nils-herrmann/clean_scirepeval huggingface dataset:
Nanoimprint of dehydrated PEDOT:PSS for organic photovoltaics.

We demonstrate the fabrication of poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) nanogratings by a dehydration-assisted nanoimprint lithographic technique. PSS increases its cohesion to protect the nanostructures formed by nanoimprinting during demolding, resulting in the formation of high quality nanogratings of 60 nm in height, 70 nm in width and 70 nm in spacing (aspect ratio of 0.86). PEDOT:PSS nanogratings are used as hole transport and an electron blocking layer in blended poly(3-hexylthiophene-2,5-diyl) (P3HT):[6,6]-penyl-C61-butyric-acid-methyl-ester (PCBM) organic photovoltaic devices (OPV), showing enhancement of photocurrent and power efficiency in comparison to OPV devices with non-patterned PEDOT:PSS films.
Finding contexts of social influence in online social networks

The ever rising popularity of online social networks has not only attracted much attention from everyday users but also from academic researchers. In particular, research has been done to investigate the effect of social influence on users' actions on items in the network. However, all social influence research in the data-mining field has been done in a context-independent setting, i.e., irrespective of an item's characteristics. It would be interesting to find the specific contexts in which users influence each other in a similar manner. In this way, applications such as recommendation engines can focus on a specific context for making recommendations. In this paper, we pose the problem of finding contexts of social influence where the social influence is similar across all items in the context. We present a full-space clustering algorithm and a subspace clustering algorithm to find these contexts and test the algorithms on the Digg data set. We demonstrate that our algorithms are capable of finding meaningful contexts of influence in addition to rediscovering the predefined categories specific to the Digg news site.
DeepPicar: A Low-Cost Deep Neural Network-Based Autonomous Car

We present DeepPicar, a low-cost deep neural network based autonomous car platform. DeepPicar is a small scale replication of a real self-driving car called DAVE-2 by NVIDIA. DAVE-2 uses a deep convolutional neural network (CNN), which takes images from a front-facing camera as input and produces car steering angles as output. DeepPicar uses the same network architecture—9 layers, 27 million connections and 250K parameters—and can drive itself in real-time using a web camera and a Raspberry Pi 3 quad-core platform. Using DeepPicar, we analyze the Pi 3's computing capabilities to support end-to-end deep learning based real-time control of autonomous vehicles. We also systematically compare other contemporary embedded computing platforms using the DeepPicar's CNN-based real-time control workload. We find that all tested platforms, including the Pi 3, are capable of supporting the CNN-based real-time control, from 20 Hz up to 100 Hz, depending on hardware platform. However, we find that shared resource contention remains an important issue that must be considered in applying CNN models on shared memory based embedded computing platforms; we observe up to 11.6X execution time increase in the CNN based control loop due to shared resource contention. To protect the CNN workload, we also evaluate state-of-the-art cache partitioning and memory bandwidth throttling techniques on the Pi 3. We find that cache partitioning is ineffective, while memory bandwidth throttling is an effective solution.
Accurate electrothermal modeling of thermoelectric generators

Thermoelectric generators (TEGs) provide a unique way for harvesting thermal energy. These devices are compact, durable, inexpensive, and scalable. Unfortunately, the conversion efficiency of TEGs is low. This requires careful design of energy harvesting systems including the interface circuitry between the TEG module and the load, with the purpose of minimizing power losses. In this paper, it is analytically shown that the traditional approach for estimating the internal resistance of TEGs may result in a significant loss of harvested power. This drawback comes from ignoring the dependence of the electrical behavior of TEGs on their thermal behavior. Accordingly, a systematic method for accurately determining the TEG input resistance is presented. Next, through a case study on automotive TEGs, it is shown that compared to prior art, more than 11% of power losses in the interface circuitry that lies between the TEG and the electrical load can be saved by the proposed modeling technique. In addition, it is demonstrated that the traditional approach would have resulted in a deviation from the target regulated voltage by as much as 59%.
Use of fresh vegetable discards as sea urchin diet: effect on gonad index and quality

This study evaluated the exploitation of unprocessed agricultural discards in the form of fresh vegetable leaves as a diet for the sea urchin Paracentrotus lividus through the assessment of their effects on gonad yield and quality. A stock of wild-caught P. lividus was fed on discarded leaves from three different species (Beta vulgaris, Brassica oleracea, and Lactuca sativa) and the macroalga Ulva lactuca for 3 months under controlled conditions. At the beginning and end of the experiment, total and gonad weight were measured, while gonad and diet total carbon (C%), nitrogen (N%), δ13C, δ15N, carbohydrates, lipids, and proteins were analyzed. The results showed that agricultural discards provided for the maintenance of gonad index and nutritional value (carbohydrate, lipid, and protein content) of initial specimens. L. sativa also improved gonadic color. The results of this study suggest that fresh vegetable discards may be successfully used in the preparation of more balanced diets for sea urchin aquaculture. The use of agricultural discards in prepared diets offers a number of advantages, including an abundant resource, the recycling of discards into new organic matter, and reduced pressure on marine organisms (i.e., macroalgae) in the production of food for cultured organisms.
Big Log Data Stream Processing: Adapting an Anomaly Detection Technique

