nils-herrmann/clean_scirepeval huggingface dataset:
Deep Asymmetric Pairwise Hashing

Recently, deep neural networks based hashing methods have greatly improved the multimedia retrieval performance by simultaneously learning feature representations and binary hash functions. Inspired by the latest advance in the asymmetric hashing scheme, in this work, we propose a novel Deep Asymmetric Pairwise Hashing approach (DAPH) for supervised hashing. The core idea is that two deep convolutional models are jointly trained such that their output codes for a pair of images can well reveal the similarity indicated by their semantic labels. A pairwise loss is elaborately designed to preserve the pairwise similarities between images as well as incorporating the independence and balance hash code learning criteria. By taking advantage of the flexibility of asymmetric hash functions, we devise an efficient alternating algorithm to optimize the asymmetric deep hash functions and high-quality binary code jointly. Experiments on three image benchmarks show that DAPH achieves the state-of-the-art performance on large-scale image retrieval.
Routing with load balancing in wireless Ad hoc networks

An ad hoc wireless mobile network is an infrastructure-less mobile network that has no fixed routers; instead, all nodes are capable of movement and can be connected dynamically in an arbitrary manner. In order to facilitate communication of mobile nodes that may not be within the wireless range of each other, an efficient routing protocol is used to discover routes between nodes so that messages may be delivered in a timely manner. In this paper, we present a novel Load-Balanced Ad hoc Routing (LBAR) protocol for communication in wireless ad hoc networks. LBAR defines a new metric for routing known as the degree of nodal activity to represent the load on a mobile node. In LBAR routing information on all paths from source to destination are forwarded through setup messages to the destination. Setup messages include nodal activity information of all nodes on the traversed path. After collecting information on all possible paths, the destination then makes a selection of the path with the best-cost value and sends an acknowledgement to the source node. LBAR also provides efficient path maintenance to patch up broken links by detouring traffic to the destination. A comprehensive simulation study was conducted to evaluate the performance of the proposed scheme. Performance results show that LBAR outperforms existing ad hoc routing protocols in terms of packet delivery and average end-to-end delay.
A dual-band wide-angle scanning phased array antenna in K/Ka bands for satellite-on-the-move applications

This study presents the design of a dual-band cavity-backed phased array antenna with wide-angle scanning capability in K/Ka bands for the geostationary (GSO)-fixed satellite service (FSS). To reduce the losses and mutual coupling, a novel antenna element similar to the cavity-backed Strip-Slot-Air-Inverted-Patch (SSAIP) is proposed as an element of designed array of 81 elements. Wide-angle scanning up to 60o is achieved at both frequency bands of the operation. The developed antenna is suitable for seamless installation on both land and air vehicles for bi-directional SatCom systems.
Application of bee colony algorithm for FANET routing

FANET are wireless ad hoc networks on unmanned aerial vehicles, and are characterized by high nodes mobility, dynamically changing topology and movement in 3D-space. FANET routing is an extremely complicated problem. The article describes the bee algorithm and the routing process based on the mentioned algorithm in ad hoc networks. The classification of FANET routing methods is given. The overview of the routing protocols based on the bee colony algorithms is provided. Owing to the experimental analysis, bio-inspired algorithms based on the bee colony were proved to show good results, having better efficiency than traditional FANET routing algorithms in most cases.
Magnetically Tunable Ferrite Loaded Substrate Integrated Waveguide Cavity Resonator

A magnetically tunable ferrite-loaded substrate integrated waveguide (SIW) cavity resonator is presented and demonstrated. X-band cavity resonator is operated in the dominant mode and the ferrite slabs are loaded onto the side walls of the cavity where the value of magnetic field is highest. Measured results for single and double ferrite-loaded SIW cavity resonators are presented. Frequency tuning range of more than 6% and 10% for single and double ferrite slabs are obtained. Unloaded Q -factor of more than 200 is achieved.
Location management in cellular mobile computing systems with dynamic hierarchical location databases

An important issue in the design of a mobile computing system is how to manage the location information of mobile clients. In the existing commercial cellular mobile computing systems, a twotier architecture is adopted (Mouly and Pautet, 1992). However, the two-tier architecture is not scalable. In the literatures (Pitoura and Samaras, 2001; Pitoura and Fudos, 1998), a hierarchical database structure is proposed in which the location information of mobile clients within a cell is managed by the location database responsible for the cell. The location databases of different cells are organized into a tree-like structure to facilitate the search of mobile clients. Although this architecture can distribute the updates and the searching workload amongst the location databases in the system, location update overheads can be very expensive when the mobility of clients is high. In this paper, we study the issues on how to generate location updates under the distance-based method for systems using hierarchical location databases. A cost-based method is proposed for calculating the optimal distance threshold with the objective to minimize the total location management cost. Furthermore, under the existing hierarchical location database scheme, the tree structure of the location databases is static. It cannot adapt to the changes in mobility patterns of mobile clients. This will affect the total location management cost in the system. In the second part of the paper, we present a re-organization strategy to re-structure the hierarchical tree of location databases according to the mobility patterns of the clients with the objective to minimize the location management cost. Extensive simulation experiments have been performed to investigate the re-organization strategy when our location update generation method is applied.
Therapeutic targeting of microRNAs: current status and future challenges

MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that have crucial roles in regulating gene expression. Increasing evidence supports a role for miRNAs in many human diseases, including cancer and autoimmune disorders. The function of miRNAs can be efficiently and specifically inhibited by chemically modified antisense oligonucleotides, supporting their potential as targets for the development of novel therapies for several diseases. In this Review we summarize our current knowledge of the design and performance of chemically modified miRNA-targeting antisense oligonucleotides, discuss various in vivo delivery strategies and analyse ongoing challenges to ensure the specificity and efficacy of therapeutic oligonucleotides in vivo. Finally, we review current progress on the clinical development of miRNA-targeting therapeutics.
A tunable filter based on miniature SIR coaxial resonators

This paper presents a method of electric tunability using varactor diodes installed on SIR coaxial resonators and associated filters. Using varactor diodes connected in parallel, in combination with the SIR coaxial resonator, makes it possible, by increasing the number of varactor diodes, to expand the tuning range and maintain the unloaded quality factor of the resonator. A second order filter, tunable in center frequency, was built with these resonators, providing a very large tuning range.
Improved Carry-in Workload Estimation for Global Multiprocessor Scheduling

As an important and fundamental tool for analyzing the schedulability of a real-time task set on the multiprocessor platform, response time analysis (RTA) has been researched for several years on both Global Fixed Priority (G-FP) and Global Earliest Deadline First (G-EDF) scheduling. This paper proposes a new analysis that improves over current state-of-the-art RTA methods for both G-FP and G-EDF scheduling, by reducing their pessimism. The key observation is that when estimating the carry-in workload, all the existing RTA techniques depend on the worst case scenario in which the carry-in job should execute as late as possible and just finishes execution before its worst case response time (WCRT). But the carry-in workload calculated under this assumption may be over-estimated, and thus the accuracy of the response time analysis may be impacted. To address this problem, we first propose a new method to estimate the carry-in workload more precisely. The proposed method does not depend on any specific scheduling algorithm and can be used for both G-FP and G-EDF scheduling. We then propose a general RTA algorithm that can improve most existing RTA tests by incorporating our carry-in estimation method. To further improve the execution efficiency, we also introduce an optimization technique for our RTA tests. Experiments with randomly generated task sets are conducted and the results show that, compared with the state-of-the-art technologies, the proposed tests exhibit considerable performance improvements, up to 9 and 7.8 percent under G-FP and G-EDF scheduling respectively, in terms of schedulability test precision.
Is early detection of abused children possible?: a systematic review of the diagnostic accuracy of the identification of abused children

Early detection of abused children could help decrease mortality and morbidity related to this major public health problem. Several authors have proposed tools to screen for child maltreatment. The aim of this systematic review was to examine the evidence on accuracy of tools proposed to identify abused children before their death and assess if any were adapted to screening.



We searched in PUBMED, PsycINFO, SCOPUS, FRANCIS and PASCAL for studies estimating diagnostic accuracy of tools identifying neglect, or physical, psychological or sexual abuse of children, published in English or French from 1961 to April 2012. We extracted selected information about study design, patient populations, assessment methods, and the accuracy parameters. Study quality was assessed using QUADAS criteria.



A total of 2 280 articles were identified. Thirteen studies were selected, of which seven dealt with physical abuse, four with sexual abuse, one with emotional abuse, and one with any abuse and physical neglect. Study quality was low, even when not considering the lack of gold standard for detection of abused children. In 11 studies, instruments identified abused children only when they had clinical symptoms. Sensitivity of tests varied between 0.26 (95% confidence interval [0.17-0.36]) and 0.97 [0.84-1], and specificity between 0.51 [0.39-0.63] and 1 [0.95-1]. The sensitivity was greater than 90% only for three tests: the absence of scalp swelling to identify children victims of inflicted head injury; a decision tool to identify physically-abused children among those hospitalized in a Pediatric Intensive Care Unit; and a parental interview integrating twelve child symptoms to identify sexually-abused children. When the sensitivity was high, the specificity was always smaller than 90%.



