nils-herrmann/clean_scirepeval huggingface dataset:
Interactive Dashboards : Using Visual Analytics for knowledge Transfer and Decision Support

With the advancement in information technologies, complex and multidimensional data are generated at an unprecedented rate. The public health sector is challenged with complex and dynamic health data that are produced and housed in health information systems. These data impose a challenge on data analysts and decision makers to understand and make informed decisions about ‘wicked’ health problems. This study synthesizes the Delphi method approach and the Visual Analytics methodology to solicit experts’ inputs and focus their skills and expertise to inform the design of a visual analytical tool that can be employed to help health professionals to understand complex and heterogeneous health data, build knowledge and make informed decisions. This study introduced the design of an Analytic Injury Dashboard (AID) to help health professionals monitor and understand health indicators to make informed decisions and initiate appropriate actions. Furthermore, this study presents an empirical evaluation of the AID dashboard in a collaborative setting with multiple health stakeholders using real domain health data. Findings generated from this study will help to inform the design of effective visualization dashboard that can be used as a decisionsupport tool within the public health sector.  Visual Analytics, Public Health, Group Analytics, Problem Solving, Decision-Making. Index Terms:	  H.5.2 [ User-Centered Design; I.3.6 [Methodology and Techniques]: Interaction Techniques; K:4:3 [Organizational Impacts]: Computer Supported Collaborative Work.
Novel Method to Minimize the Air-Gap MMF Spatial Harmonic Content in Three-Phase Windings

Most of industrial induction motors currently used employ simple winding patterns, which commonly are designed to fulfil the fundamental magnetizing flux and torque requirements, disregarding the spatial harmonic content of the air-gap magnetomotive force (MMF). However, it is well known that the lower-order MMF spatial harmonics have a negative impact on the motor efficiency, vibration, noise, and torque production. The use of different turns per coil in the winding design is a possible solution to mitigate the problem. In this paper, a novel winding optimizing algorithm is fully described. The air-gap is modelled as a linear function of the current-sheet created by the conductors in the slots. Several winding patterns with different poles for stators with different slots are optimized, and the turns per coil pattern is presented in tables for single and double layer windings with optimal coil pitch shortening. These tables can be used, as reference, in winding design projects. An application example of winding optimization is also presented.
E-Counterfeit: A Mobile-Server Platform for Document Counterfeit Detection

This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms.
Propionibacterium Acnes Phylogenetic Type III is Associated with Progressive Macular Hypomelanosis

Progressive macular hypomelanosis (PMH) is a skin disorder that is characterized by hypopigmented macules and usually seen in young adults. The skin microbiota, in particular the bacterium Propionibacterium acnes, is suggested to play a role. Here, we compared the P. acnes population of 24 PMH lesions from eight patients with corresponding nonlesional skin of the patients and matching control samples from eight healthy individuals using an unbiased, culture-independent next-generation sequencing approach. We also compared the P. acnes population before and after treatment with a combination of lymecycline and benzoylperoxide. We found an association of one subtype of P. acnes, type III, with PMH. This type was predominant in all PMH lesions (73.9% of reads in average) but only detected as a minor proportion in matching control samples of healthy individuals (14.2% of reads in average). Strikingly, successful PMH treatment is able to alter the composition of the P. acnes population by substantially diminishing the proportion of P. acnes type III. Our study suggests that P. acnes type III may play a role in the formation of PMH. Furthermore, it sheds light on substantial differences in the P. acnes phylotype distribution between the upper and lower back and abdomen in healthy individuals.
Modeling of attraction force generated by interdigital electrodes for electroadhesive robots

A new direct method for calculating the electrostatic force of electroadhesive robots generated by interdigital electrodes is presented. Here, series expansion is employed to express the spatial potential, and point matching method is used in dealing with some boundary conditions. The attraction force is calculated using the Maxwell stress tensor formula. The accuracy of this method is verified through comparing our results with that of simulation work as well as reported experimental data, the agreement is found to be very good.
Insider Threat Detection in PRODIGAL

