nils-herrmann/clean_scirepeval huggingface dataset:
More is Less: A More Complicated Network with Less Inference Complexity

In this paper, we present a novel and general network structure towards accelerating the inference process of convolutional neural networks, which is more complicated in network structure yet with less inference complexity. The core idea is to equip each original convolutional layer with another low-cost collaborative layer (LCCL), and the element-wise multiplication of the ReLU outputs of these two parallel layers produces the layer-wise output. The combined layer is potentially more discriminative than the original convolutional layer, and its inference is faster for two reasons: 1) the zero cells of the LCCL feature maps will remain zero after element-wise multiplication, and thus it is safe to skip the calculation of the corresponding high-cost convolution in the original convolutional layer, 2) LCCL is very fast if it is implemented as a 1*1 convolution or only a single filter shared by all channels. Extensive experiments on the CIFAR-10, CIFAR-100 and ILSCRC-2012 benchmarks show that our proposed network structure can accelerate the inference process by 32% on average with negligible performance drop.
Synchrony of Seed Dispersal, Hydrology and Local Climate in a Semi-arid River Reach in California

The temporal availability of propagules is a critical factor in sustaining pioneer riparian tree populations along snowmelt-driven rivers because seedling establishment is strongly linked to seasonal hydrology. River regulation in semi-arid regions threatens to decouple seed development and dispersal from the discharge regime to which they evolved. Using the lower Tuolumne River as a model system, we quantified and modeled propagule availability for Populus fremontii (POFR), Salix gooddingii (SAGO), and Salix exigua (SAEX), the tree and shrub species that dominate near-channel riparian stands in the San Joaquin Basin, CA. A degree-day model was fit to field data of seasonal seed density and local temperature from three sites in 2002–2004 to predict the onset of the peak dispersal period. To evaluate historical synchrony of seed dispersal and seasonal river hydrology, we compared peak spring runoff timing to modeled peak seed release periods for the last 75 years. The peak seed release period began on May 15 for POFR (range April 23–June 10), May 30 for SAGO (range May 19–June 11) and May 31 for SAEX (range May 8–June 30). Degree-day models for the onset of seed release reduced prediction error by 40–67% over day-of-year means; the models predicted best the interannual, versus site-to-site, variation in timing. The historical analysis suggests that POFR seed release coincided with peak runoff in almost all years, whereas SAGO and SAEX dispersal occurred during the spring flood recession. The degree-day modeling approach reduce uncertainty in dispersal timing and shows potential for guiding flow releases on regulated rivers to increase riparian tree recruitment at the lowest water cost.
Sensitivity of Double-Gate and FinFET Devices to Process Variations

We investigate the manufacturability of 20-nm double-gate and FinFET devices in integrated circuits by projecting process tolerances. Two important factors affecting the sensitivity of device electrical parameters to physical variations were quantitatively considered. The quantum effect was computed using the density gradient method and the sensitivity of threshold voltage to random dopant fluctuation was studied by Monte Carlo simulation. Our results show the 3 value ofVT variation caused by discrete impurity fluctuation can be greater than 100%. Thus, engineering the work function of gate materials and maintaining a nearly intrinsic channel is more desirable. Based on a design with an intrinsic channel and ideal gate work function, we analyzed the sensitivity of device electrical parameters to several important physical fluctuations such as the variations in gate length, body thickness, and gate dielectric thickness. We found that quantum effects have great impact on the performance of devices. As a result, the device electrical behavior is sensitive to small variations of body thickness. The effect dominates over the effects produced by other physical fluctuations. To achieve a relative variation of electrical parameters comparable to present practice in industry, we face a challenge of fin width control (less than 1 nm 3 value of variation) for the 20-nm FinFET devices. The constraint of the gate length variation is about 10 15%. We estimate a tolerance of 1 2 A 3 value of oxide thickness variation and up to 30% front-back oxide thickness mismatch.
Potential safety issues with blood flow restriction training.

