nils-herrmann/clean_scirepeval huggingface dataset:
Development and validation of the WASP classification system for optical diagnosis of adenomas, hyperplastic polyps and sessile serrated adenomas/polyps.

Accurate endoscopic differentiation would enable to resect and discard small and diminutive colonic lesions, thereby increasing cost-efficiency. Current classification systems based on narrow band imaging (NBI), however, do not include neoplastic sessile serrated adenomas/polyps (SSA/Ps). We aimed to develop and validate a new classification system for endoscopic differentiation of adenomas, hyperplastic polyps and SSA/Ps <10 mm.



We developed the Workgroup serrAted polypS and Polyposis (WASP) classification, combining the NBI International Colorectal Endoscopic classification and criteria for differentiation of SSA/Ps in a stepwise approach. Ten consultant gastroenterologists predicted polyp histology, including levels of confidence, based on the endoscopic aspect of 45 polyps, before and after participation in training in the WASP classification. After 6 months, the same endoscopists predicted polyp histology of a new set of 50 polyps, with a ratio of lesions comparable to daily practice.



The accuracy of optical diagnosis was 0.63 (95% CI 0.54 to 0.71) at baseline, which improved to 0.79 (95% CI 0.72 to 0.86, p<0.001) after training. For polyps diagnosed with high confidence the accuracy was 0.73 (95% CI 0.64 to 0.82), which improved to 0.87 (95% CI 0.80 to 0.95, p<0.01). The accuracy of optical diagnosis after 6 months was 0.76 (95% CI 0.72 to 0.80), increasing to 0.84 (95% CI 0.81 to 0.88) considering high confidence diagnosis. The combined negative predictive value with high confidence of diminutive neoplastic lesions (adenomas and SSA/Ps together) was 0.91 (95% CI 0.83 to 0.96).



We developed and validated the first integrative classification method for endoscopic differentiation of small and diminutive adenomas, hyperplastic polyps and SSA/Ps. In a still image evaluation setting, introduction of the WASP classification significantly improved the accuracy of optical diagnosis overall as well as SSA/P in particular, which proved to be sustainable after 6 months.
Simulation and singularity analysis of 3-PRS parallel manipulator

This work focuses on the modelling and simulation of 3-PRS (Prismatic - Revolute - Spherical) Tripod Parallel Manipulator. This tripod mechanism consists of base platform and movable platform, which are connected by means of three links or limbs. Spherical joints are used to connect one end of the link and the moving platform and the other end of the link is connected by revolute joint to the nut. This tripod type Parallel Manipulator is having two orientation freedoms and one translation freedom, which is actuated by means of screw pair, which in turn is operated by a stepper motor. This proposed tripod mechanism is modelled and simulated by using ADAMS®. The simulation results are obtained by considering the geometrical parameters, Transmission angle of the link and Singularity of the mechanism. From the simulation results a study is carried out based on torque at the joints, angular tilt and singular positions of the parallel manipulator.
SIC induction smart welder integrated in an industry 4.0 network

Induction industrial welding is one of the most straightforward application for the power inverter. Practical industrial welders require at the same time power levels up to 1 MW while frequencies are in the range between 200–500 kHz, depending on the characteristics of the tube to be weld. SiC devices, as per its superior high frequency characteristics, are ideal components for this type of high power, high frequency inverters, but several aspects as the long term reliability, short circuit capability, cost issues of SiC material and others have to be considered in the use of this material in industrial welders. Another important issue in todays IH inverters is smartness and their capability to be integrated in a Industry 4.0 network, as actual complex IH systems require advanced communication features The paper aims to give practical technical considerations, based on experimental results, for the realistic use of SiC devices in resonant inverters for this type of industrial material processing application as well as some ideas of providing intelligence to IH converters and advanced services for the integration in an Industry 4.0 network.
Computational Complexity and the Function-Structure-Environment Loop of the Brain

At present, the brain is viewed primarily as a biological computer. But, crucially, the plasticity of the brain’s structure leads it to vary in functionally significant ways across individuals. Understanding the brain necessitates an understanding of the range of such variation. For example, the number of neurons in the brain and its finer structures impose inherent limitations on the functionality it can realize. The relationship between such quantitative limits on the resources available and the computations that are feasible with such resources is the subject of study in computational complexity theory. Computational complexity is a potentially useful conceptual framework because it enables the meaningful study of the family of possible structures as a whole—the study of “the brain,” as opposed to some particular brain. The language of computational complexity also provides a means of formally capturing capabilities of the brain, which may otherwise be philosophically thorny.
The sudden infant death syndrome.

