nils-herrmann/clean_scirepeval huggingface dataset:
Ultrastructure and composition of Call-Exner bodies in bovine follicles

Call-Exner bodies are present in ovarian follicles of a range of species including human and rabbit, and in a range of human ovarian tumors. We have also found structures resembling Call-Exner bodies in bovine preantral and small antral follicles. Hematoxylin and eosin staining of single sections of bovine ovaries has shown that 30% of preantral follicles with more than one layer of granulosa cells and 45% of small (less than 650 μm) antral follicles have at least one Call-Exner body composed of a spherical eosinophilic region surrounded by a rosette of granulosa cells. Alcian blue stains the spherical eosinophilic region of the Call-Exner bodies. Electron microscopy has demonstrated that some Call-Exner bodies contain large aggregates of convoluted basal lamina, whereas others also contain regions of unassembled basal-lamina-like material. Individual chains of the basal lamina components type IV collagen (α1 to α5) and laminin (α1, β2 and δ1) have been immunolocalized to Call-Exner bodies in sections of fresh-frozen ovaries. Bovine Call-Exner bodies are presumably analogous to Call-Exner bodies in other species but are predominantly found in preantral and small antral follicles, rather than large antral follicles. With follicular development, the basal laminae of Call-Exner bodies change in their apparent ratio of type IV collagen to laminin, similar to changes observed in the follicular basal lamina, suggesting that these structures have a common cellular origin.
Selecting management systems for sustainable development in SMEs: A novel hybrid model based on DEMATEL, ANP, and ZOGP

In recent years, sustainable development strategy for enterprises has become an important issue around the globe. There are four management systems (i.e. ISO 9001, ISO 14001, OHSAS 18001, and SA 8000) that can help small and medium enterprises (SMEs) to create sustainable competitive advantages. In view of the fact that the shortage of resources – time, personnel, as well as money – rules most SMEs, this paper proposes a novel hybrid model for selecting optimal management systems under resource constraints, and illustrates the practical application of such a model through an example. This model first applies the Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to construct interrelations among criteria that organizations require. The second step is to obtain the criterion weights through ANP. Lastly, ANP is integrated with a zero–one goal programming (ZOGP) model to obtain optimal alternatives with desired organizational benefits by fully utilizing limited resources. The purpose of this study is to present an integrated approach that could cope with the interdependencies among various criteria and deal with the constraints on resources, and to demonstrate how to select management systems for phased implementation. Therefore, the main contribution of this paper is to enhance the capacity of SMEs to effectively address the challenge of sustainable development through a novel model of prioritizing available man-
Customer Satisfaction and Loyalty in an Online Shop : An Experiential Marketing Perspective

The rapid development of the Internet has facilitated the proliferation of online stores. How businesses can seize this enormous business opportunity and survive intense competition is an important issue. Based on strategic experiential modules (SEMs), including sense, feel, think, act, and relate, this study attempted to explore the type of experience preferred by consumers of lativ, a well-known low-cost apparel brand in Taiwan, and further examine the relationship between customer satisfaction and loyalty. Results showed that perceptions of experiential marketing differed significantly on some demographic variable; experiential marketing was positively related to customer satisfaction and customer loyalty; customer satisfaction and customer loyalty were positively related; and experiential marketing was a significant predictor of customer satisfaction and customer loyalty. The empirical results about experiential marketing were obtained from the online apparel retail industry.
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

We introduce BilBOWA (“Bilingual Bag-of-Words without Alignments”), a simple and computationally-efficient model for learning bilingual distributed representations of words which can scale to large datasets and does not require wordaligned training data. Instead it trains directly on monolingual data and extracts a bilingual signal from a smaller set of raw text sentence-aligned data. This is achieved using a novel sampled bag-of-words cross-lingual objective, which is used to regularize two noise-contrastive language models for efficient crosslingual feature learning. We show that bilingual embeddings learned using the proposed model outperforms state-of-the-art methods on a cross-lingual document classification task as well as a lexical translation task on the WMT11 data. Our code will be made available as part of the open-source word2vec toolkit.
Mott-Schottky Analysis and Impedance Spectroscopy of TiO2/6T and ZnO/6T devices.