In 2012, there is low-quality evidence on the accuracy of instruments for identifying abused children. Identified tools were not adapted to screening because of low sensitivity and late identification of abused children when they have already serious consequences of maltreatment. Development of valid screening instruments is a pre-requisite before considering screening programs.
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models

θ: model parameter p: momentum ξ: thermostat Euler Integrator  θt+1 = θt + pth pt+1 = pt−∇θŨt(θt+1)h− diag(ξt)pth + √ 2Dζt+1 ξt+1 = ξt + (pt+1 pt+1− 1)h Symmetric Spltting Integrator A : θt+1/2 = θt + pth/2, ξt+1/2 = ξt + (pt pt− 1)h/2→ B : pt+1/3 = exp(−ξt+1/2h/2) pt→ O : pt+2/3 = pt+1/3−∇θŨt(θt+1/2)h + √ 2Dζt+1→ B : pt+1 = exp(−ξt+1/2h/2) pt+2/3→ A : θt+1 = θt+1/2 + pt+1h/2, ξt+1 = ξt+1/2 + (pt+1 pt+1− 1)h/2 where h is stepsize, D is diffusion factor, and ζ is Gaussian noise
Recent advances in rechargeable battery materials: a chemist's perspective.

The constant increase in global energy demand, together with the awareness of the finite supply of fossil fuels, has brought about an imperious need to take advantage of renewable energy sources. At the same time, concern over CO(2) emissions and future rises in the cost of gasoline has boosted technological efforts to make hybrid and electric vehicles available to the general public. Energy storage is a vital issue to be addressed within this scenario, and batteries are certainly a key player. In this tutorial review, the most recent and significant scientific advances in the field of rechargeable batteries, whose performance is dependent on their underlying chemistry, are covered. In view of its utmost current significance and future prospects, special emphasis is given to progress in lithium-based technologies.
A high-fat, ketogenic diet induces a unique metabolic state in mice.

Ketogenic diets have been used as an approach to weight loss on the basis of the theoretical advantage of a low-carbohydrate, high-fat diet. To evaluate the physiological and metabolic effects of such diets on weight we studied mice consuming a very-low-carbohydrate, ketogenic diet (KD). This diet had profound effects on energy balance and gene expression. C57BL/6 mice animals were fed one of four diets: KD; a commonly used obesogenic high-fat, high-sucrose diet (HF); 66% caloric restriction (CR); and control chow (C). Mice on KD ate the same calories as mice on C and HF, but weight dropped and stabilized at 85% initial weight, similar to CR. This was consistent with increased energy expenditure seen in animals fed KD vs. those on C and CR. Microarray analysis of liver showed a unique pattern of gene expression in KD, with increased expression of genes in fatty acid oxidation pathways and reduction in lipid synthesis pathways. Animals made obese on HF and transitioned to KD lost all excess body weight, improved glucose tolerance, and increased energy expenditure. Analysis of key genes showed similar changes as those seen in lean animals placed directly on KD. Additionally, AMP kinase activity was increased, with a corresponding decrease in ACC activity. These data indicate that KD induces a unique metabolic state congruous with weight loss.
Trends in Model-based GUI Testing

This chapter gives an overview of the recent advances in GUI testing. Considering the increasing popularity and fast software development cycles (e.g., desktop and mobile applications), GUI testing gains more importance as it allows us to verify the behavior of a system from the user’s perspective. Thus, it can quickly uncover relevant bugs, which a user could face. Traditional capture-replay GUI testing approaches do not meet the demands of developers anymore. Therefore, there is an increasing research activity in modelbased GUI testing, where the user interaction behavior is simulated using a graphbased model. In the following, we outline different graphical notations to describe feasible user interactions, and methods to generate and execute test cases from these models. We discuss the benefits and limitations of the state-of-the-art in GUI testing research and give a brief outlook about new trends and possibilities to improve the GUI testing automation.
NDE application of ultrasonic tomography to a full-scale concrete structure

Newly developed ultrasonic imaging technology for large concrete elements, based on tomographic reconstruction, is presented. The developed 3-D internal images (velocity tomograms) are used to detect internal defects (polystyrene foam and pre-cracked concrete prisms) that represent structural damage within a large steel reinforced concrete element. A hybrid air-coupled/contact transducer system is deployed. Electrostatic air-coupled transducers are used to generate ultrasonic energy and contact accelerometers are attached on the opposing side of the concrete element to detect the ultrasonic pulses. The developed hybrid testing setup enables collection of a large amount of high-quality, through-thickness ultrasonic data without surface preparation to the concrete. The algebraic reconstruction technique is used to reconstruct p-wave velocity tomograms from the obtained time signal data. A comparison with a one-sided ultrasonic imaging method is presented for the same specimen. Through-thickness tomography shows some benefit over one-sided imaging for highly reinforced concrete elements. The results demonstrate that the proposed through-thickness ultrasonic technique shows great potential for evaluation of full-scale concrete structures in the field.
An All-Elastomeric Transparent and Stretchable Temperature Sensor for Body-Attachable Wearable Electronics.

