nils-herrmann/clean_scirepeval huggingface dataset:
Making Stochastic Neural Networks from Deterministic Ones

It has been believed that stochastic feedforward neural networks (SFNN) have several advantages beyond deterministic deep neural networks (DNN): they have more expressive power allowing multi-modal mappings and regularize better due to their stochastic nature. However, training SFNN is notoriously harder. In this paper, we aim at developing efficient training methods for large-scale SFNN, in particular using known architectures and pre-trained parameters of DNN. To this end, we propose a new intermediate stochastic model, called Simplified-SFNN, which can be built upon any baseline DNN and approximates certain SFNN by simplifying its upper latent units above stochastic ones. The main novelty of our approach is in establishing the connection between three models, i.e., DNN → Simplified-SFNN → SFNN, which naturally leads to an efficient training procedure of the stochastic models utilizing pre-trained parameters of DNN. Using several popular DNNs, we show how they can be effectively transferred to the corresponding stochastic models for both multi-modal and classification tasks on MNIST, TFD, CIFAR-10, CIFAR-100 and SVHN datasets. In particular, our stochastic model built from the wide residual network has 28 layers and 36 million parameters, where the former consistently outperforms the latter for the classification tasks on CIFAR-10 and CIFAR-100 due to its stochastic regularizing effect.
Suicide by skull stab wounds: a case of drug-induced psychosis.

Suicide by stabbing to the head and/or driving sharp objects into the skull is of extreme rarity. This article reports the case of a 27-year-old man, who committed suicide by multiple knife stabs and cuts to the head, the torso, one shoulder and the forearms. Autopsy showed a perforating wound of the skull and the 10-cm long broken blade of the knife being still embedded in the right temporal lobe of the brain. The deceased had no history of psychiatric illness but was currently treated by mefloquine, a quinine derivative associated with a high rate of psychiatric adverse effects. Toxicological examination confirmed a recent intake of mefloquine together with chloroquine, another antimalarial drug. To our knowledge, this is the first report of a completed suicide with very strong evidence of mefloquine implication. Discussion focuses upon mefloquine-induced psychiatric disorders and highlights the importance of performing toxicological investigations in cases of unusual suicides.
See the Glass Half Full: Reasoning About Liquid Containers, Their Volume and Content

Humans have rich understanding of liquid containers and their contents; for example, we can effortlessly pour water from a pitcher to a cup. Doing so requires estimating the volume of the cup, approximating the amount of water in the pitcher, and predicting the behavior of water when we tilt the pitcher. Very little attention in computer vision has been made to liquids and their containers. In this paper, we study liquid containers and their contents, and propose methods to estimate the volume of containers, approximate the amount of liquid in them, and perform comparative volume estimations all from a single RGB image. Furthermore, we show the results of the proposed model for predicting the behavior of liquids inside containers when one tilts the containers. We also introduce a new dataset of Containers Of liQuid contEnt (COQE) that contains more than 5,000 images of 10,000 liquid containers in context labelled with volume, amount of content, bounding box annotation, and corresponding similar 3D CAD models.
Comparison of the impact of powerpoint and chalkboard in undergraduate medical teaching: an evidence based study.

To compare the impact of the PowerPoint multimedia presentation and chalkboard in teaching by assessing the knowledge based on the marks obtained.



Cross-sectional study.


PLACE AND DURATION OF STUDY
Department of Physiology, College of Medicine, King Saud University, Riyadh, Kingdom of Saudi Arabia, from December 2007 - June 2009.



Three-hundred male medical students were divided into three groups and a selected content-based lecture in physiology was delivered. For one group lecture was delivered using PowerPoint presentation, for second group using chalkboard and for third group the lecture was delivered by using both PowerPoint as well as chalkboard. Single-best Multiple Choice Questions [MCQs] paper was used for assessing the knowledge gained. The same exercise was repeated in another medical science school for the confirmation of validity and reliability of the results.



Students who attended the class on both PowerPoint and chalkboard obtained significantly higher score in single best MCQ examination compared to those students who attended the same content based lecture on the PowerPoint or chalkboard alone (p = 0.05).



