nils-herrmann/clean_scirepeval huggingface dataset:
18F-FDG PET/CT to Predict Response to Neoadjuvant Chemotherapy and Prognosis in Inflammatory Breast Cancer.

The aim of this prospective study was to assess the predictive value of (18)F-FDG PET/CT imaging for pathologic response to neoadjuvant chemotherapy (NACT) and outcome in inflammatory breast cancer (IBC) patients.



Twenty-three consecutive patients (51 y ± 12.7) with newly diagnosed IBC, assessed by PET/CT at baseline (PET1), after the third course of NACT (PET2), and before surgery (PET3), were included. The patients were divided into 2 groups according to pathologic response as assessed by the Sataloff classification: pathologic complete response for complete responders (stage TA and NA or NB) and non-pathologic complete response for noncomplete responders (not stage A for tumor or not stage NA or NB for lymph nodes). In addition to maximum standardized uptake value (SUVmax) measurements, a global breast metabolic tumor volume (MTV) was delineated using a semiautomatic segmentation method. Changes in SUVmax and MTV between PET1 and PET2 (ΔSUV1-2; ΔMTV1-2) and PET1 and PET3 (ΔSUV1-3; ΔMTV1-3) were measured.



Mean SUVmax on PET1, PET2, and PET3 did not statistically differ between the 2 pathologic response groups. On receiver-operating-characteristic analysis, a 72% cutoff for ΔSUV1-3 provided the best performance to predict residual disease, with sensitivity, specificity, and accuracy of 61%, 80%, and 65%, respectively. On univariate analysis, the 72% cutoff for ΔSUV1-3 was the best predictor of distant metastasis-free survival (P = 0.05). On multivariate analysis, the 72% cutoff for ΔSUV1-3 was an independent predictor of distant metastasis-free survival (P = 0.01).



Our results emphasize the good predictive value of change in SUVmax between baseline and before surgery to assess pathologic response and survival in IBC patients undergoing NACT.
Coupled Node Similarity Learning for Community Detection in Attributed Networks

Attributed networks consist of not only a network structure but also node attributes. Most existing community detection algorithms only focus on network structures and ignore node attributes, which are also important. Although some algorithms using both node attributes and network structure information have been proposed in recent years, the complex hierarchical coupling relationships within and between attributes, nodes and network structure have not been considered. Such hierarchical couplings are driving factors in community formation. This paper introduces a novel coupled node similarity (CNS) to involve and learn attribute and structure couplings and compute the similarity within and between nodes with categorical attributes in a network. CNS learns and integrates the frequency-based intra-attribute coupled similarity within an attribute, the co-occurrence-based inter-attribute coupled similarity between attributes, and coupled attribute-to-structure similarity based on the homophily property. CNS is then used to generate the weights of edges and transfer a plain graph to a weighted graph. Clustering algorithms detect community structures that are topologically well-connected and semantically coherent on the weighted graphs. Extensive experiments verify the effectiveness of CNS-based community detection algorithms on several data sets by comparing with the state-of-the-art node similarity measures, whether they involve node attribute information and hierarchical interactions, and on various levels of network structure complexity.
On the feasiblity of ISAR processing of stepped frequency waveforms

Inverse synthetic aperture radar imaging of moving targets with a stepped frequency waveform presents unique challenges. Intra-step target motion introduces phase discontinuities between frequency bands, which in turn produce degraded range side lobes. Frequency stitching of the stepped-frequency waveform to emulate a contiguous bandwidth can dramatically reduce the effective pulse repetition frequency, which then may impact the maximize target size that can be unambiguously measured and imaged via ISAR. This paper analyzes these effects and validates results via simulated data.
A decision tree using CUDA GPUs

Classification is an important issue both in Machine Learning and Data Mining. Decision tree is one of the famous classification models. In the reality case, the dimension of data is high and the data size is huge. Building a decision in large data base cost much time in computation. It is a computationally expensive problem.
 GPU is a special design processor of graphic. The highly parallel features of graphic processing made today's GPU architecture. GPGPU means use GPU to solve non-graphic problems which need amounts of computation power. Since the high performance and capacity/price ratio, many researches use GPU to process lots computation. Compute Unified Device Architecture (CUDA) is a GPGPU solution provided by NVIDIA.
 This paper provides a new parallel decision tree algorithm base on CUDA. The algorithm parallel computes building phase of decision tree.
Pharmacology and Toxicology of Polyphenols with Potential As Neurotropic Agents in Non-communicable Diseases.

The central nervous system (CNS) is involved in organic integration. Nervous modulation via bioactive compounds can modify metabolism in order to prevent systemic noncommunicable diseases (NCDs). Concerning this, plant polyphenols are proposed as neurotropic chemopreventive/ therapeutic agents, given their redox and regulating properties.



