nils-herrmann/clean_scirepeval huggingface dataset:
Implicitures: Cancelability and Non-detachability *

Grice’s so-called ‘theory of conversation’ (Grice 1967a) establishes a basic distinction between two aspects of utterance meaning: what is said and what is implicated. Some authors (Carston (1988), Recanati (1989), Sperber and Wilson (1986)) have criticized this distinction and, particularly, its application to the pragmatic analysis of several linguistic phenomena, giving rise to an interesting debate on the delimitation of the different aspects of utterance meaning. Bach (1994) enters the discussion with a proposal of revision of Grice’s original distinction, including a new category: what is implicited. The aim of this paper is to participate in this debate paying attention to some questions concerning the Gricean ‘tests’ of cancelability and non-detachability for the different aspects of utterance meaning. More specifically, our claim is that these tests support Bach’s (1994) triple distinction among what is said, impliciture, and implicature, because we can establish the following results:
Vaginal Tactile Imaging

Changes in the elasticity of the vaginal walls, connective support tissues, and muscles are thought to be significant factors in the development of pelvic organ prolapse, a highly prevalent condition affecting at least 50% of women in the United States during their lifetimes. It creates two predominant concerns specific to the biomechanical properties of pelvic support tissues: how does tissue elasticity affect the development of pelvic organ prolapse and how can functional elasticity be maintained through reconstructive surgery. We designed a prototype of vaginal tactile imager (VTI) for visualization and assessment of elastic properties of pelvic floor tissues. In this paper, we analyze applicability of tactile imaging for evaluation of reconstructive surgery results and characterization of normal and pelvic organ prolapse conditions. A pilot clinical study with 13 patients demonstrated that VTI allows imaging of vaginal walls with increased rigidity due to implanted mesh grafts following reconstructive pelvic surgery and VTI has the potential for prolapse characterization and detection.
A Mars Ascent Vehicle for potential mars sample return

This paper will cover the conceptual design of a Mars Ascent Vehicle (MAV) and efforts underway to raise the TRL at both the component and system levels. A system down select was executed resulting in a Hybrid Propulsion based Single Stage To Orbit (SSTO) MAV baseline architecture. This paper covers the Point of Departure design, as well as results of hardware developments that will be tested in several upcoming flight opportunities.
The Arduino as a Hardware Random-Number Generator

Cheap micro-controllers, such as the Arduino or other controllers based on the Atmel AVR CPUs are being deployed in a wide variety of projects, ranging from sensors networks to robotic submarines. In this paper, we investigate the feasibility of using the Arduino as a true random number generator (TRNG). The Arduino Reference Manual recommends using it to seed a pseudo random number generator (PRNG) due to its ability to read random atmospheric noise from its analog pins. This is an enticing application since true bits of entropy are hard to come by. Unfortunately, we show by statistical methods that the atmospheric noise of an Arduino is largely predictable in a variety of settings, and is thus a weak source of entropy. We explore various methods to extract true randomness from the micro-controller and conclude that it should not be used to produce randomness from its analog pins.
Semantics-based Graph Approach to Complex Question-Answering

This paper suggests an architectural approach of representing knowledge graph for complex question-answering. There are four kinds of entity relations added to our knowledge graph: syntactic dependencies, semantic role labels, named entities, and coreference links, which can be effectively applied to answer complex questions. As a proof of concept, we demonstrate how our knowledge graph can be used to solve complex questions such as arithmetics. Our experiment shows a promising result on solving arithmetic questions, achieving the 3folds cross-validation score of 71.75%.
EEG Recorded from the Ear: Characterizing the Ear-EEG Method

Highlights Auditory middle and late latency responses can be recorded reliably from ear-EEG.For sources close to the ear, ear-EEG has the same signal-to-noise-ratio as scalp.Ear-EEG is an excellent match for power spectrum-based analysis. A method for measuring electroencephalograms (EEG) from the outer ear, so-called ear-EEG, has recently been proposed. The method could potentially enable robust recording of EEG in natural environments. The objective of this study was to substantiate the ear-EEG method by using a larger population of subjects and several paradigms. For rigor, we considered simultaneous scalp and ear-EEG recordings with common reference. More precisely, 32 conventional scalp electrodes and 12 ear electrodes allowed a thorough comparison between conventional and ear electrodes, testing several different placements of references. The paradigms probed auditory onset response, mismatch negativity, auditory steady-state response and alpha power attenuation. By comparing event related potential (ERP) waveforms from the mismatch response paradigm, the signal measured from the ear electrodes was found to reflect the same cortical activity as that from nearby scalp electrodes. It was also found that referencing the ear-EEG electrodes to another within-ear electrode affects the time-domain recorded waveform (relative to scalp recordings), but not the timing of individual components. It was furthermore found that auditory steady-state responses and alpha-band modulation were measured reliably with the ear-EEG modality. Finally, our findings showed that the auditory mismatch response was difficult to monitor with the ear-EEG. We conclude that ear-EEG yields similar performance as conventional EEG for spectrogram-based analysis, similar timing of ERP components, and equal signal strength for sources close to the ear. Ear-EEG can reliably measure activity from regions of the cortex which are located close to the ears, especially in paradigms employing frequency-domain analyses.
A LOW-PROFILE USER TERMINAL ANTENNA FOR MOBILE BI-DIRECTIONAL KA-BAND SATELLITE COMMUNICATIONS ESA / ESTEC , NOORDWIJK , THE NETHERLANDS 3-5 OCTOBER 2012