The integrated (PowerPoint and chalkboard) method of teaching was found more suitable tool of teaching and learning than PowerPoint or chalkboard alone.
Interactive technology and human-animal encounters at the zoo

In this paper we investigate social dimensions of technology use in human–animal interactions, through a study of interactive systems at the zoo. Zoos are a familiar place for encounters between humans and non-domesticated animals. Accordingly, we examine zoos as a significant site to extend research into animal–computer interaction (ACI). We present a case study that examines the deployment and use of new digital technologies that intervene in, and influence, human–animal relationships. The paper reports on interactive systems in use at Melbourne Zoo. The study investigates the use and impact of technology in the course of human–animal encounters, including how human use of technology in this setting shapes encounters in subtle ways. We examine five interactive systems used by visitors (Digital Signs and the Zoopermarket), by zoo personnel with visitors (Educator Screens and Volunteer iPads), and by zoo personnel with animals (Apps for Apes). Our work draws broad insights for the design and understanding of animal–human–computer interaction at the zoo, as a catalyst for further research into this site of considerable significance to animalcomputer interaction. We identified four key themes in the ways that interactive systems are intervening in human–animal encounters at the zoo. Firstly, interactive technology at the zoo risks distracting from visitors' encounters with animals. Secondly, the appearance and use of technology moreover runs counter to expectations of naturalistic zoo landscapes. Thirdly, interactive systems however offer opportunities to enhance important aspects of visitors' experience of animal encounters, and to widen the temporal and spatial dimensions of the encounter. Finally, we interpret these insights by examining how technology is used in the context of interactions between numerous human and animal actors, and in a setting impacted by complex social and organisational forces. From this, we identify the need for ACI to consider technology use by diverse people and animals; that multiple interactions may occur at once; the diverse social activities that may surround human–animal interactions; the distributed form of interactions between multiple participants; and the performative nature of some human–animal encounters. & 2016
Helical-Shaped Graphene Tubular Spring Formed Within Microchannel for Wearable Strain Sensor With Wide Dynamic Range

This article reports on a helical spring-like piezoresistive graphene strain sensor formed within a microfluidic channel. The helical spring has a tubular hollow structure and is made of a thin graphene layer coated on the inner wall of the channel using an in situ microfluidic casting method. The helical shape allows the sensor to flexibly respond to both tensile and compressive strains in a wide dynamic detection range from 24 compressive strain to 20 tensile strain. Fabrication of the sensor involves embedding a helical thin metal wire with a plastic wrap into a precursor solution of an elastomeric polymer, forming a helical microfluidic channel by removing the wire from cured elastomer, followed by microfluidic casting of a graphene thin layer directly inside the helical channel. The wide dynamic range, in conjunction with mechanical flexibility and stretchability of the sensor, will enable practical wearable strain sensor applications where large strains are often involved.
Resonant Magnetic Field Sensors Based On MEMS Technology

Microelectromechanical systems (MEMS) technology allows the integration of magnetic field sensors with electronic components, which presents important advantages such as small size, light weight, minimum power consumption, low cost, better sensitivity and high resolution. We present a discussion and review of resonant magnetic field sensors based on MEMS technology. In practice, these sensors exploit the Lorentz force in order to detect external magnetic fields through the displacement of resonant structures, which are measured with optical, capacitive, and piezoresistive sensing techniques. From these, the optical sensing presents immunity to electromagnetic interference (EMI) and reduces the read-out electronic complexity. Moreover, piezoresistive sensing requires an easy fabrication process as well as a standard packaging. A description of the operation mechanisms, advantages and drawbacks of each sensor is considered. MEMS magnetic field sensors are a potential alternative for numerous applications, including the automotive industry, military, medical, telecommunications, oceanographic, spatial, and environment science. In addition, future markets will need the development of several sensors on a single chip for measuring different parameters such as the magnetic field, pressure, temperature and acceleration.
MuSSE: A Tool to Extract Meta-Data from Game Sprite Sheets Using Blob Detection Algorithm

This paper introduces a tool to automatically generate meta-data from game sprite sheets. MuSSE is a tool developed to extract XML data from sprite sheet images with non-uniform - multi-sized - sprites. MuSSE (Multi-sized Sprite Sheet meta-data Exporter) is based on a Blob detection algorithm that incorporates a connected-component labeling system. Hence, blobs of arbitrary size can be extracted by adjusting component connectivity parameters. This image detection algorithm defines boundary blobs for each individual sprite in a sprite sheet. Every specific blob defines a sprite characteristic within the sheet: position, name and size, which allows for subsequent data specification for each blob/image. Several examples on real images illustrate the performance of the proposed algorithm and working tool.
Finding Bursty Topics from Microblogs

Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneously captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) posts published by the same user are more likely to have the same topic. The former helps find eventdriven posts while the latter helps identify and filter out “personal” posts. Our experiments on a large Twitter dataset show that there are more meaningful and unique bursty topics in the top-ranked results returned by our model than an LDA baseline and two degenerate variations of our model. We also show some case studies that demonstrate the importance of considering both the temporal information and users’ personal interests for bursty topic detection from microblogs.
Ensemble Learning Using Decorrelated Neural Networks

