nils-herrmann/clean_scirepeval huggingface dataset:
Interneuron networks in the hippocampus

The hippocampus has contributed enormously to our understanding of the operation of elemental brain circuits, not least through the classification of forebrain interneurons. Understanding the operation of interneuron networks however requires not only a wiring diagram that describes the innervation and postsynaptic targets of different GABAergic cells, but also an appreciation of the temporal dimension. Interneurons differ extensively in their intrinsic firing rates, their recruitment in different brain rhythms, and in their synaptic kinetics. Furthermore, in common with principal neurons, both the synapses innervating interneurons and the synapses made by these cells are highly modifiable, reflecting both their recent or remote use (short-term and long-term plasticity) and the action of extracellular messengers. This review examines recent progress in understanding how different hippocampal interneuron networks contribute to feedback and feed-forward inhibition at different timescales.
Clustering Techniques and the Similarity Measures used in Clustering: A Survey

Clustering is an unsupervised learning technique which aims at grouping a set of objects into clusters so that objects in the same clusters should be similar as possible, whereas objects in one cluster should be as dissimilar as possible from objects in other clusters. Cluster analysis aims to group a collection of patterns into clusters based on similarity. A typical clustering technique uses a similarity function for comparing various data items. This paper covers the survey of various clustering techniques, the current similarity measures based on distance based clustering, explains the limitations associated with the existing clustering techniques and propose that the combination of the advantages of the existing systems can help overcome the limitations of the existing systems.
Word informativity influences acoustic duration: Effects of contextual predictability on lexical representation

Language-users reduce words in predictable contexts. Previous research indicates that reduction may be stored in lexical representation if a word is often reduced. Because representation influences production regardless of context, production should be biased by how often each word has been reduced in the speaker's prior experience. This study investigates whether speakers have a context-independent bias to reduce low-informativity words, which are usually predictable and therefore usually reduced. Content word durations were extracted from the Buckeye and Switchboard speech corpora, and analyzed for probabilistic reduction effects using a language model based on spontaneous speech in the Fisher corpus. The analysis supported the hypothesis: low-informativity words have shorter durations, even when the effects of local contextual predictability, frequency, speech rate, and several other variables are controlled for. Additional models that compared word types against only other words of the same segmental length further supported this conclusion. Words that usually appear in predictable contexts are reduced in all contexts, even those in which they are unpredictable. The result supports representational models in which reduction is stored, and where sufficiently frequent reduction biases later production. The finding provides new evidence that probabilistic reduction interacts with lexical representation.
Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks

Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.
Subjective well-being. The science of happiness and a proposal for a national index.

One area of positive psychology analyzes subjective well-being (SWB), people's cognitive and affective evaluations of their lives. Progress has been made in understanding the components of SWB, the importance of adaptation and goals to feelings of well-being, the temperament underpinnings of SWB, and the cultural influences on well-being. Representative selection of respondents, naturalistic experience sampling measures, and other methodological refinements are now used to study SWB and could be used to produce national indicators of happiness.
A 'G' chromosome banding study of three cupped oyster species: Crassostrea gigas, Crassostrea angulata and Crassostrea virginica (Mollusca: Bivalvia)

The G-banding technique was performed on chromosomes from gill tissue of three cupped oyster species: Crassostrea gigas, Crassostrea angulata and Crassostrea virginica. Identification of the ten individual chromosome pairs was obtained. Comparative analysis of G-banded karyotypes of the three species showed that their banding patterns generally resembled each other, with chromosome pair 3 being similar in all three species. However, differences from one species to another were also observed. The G-banding pattern highlighted greater similarities between C. gigas and C. angulata than between these two species and C. virginica, thus providing an additional argument for genetic divergence between these two evolutionary lineages. C. gigas and C. angulata showed a different G-banding patterns on the two arms of chromosome pair 7, which agrees with their taxonomic separation. The application of this banding technique offers a new approach to specific problems in oyster taxonomy and genetics. &copy; Inra/Elsevier, Paris chromosome / G-banding / Crassostrea gigas / Crassostrea angulata / Crassostrea
Challenges in 802.11 encryption algorithms: The need for an adaptive scheme for improved performance

Wireless LAN (WLAN), despite its popularity, is subject to various security threats. Encrypting the data being transmitted is one of the approaches to address such risks. However, encryption algorithms are known to be computationally intensive and the relation between the strength of encryption and computational intensity is inversely proportional. In this paper, we discuss the challenges in the implementation of encryption algorithm in WLAN. We then compare and analyze the results of experiments to compare these algorithms vis-a-vis their energy consumption. It will be seen that different encryption schemes are fit for different types of messages. We propose an intelligent encryption scheme for optimal security.
An Energy Efficient Full-Frame Feature Extraction Accelerator With Shift-Latch FIFO in 28 nm CMOS

