies are examined. Different control strategies, both with preprogrammed and variable switching patterns, are examined and compared in terms of optimization of the system performance. Optimum digital PWM, multilevel delta modulation, and hybrid PWM/delta techniques are analyzed. The validity of the control methods was verified by simulation and experimental tests on a 60 kW prototype. It was observed that, in practice, digital PWM techniques are better suited for optimizing the AC converter performance, while delta modulation techniques give better results in terms of DC current and voltage distortion. <<ETX>>
Rapid Task-Related Plasticity of Spectrotemporal Receptive Fields in the Auditory Midbrain

Previous research has demonstrated that auditory cortical neurons can modify their receptive fields when animals engage in auditory detection tasks. We tested for this form of task-related plasticity in the inferior colliculus (IC) of ferrets trained to detect a pure tone target in a sequence of noise distractors that did not overlap in time. During behavior, responses were suppressed at the target tone frequency in approximately half of IC neurons relative to the passive state. This suppression often resulted from a combination of a local tuning change and a global change in overall excitability. Local and global suppression were stronger when the target frequency was aligned to neuronal best frequency. Local suppression in the IC was indistinguishable from that described previously in auditory cortex, while global suppression was unique to the IC. The results demonstrate that engaging in an auditory task can change selectivity for task-relevant features in the midbrain, an area where these effects have not been reported previously. SIGNIFICANCE STATEMENT Previous studies have demonstrated that the receptive fields of cortical neurons are modified when animals engage in auditory behaviors, a process that is hypothesized to provide the basis for segregating sound sources in an auditory scene. This study demonstrates for the first time that receptive fields of neurons in the midbrain inferior colliculus are also modified during behavior. The magnitude of the tuning changes is similar to previous reports in cortex. These results support a hierarchical model of behaviorally driven sound segregation that begins in the subcortical auditory network.
The KUPKB: a novel Web application to access multiomics data on kidney disease

The information gathered from the large number of omics experiments in renal biology is underexplored, as it is scattered over many publications or held in supplemental data. To address this, we have developed an open‐source Kidney and Urinary Pathway Knowledge Base (KUPKB) that facilitates simple exploration of these omics data. The KUPKB currently comprises 220 data sets (miRNA, mRNA, proteins, and metabolites) extracted from existing publications or databases. Researchers can explore the integrated data using the iKUP browser, and a simple template is provided to submit new omics data sets to the knowledge base. As an example of iKUP's use, we show how we identified, in silico, calreticulin as a protein induced in human interstitial fibrosis and tubular atrophy (IFTA) in chronic kidney transplant rejection; a link that would have been difficult to establish using existing Web‐based tools. Using immunohistochemistry, we validated in vivo this in silico result in human and rat biopsies of IFTA, thus identifying calreticulin as a potential new player in chronic kidney transplant rejection. The KUPKB provides a simple tool that enables users to quickly survey a wide range of omics data sets and has been shown to facilitate rapid hypothesis generation in the context of renal pathophysiology. —Klein, J., Jupp, S. , Moulos, P., Fernandez, M. , Buffin‐Meyer, B. , Casemayou, A. , Chaaya, R. , Charonis, A. , Bascands, J.‐L. , Stevens, R. , Schanstra, J. P. The KUPKB: a novel Web application to access multiomics data on kidney disease. FASEB J. 26, 2145‐2153 (2012). www.fasebj. org
Systematic Prediction of Pharmacodynamic Drug-Drug Interactions through Protein-Protein-Interaction Network