To review polyphenolic pharmacology and potential neurological impact on NCDs.



First, polyphenolic chemistry was presented, as well as pharmacology, i.e. kinetics and dynamics. Toxicology was particularly described. Then, functional relevance of these compounds was reviewed focusing on the metabolic CNS participation to modulate NCDs, with data being finally integrated.



Oxidative stress is a major risk factor for NCDs. Polyphenols regulate the redox biology of different organic systems including the CNS, which participates in metabolic homeostasis. Polyphenolic neurotropism is determined by certain pharmacological characteristics, modifying nervous and systemic physiopathology, acting on several biological targets. Nonetheless, because these phytochemicals can trigger toxic effects, they should not be recommended indiscriminately.



Summing up, the modulating effects of polyphenols allow for the physiological role of CNS on metabolism and organic integration to be utilized in order to prevent NCDs, without losing sight of the risks.
Downlink MIMO with Frequency-Domain Packet Scheduling for 3GPP LTE

This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques on the 3GPP Long Term Evolution (LTE) downlink. We impose the LTE MIMO constraint of selecting only one MIMO mode (spatial multiplexing or transmit diversity) per user per transmission time interval (TTI). First, we address the optimal MIMO mode selection (multiplexing or diversity) per user in each TTI in order to maximize the proportional fair (PF) criterion extended to frequency and spatial domains. We prove that the SU-MIMO (single-user MIMO) FDPS problem under the LTE requirement is NP-hard and therefore, we develop two approximation algorithms (one with full channel feedback and the other with partial channel feedback) with provable performance bounds. Based on 3GPP LTE system model simulations, the approximation algorithm with partial channel feedback is shown to have comparable performance to the one with full channel feedback, while significantly reducing the channel feedback overhead by nearly 50%.
COCA: Computation Offload to Clouds Using AOP

In this paper, we describe COCA -- Computation Offload to Clouds using AOP (aspect-oriented programming). COCA is a programming framework that allows smart phones application developers to offload part of the computation to servers in the cloud easily. COCA works at the source level. By harnessing the power of AOP, \name inserts appropriate offloading code into the source code of the target application based on the result of static and dynamic profiling. As a proof of concept, we integrate \name into the Android development environment and fully automate the new build process, making application programming and software maintenance easier. With COCA, mobile applications can now automatically offload part of the computation to the cloud, achieving better performance and longer battery life. Smart phones such as iPhone and Android phones can now easily leverage the immense computing power of the cloud to achieve tasks that were considered difficult before, such as having a more complicated artificial-intelligence engine.
Modelling pollution dispersion, the ecosystem and water quality in coastal waters: a review

This review is intended as a comprehensive but concise summary of present capabilities in coastal pollutant, ecosystem and water quality modelling. It reflects the recent rapid developments in multidisciplinary modelling in shelf seas. The behaviour of conservative pollutants that act as passive tracers is contrasted with those that have more complex behaviours, including oil spills. The importance of sediment modelling is emphasised, since contaminants commonly exist in both a dissolved and a particulate state, or adhere to sediments. Recently developed ecological models can have great complexity, reflecting the complexity of the real ecosystem. These models are now being linked to physical models of coastal waters and run with the same resolution. This has become possible only recently because of increases in computer power, particularly the availability of parallel systems at reasonable cost. The main advances in physical modelling are likely to come through greater understanding of turbulence and other sub-gridscale processes as well as increased resolution. In the coastal seas there is often a lack of oceanographic data, which is even greater for the many biological and chemical variables than it is for physical variables. This is probably the single most important factor limiting the progress of operational water quality models.  2002
A high-slope PTAT temperature sensor for frequency compensation of an RTC oscillator

A temperature sensor used to compensate the crystal oscillator frequency instability of a real time clock (RTC) is proposed in this paper. The sensor utilizes the difference of a current proportional to the absolute temperature (PTAT) and another complementary to the absolute temperature (CTAT), generating a high-slope PTAT voltage with minimum value close to zero. The introduced approach provides a voltage signal range that reduces the power and area consumption of a 7-bit successive approximation analog-to-digital converter (SAR-ADC). The principles of the circuit topology alongside the simulation results of corners and Monte Carlo analyzes are presented. A prototype is fabricated in a 0.18 μm CMOS technology and experimental results showed a temperature inaccuracy of -0.812 to 0.266 °C, with an average resolution of 18.01 mV/°C, using a one-point calibration within the range of 0 to 40 °C. The sensor features an area of 0.08 mm2 and consumes less than 73.8 μW from a 1.8 V voltage supply.
An effective solution for a real cutting stock problem in manufacturing plastic rolls

