nils-herrmann/clean_scirepeval huggingface dataset:
A 5.75 to 44 Gb/s Quarter Rate CDR With Data Rate Selection in 90 nm Bulk CMOS

This paper presents a quarter-rate clock and data recovery (CDR) circuit for plesiochronous serial I/O-links. The 2times-oversampling phase-tracking CDR, implemented in 90 nm bulk CMOS technology, covers the whole range of data rates from 5.75 to 44 Gb/s realized in a single IC by the novel feature of a data rate selection logic. Input data are sampled with eight parallel differential master-slave flip-flops, where bandwidth enhancement techniques were necessary for 90 nm CMOS. Precise and low-jitter local clock phases are generated by an analog delay-locked loop. These clock phases are aligned to the incoming data by four parallel phase rotators. The phase-tracking loop of the CDR is realized as a digital delay-locked loop and is therefore immune against process tolerances. The CDR is able to track a maximum frequency deviation of plusmn615 ppm between incoming data and a local reference clock and fulfills the extended XAUI jitter tolerance mask. A bit error rate <10-12 was verified up to 38 Gb/s using a 27 -1 PRBS pattern. With a low power consumption per data rate of only 5.74 mW/(Gb/s) the CDR meets the specifications of the International Technology Roadmap for Semiconductors for 90 nm CMOS serial I/O-links at the maximal data rate of 44 Gb/s. The CDR occupies a chip area of 0.2 mm2.
Eigen-gap of structure transition matrix: A new criterion for Image Quality Assessment

A new approach to Image Quality Assessment (IQA) is presented. The idea is based on the fact that two images are similar if their structural relationship within their blocks is preserved. To this end, a transition matrix is defined which exploits structural transitions between corresponding blocks of two images. The matrix contains valuable information about differences of two images, which should be transformed to a quality index. Eigen-value analysis over the transition matrix leads to a new distance measure called Eigen-gap. According to simulation results, the Eigen-gap is not only highly correlated to subjective scores but also, its performance is as good as the SSIM, a trustworthy index.
Adaptive Optical Self-Interference Cancellation Using a Semiconductor Optical Amplifier

We experimentally demonstrate an optical system that uses a semiconductor optical amplifier (SOA) to perform adaptive, analog self-interference cancellation for radio-frequency signals. The system subtracts a known interference signal from a corrupted received signal to recover a weak signal of interest. The SOA uses a combination of slow and fast light and cross-gain modulation to perform precise amplitude and phase matching to cancel the interference. The system achieves 38 dB of cancellation across 60-MHz instantaneous bandwidth and 56 dB of narrowband cancellation, limited by noise. The Nelder-Mead simplex algorithm is used to adaptively minimize the interference power through the control of the semiconductor's bias current and input optical power.
Neural Interface Emotiv EPOC and Arduino: Brain-Computer Interaction in a Proof of Concept

This study aims to demonstrate the interaction between the human being and the machine through a neural pattern recognizing interface, namely Emotiv EPOC, and a robotic device made by Arduino. The union of these technologies is assessed in specific tests, seeking a usable and stable binding with the smallest possible rate of error, based on a study of how the human electrical synapses are produced and captured by the electroencephalogram device, through examples of projects that achieved success using these technologies. In this study, the whole configuration of the software used to bind these technologies, as well as how they work, is explained, and the result of the experiments through an analysis of the tests performed is addressed. The difference in the results between genders and the influence of user feedback, as well as the accuracy of the technologies, are explained during the analysis of the data captured.
Multi-objectivization of short-term unit commitment under uncertainty using evolutionary algorithm

The short-term unit commitment problem is traditionally solved as a single-objective optimization problem with system operation cost as the only objective. This paper presents multi-objectivization of the short-term unit commitment problem in uncertain environment by considering reliability as an additional objective along with the economic objective. The uncertainties occurring due to unit outage and load forecast error are incorporated using loss of load probability (LOLP) and expected unserved energy (EUE) reliability indices. The multi-objectivized unit commitment problem in uncertain environment is solved using our earlier proposed multi-objective evolutionary algorithm . Simulations are performed on a test system of 26 thermal generating units and the results obtained are benchmarked against the study  where the unit commitment problem was solved as a reliability-constrained single-objective optimization problem. The simulation results demonstrate that the proposed multi-objectivized approach can find solutions with considerably lower cost than those obtained in the benchmark. Further, the efficiency and consistency of the proposed algorithm for multi-objectivized unit commitment problem is demonstrated by quantitative performance assessment using hypervolume indicator.
Feature-based surface parameterization and texture mapping