The focal point of previous literature was establishing the efficacy of blood flow restriction training with respect to muscular strength, muscular hypertrophy, and muscular endurance. After mounting evidence supporting the efficacy of low-intensity blood flow restriction training, research has shifted to the overall safety of this training modality. The aim of this review was to summarize the research on the overall safety of blood flow restriction training, focusing on the cardiovascular system (central and peripheral), muscle damage, oxidative stress, and nerve conduction velocity responses compared with those observed with regular exercise. Although still sparse, the blood flow restriction training research thus far is promising with respect to safety outcomes. Individuals respond similarly to blood flow restriction training and to regular exercise; however, longer term studies are required to better understand the chronic effects of low-intensity blood flow restriction training and possible safety issues.
Dysregulation of FGFR Signaling in Human Malignancies

The fibroblast growth factor signaling pathway (FGFR signaling) is an evolutionary conserved signaling cascade that regulates several basic biologic processes, including tissue development, angiogenesis, and tissue regeneration. Substantial evidence indicates that aberrant FGFR signaling is involved in the pathogenesis of cancer. Recent developments of deep sequencing technologies have allowed the discovery of frequent molecular alterations in components of FGFR signaling among several solid tumor types. Moreover, compelling preclinical models have demonstrated the oncogenic potential of these aberrations in driving tumor growth, promoting angiogenesis, and conferring resistance mechanisms to anticancer therapies. Recently, the field of FGFR targeting has exponentially progressed thanks to the development of novel agents inhibiting FGFs or FGFRs, which had manageable safety profiles in early-phase trials. Promising treatment efficacy has been observed in different types of malignancies, particularly in tumors harboring aberrant FGFR signaling, thus offering novel therapeutic opportunities in the era of precision medicine. The most exciting challenges now focus on selecting patients who are most likely to benefit from these agents, increasing the efficacy of therapies with the development of novel potent compounds and combination strategies, and overcoming toxicities associatedwith FGFR inhibitors. After examination of the basic and translational research studies that validated the oncogenic potential of aberrant FGFR signaling, this review focuses on recent data from clinical trials evaluating FGFR targeting therapies and discusses the challenges and perspectives for the development of these agents.  No potential conflicts of interest were disclosed by the other authors. Editor's Disclosures The following editor(s) reported relevant financial relationships: S.E. Bates reports receiving a commercial research grant from Celgene
Recent advances in features extraction and description algorithms: A comprehensive survey

Computer vision is one of the most active research fields in information technology today. Giving machines and robots the ability to see and comprehend the surrounding world at the speed of sight creates endless potential applications and opportunities. Feature detection and description algorithms can be indeed considered as the retina of the eyes of such machines and robots. However, these algorithms are typically computationally intensive, which prevents them from achieving the speed of sight real-time performance. In addition, they differ in their capabilities and some may favor and work better given a specific type of input compared to others. As such, it is essential to compactly report their pros and cons as well as their performances and recent advances. This paper is dedicated to provide a comprehensive overview on the state-of-the-art and recent advances in feature detection and description algorithms. Specifically, it starts by overviewing fundamental concepts. It then compares, reports and discusses their performance and capabilities. The Maximally Stable Extremal Regions algorithm and the Scale Invariant Feature Transform algorithms, being two of the best of their type, are selected to report their recent algorithmic derivatives.
Surface functionalization of poly(ε-caprolactone) improves its biocompatibility as scaffold material for bioartificial vessel prostheses.

Within this study, chemically modified polymer surfaces were to be developed, which should enhance the subsequent immobilization of various bioactive substances. To improve the hemocompatibility and endothelialization of poly(ε-caprolactone) (PCL) intended as scaffold material for bioartificial vessel prostheses, terminal amino groups via ammonia (NH₃) plasma, oxygen (O₂) plasma/aminopropyltriethoxysilane (APTES), and 4,4'-methylenebis(phenyl isocyanate) (MDI)/water were provided. Then, immobilization of the anti-inflammatory and antithrombogenic model drug acetylsalicylic acid (ASA) and vascular endothelial growth factor (VEGF) were performed by employing N,N-disuccinimidyl carbonate (DSC) as crosslinker. Contact angle and fluorescence measurements, X-ray photoelectron spectroscopy and infrared spectroscopy confirmed the surface modification. Here the highest functionalization was observed for the O₂ plasma/APTES modification. Furthermore, biocompatibility studies demonstrated that the surface reactions have no negative influence, neither on the viability of L929 mouse fibroblasts, nor on primary or secondary hemostasis. Release studies showed that the immobilization of ASA and VEGF on the modified PCL surface via DSC is greatly improved compared to the adsorption-only reference. The advantage of DSC is that it immobilizes both bioactive substances via non-hydrolyzable and/or hydrolyzable covalent bonding. The highest ASA loading and cumulative release was detected using NH₃ plasma-activated PCL samples. For VEGF, the O₂ plasma/APTES-modified PCL samples were most efficient with regard to loading and cumulative release. In conclusion, both modifications are promising methods to optimize PCL as scaffold material for bioartificial vessel prostheses.
A social network-aware top-N recommender system using GPU