Schottky junctions have been realized by evaporating gold spots on top of sexithiophen (6T), which is deposited on TiO 2 or ZnO with e-beam and spray pyrolysis. Using Mott-Schottky analysis of 6T/TiO2 and 6T/ZnO devices acceptor densities of 4.5x10(16) and 3.7x10(16) cm(-3) are obtained, respectively. For 6T/TiO2 deposited with the e-beam evaporation a conductivity of 9x10(-8) S cm(-1) and a charge carrier mobility of 1.2x10(-5) cm2/V s is found. Impedance spectroscopy is used to model the sample response in detail in terms of resistances and capacitances. An equivalent circuit is derived from the impedance measurements. The high-frequency data are analyzed in terms of the space-charge capacitance. In these frequencies shallow acceptor states dominate the heterojunction time constant. The high-frequency RC time constant is 8 micros. Deep acceptor states are represented by a resistance and a CPE connected in series. The equivalent circuit is validated in the potential range (from -1.2 to 0.8 V) for 6T/ZnO obtained with spray pyrolysis.
MTJ variation monitor-assisted adaptive MRAM write

Spin-transfer torque random access memory (STT-RAM) and magnetoelectric random access memory (MeRAM) are promising non-volatile memory technologies. But STT-RAM and Me RAM both suffer from high write error rate due to thermal fluctuation of magnetization. Temperature and wafer-level process variation significantly exacerbate these problems. In this paper, we propose a design that adaptively selects optimized write pulse for STT-RAM and MeRAM to overcome ambient process and temperature variation. To enable the adaptive write, we design specific MTJ-based variation monitor, which precisely senses process and temperature variation. The monitor is over 10X faster, 5X more energy-efficient, and 20X smaller compared with conventional thermal monitors of similar accuracy. With adaptive write, the write latency of STT-RAM and MeRAM cache are reduced by up to 17% and 59% respectively, and application run time is improved by up to 41%.
Multi-shape Descriptor Vehicle Classification for Urban Traffic

This paper investigates the effectiveness of state-of-the-art classification algorithms to categorise road vehicles for an urban traffic monitoring system using a multi-shape descriptor. The analysis is applied to monocular video acquired from a static pole-mounted road side CCTV camera on a busy street. Manual vehicle segmentation was used to acquire a large (>2000 sample) database of labelled vehicles from which a set of measurement-based features (MBF) in combination with a pyramid of HOG (histogram of orientation gradients, both edge and intensity based) features. These are used to classify the objects into four main vehicle categories: car, van, bus and motorcycle. Results are presented for a number of experiments that were conducted to compare support vector machines (SVM) and random forests (RF) classifiers. 10-fold cross validation has been used to evaluate the performance of the classification methods. The results demonstrate that all methods achieve a recognition rate above 95% on the dataset, with SVM consistently outperforming RF. A combination of MBF and IPHOG features gave the best performance of 99.78%.
Design & analysis of K-means algorithm for cognitive fatigue detection in vehicular driver using Respiration signal

Vehicular drivers and shift workers in industry are at most risk of handling life critical tasks. The drivers traveling long distances or when they are tired, are at risk of a meeting an accident. The early hours of the morning and the middle of the afternoon are the peak times for fatigue driven accidents. The difficulty in determining the incidence of fatigue-related accidents is due, at least in part, to the difficulty in identifying fatigue as a causal or causative factor in accidents. In this paper we propose an alternative approach for fatigue detection in vehicular drivers using Respiration (RSP) signal to reduce the losses of the lives and vehicular accidents those occur due to cognitive fatigue of the driver. We are using basic K-means algorithm with proposed two modifications as classifier for detection of Respiration signal two state fatigue data recorded from the driver. The K-means classifiers [11] were trained and tested for wavelet feature of Respiration signal. The extracted features were treated as individual decision making parameters. From test results it could be found that some of the wavelet features could fetch 100 % classification accuracy.
Development and psychometric evaluation of a three-dimensional Gambling Motives Questionnaire.

This study was designed to develop and evaluate a self-report measure of gambling motives.  A community-recruited sample of 193 gamblers (70% male; mean age = 35.5 years) were selected to fill two groups according to scores on the South Oaks Gambling Screen: probable pathological gamblers (PPG; n = 154) and non-pathological gamblers (NPG; n = 39).



Participants completed a novel 15-item measure of gambling motives called the Gambling Motives Questionnaire (GMQ), which was modeled after the original Drinking Motives Questionnaire, as well as a variety of gambling behavior and problem criterion measures.



An exploratory principal components analysis revealed three intercorrelated factors tapping enhancement (ENH), coping (COP), and social (SOC) motives, respectively. Each GMQ subscale showed good internal consistency (alphas > 0.80). The PPG group scored higher on all three scales than the NPG group, with larger differences for ENH and COP. In line with the clinical literature, PPG women scored higher than PPG men on the COP subscale but also, unexpectedly, on the SOC subscale. In concurrent validity analyses, ENH consistently predicted greater gambling behavior, and COP and ENH consistently predicted more severe gambling problems. With gambling behavior levels controlled, only COP remained a significant predictor of gambling problem severity. Finally, gender interacted with gambling motives in predicting gambling problem severity: COP predicted gambling problems more strongly in women, whereas ENH predicted gambling problems more strongly in men.