Surface parameterization is necessary for many graphics tasks: texture-preserving simplification, remeshing, surface painting, and precomputation of solid textures. The stretch caused by a given parameterization determines the sampling rate on the surface. In this article, we present an automatic parameterization method for segmenting a surface into patches that are then flattened with little stretch.
 Many objects consist of regions of relatively simple shapes, each of which has a natural parameterization. Based on this observation, we describe a three-stage feature-based patch creation method for manifold surfaces. The first two stages, genus reduction and feature identification, are performed with the help of distance-based surface functions. In the last stage, we create one or two patches for each feature region based on a covariance matrix of the feature's surface points.
 To reduce stretch during patch unfolding, we notice that stretch is a 2 × 2 tensor, which in ideal situations is the identity. Therefore, we use the <i>Green-Lagrange tensor</i> to measure and to guide the optimization process. Furthermore, we allow the boundary vertices of a patch to be optimized by adding <i>scaffold triangles</i>. We demonstrate our feature-based patch creation and patch unfolding methods for several textured models.
 Finally, to evaluate the quality of a given parameterization, we describe an image-based error measure that takes into account stretch, seams, smoothness, packing efficiency, and surface visibility.
Reinventing germanium avalanche photodetector for nanophotonic on-chip optical interconnects

Integration of optical communication circuits directly into high-performance microprocessor chips can enable extremely powerful computer systems. A germanium photodetector that can be monolithically integrated with silicon transistor technology is viewed as a key element in connecting chip components with infrared optical signals. Such a device should have the capability to detect very-low-power optical signals at very high speed. Although germanium avalanche photodetectors (APD) using charge amplification close to avalanche breakdown can achieve high gain and thus detect low-power optical signals, they are universally considered to suffer from an intolerably high amplification noise characteristic of germanium. High gain with low excess noise has been demonstrated using a germanium layer only for detection of light signals, with amplification taking place in a separate silicon layer. However, the relatively thick semiconductor layers that are required in such structures limit APD speeds to about 10 GHz, and require excessively high bias voltages of around 25 V (ref. 12). Here we show how nanophotonic and nanoelectronic engineering aimed at shaping optical and electrical fields on the nanometre scale within a germanium amplification layer can overcome the otherwise intrinsically poor noise characteristics, achieving a dramatic reduction of amplification noise by over 70 per cent. By generating strongly non-uniform electric fields, the region of impact ionization in germanium is reduced to just 30 nm, allowing the device to benefit from the noise reduction effects that arise at these small distances. Furthermore, the smallness of the APDs means that a bias voltage of only 1.5 V is required to achieve an avalanche gain of over 10 dB with operational speeds exceeding 30 GHz. Monolithic integration of such a device into computer chips might enable applications beyond computer optical interconnects—in telecommunications, secure quantum key distribution, and subthreshold ultralow-power transistors.
RECENT APPLICATIONS OF DESIGN OPTIMIZATION TO ROTORCRAFT — A SURVEY

This paper presents a survey of applications of design optimization to helicopter problems carried out in the last decade. Helicopter optimization has not yet reached the same maturity as structural optimization, and some potential reasons are discussed first. Next, published optimization studies are reviewed, divided into sensitivity analysis studies, applications to rotor dynamics and aeroelasticity, applications to other helicopter problems, emerging technologies such as genetic algorithms and simulated annealing, and studies with experimental verification. The usefulness of design optimization for helicopter applications will increase with the availability of improved analyses, more efficient algorithms especially for sensitivity calculations, and further experimental verifications. The formulation of representative optimization test problem, including experimental verification, is also recommended.
Predicting penile size during erection

The aim of this prospective study was to identify clinical and engineering parameters of the flaccid penis for prediction of penile size during erection. Dorsal and ventral penile lengths, as well as base and tip circumferences were measured in flaccid states, gently stretched states and at full erection resulting from intracavernosal injection of prostaglandin E1 in 55 patients. The forces required to stretch the penis were measured by a specially designed gauge and regression relationships of the measured dimensions were calculated. An engineering model was developed to analyze differences between results obtained during stretching and erection, as well as to approximate the optimal force values which should be applied during the stretching part of the clinical evaluation of penile size. The ratio between the flaccid to stretched penile lengths was shown to be the best predictor for the ventral elongation from flaccid to erect penile lengths. The engineering analysis predicted that a minimal tension force of approximately 450 g during stretching of the penis is required to reach the potential erection length. The stretching forces exerted by the urologist in the clinical setting were experimentally shown to be significantly (P<0.01) less than this value. The values of the relative and absolute elongations of the stretched penis at its ventral aspect provide reliable estimations of its potential maximal elongation during erection. The model designed for this study may obviate the use of intracavernosal injections for estimating penile length during erection.
Deep Learning and Medical Diagnosis: A Review of Literature