Robert M. Golub, MD, Editor The JAMA Patient Page is a public service of JAMA. The information and recommendations appearing on this page are appropriate in most instances, but they are not a substitute for medical diagnosis. For specific information concerning your personal medical condition, JAMA suggests that you consult your physician. This page may be photocopied noncommercially by physicians and other health care professionals to share with patients. To purchase bulk reprints, call 312/464-0776. C H IL D H E A TH The Journal of the American Medical Association
Collocation Software for Boundary-Value ODEs

The use of a general-purpose code, COLSYS, is described. The code is capable of solving mixed-order systems of boundary-value problems in ordinary differential equations. The method of spline collocation at Gaussian points is implemented using a B-spline basis. Approximate solutions are computed on a sequence of automatically selected meshes until a user-specified set of tolerances is satisfied. A damped Newton's method is used for the nonlinear iteration. The code has been found to be particularly effective for difficult problems. It is intended that a user be able to use COLSYS easily after reading its algorithm description. The use of the code is then illustrated by examples demonstrating its effectiveness and capabilities.
Design of a High-performance Envelope Detector

A novel envelope detector structure is proposed in this paper that overcomes the traditional trade-off required in these circuits, improving both the tracking and keeping of the signal. The method relies on holding the signal by two capacitors, discharging one when the other is in hold mode and employing the held signals to form the output. Simulation results show a saving greater than 60% of the capacitor area for the same ripple (0.3%) and a release time constant (0.4¿s) much smaller than that obtained by the conventional circuits.
A 1.2 V Low-Power CMOS Chopper-Stabilized Analog Front-End IC for Glucose Monitoring

A low-power 1.2 V CMOS chopper-stabilized analog front-end integrated circuit (IC) for glucose monitoring is presented in this letter. The operating parameters of the IC, including reference voltage in potentiostat, current offset, output gain, and offset, are fully programmable. The IC is fabricated using 0.13-μm CMOS technology, has an active area of 1.4 mm × 4.3 mm, and its power consumption is 30.2 μW. Furthermore, a chopper-stabilized open-loop transimpedance amplifier is proposed for low-power and low-noise implementation. The integrated input-referred current noise is 260 pArms with a bandwidth of 100 Hz.
Fuel cell applications on more electrical aircraft

In order to meet the increasing environmental and economic requirements, commercial aircraft industries have been challenged to reduce fuel consumption, noise and emissions. As a result, more electrical aircraft (MEA), on which engine driven electrical power replaces other primary powers, is being investigated. However, with the increasing demands of electrical power capacity on MEA, the engines have to be redesigned to supply enough power and space for bigger generators. In order to avoid this problem, fuel cell systems could partially/entirely replace the engine driven generators to supply electric power on board. Compared to the traditional electrical power system which is driven by main engines/auxiliary power unit (APU) on MEA, fuel cell based systems would be more efficient and more environmental friendly. Also, fuel cells could work continuously during the entire flight envelope. This paper introduces fuel cell system concepts on MEA. Characters of solid oxide fuel cell (SOFC) and polymer electrolyte membrane fuel cell (PEMFC) are compared. An SOFC APU application on MEA is introduced. Finally, challenges of fell cells application on MEA are discussed.
79 GHz Slot Antennas Based on Substrate Integrated Waveguides (SIW) in a Flexible Printed Circuit Board

The design, fabrication and characterization of 79 GHz slot antennas based on substrate integrated waveguides (SIW) are presented in this paper. All the prototypes are fabricated in a polyimide flex foil using printed circuit board (PCB) fabrication processes. A novel concept is used to minimize the leakage losses of the SIWs at millimeter wave frequencies. Different losses in the SIWs are analyzed. SIW-based single slot antenna, longitudinal and four-by-four slot array antennas are numerically and experimentally studied. Measurements of the antennas show approximately 4.7%, 5.4% and 10.7% impedance bandwidth (S11=-10 dB) with 2.8 dBi, 6.0 dBi and 11.0 dBi maximum antenna gain around 79 GHz, respectively. The measured results are in good agreement with the numerical simulations.
A Machine Learning Approach for Evaluating Creative Artifacts

Much work has been done in understanding human creativity and defining measures to evaluate creativity. This is necessary mainly for the reason of having an objective and automatic way of quantifying creative artifacts. In this work, we propose a regression-based learning framework which takes into account quantitatively the essential criteria for creativity like novelty, influence, value and unexpectedness. As it is often the case with most creative domains, there is no clear ground truth available for creativity. Our proposed learning framework is applicable to all creative domains; yet we evaluate it on a dataset of movies created from IMDb and Rotten Tomatoes due to availability of audience and critic scores, which can be used as proxy ground truth labels for creativity. We report promising results and observations from our experiments in the following ways : 1) Correlation of creative criteria with critic scores, 2) Improvement in movie rating prediction with inclusion of various creative criteria, and 3) Identification of creative movies.
Multiband MIMO Antenna for GSM, DCS, and LTE Indoor Applications