This paper presents a low-profile user-terminal antenna for mobile bi-directional Ka-band satellite communication networks for emergency scenarios. We have devised an antenna with a circularly polarised radiation pattern and dual-band capability, which addresses a hybrid tracking. The principle of operation of a rectangular antenna panel applying a dual-band partially reflective surface (PRS) of 60 mm by 200 mm was manufactured and successfully verified. This publication describes the design of the panel and analyses measurement results. Furthermore, our first low-profile antenna demonstrator is presented, intended to be evaluated at a testbed for satellite communications in Ilmenau.
Analysis, design and implementation of an active clamp flyback converter

This paper presents the detailed circuit operation, mathematical analysis, and design example of the active clamp flyback converter. The auxiliary switch and clamp capacitor are used in the flyback converter to recycle the energy stored in the transformer leakage in order to minimize the spike voltage at the transformer primary side. Therefore the voltage stress of main switch can be reduced. The active clamped circuit can also help the main switch to turn on at ZVS using the switch output capacitor and transformer leakage inductance. First the circuit operation and mathematical analysis are provided. The design example of active clamp flyback converter is also presented. Finally the experimental results based on a 120 W prototype circuit are provided to verify the system performance
Learning A Second Language with a Socially Assistive Robot

We created a socially assistive robotic learning companion to support English-speaking children’s acquisition of a new language (Spanish). In a two-month microgenetic study, 34 preschool children will play an interactive game with a fully autonomous robot and the robot’s virtual sidekick, a Toucan shown on a tablet screen. Two aspects of the interaction were personalized to each child: (1) the content of the game (i.e., which words were presented), and (2) the robot’s affective responses to the child’s emotional state and performance. We will evaluate whether personalization leads to greater engagement and learning.
A Hybrid Deep Learning Architecture for Paraphrase Identification

The binary classification task of Paraphrase Identification (PI) is vital in the field of Natural Language Processing. The objective of this study is to propose an optimized Deep Learning architecture in combination with usage of word embedding technique for the classification of sentence pairs as paraphrases or not. For Paraphrase Identification task, this paper proposes a hybrid Deep Learning architecture aiming to capture as many features from the inputted sentences in natural language. The aim is to accurately classify whether the pair of sentences are paraphrases of each other or not. The importance of using an optimized word-embedding approach in combination with the proposed hybrid Deep Learning architecture is explained. This study also deals with the lack of the training data required to generate a robust Deep Learning model. The intention is to harness the memorizing power of Long Short Term Memory (LSTM) neural network and the feature extracting capability of Convolutional Neural Network (CNN) in combination with the optimized word-embedding approach which aims to capture wide-sentential contexts and word-order. The proposed model is compared with existing systems and it surpasses all the existing systems in the performance in terms of accuracy.
Detection of Cymbidium Mosaic Virus ( CYMV ) on Vanda Plants

Orchid plants are the members of Orchidaceae consisting of more than 25,000 species, which are distributed almost all over the world but more abundantly in the tropics. There are 177 genera, 1,125 species of orchids that originated in Thailand. Orchid plant collected from different nurseries showing Chlorotic and mosaic symptoms were observed on Vanda plants and it was suspected to infect with virus. So the symptomatic plants were tested for Cymbidium Mosaic Virus (CYMV), Odontoglossum ring spot virus (ORSV), Poty virus and Tomato Spotted Wilt Virus (TSWV) with Direct Antigen CoatingEnzyme Linked Immunosorbent Assay (DAC-ELISA) and further confirmed by Transmission Electron Microscopy (TEM). With the two methods CYMV and ORSV were detected positively from the suspected imported samples and low positive results were observed for Potex, Poty virus and Tomato Spotted Wilt Virus (TSWV).
An eye for deception: A case study in utilizing the human-as-a-security-sensor paradigm to detect zero-day semantic social engineering attacks