Identifying drug-drug interactions (DDIs) is a major challenge in drug development. Previous attempts have established formal approaches for pharmacokinetic (PK) DDIs, but there is not a feasible solution for pharmacodynamic (PD) DDIs because the endpoint is often a serious adverse event rather than a measurable change in drug concentration. Here, we developed a metric “S-score” that measures the strength of network connection between drug targets to predict PD DDIs. Utilizing known PD DDIs as golden standard positives (GSPs), we observed a significant correlation between S-score and the likelihood a PD DDI occurs. Our prediction was robust and surpassed existing methods as validated by two independent GSPs. Analysis of clinical side effect data suggested that the drugs having predicted DDIs have similar side effects. We further incorporated this clinical side effects evidence with S-score to increase the prediction specificity and sensitivity through a Bayesian probabilistic model. We have predicted 9,626 potential PD DDIs at the accuracy of 82% and the recall of 62%. Importantly, our algorithm provided opportunities for better understanding the potential molecular mechanisms or physiological effects underlying DDIs, as illustrated by the case studies.
Experiences with Electronic Auctions in the Dutch Flower Industry

1 electronic markets is expected to grow rap1 point of view by Davis and Holt (1993), Hendricks and Por te r (1988) , a n d Rothkopf and Harstad (1994). More recently, the flower auction markets were investigated in more detail. Ajit Kambil and Eric van Heck (1996) specified a generalizable model of exchange processes and developed a process-stakeholder analysis framework to evaluate alternative market designs. In this framework, see figure 1, five trade processes (search, valuation, logistics, payments and settlements, authentication) and five trade context processes (communications and computing, product representation, legitimation, influence, and dispute resolution) are distinguished.
ImpEDE: A multidimensional design-space exploration framework for biomedical-implant processors

The demand for biomedical implants keeps increasing. However, most of the current implant design methodologies involve custom-ASIC design. The SiMS project aims to change this process and make implant design more modular, flexible, faster and extensible. The most recent work within the SiMS context provides ImpEDE, a framework based on a multiobjective genetic algorithm, for automatic exploration of the design space of implant processors. The framework provides the processor designer with a Pareto front through which informed decisions can be made about specific implant families after analyzing their particular tradeoffs and requirements. A highly efficient, parallelized version of the genetic algorithm is also used to evolve the front and has as its objectives the optimization of power, performance and area. In addition, we illustrate the extensibility of our framework by modifying it to include a case study of a synthetic implant application with hard realtime deadlines.
Effects of TAT-conjugated platinum nanoparticles on lifespan of mitochondrial electron transport complex I-deficient Caenorhabditis elegans, nuo-1

Platinum nanoparticle (Pt-np) species are superoxide dismutase/catalase mimetics and also have an activity similar to that of mitochondrial electron transport complex I. To examine if this complex I-like activity functions in vivo, we studied the effects of Pt-nps on the lifespan of a mitochondrial complex I-deficient Caenorhabditis elegans mutant, nuo-1 (LB25) compared with wild-type N2. We synthesized a fusion protein of a cell-penetrating peptide, human immunodeficiency virus-1 TAT (48–60), C-terminally linked to a peptide with a high affinity to platinum (GRKKRRQRRRPPQ-DRTSTWR). Pt-nps were functionalized by conjugation with this fusion protein at a 1:1 ratio of TAT-PtBP to Pt atoms. Adult worms were treated with conjugated Pt-nps for 10 days. The mean lifespan of untreated N2 and LB25 was 19.6 ± 0.4 and 11.8 ± 0.3 days, respectively. Using 5 μM of conjugated Pt-nps, the lifespan of N2 and LB25 was maximally extended. This maximal lifespan extension of LB25 was 31.9 ± 2.6%, which was significantly greater than that of N2 (21.1 ± 1.7%, P < 0.05 by Student’s t-test). Internalization of Pt into the whole body and mitochondria was similar between these two strains. Excessive accumulation of reactive oxygen species was not observed in the cytosol or mitochondria of untreated LB25. Treatment for five days with 5 μM conjugated Pt-nps decreased cytosolic and mitochondrial reactive oxygen species in N2 and LB25 to a similar extent. The ratio of [NAD+]/[NADH] was very low in the whole body and mitochondria of control LB25. After five days of treatment with 5 μM conjugated Pt-nps, the ratio of [NAD+]/[NADH] was increased in N2 and LB25. However, the degree of the increase was much higher in LB25 than in N2. Pt-nps function as NADH oxidase and recover the [NAD+]/[NADH] ratio in LB25, leading to effective extension of the lifespan of LB25.
Deep Learning Neural Network with Semi supervised Segmentation for Predicting Retinal and Cancer Cell Diseased Images.