A novel and compact planar multiband multiple-input-multiple-output (MIMO) antenna is presented. The proposed antenna is composed of two symmetrical radiating elements connected by neutralizing line to cancel the reactive coupling. The radiating element is designed for different frequencies operating in GSM 900 MHz, DCS 1800 MHz, LTE-E 2300 MHz, and LTE-D 2600 MHz, which consists of a folded monopole and a beveled rectangular metal patch. The presented antenna is fed by using 50-Ω coplanar waveguide (CPW) transmission lines. Four slits are etched into the ground plane for reducing the mutual coupling. The measured results show that the proposed antenna has good impedance matching, isolation, peak gain, and radiation patterns. The radiation efficiency and diversity gain (DG) in the servicing frequencies are pretty well. In the Ericsson indoor experiment, three kinds of antenna feed systems are discussed. The proposed antenna shows good performance in Long Term Evolution (LTE) reference signal receiving power (RSRP), download speed, and upload speed.
Evaluating semantic metamemory: Retrospective confidence judgements on the information subtest.

The current research explored the potential value of adding a supplementary measure of metamemory to the Information subtest of the Wechsler Adult Intelligence Scale - Third Edition (WAIS-III in Study 1) or Fourth Edition (WAIS-IV in Study 2) in order to assess its relationship to other neuropsychological measures and to brain injury. After completing the Information subtest, neuropsychological examinees were asked to make retrospective confidence judgements (RCJ) by rating their answer certainty in the original order of item administration. In Study 1 (N = 52) and study 2 (N = 30), correct answers were rated with significantly more certainty than wrong answers (termed a "confidence gap"), and in both studies, higher confidence for wrong answers was significantly correlated with poorer performance on the Wisconsin Card Sorting Test (for categories completed r = -.58 in Study 1, and r = -.47 in Study 2; for perseverative errors r = .44 in Study 1, and r = .45 in Study 2). In both studies, a number of examinees with positive CT findings had a very small or reversed confidence gap. These findings suggest that semantic metamemory is sensitive to executive functioning and brain injury and should be assessed in the neuropsychological examination.
A Cost-based Optimizer for Gradient Descent Optimization

As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a specific form. Furthermore, these optimization problems can be efficiently solved using variations of the gradient descent (GD) algorithm. Thus, to decouple a user specification of an ML task from its execution, a key component is a GD optimizer. We propose a cost-based GD optimizer that selects the best GD plan for a given ML task. To build our optimizer, we introduce a set of abstract operators for expressing GD algorithms and propose a novel approach to estimate the number of iterations a GD algorithm requires to converge. Extensive experiments on real and synthetic datasets show that our optimizer not only chooses the best GD plan but also allows for optimizations that achieve orders of magnitude performance speed-up.
Chinese Dialect Identification Using Tone Features Based on Pitch Flux

This paper presents a method to extract tone relevant features based on pitch flux from continuous speech signal. The autocorrelations of two adjacent frames are calculated and the covariance between them is estimated to extract multi-dimensional pitch flux features. These features, together with MFCCs, are modeled in a 2-stream GMM models, and are tested in a 3-dialect identification task for Chinese. The pitch flux features have shown to be very effective in identifying tonal languages with short speech segments. For the test speech segments of 3 seconds, 2-stream model achieves more than 30% error reduction over MFCC-based model
A Microtext Corpus for Persuasion Detection in Dialog

Automatic detection of persuasion is essential for machine interaction on the social web. To facilitate automated persuasion detection, we present a novel microtext corpus derived from hostage negotiation transcripts as well as a detailed manual (codebook) for persuasion annotation. Our corpus, called the NPS Persuasion Corpus, consists of 37 transcripts from four sets of hostage negotiation transcriptions. Each utterance in the corpus is hand annotated for one of nine categories of persuasion based on Cialdini’s model: reciprocity, commitment, consistency, liking, authority, social proof, scarcity, other, and not persuasive. Initial results using three supervised learning algorithms (Naı̈ve Bayes, Maximum Entropy, and Support Vector Machines) combined with gappy and orthogonal sparse bigram feature expansion techniques show that the annotation process did capture machine learnable features of persuasion with F-scores better than baseline.
A New Delayless Subband Adaptive Filtering Algorithm for Active Noise Control Systems

Subband adaptive filtering (SAF) techniques play a prominent role in designing active noise control (ANC) systems. They reduce the computational complexity of ANC algorithms, particularly, when the acoustic noise is a broadband signal and the system models have long impulse responses. In the commonly used uniform-discrete Fourier transform (DFT)-modulated (UDFTM) filter banks, increasing the number of subbands decreases the computational burden but can introduce excessive distortion, degrading performance of the ANC system. In this paper, we propose a new UDFTM-based adaptive subband filtering method that alleviates the degrading effects of the delay and side-lobe distortion introduced by the prototype filter on the system performance. The delay in filter bank is reduced by prototype filter design and the side-lobe distortion is compensated for by oversampling and appropriate stacking of subband weights. Experimental results show the improvement of performance and computational complexity of the proposed method in comparison to two commonly used subband and block adaptive filtering algorithms.
DEVELOPING INNOVATION CAPABILITY IN ORGANISATIONS : A DYNAMIC CAPABILITIES APPROACH