This paper presents an energy-efficient feature extraction accelerator design aimed at visual navigation. The hardware-oriented algorithmic modifications such as a circular-shaped sampling region and unified description are proposed to minimize area and energy consumption while maintaining feature extraction quality. A matched-throughput accelerator employs fully-unrolled filters and single-stream descriptor enabled by algorithm-architecture co-optimization, which requires lower clock frequency for the given throughput requirement and reduces hardware cost of description processing elements. Due to the large number of FIFO blocks, a robust low-power FIFO architecture for the ultra-low voltage (ULV) regime is also proposed. This approach leverages shift-latch delay elements and balanced-leakage readout technique to achieve 62% energy savings and 37% delay reduction. We apply these techniques to a feature extraction accelerator that can process 30 fps VGA video in real time and is fabricated in 28 nm LP CMOS technology. The design consumes 2.7 mW with a clock frequency of 27 MHz at Vdd = 470 mV, providing 3.5× better energy efficiency than previous state-of-the-art while extracting features from entire image.
Failover mechanisms for distributed SDN controllers

Distributed SDN controllers have been proposed to address performance and resilience issues. While approaches for datacenters are built on strongly-consistent state sharing among controllers, others for WAN and constrained networks rely on a loosely-consistent distributed state. In this paper, we address the problem of failover for distributed SDN controllers by proposing two strategies for neighbor active controllers to take over the control of orphan OpenFlow switches: (1) a greedy incorporation and (2) a pre-partitioning among controllers. We built a prototype with distributed Floodlight controllers to evaluate these strategies. The results show that the failover duration with the greedy approach is proportional to the quantity of orphan switches while the pre-partitioning approach, introducing a very small additional control traffic, enables to react quicker in less than 200ms.
Approximation and Inapproximation for the Influence Maximization Problem in Social Networks under Deterministic Linear Threshold Model

Influence Maximization is the problem of finding a certain amount of people in a social network such that their aggregation influence through the network is maximized. In the past this problem has been widely studied under a number of different models. In 2003, Kempe \emph{et al.} gave a $(1-{1 \over e})$-approximation algorithm for the \emph{linear threshold model} and the \emph{independent cascade model}, which are the two main models in the social network analysis. In addition, Chen \emph{et al.} proved that the problem of exactly computing the influence given a seed set in the two models is $\#$P-hard. Both the \emph{linear threshold model} and the \emph{independent cascade model} are based on randomized propagation. However such information might be obtained by surveys or data mining techniques, which makes great difference on the properties of the problem. In this paper, we study the Influence Maximization problem in the \emph{deterministic linear threshold model}. As a contrast, we show that in the \emph{deterministic linear threshold model}, there is no polynomial time $n^{1-\epsilon}$-approximation unless P=NP even at the simple case that one person needs at most two active neighbors to become active. This inapproximability result is derived with self-contained proofs without using PCP theorem. In the case that a person can be activated when one of its neighbors become active, there is a polynomial time ${e\over e-1}$-approximation, and we prove it is the best possible approximation under a reasonable assumption in the complexity theory, $NP \not\subset DTIME(n^{\log\log n})$. We also show that the exact computation of the final influence given a seed set can be solved in linear time in the \emph{deterministic linear threshold model}. The Least Seed Set problem, which aims to find a seed set with least number of people to activate all the required people in a given social network, is discussed. Using an analysis framework based on Set Cover, we show a $O($log$n)$-approximation in the case that a people become active when one of its neighbors is activated.
Sentiment-Aspect Extraction based on Restricted Boltzmann Machines

Aspect extraction and sentiment analysis of reviews are both important tasks in opinion mining. We propose a novel sentiment and aspect extraction model based on Restricted Boltzmann Machines to jointly address these two tasks in an unsupervised setting. This model reflects the generation process of reviews by introducing a heterogeneous structure into the hidden layer and incorporating informative priors. Experiments show that our model outperforms previous state-of-the-art methods.
The Adaptive Place Advisor: A Conversational Recommendation System

In this paper, we describe the Adaptive Place Advi sor, a conversational recommendation system designed to he lp users decide on a destination. We view the selection of destinations a an interactive, conversational process, with the advisory system in quiring about desired item characteristics and the human responding. The user model, which contains preferences regarding items, attributes, values and v lue combinations, is also acquired during the conversation. The system enhanc es the user’s requirements with the user model and retrieves suitable items fr om a case-base. If the number of items found by the system is unsuitable (too hig h, too low) the next attribute to be constrained or relaxed is selected based on t he information gain associated with the attributes. We also describe the current s tatu of the system and future work.
An Accurate Bioimpedance Measurement System for Blood Pressure Monitoring