With the continuous increase in data velocity and volume nowadays, preserving system and data security is particularly affected. In order to handle the huge amount of data and to discover security incidents in real-time, analyses of log data streams are required. However, most of the log anomaly detection techniques fall short in considering continuous data processing. Thus, this paper aligns an anomaly detection technique for data stream processing. It thereby provides a conceptual basis for future adaption of other techniques and further delivers proof of concept by prototype implementation.
Reduced complexity iterative decoding of low-density parity check codes based on belief propagation

In this paper, two simplified versions of the belief propagation algorithm for fast iterative decoding of low-density parity check codes on the additive white Gaussian noise channel are proposed. Both versions are implemented with real additions only, which greatly simplifies the decoding complexity of belief propagation in which products of probabilities have to be computed. Also, these two algorithms do not require any knowledge about the channel characteristics. Both algorithms yield a good performance–complexity tradeoff and can be efficiently implemented in software as well as in hardware, with possibly quantized received values.
Design of multi-phase permanent magnet motor for ship propulsion

In this paper, a permanent magnet synchronous motor for ship propulsion is designed. The appropriate number of poles and slots are selected and the cogging torque is minimized in order to reduce noise and vibrations. To perform high efficiency and reliability, the inverter system consists of multiple modules and the stator coil has multi phases and groups. Because of the modular structure, the motor can be operated with some damaged inverters. In order to maintain high efficiency at low speed operation, same phase coils of different group are connected in series and excited by the half number of inverters than at high speed operation. A MW-class motor is designed and the performances with the proposed inverter control method are calculated.
Auricular reconstruction: indications for autogenous and prosthetic techniques.

After studying this article, the participant should be able to: 1. Describe the alternatives for auricular reconstruction. 2. Discuss the pros and cons of autogenous reconstruction of total or subtotal auricular defects. 3. Enumerate the indications for prosthetic reconstruction of total or subtotal auricular defects. 4. Understand the complexity of and the expertise required for prosthetic reconstruction of auricular defects. The indications for autogenous auricular reconstruction versus prosthetic reconstruction with osseointegrated implant-retained prostheses were outlined in Plastic and Reconstructive Surgery in 1994 by Wilkes et al. of Canada, but because of the relatively recent Food and Drug Administration approval (1995) of extraoral osseointegrated implants, these indications had not been examined by a surgical unit in the United States. The purpose of this article is to present an evolving algorithm based on an experience with 98 patients who underwent auricular reconstruction over a 10-year period. From this experience, the authors conclude that autogenous reconstruction is the procedure of choice in the majority of pediatric patients with microtia. Prosthetic reconstruction of the auricle is considered in such pediatric patients with congenital deformities for the following three relative indications: (1) failed autogenous reconstruction, (2) severe soft-tissue/skeletal hypoplasia, and/or (3) a low or unfavorable hairline. A fourth, and in our opinion the ideal, indication for prosthetic ear reconstruction is the acquired total or subtotal auricular defect, most often traumatic or ablative in origin, which is usually encountered in adults. Although prosthetic reconstruction requires surgical techniques that are less demanding than autogenous reconstruction, construction of the prosthesis is a time-consuming task requiring experience and expertise. Although autogenous reconstruction presents a technical challenge to the surgeon, it is the prosthetic reconstruction that requires lifelong attention and may be associated with late complications. This article reports the first American series of auricular reconstruction containing both autogenous and prosthetic methods by a single surgical team.
Mental rotation in human infants: a sex difference.

A sex difference on mental-rotation tasks has been demonstrated repeatedly, but not in children less than 4 years of age. To demonstrate mental rotation in human infants, we habituated 5-month-old infants to an object revolving through a 240 degrees angle. In successive test trials, infants saw the habituation object or its mirror image revolving through a previously unseen 120 degrees angle. Only the male infants appeared to recognize the familiar object from the new perspective, a feat requiring mental rotation. These data provide evidence for a sex difference in mental rotation of an object through three-dimensional space, consistently seen in adult populations.
Exploring the Use of Leaf Shape Frequencies for Plant Classification