We describe a decorrelation network training method for improving the quality of regression learning in \en-semble" neural networks that are composed of linear combinations of individual neural networks. In this method, individual networks are trained by backpropagation to not only reproduce a desired output, but also to have their errors be linearly decorrelated with the other networks. Outputs from the individual networks are then linearly combined to produce the output of the ensemble network. We demonstrate the performances of decorrelated network training on learning the \3 Parity" logic function, a noisy sine function, and a one dimensional nonlinear function, and compare the results with the ensemble networks composed of independently trained individual networks (without decorrelation training). Empirical results show that when individual networks are forced to be decorrelated with one another the resulting ensemble neural networks have lower mean squared errors than the ensemble networks having independently trained individual networks. This method is particularly applicable when there is insuucient data to train each individual network on disjoint subsets of training patterns.
Memory Forensics over the IEEE 1394 Interface

The IEEE 1394 “FireWire” interface provides a means for acquiring direct memory access. We discuss how this can be used to perform live memory forensics on a target system. We also present libforensic1394 an open-source software library designed especially for this purpose. Passive and active applications of live memory forensics are analysed. Memory imaging techniques are discussed at length. It is demonstrated how the interface can be used both to dump the memory of a live system and to compromise contemporary operating systems.
Advances in quantum teleportation

641 It has been over two decades since the discovery of quantum tele­ portation, in what is arguably one of the most interesting and exciting implications of the ‘weirdness’ of quantum mechanics. Prior to this landmark discovery, the fascinating idea of teleporta­ tion belonged in the realm of science fiction. First coined in 1931 by Charles H. Fort1, the term ‘teleportation’ has since been used to refer to the process by which bodies and objects are transferred from one location to another, without actually making the jour­ ney along the way. Since then it has become a fixture of pop cul­ ture, perhaps best exemplified by Star Trek’s celebrated catchphrase “Beam me up, Scotty.” In 1993, a seminal paper2 described a quantum information protocol, dubbed quantum teleportation, that shares several of the above features. In this protocol, an unknown quantum state of a physical system is measured and subsequently reconstructed or ‘reassembled’ at a remote location (the physical constituents of the original system remain at the sending location). This process requires classical communication and excludes superluminal com­ munication. Most importantly, it requires the resource of quantum entanglement3,4. Indeed, quantum teleportation can be seen as the protocol in quantum information that most clearly demonstrates the character of quantum entanglement as a resource: without its presence, such a quantum state transfer would not be possible within the laws of quantum mechanics. Quantum teleportation plays an active role in the progress of quantum information science5–8. On the one hand, it is a concep­ tual protocol that is crucial in the development of formal quantum information theory; on the other, it represents a fundamental ingre­ dient to the development of many quantum technologies. Quantum repeaters9, quantum gate teleportation10, measurement­based quan­ tum computing11 and port­based teleportation12 all derive from the basic scheme of quantum teleportation. The vision of a quantum network13 draws inspiration from this scheme. Teleportation has also been used as a simple tool for exploring ‘extreme’ physics, such as closed time­like curves14. Today, quantum teleportation has been achieved in laboratories around the world using a variety of different substrates and technolo­ gies, including photonic qubits (light polarization15–21, single rail22,23, dual rails24,25, time­bin26–28 and spin­orbital qubits29), nuclear mag­ netic resonance (NMR)30, optical modes31–39, atomic ensembles40–43, Advances in quantum teleportation
Extracting Business Value from IT: A Sensemaking Perspective of Post-Adoptive Use

Fellowship, Awards, and Recognition 2015: Annual Outstanding Special Interest Group (SIG) Award, awarded by Association of Information System (AIS) in recognition of excellence in SIG operations, communications, educational and/or professional development events, and research publications for 2014. Dr. Hsieh served as the President of SIG-ADIT (Adoption and Diffusion of Innovation) for the year of 2014.
Automotive battery management systems

Battery management system (BMS) is an integral part of an automobile. It protects the battery from damage, predicts battery life and maintains the battery in an operational condition. The BMS performs these tasks by integrating one or more of the functions, such as protecting the cell, controlling the charge, determining the state of charge (SOC), the state of health (SOH), and the remaining useful life (RUL) of the battery, cell balancing, as well as monitoring and storing historical data. In this paper, we propose a BMS that estimates three critical characteristics of the battery (SOC, SOH, and RUL) using a data-driven approach. Our estimation procedure is based on an equivalent circuit battery model consisting of resistors, capacitor, and Warburg impedance. The resistors usually characterize the self-discharge and internal resistance of the battery, the capacitor generally represents the charge stored in the battery, and the Warburg impedance represents the diffusion phenomenon. We investigate the use of support vector machines to predict the capacity fade and power fade, which characterize the SOH of a battery, as well as estimate the SOC of the battery. The circuit parameters are estimated from electrochemical impedance spectroscopy (EIS) test data using nonlinear least squares estimation techniques. Predictions of remaining useful life (RUL) of the battery are obtained by support vector regression of the power fade and capacity fade estimates.
Evaluating the Effect of Copper Nanoparticles in Inhibiting Pseudomonas aeruginosa and Listeria monocytogenes Biofilm Formation