One potential method to estimate noninvasive cuffless blood pressure (BP) is pulse wave velocity (PWV), which can be calculated by using the distance and the transit time of the blood between two arterial sites. To obtain the pulse waveform, bioimpedance (BI) measurement is a promising approach because it continuously reflects the change in BP through the change in the arterial cross-sectional area. Many studies have investigated BI channels in a vertical direction with electrodes located along the wrist and the finger to calculate PWV and convert to BP; however, the measurement systems were relatively large in size. In order to reduce the total device size for use in a PWV-based BP smartwatch, this study proposed and examined a robust horizontal BI structure. The BI device was also designed to apply in a very small body area. The proposed structure was based on two sets of four electrodes attached around the wrist. Our model was evaluated on 15 human subjects; the PWV values were obtained with various distances between two BI channels to assess the efficacy. The results showed that the designed BI system can monitor pulse rate efficiently in only a 0.5 × 1.75 cm² area of the body. The correlation of pulse rate from the proposed design against the reference was 0.98 ± 0.07 (p < 0.001). Our structure yielded higher detection ratios for PWV measurements of 99.0 ± 2.2%, 99.0 ± 2.1%, and 94.8 ± 3.7% at 1, 2, and 3 cm between two BI channels, respectively. The measured PWVs correlated well with the BP standard device at 0.81 ± 0.08 and 0.84 ± 0.07 with low root-mean-squared-errors at 7.47 ± 2.15 mmHg and 5.17 ± 1.81 mmHg for SBP and DBP, respectively. The result demonstrates the potential of a new wearable BP smartwatch structure.
Construct validity and reliability of the Practice Environment Scale of the Nursing Work Index ( PES-NWI ) for Queensland Nurses

This article reports on construct validity and reliability of 30 items of the Practice Environment Scale of the Nursing Work Index (PES-NWI).  Australia, like other countries is experiencing a shortage of nurses and a multifactor approach to retention of nurses is required. One significant factor that has received increasing attention in the last decade, particularly in the United States is the nursing practice environment.  The reliability of the 30 items of the PES-NWI was assessed by Cronbach’s alpha and factor analysis was performed using principal component analysis.  The PES-NWI was completed by nurses working in the aged care, private and public sectors in Queensland,   A total of 3,000 were distributed to a random sample of members of the Queensland Nurses Union. Of these 1192 surveys were returned, a response rate of 40%.  The PES-NWI was shown to be reliable demonstrating internal consistency with a Cronbach’s alpha of the total scale of 0.948. The 30 items loaded onto 5 factors explaining 57.7% of the variance. The items across the factors differed slightly from those reported by the original author of the PES-NWI.  This study indicates that the PES-NWI has construct validity and reliability in the Australian setting for nurses.
Geolocation of data in the cloud

We introduce and analyze a general framework for authentically binding data to a location while providing strong assurances against cloud storage providers that (either accidentally or maliciously) attempt to re-locate cloud data. We then evaluate a preliminary solution in this framework that combines constraint-based host geolocation with proofs of data possession, called constraint-based data geolocation (CBDG). We evaluate CBDG using a combination of experiments with PlanetLab and real cloud storage services, demonstrating that we can bind fetched data to the location originally hosting it with high precision. We geolocate data hosted on the majority of our PlanetLab targets to regions no larger than 118,000 km^2, and we geolocate data hosted on Amazon S3 to an area no larger than 12,000 km^2, sufficiently small to identify the state or service region.
Blockade of insulin sensitive steady-state R-type Ca<Superscript>2</Superscript> channel by PN 200-110 in heart and vascular smooth muscle