Plant identification and classification play an important role in ecology, but the manual process is cumbersome even for experimented taxonomists. Technological advances allows the development of strategies to make these tasks easily and faster. In this context, this paper describes a methodology for plant identification and classification based on leaf shapes, that explores the discriminative power of the contour-centroid distance in the Fourier frequency domain in which some invariance (e.g. Rotation and scale) are guaranteed. In addition, it is also investigated the influence of feature selection techniques regarding classification accuracy. Our results show that by combining a set of features vectors - in the principal components space - and a feed forward neural network, an accuracy of 97.45% was achieved.
The effect of different air-gap positions on the winding losses of modern planar ferrite cores in switch mode power supplies

The development of power supply technology has always been associated with the need for further miniaturization. One aspect of this trend is a design based on mathematical and physical principles and the implementation of magnetic components. The use of planar inductors and transformers offers the best preconditions for realizing this objective as they allow the windings to be integrated directly in the circuit board. Even when only a single series of planar cores is used, exactly identical winding configurations may have different air-gap positions. Different winding losses then result as a function of this position. The following paper presents a procedure for determining the effect of the air-gap position on the winding losses in planar inductors and its practical applicability on the basis of real examples.
A Simple Subthreshold CMOS Voltage Reference Circuit With Channel- Length Modulation Compensation

This brief presents a simple reference circuit with channel-length modulation compensation to generate a reference voltage of 221 mV using subthreshold of MOSFETs at supply voltage of 0.85 V with power consumption of 3.3 muW at room temperature using TSMC 0.18-mum technology. The proposed circuit occupied in less than 0.0238 mm 2  achieves the reference voltage variation of 2 mV/V for supply voltage from 0.9 to 2.5V and about 6 mV of temperature variation in the range from -20degC to 120 degC. The agreement of simulation and measurement data is demonstrated
A Theory of Market Efficiency

We introduce a mathematical theory called market connectivity that gives concrete ways to both measure the efficiency of markets and find inefficiencies in large markets. The theory leads to new methods for testing the famous efficient markets hypothesis that do not suffer from the joint-hypothesis problem that has plagued past work. Our theory suggests metrics that can be used to compare the efficiency of one market with another, to find inefficiencies that may be profitable to exploit, and to evaluate the impact of policy and regulations on market efficiency. A market’s efficiency is tied to its ability to communicate information relevant to market participants. Market connectivity calculates the speed and reliability with which this communication is carried out via trade in the market. We model the market by a network called the trade network, which can be computed by recording transactions in the market over a fixed interval of time. The nodes of the network correspond to participants in the market. Every pair of nodes that trades in the market is connected by an edge that is weighted by the rate of trade, and associated with a vector that represents the type of item that is bought or sold. We evaluate the ability of the market to communicate by considering how it deals with shocks. A shock is a change in the beliefs of market participants about the value of the products that they trade. We compute the effect of every potential significant shock on trade in the market. We give mathematical definitions for a few concepts: • The tension and energy of the network are related concepts that measure the strength of the connections between sets of participants that trade similar items. They measure the amount of trade that is affected by significant shocks. They are high when there are many paths of high rate of trade that connect those with differing beliefs about the value of items. They are low when information from some large set of participants must take a long time to reach some other large set via trade. • A bottleneck in the network is a small set of nodes that monopolizes an unusually large share of the trade in the network. The nodes in the bottleneck have an incentive to set prices incorrectly and interfere with the fair transmission of information in the market. We give explicit mathematical definitions that capture these concepts and allow for quantitative measurements of market inefficiency. 1 ar X iv :1 70 2. 03 29 0v 1 [ qfi n.  9 F eb 2 01 7
New color GPHOG descriptors for object and scene image classification

This paper presents a novel set of image descriptors that encodes information from color, shape, spatial and local features of an image to improve upon the popular Pyramid of Histograms of Oriented Gradients (PHOG) descriptor for object and scene image classification. In particular, a new Gabor-PHOG (GPHOG) image descriptor created by enhancing the local features of an image using multiple Gabor filters is first introduced for feature extraction. Second, a comparative assessment of the classification performance of the GPHOG descriptor is made in grayscale and six different color spaces to further propose two novel color GPHOG descriptors that perform well on different object and scene image categories. Finally, an innovative Fused Color GPHOG (FC–GPHOG) descriptor is presented by integrating the Principal Component Analysis (PCA) features of the GPHOG descriptors in the six color spaces to combine color, shape and local feature information. Feature extraction for the proposed descriptors employs PCA and Enhanced Fisher Model (EFM), and the nearest neighbor rule is used for final classification. Experimental results using the MIT Scene dataset and the Caltech 256 object categories dataset show that the proposed new FC–GPHOG descriptor achieves a classification performance better than or comparable to other popular image descriptors, such as the Scale Invariant Feature Transform (SIFT) based Pyramid Histograms of visual Words descriptor, Color SIFT four Concentric Circles, Spatial Envelope, and Local Binary Patterns.
New Dromaeosaurids (Dinosauria: Theropoda) from the Lower Cretaceous of Utah, and the Evolution of the Dromaeosaurid Tail