This paper draws together knowledge from a variety of fields to propose that innovation management can be viewed as a form of organisational capability. Excellent companies invest and nurture this capability, from which they execute effective innovation processes, leading to innovations in new product, services and processes, and superior business performance results. An extensive review of the literature on innovation management, along with a case study of Cisco Systems, develops a conceptual model of the firm as an innovation engine. This new operating model sees substantial investment in innovation capability as the primary engine for wealth creation, rather than the possession of physical assets. Building on the dynamic capabilities literature, an “innovation capability” construct is proposed with seven elements. These are vision and strategy, harnessing the competence base, organisational intelligence, creativity and idea management, organisational structures and systems, culture and climate, and management of technology.
Product Recommendation Method based on Onomatopoeia Expressing Texture

With the widespread use of online shopping in recent years, consumer search requests for products have become more diverse. Previous web search methods have used adjectives as input by consumers. However, given that the number of adjectives that can be used to express textures is limited, it is debatable whether adjectives are capable of richly expressing variations of product textures. In Japanese, tactile experiences are easily and frequently expressed by onomatopoeia, such as “ fuwa-fuwa” which indicates a soft and light sensation. Onomatopoeia are useful for understanding not only material textures but also a user’s intuitive, sensitive, and even ambiguous feelings evoked by materials. In this study, we propose a system to recommend products corresponding to product textures associated with Japanese onomatopoeia based on their symbolic sound associations between the onomatopoeia phonemes and the texture sensations. Our system quantitatively estimates the texture sensations of onomatopoeia input by users, and calculates the similarities between the users’ impressions of the onomatopoeia and those of product pictures. Our system also suggests products which best match the entered onomatopoeia. An evaluation of our method revealed that the best performance was achieved when the SIFT features, the colors of product pictures, and text describing product pictures were used; Specifically, precision was 66 for the top 15 search results. Our system is expected to contribute to online shopping activity as an intuitive product recommendation system.
Enhancing Reputation via Price Discounts in E-Commerce Systems: A Data-Driven Approach

Reputation systems have become an indispensable component of modern E-commerce systems, as they help buyers make informed decisions in choosing trustworthy sellers. To attract buyers and increase the transaction volume, sellers need to earn reasonably high reputation scores. This process usually takes a substantial amount of time. To accelerate this process, sellers can provide price discounts to attract users, but the underlying difficulty is that sellers have no prior knowledge on buyers’ preferences over price discounts. In this article, we develop an online algorithm to infer the optimal discount rate from data. We first formulate an optimization framework to select the optimal discount rate given buyers’ discount preferences, which is a tradeoff between the short-term profit and the ramp-up time (for reputation). We then derive the closed-form optimal discount rate, which gives us key insights in applying a stochastic bandits framework to infer the optimal discount rate from the transaction data with regret upper bounds. We show that the computational complexity of evaluating the performance metrics is infeasibly high, and therefore, we develop efficient randomized algorithms with guaranteed performance to approximate them. Finally, we conduct experiments on a dataset crawled from eBay. Experimental results show that our framework can trade 60% of the short-term profit for reducing the ramp-up time by 40%. This reduction in the ramp-up time can increase the long-term profit of a seller by at least 20%.
A Computationally Efficient Evolutionary Algorithm for Real-Parameter Optimization

Due to increasing interest in solving real-world optimization problems using evolutionary algorithms (EAs), researchers have recently developed a number of real-parameter genetic algorithms (GAs). In these studies, the main research effort is spent on developing an efficient recombination operator. Such recombination operators use probability distributions around the parent solutions to create an offspring. Some operators emphasize solutions at the center of mass of parents and some around the parents. In this paper, we propose a generic parent-centric recombination operator (PCX) and a steady-state, elite-preserving, scalable, and computationally fast population-alteration model (we call the G3 model). The performance of the G3 model with the PCX operator is investigated on three commonly used test problems and is compared with a number of evolutionary and classical optimization algorithms including other real-parameter GAs with the unimodal normal distribution crossover (UNDX) and the simplex crossover (SPX) operators, the correlated self-adaptive evolution strategy, the covariance matrix adaptation evolution strategy (CMA-ES), the differential evolution technique, and the quasi-Newton method. The proposed approach is found to consistently and reliably perform better than all other methods used in the study. A scale-up study with problem sizes up to 500 variables shows a polynomial computational complexity of the proposed approach. This extensive study clearly demonstrates the power of the proposed technique in tackling real-parameter optimization problems.