We confront a practical cutting stock problem from a production plant of plastic rolls. The problem is a variant of the well-known one dimensional cutting stock, with particular constraints and optimization criteria defined by the experts of the company. We start by giving a problem formulation in which optimization criteria have been considered in linear hierarchy according to expert preferences, and then propose a heuristic solution based on a GRASP algorithm. The generation phase of this algorithm solves a simplified version which is rather similar to the conventional one dimensional cutting stock. To do that, we propose a Sequential Heuristic Randomized Procedure (SHRP). Then in the repairing phase, the solution of the simplified problem is transformed into a solution to the real problem. For experimental study we have chosen a set of problem instances of com-mon use to compare SHRP with another recent approach. Also, we show by means of examples, how our approach works over instances taken from the real production process. All authors are supported by MEC-FEDER Grant TIN2007-67466-C02-01 and by contract CN-05-127 of the University of Oviedo and the company ERVISA, and by FICYT under grant BP04-021. Ramiro Varela · Camino R. Vela · Jorge Puente Computing Technologies Group. Department of Computing, Artificial Intelligence Center, University of Oviedo, Spain. Campus de Viesques, 33271 Gijón. Ramiro Varela E-mail: ramiro@uniovi.es Camino R. Vela E-mail: crvela@uniovi.es Jorge Puente E-mail: puente@uniovi.es Maŕıa Sierra · Inés González-Rodŕıguez Department of Mathematics, Statistics and Computing. University of Cantabria, Spain. Los Castros s/n, 39005 Santander. Maŕıa Sierra E-mail: mariarita.sierra@unican.es Inés González-Rodŕıguez E-mail: ines.gonzalez@unican.es
The nature of correlation perception in scatterplots

For scatterplots with gaussian distributions of dots, the perception of Pearson correlation r can be described by two simple laws: a linear one for discrimination, and a logarithmic one for perceived magnitude (Rensink & Baldridge, 2010). The underlying perceptual mechanisms, however, remain poorly understood. To cast light on these, four different distributions of datapoints were examined. The first had 100 points with equal variance in both dimensions. Consistent with earlier results, just noticeable difference (JND) was a linear function of the distance away from r = 1, and the magnitude of perceived correlation a logarithmic function of this quantity. In addition, these laws were linked, with the intercept of the JND line being the inverse of the bias in perceived magnitude. Three other conditions were also examined: a dot cloud with 25 points, a horizontal compression of the cloud, and a cloud with a uniform distribution of dots. Performance was found to be similar in all conditions. The generality and form of these laws suggest that what underlies correlation perception is not a geometric structure such as the shape of the dot cloud, but the shape of the probability distribution of the dots, likely inferred via a form of ensemble coding. It is suggested that this reflects the ability of observers to perceive the information entropy in an image, with this quantity used as a proxy for Pearson correlation.
A Meta-Study of Algorithm Visualization Effectiveness

Algorithm visualization (AV) technology graphically illustrates how algorithms work. Despite the intuitive appeal of the technology, it has failed to catch on in mainstream computer science education. Some have attributed this failure to the mixed results of experimental studies designed to substantiate AV technology’s educational effectiveness. However, while several integrative reviews of AV technology have appeared, none has focused specifically on the software’s effectiveness by analyzing this body of experimental studies as a whole. In order to better understand the effectiveness of AV technology, we present a systematic metastudy of 24 experimental studies. We pursue two separate analyses: an analysis of independent variables, in which we tie each study to a particular guiding learning theory in an attempt to determine which guiding theory has had the most predictive success; and an analysis of dependent variables, which enables us to determine which measurement techniques have been most sensitive to the learning benefits of AV technology. Our most significant finding is that how students use AV technology has a greater impact on effectiveness than what AV technology shows them. Based on our findings, we formulate an agenda for future research into AV effectiveness. A META-
Advancement in Wide Area Monitoring Protection and Control Using PMU ’ s Model in MATLAB / SIMULINK

A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power systems worldwide and has led to operation of power systems closer to their stability limits and to power exchange in new patterns. These issues, as well as the on-going worldwide trend towards deregulation of the entire industry on the one hand and the increased need for accurate and better network monitoring on the other hand, force power utilities exposed to this pressure to demand new solutions for wide area monitoring, protection and control. Wide-area monitoring, protection, and control require communicating the specific-node information to a remote station but all information should be time synchronized so that to neutralize the time difference between information. It gives a complete simultaneous snap shot of the power system. The conventional system is not able to satisfy the time-synchronized requirement of power system. Phasor Measurement Unit (PMU) is enabler of time-synchronized measurement, it communicate the synchronized local information to remote station.
3D printed cardiovascular models for surgical planning in complex congenital heart diseases