The Yellow Cat Member of the Cedar Mountain Formation (Early Cretaceous, Barremian?--Aptian) of Utah has yielded a rich theropod fauna, including the coelurosaur Nedcolbertia justinhofmanni, the therizinosauroid Falcarius utahensis, the troodontid Geminiraptor suarezarum, and the dromaeosaurid Utahraptor ostrommaysorum. Recent excavation has uncovered three new dromaeosaurid specimens. One specimen, which we designate the holotype of the new genus and species Yurgovuchia doellingi, is represented by a partial axial skeleton and a partial left pubis. A second specimen consists of a right pubis and a possibly associated radius. The third specimen consists of a tail skeleton that is unique among known Cedar Mountain dromaeosaurids.



Y. doellingi resembles Utahraptor ostrommaysorum in that its caudal prezygapophyses are elongated but not to the degree present in most dromaeosaurids. The specimen represented by the right pubis exhibits a pronounced pubic tubercle, a velociraptorine trait that is absent in Y. doellingi. The specimen represented by the tail skeleton exhibits the extreme elongation of the caudal prezygapophyses that is typical of most dromaeosaurids. Here we perform a phylogenetic analysis to determine the phylogenetic position of Y. doellingi. Using the resulting phylogeny as a framework, we trace changes in character states of the tail across Coelurosauria to elucidate the evolution of the dromaeosaurid tail.



The new specimens add to the known diversity of Dromaeosauridae and to the known diversity within the Yellow Cat paleofauna. Phylogenetic analysis places Y. doellingi in a clade with Utahraptor, Achillobator, and Dromaeosaurus. Character state distribution indicates that the presence of intermediate-length caudal prezygapophyses in that clade is not an evolutionarily precursor to extreme prezygapophyseal elongation but represents a secondary shortening of caudal prezygapophyses. It appears to represent part of a trend within Dromaeosauridae that couples an increase in tail flexibility with increasing size.
Streams in the Urban Landscape

!  The world’s population is concentrated in urban areas. This change in demography has brought landscape transformations that have a number of documented effects on stream ecosystems. The most consistent and pervasive effect is an increase in impervious surface cover within urban catchments, which alters the hydrology and geomorphology of streams. This results in predictable changes in stream habitat. In addition to imperviousness, runoff from urbanized surfaces aswell asmunicipal and industrial discharges result in increased loading of nutrients, metals, pesticides, and other contaminants to streams. These changes result in consistent declines in the richness of algal, invertebrate, and fish communities in urban streams. Although understudied in urban streams, ecosystem processes are also affected by urbanization. Urban streams represent opportunities for ecologists interested in studying disturbance and contributing to more effective landscape management.
An Implicit Shape Model for Combined Object Categorization and Segmentation

We present a method for object categorization in real-world scenes. Following a common consensus in the field, we do not assume that a figure-ground segmentation is available prior to recognition. However, in contrast to most standard approaches for object class recognition, our approach automatically segments the object as a result of the categorization. This combination of recognition and segmentation into one process is made possible by our use of an Implicit Shape Model, which integrates both capabilities into a common probabilistic framework. This model can be thought of as a non-parametric approach which can easily handle configurations of large numbers of object parts. In addition to the recognition and segmentation result, it also generates a per-pixel confidence measure specifying the area that supports a hypothesis and how much it can be trusted. We use this confidence to derive a natural extension of the approach to handle multiple objects in a scene and resolve ambiguities between overlapping hypotheses with an MDL-based criterion. In addition, we present an extensive evaluation of our method on a standard dataset for car detection and compare its performance to existing methods from the literature. Our results show that the proposed method outperforms previously published methods while needing one order of magnitude less training examples. Finally, we present results for articulated objects, which show that the proposed method can categorize and segment unfamiliar objects in different articulations and with widely varying texture patterns, even under significant partial occlusion.
The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning

Transferring knowledge across a sequence of related tasks is an important challenge in reinforcement learning. Despite much encouraging empirical evidence that shows benefits of transfer, there has been very little theoretical analysis. In this paper, we study a class of lifelong reinforcementlearning problems: the agent solves a sequence of tasks modeled as finite Markov decision processes (MDPs), each of which is from a finite set of MDPs with the same state/action spaces and different transition/reward functions. Inspired by the need for cross-task exploration in lifelong learning, we formulate a novel online discovery problem and give an optimal learning algorithm to solve it. Such results allow us to develop a new lifelong reinforcement-learning algorithm, whose overall sample complexity in a sequence of tasks is much smaller than that of single-task learning, with high probability, even if the sequence of tasks is generated by an adversary. Benefits of the algorithm are demonstrated in a simulated problem.