This paper reports on insider threat detection research, during which a prototype system (PRODIGAL) was developed and operated as a testbed for exploring a range of detection and analysis methods. The data and test environment, system components, and the core method of unsupervised detection of insider threat leads are presented to document this work and benefit others working in the insider threat domain. We also discuss a core set of experiments evaluating the prototype’s ability to detect both known and unknown malicious insider behaviors. The experimental results show the ability to detect a large variety of insider threat scenario instances imbedded in real data with no prior knowledge of what scenarios are present or when they occur. We report on an ensemble-based, unsupervised technique for detecting potential insider threat instances. When run over 16 months of real monitored computer usage activity augmented with independently developed and unknown but realistic, insider threat scenarios, this technique robustly achieves results within five percent of the best individual detectors identified after the fact. We discuss factors that contribute to the success of the ensemble method, such as the number and variety of unsupervised detectors and the use of prior knowledge encoded in detectors designed for specific activity patterns. Finally, the paper describes the architecture of the prototype system, the environment in which we conducted these experiments and that is in the process of being transitioned to operational users.
Multicolor CRISPR labeling of chromosomal loci in human cells.

The intranuclear location of genomic loci and the dynamics of these loci are important parameters for understanding the spatial and temporal regulation of gene expression. Recently it has proven possible to visualize endogenous genomic loci in live cells by the use of transcription activator-like effectors (TALEs), as well as modified versions of the bacterial immunity clustered regularly interspersed short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system. Here we report the design of multicolor versions of CRISPR using catalytically inactive Cas9 endonuclease (dCas9) from three bacterial orthologs. Each pair of dCas9-fluorescent proteins and cognate single-guide RNAs (sgRNAs) efficiently labeled several target loci in live human cells. Using pairs of differently colored dCas9-sgRNAs, it was possible to determine the intranuclear distance between loci on different chromosomes. In addition, the fluorescence spatial resolution between two loci on the same chromosome could be determined and related to the linear distance between them on the chromosome's physical map, thereby permitting assessment of the DNA compaction of such regions in a live cell.
Visual Attention driven by Convolutional Features

The understanding of where humans look in a scene is a problem of great interest in visual perception and computer vision. When eye-tracking devices are not a viable option, models of human attention can be used to predict fixations. In this paper we give two contribution. First, we show a model of visual attention that is simply based on deep convolutional neural networks trained for object classification tasks. A method for visualizing saliency maps is defined which is evaluated in a saliency prediction task. Second, we integrate the information of these maps with a bottom-up differential model of eye-movements to simulate visual attention scanpaths. Results on saliency prediction and scores of similarity with human scanpaths demonstrate the effectiveness of this model.
Superpixel Sampling Networks

Superpixels provide an efficient low/mid-level representation of image data, which greatly reduces the number of image primitives for subsequent vision tasks. Existing superpixel algorithms are not differentiable, making them difficult to integrate into otherwise end-to-end trainable deep neural networks. We develop a new differentiable model for superpixel sampling that leverages deep networks for learning superpixel segmentation. The resulting Superpixel Sampling Network (SSN) is end-to-end trainable, which allows learning task-specific superpixels with flexible loss functions and has fast runtime. Extensive experimental analysis indicates that SSNs not only outperform existing superpixel algorithms on traditional segmentation benchmarks, but can also learn superpixels for other tasks. In addition, SSNs can be easily integrated into downstream deep networks resulting in performance improvements.
Security Considerations in Minutiae-Based Fuzzy Vaults

The fuzzy vault scheme is a cryptographic primitive that can be used to protect human fingerprint templates where stored. Analyses for most implementations account for brute-force security only. There are, however, other risks that have to be consider, such as false-accept attacks, record multiplicity attacks, and information leakage from auxiliary data, such as alignment parameters. In fact, the existing work lacks analyses of these weaknesses and are even susceptible to a variety of them. In view of these vulnerabilities, we redesign a minutiae-based fuzzy vault implementation preventing an adversary from running attacks via record multiplicity. Furthermore, we propose a mechanism for robust absolute fingerprint prealignment. In combination, we obtain a fingerprint-based fuzzy vault that resists known record multiplicity attacks and that does not leak information about the protected fingerprints from auxiliary alignment data. By experiments, we evaluate the performance of our security-improved implementation that, even though it has slight usability merits as compared with other minutiae-based implementations, provides improved security. However, despite heavy efforts spent in improving security, our implementation is, like all other implementations based on a single finger, subjected to a fundamental security limitation related to the false acceptance rate, i.e., false-accept attack. Consequently, this paper supports the notion that a single finger is not sufficient to provide acceptable security. Instead, implementations for multiple finger or even multiple modalities should be deployed the security of which may be improved by the technical contributions of this paper.
Automating the Assignment of Submitted Manuscripts to Reviewers