In a number of information security scenarios, human beings can be better than technical security measures at detecting threats. This is particularly the case when a threat is based on deception of the user rather than exploitation of a specific technical flaw, as is the case of spear-phishing, application spoofing, multimedia masquerading and other semantic social engineering attacks. Here, we put the concept of the human-as-a-security-sensor to the test with a first case study on a small number of participants subjected to different attacks in a controlled laboratory environment and provided with a mechanism to report these attacks if they spot them. A key challenge is to estimate the reliability of each report, which we address with a machine learning approach. For comparison, we evaluate the ability of known technical security countermeasures in detecting the same threats. This initial proof of concept study shows that the concept is viable.
Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications

Social Virtual Reality based Learning Environments (VRLEs) such as vSocial render instructional content in a three-dimensional immersive computer experience for training youth with learning impediments. There are limited prior works that explored attack vulnerability in VR technology, and hence there is a need for systematic frameworks to quantify risks corresponding to security, privacy, and safety (SPS) threats. The SPS threats can adversely impact the educational user experience and hinder delivery of VRLE content. In this paper, we propose a novel risk assessment framework that utilizes attack trees to calculate a risk score for varied VRLE threats with rate and duration of threats as inputs. We compare the impact of a well-constructed attack tree with an adhoc attack tree to study the trade-offs between overheads in managing attack trees, and the cost of risk mitigation when vulnerabilities are identified. We use a vSocial VRLE testbed in a case study to showcase the effectiveness of our framework and demonstrate how a suitable attack tree formalism can result in a more safer, privacy-preserving and secure VRLE system.
Ischaemic and haemorrhagic stroke in the dog.

Cerebrovascular disease results from any pathological process of the blood vessels supplying the brain. Stroke, characterised by its abrupt onset, is the third leading cause of death in humans. This rare condition in dogs is increasingly being recognised with the advent of advanced diagnostic imaging. Magnetic resonance imaging (MRI) is the first choice diagnostic tool for stroke, particularly using diffusion-weighted images and magnetic resonance angiography for ischaemic stroke and gradient echo sequences for haemorrhagic stroke. An underlying cause is not always identified in either humans or dogs. Underlying conditions that may be associated with canine stroke include hypothyroidism, neoplasia, sepsis, hypertension, parasites, vascular malformation and coagulopathy. Treatment is mainly supportive and recovery often occurs within a few weeks. The prognosis is usually good if no underlying disease is found.
Online Model Based Estimation of Complete Joint Stiffness of Human Arm

The endpoint stiffness of the human arm has been long recognized as a key component ensuring the quasi-static stability of the arm physical interactions with the external world. Similarly, the understanding of the joint stiffness behavior can provide complementary insights, e.g., on the underlying stiffness regulation principles across different joints including the nullspace stiffness profiles. Traditionally, the experimental modeling and estimation of the human arm joint stiffness is achieved by the transformation of the identified arm endpoint stiffness to the joint coordinates. Due to the underlying kinematic redundancy, the obtained joint stiffness matrix is rank-deficient which implies that the information in the joint stiffness matrix is incomplete. While in robotics applications this issue can be addressed by designing a desired nullspace stiffness behavior through appropriate projections, the use of a similar technique in the identification of human joint stiffness profile is meaningless. Hence, the first objective of this work is to address this issue by developing a novel technique to identify the complete and physiologically meaningful joint stiffness of human arm. Second, we present a model-based online estimation technique to estimate the seven-dimensional complete joint stiffness in various arm poses and activation levels of the two dominant arm muscles that correspond to the geometric and volume modifications of the joint stiffness profile, respectively.
Turkish sign language alphabet translator

This study aims to facilitate communication of deaf and dumb people by means of a data glove. The Turkish Sign Language translator glove is designed as a portable, low-cost and user-friendly system. The glove is equipped with flexible sensors to detect finger movements and a gyroscope to detect hand motion. The data from the sensors is analyzed with a microcontroller and 18 letters of the Turkish alphabet are successfully obtained. The Turkish Sign Language requires the use of both hands, however, this work aims to detect the entire alphabet with a single glove.
Five generations in the nursing workforce: implications for nursing professional development.