In this review the application of deep learning for medical diagnosis is addressed. A thorough analysis of various scientific articles in the domain of deep neural networks application in the medical field has been conducted. More than 300 research articles were obtained, and after several selection steps, 46 articles were presented in more detail. The results indicate that convolutional neural networks (CNN) are the most widely represented when it comes to deep learning and medical image analysis. Furthermore, based on the findings of this article, it can be noted that the application of deep learning technology is widespread, but the majority of applications are focused on bioinformatics, medical diagnosis and other similar fields.
A simple boundary process technique for empirical mode decomposition

The empirical mode decomposition (EMD) proposed by Huang et al. in 1998 shows remarkably effective in analyzing nonlinear signals. It adaptively represents nonstationary signals as sums of zero-mean amplitude modulation-frequency modulation (AM-FM) components by iteratively conducting the sifting process. How to determine the boundary conditions of the cubic spline when constructing the envelopes of data is the critical issue of the sifting process. A simple bound hit process technique is presented in this paper which constructs two periodic series from the original data by even and odd extension and then builds the envelopes using cubic spline with periodic boundary condition. The EMD is conducted fluently without any assumptions of the processed data by this approach. An example is presented to pick out the weak modulation of internal waves from an Envisat ASAR image by EMD with the boundary process technique
A Survey of the Usages of Deep Learning in Natural Language Processing

Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This survey provides a brief introduction to the field and a quick overview of deep learning architectures and methods. It then sifts through the plethora of recent studies and summarizes a large assortment of relevant contributions. Analyzed research areas include several core linguistic processing issues in addition to a number of applications of computational linguistics. A discussion of the current state of the art is then provided along with recommendations for future research in the field.
Boosting Cross-Language Retrieval by Learning Bilingual Phrase Associations from Relevance Rankings

We present an approach to learning bilingual n-gram correspondences from relevance rankings of English documents for Japanese queries. We show that directly optimizing cross-lingual rankings rivals and complements machine translation-based cross-language information retrieval (CLIR). We propose an efficient boosting algorithm that deals with very large cross-product spaces of word correspondences. We show in an experimental evaluation on patent prior art search that our approach, and in particular a consensus-based combination of boosting and translation-based approaches, yields substantial improvements in CLIR performance. Our training and test data are made publicly available.
Bayesian Multi-view Tensor Factorization

We introduce a Bayesian extension of the tensor factorization problem to multiple coupled tensors. For a single tensor it reduces to standard PARAFAC-type Bayesian factorization, and for two tensors it is the first Bayesian Tensor Canonical Correlation Analysis method. It can also be seen to solve a tensorial extension of the recent Group Factor Analysis problem. The method decomposes the set of tensors to factors shared by subsets of the tensors, and factors private to individual tensors, and does not assume orthogonality. For a single tensor, the method empirically outperforms existing methods, and we demonstrate its performance on multiple tensor factorization tasks in toxicogenomics and functional neuroimaging.
Trilobite tagmosis and body patterning from morphological and developmental perspectives.

The Trilobita were characterized by a cephalic region in which the biomineralized exoskeleton showed relatively high morphological differentiation among a taxonomically stable set of well defined segments, and an ontogenetically and taxonomically dynamic trunk region in which both exoskeletal segments and ventral appendages were similar in overall form. Ventral appendages were homonomous biramous limbs throughout both the cephalon and trunk, except for the most anterior appendage pair that was antenniform, preoral, and uniramous, and a posteriormost pair of antenniform cerci, known only in one species. In some clades trunk exoskeletal segments were divided into two batches. In some, but not all, of these clades the boundary between batches coincided with the boundary between the thorax and the adult pygidium. The repeated differentiation of the trunk into two batches of segments from the homonomous trunk condition indicates an evolutionary trend in aspects of body patterning regulation that was achieved independently in several trilobite clades. The phylogenetic placement of trilobites and congruence of broad patterns of tagmosis with those seen among extant arthropods suggest that the expression domains of trilobite cephalic Hox genes may have overlapped in a manner similar to that seen among extant arachnates. This, coupled with the fact that trilobites likely possessed ten Hox genes, presents one alternative to a recent model in which Hox gene distribution in trilobites was equated to eight putative divisions of the trilobite body plan.
Anchorage capacity of osseointegrated and conventional anchorage systems: a randomized controlled trial.

Our aim in this investigation was to evaluate and compare orthodontic anchorage capacity of 4 anchorage systems during leveling/aligning and space closure after maxillary premolar extractions.