The 117 manuscripts submitted for the Hypertext '91 conference were assigned to members of the review committee, using a variety of automated methods based on information retrieval principles and Latent Semantic Indexing. Fifteen reviewers provided exhaustive ratings for the submitted abstracts, indicating how well each abstract matched their interests. The automated methods do a fairly good job of assigning relevant papers for review, but they are still somewhat poorer than assignments made manually by human experts and substantially poorer than an assignment perfectly matching the reviewers' own ranking of the papers. A new automated assignment method called “n of 2n” achieves better performance than human experts by sending reviewers more papers than they actually have to review and then allowing them to choose part of their review load themselves.
Unsupervised Polyglot Text To Speech

We present a TTS neural network that is able to produce speech in multiple languages. The proposed network is able to transfer a voice, which was presented as a sample in a source language, into one of several target languages. Training is done without using matching or parallel data, i.e., without samples of the same speaker in multiple languages, making the method much more applicable. The conversion is based on learning a polyglot network that has multiple perlanguage sub-networks and adding loss terms that preserve the speaker’s identity in multiple languages. We evaluate the proposed polyglot neural network for three languages with a total of more than 400 speakers and demonstrate convincing conversion capabilities.
9 . 7-ENOB SAR ADC for Compressed Sensing

Moore’s law has allowed the microprocessor market to innovate at an astonishing rate. We believe microchip implants are the next frontier for the integrated circuit industry. Current health monitoring technologies are large, expensive, and consume significant power. By miniaturizing and reducing power, monitoring equipment can be implanted into the body and allow 24/7 health monitoring. We plan to implement a new transmitter topology, compressed sensing, which can be used for wireless communications with microchip implants. This paper focuses on the ADC used in the compressed sensing signal chain. Using the Cadence suite of tools and a 32/28nm process, we produced simulations of our compressed sensing Analog to Digital Converter to feed into a Digital Compression circuit. Our results indicate that a 12-bit, 20Ksample, 9.8nW Successive Approximation ADC is possible for diagnostic resolution (10 bits). By incorporating a hybrid-C2C DAC with differential floating voltage shields, it is possible to obtain 9.7 ENOB. Thus, we recommend this ADC for use in compressed sensing for biomedical purposes. Not only will it be useful in digital compressed sensing, but this can also be repurposed for use in analog compressed sensing.
IoFClime: The fuzzy logic and the Internet of Things to control indoor temperature regarding the outdoor ambient conditions

The Internet of Things is arriving to our homes or cities through fields already known like Smart Homes, Smart Cities, or Smart Towns. The monitoring of environmental conditions of cities can help to adapt the indoor locations of the cities in order to be more comfortable for people who stay there. A way to improve the indoor conditions is an efficient temperature control, however, it depends on many factors like the different combinations of outdoor temperature and humidity. Therefore, adjusting the indoor temperature is not setting a value according to other value. There are many more factors to take into consideration, hence the traditional logic based in binary states cannot be used. Many problems cannot be solved with a set of binary solutions and we need a new way of development. Fuzzy logic is able to interpret many states, more than two states, giving to computers the capacity to react in a similar way to people. In this paper we will propose a new approach to control the temperature using the Internet of Things together its platforms and fuzzy logic regarding not only the indoor temperature but also the outdoor temperature and humidity in order to save energy and to set a more comfortable environment for their users. Finally, ∗Corresponding author Email addresses: danielmeanallorian@gmail.com (Daniel Meana-Llorián), gonzalezgarciacristian@hotmail.com (Cristian González Garćıa), crispelayo@uniovi.es (B. Cristina Pelayo G-Bustelo), cueva@uniovi.es (Juan Manuel Cueva Lovelle),
Synthetic polymeric biomaterials for wound healing: a review

Wounds are of a variety of types and each category has its own distinctive healing requirements. This realization has spurred the development of a myriad of wound dressings, each with specific characteristics. It is unrealistic to expect a singular dressing to embrace all characteristics that would fulfill generic needs for wound healing. However, each dressing may approach the ideal requirements by deviating from the 'one size fits all approach', if it conforms strictly to the specifications of the wound and the patient. Indeed, a functional wound dressing should achieve healing of the wound with minimal time and cost expenditures. This article offers an insight into several different types of polymeric materials clinically used in wound dressings and the events taking place at cellular level, which aid the process of healing, while the biomaterial dressing interacts with the body tissue. Hence, the significance of using synthetic polymer films, foam dressings, hydrocolloids, alginate dressings, and hydrogels has been reviewed, and the properties of these materials that conform to wound-healing requirements have been explored. A special section on bioactive dressings and bioengineered skin substitutes that play an active part in healing process has been re-examined in this work.
An Identity Based Digital Signature from ECDSA

There are many proposed identity-based digital signature protocols based on bilinear pairings. But the computation of pairing is time-consuming, the performance of those agreements is unacceptable. An Identity based digital signature protocol which based on ECDSA is proposed in this paper. As a result, up to 95% of the computation cost can be saved when compared to other identity based signature protocols using pairing. The proposed protocol can be implemented by the exiting component of ECDSA.
Managing meiotic recombination in plant breeding.