The effect of high K-concentration, insulin and the L-type Ca 2+ channel blocker PN 200-110 on cytosolic intracellular free calcium ([Ca2+]i) was studied in single ventricular myocytes of 10-day-old embryonic chick heart, 20-week-old human fetus and rabbit aorta (VSM) single cells using the Ca2+-sensitive fluorescent dye, Fura-2 microfluorometry and digital imaging technique. Depolarization of the cell membrane of both heart and VSM cells with continuous superfusion of 30 mM [K+]o induced a rapid transient increase of [Ca2+]j that was followed by a sustained component. The early transient increase of [Ca2+]i by high [K+]o was blocked by the L-type calcium channel antagonist nifedipine. However, the sustained component was found to be insensitive to this drug. PN 200-110 another L-type Ca 2+ blocker was found to decrease both the early transient and the sustained increase of [Ca2+]i induced by depolarization of the cell membrane with high [K+]o. Insulin at a concentration of 40 to 80 tzU/rnl only produced a sustained increase of [Ca2+]i that was blocked by PN 200-110 or by lowering the extracellular Ca 2+ concentration with EGTA. The sustained increase of [Ca2+]i induced by high [K+]o or insulin was insensitive to metabolic inhibitors such as KCN and ouabain as well to the fast Na + channel blocker, tetrodotoxin and to the increase of intracellular concentrations of cyclic nucleotides. Using the patch clamp technique, insulin did not affect the L-type Ca 2+ current and the delayed outward K + current. These results suggest that the early increase of [Ca2+]i during depolarization of the cell membrane of heart and VSM cells with high [K+]o is due to the opening and decay of an L-type Ca z+ channel. However, the sustained increase of [Ca2+]i during a sustained depolarization is due to the activation of a resting (R) Ca 2+ channel that is insensitive to lowering [ATP]i and sensitive to insulin.
IntentStreams: Smart Parallel Search Streams for Branching Exploratory Search

The user's understanding of information needs and the information available in the data collection can evolve during an exploratory search session. Search systems tailored for well-defined narrow search tasks may be suboptimal for exploratory search where the user can sequentially refine the expressions of her information needs and explore alternative search directions. A major challenge for exploratory search systems design is how to support such behavior and expose the user to relevant yet novel information that can be difficult to discover by using conventional query formulation techniques. We introduce IntentStreams, a system for exploratory search that provides interactive query refinement mechanisms and parallel visualization of search streams. The system models each search stream via an intent model allowing rapid user feedback. The user interface allows swift initiation of alternative and parallel search streams by direct manipulation that does not require typing. A study with 13 participants shows that IntentStreams provides better support for branching behavior compared to a conventional search system.
Cost and Management Accounting Practices : A Survey of Manufacturing Companies

The purpose of this study is to explore cost and management accounting practices utilized by manufacturing companies operating in Istanbul, Turkey. The sample of the study consists of 61 companies, containing both small and medium-sized enterprises, and large companies. The data collection methodology of the study is questionnaire survey. The content of the questionnaire survey is based on several previous studies. The major findings of the study are as follows: the most widely used product costing method is job costing; the complexity in production poses as the highest ranking difficulty in product costing; the most widely used three overhead allocation bases are prime costs, units produced, and direct labor cost; pricing decisions is the most important area where costing information is used; overall mean of the ratio of overhead to total cost is 34.48 percent for all industries; and the most important three management accounting practices are budgeting, planning and control, and cost-volume-profit analysis. Furthermore, decreasing profitability, increasing costs and competition, and economic crises are the factors, which increase the perceived importance of cost accounting. The findings indicate that companies perceive traditional management accounting tools still important. However, new management accounting practices such as strategic planning, and transfer pricing are perceived less important than traditional ones. Therefore, companies need to improve themselves in this aspect.
Parameter Selection and Preconditioning for a Graph Form Solver

In a recent paper, Parikh and Boyd describe a method for solving a convex optimization problem, where each iteration involves evaluating a proximal operator and projection onto a subspace. In this paper we address the critical practical issues of how to select the proximal parameter in each iteration, and how to scale the original problem variables, so as the achieve reliable practical performance. The resulting method has been implemented as an open-source software package called POGS (Proximal Graph Solver), that targets multi-core and GPU-based systems, and has been tested on a wide variety of practical problems. Numerical results show that POGS can solve very large problems (with, say, more than a billion coefficients in the data), to modest accuracy in a few tens of seconds. As just one example, a radiation treatment planning problem with around 100 million coefficients in the data can be solved in a few seconds, as compared to around one hour with an interior-point method.
Measuring self-disclosure online: Blurring and non-response to sensitive items in web-based surveys

People are increasingly required to disclose personal information to computerand Internetbased systems in order to register, identify themselves or simply for the system to work as designed. In the present paper, we outline two different methods to easily measure people’s behavioral self-disclosure to web-based forms. The first, the use of an ‘I prefer not to say’ option to sensitive questions is shown to be responsive to the manipulation of level of privacy concern by increasing the salience of privacy issues, and to experimental manipulations of privacy. The second, blurring or increased ambiguity was used primarily by males in response to an income question in a high privacy condition. Implications for the study of self-disclosure in human–computer interaction and web-based research are discussed.