A precise understanding of the anatomical structures of the heart and great vessels is essential for surgical planning in order to avoid unexpected findings. Rapid prototyping techniques are used to print three-dimensional (3D) replicas of patients’ cardiovascular anatomy based on 3D clinical images such as MRI. The purpose of this study is to explore the use of 3D patient-specific cardiovascular models using rapid prototyping techniques to improve surgical planning in patients with complex congenital heart disease.
The Hidden Cost of Microtransactions: Buying In-Game Advantages in Online Games Decreases a Player’s Status

With the advent of the internet, computer games have undergone substantial changes. Many games now contain some form of social interaction with other players. Furthermore, many games offer players the opportunity to buy upgrades using microtransactions. Based on social psychological theories on social comparisons, deservedness, and envy, we tested whether the use of these microtransactions would affect how players perceive another player using them. In one survey and two experimental scenario-studies with active gamers as participants (total N = 532), we found evidence supporting the idea that a player using microtransactions will be judged more negatively. More specifically, we find that gamers dislike it more when microtransactions allow the buying of functional benefits (that provide an in-game advantage) than when they are merely ornamental, and players who buy these functional benefits are respected less. In Studies 2 and 3 we found that players who use microtransactions are perceived as having a lower skill and status. This happens both when the microtransaction-using player is an enemy who bought a competitive advantage, as well as in games where one cooperates with the microtransaction-using player and the advantage is thus effectively shared. The findings have important practical implications for game design. They indicate how microtransactions can be implemented so that they have fewer negative social consequences, demonstrate the value of social psychological theories in predicting online behavior, and provide several avenues for further theoretical exploration.
Design and Simulation of Low Noise Amplifier Circuit for 5 GHz to 6 GHz

In first stage of each microwave receiver there is Low Noise Amplifier (LNA) circuit, and this stage has important rule in quality factor of the receiver. The design of a LNA in Radio Frequency (RF) circuit requires the trade-off many importance characteristics such as gain, Noise Figure (NF), stability, power consumption and complexity. This situation Forces desingners to make choices in the desing of RF circuits. In this paper the aim is to design and simulate a single stage LNA circuit with high gain and low noise using MESFET for frequency range of 5 GHz to 6 GHz. The desing simulation process is down using Advance Design System (ADS). A single stage LNA has successfully designed with 15.83 dB forward gain and 1.26 dB noise figure in frequency of 5.3 GHz. Also the designed LNA should be working stably In a frequency range of 5 GHz to 6 GHz. Advance Design System, Low Noise Amplifier, Radio Frequency,
Povidone-iodine induced post-surgical irritant contact dermatitis localized outside of the surgical incision area. Report of 27 cases and a literature review.

Povidone-iodine solution is an antiseptic that is used worldwide as surgical paint and is considered to have a low irritant potential. Post-surgical severe irritant dermatitis has been described after the misuse of this antiseptic in the surgical setting.



Between January 2011 and June 2013, 27 consecutive patients with post-surgical contact dermatitis localized outside of the surgical incision area were evaluated. Thirteen patients were also available for patch testing.



All patients developed dermatitis the day after the surgical procedure. Povidone-iodine solution was the only liquid in contact with the skin of our patients. Most typical lesions were distributed in a double lumbar parallel pattern, but they were also found in a random pattern or in areas where a protective pad or an occlusive medical device was glued to the skin. The patch test results with povidone-iodine were negative.



Povidone-iodine-induced post-surgical dermatitis may be a severe complication after prolonged surgical procedures. As stated in the literature and based on the observation that povidone-iodine-induced contact irritant dermatitis occurred in areas of pooling or occlusion, we speculate that povidone-iodine together with occlusion were the causes of the dermatitis epidemic that occurred in our surgical setting. Povidone-iodine dermatitis is a problem that is easily preventable through the implementation of minimal routine changes to adequately dry the solution in contact with the skin.
Analysis of Drain-Induced Barrier Rising in Short-Channel Negative-Capacitance FETs and Its Applications

We investigate the performance of hysteresis-free short-channel negative-capacitance FETs (NCFETs) by combining quantum-mechanical calculations with the Landau–Khalatnikov equation. When the subthreshold swing (SS) becomes smaller than 60 mV/dec, a negative value of drain-induced barrier lowering is obtained. This behavior, drain-induced barrier rising (DIBR), causes negative differential resistance in the output characteristics of the NCFETs. We also examine the performance of an inverter composed of hysteresis-free NCFETs to assess the effects of DIBR at the circuit level. Contrary to our expectation, although hysteresis-free NCFETs are used, hysteresis behavior is observed in the transfer properties of the inverter. Furthermore, it is expected that the NCFET inverter with hysteresis behavior can be used as a Schmitt trigger inverter.