Crossover recombination is a crucial process in plant breeding because it allows plant breeders to create novel allele combnations on chromosomes that can be used for breeding superior F1 hybrids. Gaining control over this process, in terms of increasing crossover incidence, altering crossover positions on chromosomes or silencing crossover formation, is essential for plant breeders to effectively engineer the allelic composition of chromosomes. We review the various means of crossover control that have been described or proposed. By doing so, we sketch a field of science that uses both knowledge from classic literature and the newest discoveries to manage the occurrence of crossovers for a variety of breeding purposes.
A coding approach to event correlation

This paper describes a novel approach to event correlation in networks based on coding techniques. Observable symptom events are viewed as a code that identifies the problems that caused them; correlation is performed by decoding the set of observed symptoms. The coding approach has been implemented in SMARTS Event Management System (SEMS), as a server running under Sun Solaris 2.3. Preliminary benchmarks of the SEMS demonstrate that the coding approach provides a speedup at least two orders of magnitude over other published correlation systems. In addition, it is resilient to high rates of symptom loss and false alarms. Finally, the coding approach scales well to very large domains involving thousands of problems.
The Evaluation of Question Answering Systems : Lessons Learned from the TREC QA Track

The TREC question answering (QA) track was the first large-sc ale evaluation of open-domain question answering systems. In addition to successfully fostering research on the QA task, the track h s also been used to investigate appropriate evaluation me thodologies for question answering systems. This paper gives a brief histor y of the TREC QA track, motivating the decisions made in its im plementation and summarizing the results. The lessons learned from the tr ack will be used to evolve new QA evaluations for both the trac k nd the ARDA AQUAINT program.
Opportunities and Challenges in Building a Spatiotemporal Multi-scale Model of the Human Pancreatic β Cell

The construction of a predictive model of an entire eukaryotic cell that describes its dynamic structure from atomic to cellular scales is a grand challenge at the intersection of biology, chemistry, physics, and computer science. Having such a model will open new dimensions in biological research and accelerate healthcare advancements. Developing the necessary experimental and modeling methods presents abundant opportunities for a community effort to realize this goal. Here, we present a vision for creation of a spatiotemporal multi-scale model of the pancreatic β-cell, a relevant target for understanding and modulating the pathogenesis of diabetes.
Mathematical model and control strategy of a two-wheeled self-balancing robot

In this paper a control strategy and sensor concept for a two-wheeled self-balancing robot is proposed. First a mathematical model of the robot is derived using Lagrangian mechanics. Based on the model a full state feedback controller, in combination with two higher-level controls are deployed for stabilization and drive control. A gyroscope, an accelerometer and rotational encoders are used for state determination, introducing a new method of measurement data fusion for the accelerometer and the gyro by using a drift compensation controller. Furthermore measurement proceedings for the model parameters of a real prototype robot are suggested and the control for this robot is designed. The proposed mathematical model, as well as the control strategy are then verified by comparing the behavior of the constructed robot with model simulations.
A Multiband Millimeter-Wave Two-Dimensional Array Based on Enhanced Franklin Antenna for 5 G Wireless Systems

This letter presents a novel and compact antenna array suggesting geometrical modifications in the concept of collinear arrays at millimeter-wave (MMW) spectrum. The extension of the standard narrowband Franklin linear antenna array in a compact two-dimensional (2D) assembly is proposed and multiband response is accomplished in this work which fulfills demands of future 5G systems. The proposed 2D antenna array is designed to operate at licensed frequency bands of 28GHz and 37-39 GHz recommended by Federal Communications Commission (FCC) for 5G wireless networks, as well as at 33GHz for satellite communications and radio navigation. Measurements validate the triple-band response at the desired frequencies of operation. The proposed antenna array also offers distinguishing performance in terms of high gain and significant efficiency above 70% in all the MMW operating bands.