Biofilm formation is a major virulence factor in different bacteria. Biofilms allow bacteria to resist treatment with antibacterial agents. The biofilm formation on glass and steel surfaces, which are extremely useful surfaces in food industries and medical devices, has always had an important role in the distribution and transmission of infectious diseases.



In this study, the effect of coating glass and steel surfaces by copper nanoparticles (CuNPs) in inhibiting the biofilm formation by Listeria monocytogenes and Pseudomonas aeruginosa was examined.



The minimal inhibitory concentrations (MICs) of synthesized CuNPs were measured against L. monocytogenes and P. aeruginosa by using the broth-dilution method. The cell-surface hydrophobicity of the selected bacteria was assessed using the bacterial adhesion to hydrocarbon (BATH) method. Also, the effect of the CuNP-coated surfaces on the biofilm formation of the selected bacteria was calculated via the surface assay.



The MICs for the CuNPs according to the broth-dilution method were ≤ 16 mg/L for L. monocytogenes and ≤ 32 mg/L for P. aeruginosa. The hydrophobicity of P. aeruginosa and L. monocytogenes was calculated as 74% and 67%, respectively. The results for the surface assay showed a significant decrease in bacterial attachment and colonization on the CuNP-covered surfaces.



Our data demonstrated that the CuNPs inhibited bacterial growth and that the CuNP-coated surfaces decreased the microbial count and the microbial biofilm formation. Such CuNP-coated surfaces can be used in medical devices and food industries, although further studies in order to measure their level of toxicity would be necessary.
Patient and surgeon ranking of the severity of symptoms associated with fecal incontinence: the fecal incontinence severity index.

The purpose of this research was to develop and evaluate a severity rating score for fecal incontinence, the Fecal Incontinence Severity Index.



The Fecal Incontinence Severity Index is based on a type x frequency matrix. The matrix includes four types of leakage commonly found in the fecal incontinent population: gas, mucus, and liquid and solid stool and five frequencies: one to three times per month, once per week, twice per week, once per day, and twice per day. The Fecal Incontinence Severity Index was developed using both colon and rectal surgeons and patient input for the specification of the weighting scores.



Surgeons and patients had very similar weightings for each of the type x frequency combinations; significant differences occurred for only 3 of the 20 different weights. The Fecal Incontinence Severity Index score of a group of patients with fecal incontinence (N = 118) demonstrated significant correlations with three of the four scales found in a fecal incontinence quality-of-life scale.



Evaluation of the Fecal Incontinence Severity Index indicates that the index is a tool that can be used to assess severity of fecal incontinence. Overall, patient and surgeon ratings of severity are similar, with minor differences associated with the accidental loss of solid stool.
Relationships between common water bacteria and pathogens in drinking-water

6 Relationships between common water bacteria and pathogens in drinking-water H. Leclerc 6.1  To perform a risk analysis for pathogens in drinking-water, it is necessary, on the one hand, to promote epidemiological studies, such as prospective cohort and case–control studies. It is also appropriate, on the other hand, to better understand the ecology of these microorganisms, especially in analysing in detail the interactions between common water bacteria and pathogens in such diverse habitats as free water and biofilms. It appears essential to distinguish two categories of drinking-water sources: surface water and groundwater under the direct influence of surface water
Interleukin-7 mediates the homeostasis of naïve and memory CD8 T cells in vivo

The naïve and memory T lymphocyte pools are maintained through poorly understood homeostatic mechanisms that may include signaling via cytokine receptors. We show that interleukin-7 (IL-7) plays multiple roles in regulating homeostasis of CD8+ T cells. We found that IL-7 was required for homeostatic expansion of naïve CD8+ and CD4+ T cells in lymphopenic hosts and for CD8+ T cell survival in normal hosts. In contrast, IL- 7 was not necessary for growth of CD8+ T cells in response to a virus infection but was critical for generating T cell memory. Up-regulation of Bcl-2 in the absence of IL-7 signaling was impaired after activation in vivo. Homeostatic proliferation of memory cells was also partially dependent on IL-7. These results point to IL-7 as a pivotal cytokine in T cell homeostasis.