A book recommender system is very useful for a digital library. Good book recommender systems can effectively help users find interesting and relevant books from the massive resources, by providing individual recommendation book list for each end-user. By now, a variety of collaborative filtering algorithms have been invented, which are the cores of most recommender systems. However, because of the explosion of information, especially in the Internet, the improvement of the efficiency of the collaborative filting (CF) algorithm becomes more and more important. In this paper, we first propose a parallel Top-N recommendation algorithm in CUDA (Compute Unified Device Architecture) which combines the collaborative filtering and trust-based approach to deal with the cold-start user problem. Then based on this algorithm, we present a parallel book recommender system on a GPU (Graphics Processor unit) for CADAL digital library platform. Our experimental results show our algorithm is very efficient to process the large-scale datasets with good accuracy, and we report the impact of different values of parameters on the recommendation performance.
An improved upper bound for the most informative boolean function conjecture

Suppose X is a uniformly distributed n-dimensional binary vector and Y is obtained by passing X through a binary symmetric channel with crossover probability α. A recent conjecture by Courtade and Kumar postulates that I(f(X); Y ) ≤ 1 - h(α) for any Boolean function f. So far, the best known upper bound was essentially I(f(X); Y ) ≤ (1 - 2α)2. In this paper, we derive a new upper bound that holds for all balanced functions, and improves upon the best known previous bound for α > 1 over 3.
Face Recognition from Video by Matching Image Sets

As opposed to still-image based paradigms, video-based face recognition involves identifying a person from a video input. In video-based approaches, face detection and tracking are performed together with recognition, as usually the background is included in the video and the person could be moving or being captured unknowingly. By detecting and raster-scanning a face sub-image to be a vector, we can concatenate all extracted vectors to form an image set, thus allowing the application of face recognition algorithms based on matching image sets. It has been reported that linear subspace-based methods for face recognition using image sets achieve good recognition results. The challenge that remains is to update the linear subspace representation and perform recognition on-the-fly so that the recognition-from-video objective is not defeated. Here, we demonstrate how this can be achieved by using a well-studied incremental SVD updating procedure. We then present our online face recognition-from-video framework and the recognition results obtained.
Towards Benchmarking IaaS and PaaS Clouds for Graph Analytics

Cloud computing is a new paradigm for using ICT services— only when needed and for as long as needed, and paying only for service actually consumed. Benchmarking the increasingly many cloud services is crucial for market growth and perceived fairness, and for service design and tuning. In this work, we propose a generic architecture for benchmarking cloud services. Motivated by recent demand for data-intensive ICT services, and in particular by processing of large graphs, we adapt the generic architecture to Graphalytics, a benchmark for distributed and GPU-based graph analytics platforms. Graphalytics focuses on the dependence of performance on the input dataset, on the analytics algorithm, and on the provisioned infrastructure. The benchmark provides components for platform configuration, deployment, and monitoring, and has been tested for a variety of platforms. We also propose a new challenge for the process of benchmarking data-intensive services, namely the inclusion of the data-processing algorithm in the system under test; this increases significantly the relevance of benchmarking results, albeit, at the cost of increased benchmarking duration.
FPGA Implementation of Carrier Synchronization for QAM Receivers

Software defined radios (SDR) are highly configurable hardware platforms that provide the technology for realizing the rapidly expanding third (and future) generation digital wireless communication infrastructure. While there are a number of silicon alternatives available for implementing the various functions in a SDR, field programmable gate arrays (FPGAs) are an attractive option for many of these tasks for reasons of performance, power consumption and flexibility. Amongst the more complex tasks performed in a high data rate wireless system is synchronization. This paper examines carrier synchronization in SDRs using FPGA based signal processors. We provide a tutorial style overview of carrier recovery techniques for QPSK and QAM modulation schemes and report on the design and FPGA implementation of a carrier recovery loop for a 16-QAM modern. Two design alternatives are presented to highlight the rich design space accessible using configurable logic. The FPGA device utilization and performance for a carrier recovery circuit using a look-up table approach and CORDIC arithmetic are presented. The simulation and FPGA implementation process using a recent system level design tool called System GeneratorTM for DSP described.
Pythium insidiosum keratitis in Israel.

To report with morphologic and phylogenetic speciation the first case from Israel of Pythium insidiosum keratitis associated with contact-lens wear.



Case report and literature review.



A 21-year-old man with a history of contact-lens use and water exposure was hospitalized in Israel for a corneal ulcer. The ulcer progressed despite intensive antibiotics. He flew home to the United States for further care. Examination revealed a corneal ulcer with hypopyon. The infection progressed despite intensive medical therapy, and a therapeutic penetrating keratoplasty was performed. Histology and cornea cultures from the host cornea revealed sparsely septate, branching hyphae, consistent with P. insidiosum. DNA sequencing of the Pythium isolate supported the clinical history that the infection was acquired outside of the United States. Despite intensive medical therapy and a second corneal transplant, the ulcer progressed, ultimately requiring enucleation.