A transparent stretchable (TS) gated sensor array with high optical transparency, conformality, and high stretchability of up to 70% is demonstrated. The TS-gated sensor array has high responsivity to temperature changes in objects and human skin. This unprecedented TS-gated sensor array, as well as the integrated platform of the TS-gated sensor with a transparent and stretchable strain sensor, show great potential for application to wearable skin electronics for recognition of human activity.
GANs for Medical Image Analysis

Generative Adversarial Networks (GANs) and their extensions have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical image denoising, reconstruction, segmentation, data simulation, detection or classification. Furthermore, their ability to synthesize images at unprecedented levels of realism also gives hope that the chronic scarcity of labeled data in the medical field can be resolved with the help of these generative models. In this review paper, a broad overview of recent literature on GANs for medical applications is given, the shortcomings and opportunities of the proposed methods are thoroughly discussed and potential future work is elaborated. A total of 63 papers published until end of July 2018 are reviewed. For quick access, the papers and important details such as the underlying method, datasets and performance are summarized in tables.
Circulating current minimization and current sharing control of parallel boost converters based on Droop Index

This paper investigates the relationship between current sharing difference and circulating current for two parallel connected dc-dc converters. In the proposed algorithm a new figure-of-merit called Droop Index is introduced, which is a function of normalized current sharing difference and losses in the output side of the converters. This algorithm minimizes the circulating current and current sharing difference between the converters. Although there may exist a trade-off between current sharing difference and voltage regulation, the proposed droop index algorithm gives better performance and low voltage regulation. The detailed analysis and design procedure are explained for two dc-dc boost converters connected in parallel. The effectiveness of proposed method is verified using MATLAB simulation.
Templates in Chess Memory: A Mechanism for Recalling Several Boards

This paper addresses empirically and theoretically a question derived from the chunking theory of memory (Chase & Simon, 1973a, 1973b): To what extent is skilled chess memory limited by the size of short-term memory (about seven chunks)? This question is addressed first with an experiment where subjects, ranking from class A players to grandmasters, are asked to recall up to five positions presented during 5 s each. Results show a decline of percentage of recall with additional boards, but also show that expert players recall more pieces than is predicted by the chunking theory in its original form. A second experiment shows that longer latencies between the presentation of boards facilitate recall. In a third experiment, a Chessmaster gradually increases the number of boards he can reproduce with higher than 70% average accuracy to nine, replacing as many as 160 pieces correctly. To account for the results of these experiments, a revision of the Chase-Simon theory is proposed. It is suggested that chess players, like experts in other recall tasks, use long-term memory retrieval structures (Chase & Ericsson, 1982) or templates in addition to chunks in short-term memory to store information rapidly.
Waggle: An open sensor platform for edge computing

Many advanced sensors are capable of producing extremely large and continuous data streams. Hyperspectral imagers, microphones, high-resolution cameras, and 3D scanning devices can easily generate gigabytes of data per day, making it impractical for many wireless sensor platforms to stream all collected data to the cloud for analysis. Furthermore, in some sensor deployments, privacy concerns may restrict the resolution or content of data leaving the devices and being routinely stored in the cloud. To address this situation, sensor platforms must reduce or transform the data in situ, sending only the analyzed results to a central server. In designing an open sensor platform capable of leveraging advances in machine learning to support edge computing, several challenges arise, including resilience, performance isolation, and data privacy. This paper describes the architecture of the Waggle platform developed at Argonne National Laboratory. As an open platform, Waggle supports a wide range of sensors, including experimental sensors to measure airborne pollutants such as hydrogen sulfide and ozone, as well as cameras intended to detect urban flooding and automobile traffic. The Waggle platform is used by the Array of Things, a National Science Foundation project to deploy 500 sensor platforms in the city of Chicago, beginning in mid-2016.
A Triangular Periodic Table of Elementary Circuit Elements

Chua proposed an Elementary Circuit Element Quadrangle including the three classic elements (resistor, inductor, and capacitor) and his formulated, named memristor as the fourth element. Based on an observation that this quadrangle may not be symmetric, I proposed an Elementary Circuit Element Triangle, in which memristor as well as mem-capacitor and mem-inductor lead three basic element classes, respectively. An intrinsic mathematical relationship is found to support this new classification. It is believed that this triangle is concise, mathematically sound and aesthetically beautiful, compared with Chua's quadrangle. The importance of finding a correct circuit element table is similar to that of Mendeleev's periodic table of chemical elements in chemistry and the table of 61 elementary particles in physics, in terms of categorizing the existing elements and predicting new elements. A correct circuit element table would also request to rewrite the 20th century textbooks.