The GMQ appears to be a promising tool for both research and clinical applications with problem gamblers.
Stopped Object Detection by Learning Foreground Model in Videos

The automatic detection of objects that are abandoned or removed in a video scene is an interesting area of computer vision, with key applications in video surveillance. Forgotten or stolen luggage in train and airport stations and irregularly parked vehicles are examples that concern significant issues, such as the fight against terrorism and crime, and public safety. Both issues involve the basic task of detecting static regions in the scene. We address this problem by introducing a model-based framework to segment static foreground objects against moving foreground objects in single view sequences taken from stationary cameras. An image sequence model, obtained by learning in a self-organizing neural network image sequence variations, seen as trajectories of pixels in time, is adopted within the model-based framework. Experimental results on real video sequences and comparisons with existing approaches show the accuracy of the proposed stopped object detection approach.
Modal Space: A Physics-Based Model for Sequential Estimation of Time-Varying Shape from Monocular Video

This paper describes two sequential methods for recovering the camera pose together with the 3D shape of highly deformable surfaces from a monocular video. The nonrigid 3D shape is modeled as a linear combination of mode shapes with time-varying weights that define the shape at each frame and are estimated on-the-fly. The low-rank constraint is combined with standard smoothness priors to optimize the model parameters over a sliding window of image frames. We propose to obtain a physics-based shape basis using the initial frames on the video to code the time-varying shape along the sequence, reducing the problem from trilinear to bilinear. To this end, the 3D shape is discretized by means of a soup of elastic triangular finite elements where we apply a force balance equation. This equation is solved using modal analysis via a simple eigenvalue problem to obtain a shape basis that encodes the modes of deformation. Even though this strategy can be applied in a wide variety of scenarios, when the observations are denser, the solution can become prohibitive in terms of computational load. We avoid this limitation by proposing two efficient coarse-to-fine approaches that allow us to easily deal with dense 3D surfaces. This results in a scalable solution that estimates a small number of parameters per frame and could potentially run in real time. We show results on both synthetic and real videos with ground truth 3D data, while robustly dealing with artifacts such as noise and missing data.
Wideband 3 dB Branch Line Coupler Based on $\lambda/4$ Open Circuited Coupled Lines

This letter introduces a new 3 dB branch line coupler for wideband applications. The wideband matching property of the coupler with four λ/4 open circuited coupled lines is briefly derived. The coupler with a suspended microstrip and microstrip line structures has been simulated with HFSS and fabricated. Measurement results show insertion loss better than 3.6 dB with a power imbalance of 0.5 dB; return loss and isolation characteristics both better than 20 dB over 49% fractional bandwidth.
Heart rhythm monitoring system and IoT device for people with heart problems

This paper describes the design and implementation of a prototype of a mobile real time heart rate monitoring system, in order to get a preventive or detective control of the status of a person who had been diagnosed a heart disease. The system combines a mobile wearable device that senses cardiac rhythm and identify the geographical location of a person, then transmits by GPRS (General Packet Radio Service) technology to a web service where a web application stores, interprets, presents the data and notifies an unusual behavior.
Distribution, morphological and histochemical characteristics of foliar trichomes of Plectranthus zuluensis (Lamiaceae)

There are problems in the delimitation/identification of Plectranthus species and this investigation aims to contribute toward solving such problems through structural and histochemical study of the trichomes. Considering the importance of P. zuluensis as restricted to semi-coastal forests of Natal that possess only two fertile stamens not four as the other species of this genus. The objective of this work was to study in detail the distribution, morphology and histochemistry of the foliar trichomes of this species using light and electron microscopy. Distribution and morphology of two types of non-glandular, capitate and peltate glandular trichomes are described on both leaf sides. This study provides a description of the different secretion modes of glandular trichomes. Results of histochemical tests showed a positive reaction to terpenoids, lipids, polysaccharides and phenolics in the glandular trichomes. We demonstrated that the presence, types and structure of glandular and non-glandular trichomes are important systematic criteria for the species delimitation in the genus.
Digital reading: An overview

Digital reading is an important research topic in contemporary information science research. This paper aims to provide a snapshot of major studies on digital reading over the past few years.  This paper begins by introducing the background in digital reading, then outlines major research findings.  The paper demonstrates the growth of interest in information science and other disciplines in digital reading behavior. Five areas are highlighted: Digital reading behavior, print vs. digital, preference for reading medium, multi-tasking and learning, and technological advancement and traditional attachment.  Only major studies in the North American and European countries are covered.  Understanding reading behavior in the digital environment would help develop more effective reading devices and empower readers in the online environment.  The paper represents a first attempt to compare, evaluate, and synthesize recent studies on digital reading. Implications for the changes in reading behavior are discussed, and directions for future research are suggested.
Cloud authorization: exploring techniques and approach towards effective access control framework