This is the first reported case of culture-proven, contact lens-related Pythium keratitis originating from Israel. Pythium is a fungus-like, aquatic oomycete found in tropical climates. Human pythiosis is uncommon but associated with high morbidity. Case reports describe surgical cure of Pythium keratitis, but this case recurred despite two penetrating keratoplasties and maximal antifungal therapy. In cases of presumed fungal keratitis that do not respond to antifungals, the fungus should be sent for speciation because early surgical intervention is the only means to save the eye in ocular pythiosis.
Design, modeling, estimation and control for aerial grasping and manipulation

This paper addresses mechanics, design, estimation and control for aerial grasping. We present the design of several light-weight, low-complexity grippers that allow quadrotors to grasp and perch on branches or beams and pick up and transport payloads. We then show how the robot can use rigid body dynamic models and sensing to verify a grasp, to estimate the the inertial parameters of the grasped object, and to adapt the controller and improve performance during flight. We present experimental results with different grippers and different payloads and show the robot's ability to estimate the mass, the location of the center of mass and the moments of inertia to improve tracking performance.
Interobserver reliability of the Australian Spasticity Assessment Scale (ASAS).

The aim of this paper is to present the Australian Spasticity Assessment Scale (ASAS) and to report studies of its interrater reliability. The ASAS identifies the presence of spasticity by confirming a velocity-dependent increased response to rapid passive movement and quantifies it using an ordinal scale.



The rationale and procedure for the ASAS is described. Twenty-two participants with spastic CP (16 males; age range 1y 11mo-15y 3mo) who had not had botulinum neurotoxin-A within 4 months, or bony or soft tissue surgery within 12 months, were recruited from the spasticity management clinic of a tertiary paediatric teaching hospital. Fourteen muscles in each child were assessed by each of three experienced independent raters. ASAS was recorded for all muscles. Interrater reliability was calculated using the weighted kappa statistic (quadratic weighting; κqw) for individual muscles, for upper limbs, for lower limbs, and between raters.



The weighted kappa ranged between 0.75 and 0.92 for individual muscle groups and was 0.87 between raters.



The ASAS complies with the definition of spasticity and is clinically feasible in paediatric settings. Our estimates of interrater reliability for the ASAS exceed that of the most commonly used spasticity scoring systems.
Technological aids to support choice strategies by three girls with Rett syndrome.

This study was aimed at extending the use of assistive technology (i.e., photocells, interface and personal computer) to support choice strategies by three girls with Rett syndrome and severe to profound developmental disabilities. A second purpose of the study was to reduce stereotypic behaviors exhibited by the participants involved (i.e., body rocking, hand washing and hand mouthing). Finally, a third goal of the study was to monitor the effects of such program on the participants' indices of happiness. The study was carried out according to a multiple probe design across responses for each participant. Results showed that the three girls increased the adaptive responses and decreased the stereotyped behaviors during intervention phases compared to baseline. Moreover, during intervention phases, the indices of happiness augmented for each girl as well. Clinical, psychological and rehabilitative implications of the findings are discussed.
Computational design of reconfigurables

A reconfigurable is an object or collection of objects whose transformation between various states defines its functionality or aesthetic appeal. For example, consider a mechanical assembly composed of interlocking pieces, a transforming folding bicycle, or a space-saving arrangement of apartment furniture. Unlike traditional computer-aided design of static objects, specialized tools are required to address problems unique to the computational design and revision of objects undergoing rigid transformations. Collisions and interpenetrations as objects transition from one configuration to another prevent the physical realization of a design. We present a software environment intended to support fluid interactive design of reconfigurables, featuring tools that identify, visualize, monitor and resolve infeasible configurations. We demonstrate the versatility of the environment on a number of examples spanning mechanical systems, urban dwelling, and interlocking puzzles, some of which we then realize via additive manufacturing.
 Spatial-temporal information about collisions between objects is presented to the designer according to a cascading order of precedence. A designer may quickly determine when, and then where, and then how objects are colliding. This precedence guides the design and implementation of our four-dimensional spacetime bounding volume hierarchy for interactive-rate collision detection. On screen, the designer experiences a suite of interactive visualization and monitoring tools during editing: timeline notifications of new collisions, picture-in-picture windows for tracking collisions and suggestive hints for contact resolution. Contacts too tedious to remove manually can be eliminated automatically via our proposed constrained numerical optimization and swept-volume carving.