One hundred twenty patients (60 girls, 60 boys; mean age, 14.3 years; SD 1.73) were recruited and randomized into 4 anchorage systems: Onplant (Nobel Biocare, Gothenburg, Sweden), Orthosystem implant (Institut Straumann AG, Basel, Switzerland), headgear, and transpalatal bar. The main outcome measures were cephalometric analysis of maxillary first molar and incisor movement, sagittal growth changes of the maxilla, and treatment time. The results were also analyzed on an intention-to-treat basis.



The maxillary molars were stable during the leveling/aligning in the Onplant, Orthosystem implant, and headgear groups, but the transpalatal bar group had anchorage loss (mean, 1.0 mm; P <.001). During the space-closure phase, the molars were still stable in the Onplant and Orthosystem groups, whereas the headgear and transpalatal bar groups had anchorage loss (means, 1.6 and 1.0 mm, respectively; P <.001). Thus, the Onplant and the Orthosystem implant groups had significantly higher success rates for anchorage than did the headgear and transpalatal bar groups. Compared with the Orthosystem implant, there were more technical problems with the Onplant.



If maximum anchorage is required, the Orthosystem implant is the system of choice.
Benefits of polyphenols on gut microbiota and implications in human health.

The biological properties of dietary polyphenols are greatly dependent on their bioavailability that, in turn, is largely influenced by their degree of polymerization. The gut microbiota play a key role in modulating the production, bioavailability and, thus, the biological activities of phenolic metabolites, particularly after the intake of food containing high-molecular-weight polyphenols. In addition, evidence is emerging on the activity of dietary polyphenols on the modulation of the colonic microbial population composition or activity. However, although the great range of health-promoting activities of dietary polyphenols has been widely investigated, their effect on the modulation of the gut ecology and the two-way relationship "polyphenols ↔ microbiota" are still poorly understood. Only a few studies have examined the impact of dietary polyphenols on the human gut microbiota, and most were focused on single polyphenol molecules and selected bacterial populations. This review focuses on the reciprocal interactions between the gut microbiota and polyphenols, the mechanisms of action and the consequences of these interactions on human health.
Building DC microgrids: Planning of an experimental platform with power hardware in the loop features

DC power distribution systems for building application are gaining interest both in academic and industrial world, due to potential benefits in terms of energy efficiency and capital savings. These benefits are more evident were the end-use loads are natively DC (e.g., computers, solid-state lighting or variable speed drives for electric motors), like in data centers and commercial buildings, but also in houses. When considering the presence of onsite renewable generation, e.g. PV or micro-wind generators, storage systems and electric vehicles, DC-based building microgrids can bring additional benefits, allowing direct coupling of DC loads and DC Distributed energy Resources (DERs). A number of demonstrating installations have been built and operated around the world, and an effort is being made both in USA and Europe to study different aspects involved in the implementation of a DC distribution system (e.g. safety, protection, control) and to develop standards for DC building application. This paper discusses on the planning of an experimental DC microgrid with power hardware in the loop features at the University of Naples Federico II, Dept. of Electr.  The microgrid consists of a 3-wire DC bus, with positive, negative and neutral poles, with a voltage range of +/-0÷400 V. The system integrates a number of DERs, like PV, Wind and Fuel Cell generators, battery and super capacitor based storage systems, EV chargers, standard loads and smart loads. It will include also a power-hardware-in-the-loop platform with the aim to enable the real time emulation of single components or parts of the microgrid, or of systems and sub-systems interacting with the microgrid, thus realizing a virtual extension of the scale of the system. Technical features and specifications of the power amplifier to be used as power interface of the PHIL platform will be discussed in detail.
InformationSense: Trade-offs for the Design and the Implementation of a Large Highly Deformable Cloth Display

Deformable displays can provide two major benefits compared to rigid displays: Objects of different shapes and deformabilities, situated in our physical environment, can be equipped with deformable displays, and users can benefit from their pre-existing knowledge about the interaction with physical objects when interacting with deformable displays. In this article we present InformationSense, a large, highly deformable cloth display. The article contributes to two research areas in the context of deformable displays: It presents an approach for the tracking of large, highly deformable surfaces, and it presents one of the first UX analyses of cloth displays that will help with the design of future interaction techniques for this kind of display. The comparison of InformationSense with a rigid display interface unveiled the trade-off that while users are able to interact with InformationSense more naturally and significantly preferred InformationSense in terms of joy of use, they preferred the rigid display interfaces in terms of efficiency. This suggests that deformable displays are already suitable if high hedonic qualities are important but need to be enhanced with additional digital power if high pragmatic qualities are required.