Despite the various attractive features that Cloud has to offer, the rate of Cloud migration is rather slow, primarily due to the serious security and privacy issues that exist in the paradigm. One of the main problems in this regard is that of authorization in the Cloud environment, which is the focus of our research. In this paper, we present a systematic analysis of the existing authorization solutions in Cloud and evaluate their effectiveness against well-established industrial standards that conform to the unique access control requirements in the domain. Our analysis can benefit organizations by helping them decide the best authorization technique for deployment in Cloud; a case study along with simulation results is also presented to illustrate the procedure of using our qualitative analysis for the selection of an appropriate technique, as per Cloud consumer requirements. From the results of this evaluation, we derive the general shortcomings of the extant access control techniques that are keeping them from providing successful authorization and, therefore, widely adopted by the Cloud community. To that end, we enumerate the features an ideal access control mechanisms for the Cloud should have, and combine them to suggest the ultimate solution to this major security challenge — access control as a service (ACaaS) for the software as a service (SaaS) layer. We conclude that a meticulous research is needed to incorporate the identified authorization features into a generic ACaaS framework that should be adequate for providing high level of extensibility and security by integrating multiple access control models.
Gaze vs. Mouse: A Fast and Accurate Gaze-Only Click Alternative

Eye gaze tracking is a promising input method which is gradually finding its way into the mainstream. An obvious question to arise is whether it can be used for point-and-click tasks, as an alternative for mouse or touch. Pointing with gaze is both fast and natural, although its accuracy is limited. There are still technical challenges with gaze tracking, as well as inherent physiological limitations. Furthermore, providing an alternative to clicking is challenging.
 We are considering use cases where input based purely on gaze is desired, and the click targets are discrete user interface (UI) elements which are too small to be reliably resolved by gaze alone, e.g., links in hypertext. We present Actigaze, a new gaze-only click alternative which is fast and accurate for this scenario. A clickable user interface element is selected by dwelling on one of a set of confirm buttons, based on two main design contributions: First, the confirm buttons stay on fixed positions with easily distinguishable visual identifiers such as colors, enabling procedural learning of the confirm button position. Secondly, UI elements are associated with confirm buttons through the visual identifiers in a way which minimizes the likelihood of inadvertent clicks. We evaluate two variants of the proposed click alternative, comparing them against the mouse and another gaze-only click alternative.
A survey on optical character recognition for Bangla and Devanagari scripts

The past few decades have witnessed an intensive research on optical character recognition (OCR) for Roman, Chinese, and Japanese scripts. A lot of work has been also reported on OCR efforts for various Indian scripts, like Devanagari, Bangla, Oriya, Tamil, Telugu, Malayalam, Kannada, Gurmukhi, Gujarati, etc. In this paper, we present a review of OCR work on Indian scripts, mainly on Bangla and Devanagari—the two most popular scripts in India. We have summarized most of the published papers on this topic and have also analysed the various methodologies and their reported results. Future directions of research in OCR for Indian scripts have been also given.
Wireless communications with unmanned aerial vehicles: opportunities and challenges

Wireless communication systems that include unmanned aerial vehicles promise to provide cost-effective wireless connectivity for devices without infrastructure coverage. Compared to terrestrial communications or those based on high-altitude platforms, on-demand wireless systems with low-altitude UAVs are in general faster to deploy, more flexibly reconfigured, and likely to have better communication channels due to the presence of short-range line-of-sight links. However, the utilization of highly mobile and energy-constrained UAVs for wireless communications also introduces many new challenges. In this article, we provide an overview of UAV-aided wireless communications, by introducing the basic networking architecture and main channel characteristics, highlighting the key design considerations as well as the new opportunities to be exploited.
dRBAC: Distributed Role-based Access Control for Dynamic Coalition Environments

Distributed Role-Based Access Control (dRBAC) is a scalable, decentralized trust-management and access-control mechanism for systems that span multiple administrative domains. dRBAC represents controlled actions in terms of roles, which are defined within the trust domain of one entity and can be transitively delegated to other roles within a different trust domain. dRBAC utilizes PKI to identify all entities engaged in trust-sensitive operations and to validate delegation certificates. The mapping of roles to authorized name spaces obviates the need to identify additional policy roots. dRBAC distinguishes itself from previous trust management and role-based access control approaches in its support for three features: (1) third-party delegations , which improve expressiveness by allowing an entity to delegate roles outside its namespace when authorized by an explicit delegation of assignment ; (2) valued attributes , which modulate transferred access rights via mechanisms that assign and manipulate numerical values associated with roles; and (3) credential subscriptions , which enable continuous monitoring of established trust relationships using a pub/sub infrastructure to track the status of revocable credentials. This paper describes the dRBAC model, its scalable implementation using a graph-based model of credential discovery and validation, and its application in a larger security context.