Positive patient outcomes require effective teamwork, communication, and technological literacy. These skills vary among the unprecedented five generations in the nursing workforce, spanning the "Silent Generation" nurses deferring retirement to the newest "iGeneration." Nursing professional development educators must understand generational differences; address communication, information technology, and team-building competencies across generations; and promote integration of learner-centered strategies into professional development activities.
Performance Comparison Between Surface-Mounted and Interior PM Motor Drives for Electric Vehicle Application

Electric vehicles make use of permanent-magnet (PM) synchronous traction motors for their high torque density and efficiency. A comparison between interior PM and surface-mounted PM (SPM) motors is carried out, in terms of performance at given inverter ratings. The results of the analysis, based on a simplified analytical model and confirmed by finite element (FE) analysis, show that the two motors have similar rated power but that the SPM motor has barely no overload capability, independently of the available inverter current. Moreover, the loss behavior of the two motors is rather different in the various operating ranges with the SPM one better at low speed due to short end connections but penalized at high speed by the need of a significant deexcitation current. The analysis is validated through FE simulation of two actual motor designs.
Design of a Cyber Threat Information Collection System for Cyber Attack Correlation

Nowadays, the number of cyber threats is increasing continuously, and attack techniques are becoming increasingly advanced and intelligent. One important thing that should be noted with regard to this situation is the marked increase in similar cyber incidents which use the same IP, domain, and malicious code for one cyberattack. Therefore, it is essential to understand the correlation between cyberattacks that occur due to the re-use of the same attack infrastructure (IP, domain, malicious code, etc.) for different cyberattacks, in order to detect and respond promptly to similar cyberattacks. To understand the correlation between cyberattacks, it is necessary to collect the related data concerning the procedures and techniques of cyberattacks. This paper proposes the design details of the cyber threat information collection system according to such needs. The proposed system performs the function of collecting the attack infrastructure data (IoCs) exploited for the cyberattack from various open data sources (OSINT, Open Source INTelligence), and uses the collected data as an input value to collect more data recursively. The relationship of the collected data can also be collected, saved, and managed, so that the data can be used to analyze the collection of cyberattacks. The proposed system uses a virtualization structure and distributed processing technology to collect data stably from various collection channels.
Accelerometer-Based Hand Gesture Recognition by Neural Network and Similarity Matching

In this paper, we present an accelerometer-based pen-type sensing device and a user-independent hand gesture recognition algorithm. Users can hold the device to perform hand gestures with their preferred handheld styles. Gestures in our system are divided into two types: the basic gesture and the complex gesture, which can be represented as a basic gesture sequence. A dictionary of 24 gestures, including 8 basic gestures and 16 complex gestures, is defined. An effective segmentation algorithm is developed to identify individual basic gesture motion intervals automatically. Through segmentation, each complex gesture is segmented into several basic gestures. Based on the kinematics characteristics of the basic gesture, 25 features are extracted to train the feedforward neural network model. For basic gesture recognition, the input gestures are classified directly by the feedforward neural network classifier. Nevertheless, the input complex gestures go through an additional similarity matching procedure to identify the most similar sequences. The proposed recognition algorithm achieves almost perfect user-dependent and user-independent recognition accuracies for both basic and complex gestures. Experimental results based on 5 subjects, totaling 1600 trajectories, have successfully validated the effectiveness of the feedforward neural network and similarity matching-based gesture recognition algorithm.
Exposing some important barriers to health care access in the rural USA.

To review research published before and after the passage of the Patient Protection and Affordable Care Act (2010) examining barriers in seeking or accessing health care in rural populations in the USA.



This literature review was based on a comprehensive search for all literature researching rural health care provision and access in the USA.



Pubmed, Proquest Allied Nursing and Health Literature, National Rural Health Association (NRHA) Resource Center and Google Scholar databases were searched using the Medical Subject Headings (MeSH) 'Rural Health Services' and 'Rural Health.' MeSH subtitle headings used were 'USA,' 'utilization,' 'trends' and 'supply and distribution.' Keywords added to the search parameters were 'access,' 'rural' and 'health care.' Searches in Google Scholar employed the phrases 'health care disparities in the USA,' inequalities in 'health care in the USA,' 'health care in rural USA' and 'access to health care in rural USA.' After eliminating non-relevant articles, 34 articles were included.



Significant differences in health care access between rural and urban areas exist. Reluctance to seek health care in rural areas was based on cultural and financial constraints, often compounded by a scarcity of services, a lack of trained physicians, insufficient public transport, and poor availability of broadband internet services. Rural residents were found to have poorer health, with rural areas having difficulty in attracting and retaining physicians, and maintaining health services on a par with their urban counterparts.



Rural and urban health care disparities require an ongoing program of reform with the aim to improve the provision of services, promote recruitment, training and career development of rural health care professionals, increase comprehensive health insurance coverage and engage rural residents and healthcare providers in health promotion.