In medical field, diagnosis of diseases competently carried out by using the image processing. So that to retrieve the relevant data from the amalgamation of resulting image is too difficult. Here the segmentation done by semi supervised learning then the result is tuned by using Deep Learning Neural Network. Higher tuning of results will leads to efficient detection of disease. The experiment done by using retinal image data sets in order to predict any disease affected or not. The aim of this paper is to keenly predict diseased image or not by the efficient tuning of image. Keywords—segmentation; semi supervised learning; Neural network; Deep learning neural network. I. INTRODUCTION Nowadays diseases related to eye are increasing and many people fell in to blindness. Image processing is the area which leads with image analysis and which involves the study of feature extraction, segmentation and classification. The process of recognizing the patterns that are used to the performance of an image . Diabetic retinopathy one of the complicated disease which affects to the retina and outcome is the total blindness. The technique segmentation is the method of identifying regions of pixels in an image so as to find out the correlation with objects. The programmed mining of blood vessels in retinal images is one of the important step in computer aided diagnosis and treatment of diabetic retinopathy, glaucoma, arteriosclerosis, obesity, retinal artery occlusion and hypertension. Segmentation can be done by supervised, unsupervised or semi supervised. Here using semi supervised segmentation method because of easy to use labeled data and unlabeled data together. Semi supervised segmentation have much applications in medical image data sets. To efficient tuning purpose, the segmented output classified under the neural network. Neural Network has good performance in non linear data bases such a way that multi-layer neural network could accurately estimated to any linear or non-linear capacity. Through tuning the incomplete data , can achieve the estimate prediction of the whole data with the generalization capability of neural network. By using neural network easy to store information of the continuous quantity ,by using adjacent sampling points relationship. Neural network store the continuous quantity so as to reduce the amount of storage space. For analysis of medical images , we can consider the ideal
Stressful Events and Continued Smoking and Continued Alcohol Consumption during Mid-Pregnancy

Aim to examine whether the severity of different categories of stressful events is associated with continued smoking and alcohol consumption during mid-pregnancy. Also, we explored the explanation of these associations by anxiety and depressive symptoms during pregnancy. Finally, we studied whether the severity of stressful events was associated with the amount of cigarettes and alcohol used by continued users. Method we conducted a cross-sectional analysis using data from a population-based prospective cohort study. Pregnant women were recruited via midwifery practices throughout The Netherlands. We analyzed women who continued smoking (n = 113) or quit (n = 290), and women who continued alcohol consumption (n = 124) or quit (n = 1403) during pregnancy. Smoking, alcohol consumption, and perceived severity of stressful events were measured at 19 weeks of gestation. The State Trait Anxiety Inventory and the Edinburgh Postnatal Depression Scale were filled out at 14 weeks of gestation. Odds ratios were calculated as association measures and indicated the relative increase for the odds of continuation of smoking and alcohol consumption for the maximum severity score compared to the minimum score. Findings severity of the following stressful event categories was associated with continued alcohol consumption: ‘conflict with loved ones’ (OR = 10.4, p<0.01), ‘crime related’ (OR = 35.7, p<0.05), ‘pregnancy-specific’ (OR = 13.4, p<0.05), and the total including all events (OR = 17.2, p<0.05). Adjustment for potential confounders (age, parity and educational level) did not notably change the estimates. There was no association of anxiety and depressive symptoms with continued smoking or alcohol consumption. No associations emerged for continued smoking and severity of stressful events. The amount of cigarettes and alcohol consumption among continued users was not associated with severity of stressful events. Conclusions Our findings may be relevant for health care providers, in particular midwives and general practitioners. The impact of stressful events may be considered when advising pregnant women on smoking and alcohol consumption.