LLukas22/scidocs huggingface dataset:
The impact of corporate reputation on brand attitude and purchase intention

Introduction Researchers have agreed that a favorable corporate reputation is one of the most important intangible assets driving company performance (Chun 2005; Fisher-Buttinger and Vallaster 2011; Gibson et al. 2006). Not to be confused with brand identity and image, corporate reputation is often defined as consumers’ accumulated opinions, perceptions, and attitudes towards the company (Fombrun et al. 2000; Fombrun and Shanley 1990; Hatch and Schultz 2001; Weigelt and Camerer 1988). In addition, corporate reputation is established by individuals’ relative perspective; thus, corporate reputation is closely linked to the consumers’ subjective evaluation about the company (Fombrun and Shanley 1990; Weigelt and Camerer 1988). The effect of corporate reputation on corporate performance has been supported in many articles. Earlier studies have reported that a positive reputation has a significant Abstract
A New Low-Cost Hybrid Switched Reluctance Motor for Adjustable-Speed Pump Applications

This paper presents a new low-cost hybrid switched reluctance (HSR) motor intended for use in adjustable-speed pump drive systems. The motor is a single-phase motor, driven by a unipolar converter, which uses both the reluctance torque and the permanent magnet interaction torque. Compared with conventional single-phase switched reluctance motors, it has an increased torque density. The cogging torque is beneficially used in this motor for reducing the torque ripple. It is demonstrated that such a motor drive system can be a suitable candidate to advantageously compete with the existing motor drive systems for low-cost applications. Finite-element models are used to analyze and predict the motor's performance. The proposed motor drive system has been fabricated, and its performance has been tested in the laboratory. These experimental results are also presented.
Correlated neuronal activity and the flow of neural information

For years we have known that cortical neurons collectively have synchronous or oscillatory patterns of activity, the frequencies and temporal dynamics of which are associated with distinct behavioural states. Although the function of these oscillations has remained obscure, recent experimental and theoretical results indicate that correlated fluctuations might be important for cortical processes, such as attention, that control the flow of information in the brain.
Deep Convolutional Framelets: A General Deep Learning for Inverse Problems

Recently, deep learning approaches with various network architectures have achieved significant performance improvement over existing iterative reconstruction methods in various imaging problems. However, it is still unclear why these deep learning architectures work for specific inverse problems. Moreover, unlike the usual evolution of signal processing theory around the classical theories, the link between the deep learning and the classical signal processing approaches such as wavelet, non-local processing, compressed sensing, etc, is still not well understood, which often makes signal processors in deep troubles. To address these issues, here we show that the long-searched-for missing link is the convolutional framelet for representing a signal by convolving local and non-local bases. The convolutional framelets was originally developed to generalize the recent theory of low-rank Hankel matrix approaches, and this paper significantly extends the idea to derive a deep neural network using multi-layer convolutional framelets with perfect reconstruction (PR) under rectified linear unit (ReLU) nonlinearity. Our analysis also shows that the popular deep network components such as residual block, redundant filter channels, and concatenated ReLU (CReLU) indeed help to achieve the PR, while the pooling and unpooling layers should be augmented with multi-resolution convolutional framelets to achieve PR condition. This discovery reveals the limitations of many existing deep learning architectures for inverse problems, and leads us to propose a novel deep convolutional framelets neural network. Using numerical experiments with sparse view x-ray computed tomography (CT), we demonstrated that our deep convolution framelets network shows consistent improvement over existing deep architectures at all downsampling factors. This discovery suggests that the success of deep learning is not from a magical power of a black-box, but rather comes from the power of a novel signal representation using non-local basis combined with data-driven local basis, which is indeed a natural extension of classical signal processing theory. Index Terms Convolutional framelets, deep learning, inverse problems, ReLU, perfect reconstruction condition Correspondence to: Jong Chul Ye, Ph.D KAIST Endowed Chair Professor Department of Bio and Brain Engineering Department of Mathematical Sciences Korea Advanced Institute of Science and Technology (KAIST) 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea Tel: +82-42-350-4320 Email: jong.ye@kaist.ac.kr J.C. Ye and Y. S. Han are with the Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea (e-mail: {jong.ye,hanyoseob}@kaist.ac.kr). ar X iv :1 70 7. 00 37 2v 1 [ st at .M L ] 3 J ul 2 01 7
DESIGN OF COMPACT WIDEBAND MEANDERING LOOP ANTENNA WITH A MONOPOLE FEED FOR WIRELESS APPLICATIONS

A novel compact wideband printed loop antenna is presented for wireless applications. The wideband characteristic is achieved by combining three different loop resonant modes of the antenna. The antenna geometry is simple and consists of a rectangular meandering loop, a coplanar waveguide (CPW) structure, and a monopole feed. This proposed antenna has the dimension of only 27×20×1 mm3 while operates at a wideband from 2.4 GHz to 5.9 GHz (84.3%) with stable gain, radiation pattern and vertical linear polarization. This antenna is suitable for WLAN and future 5G sub-6GHz spectrum communications. Good agreement between the simulation and measurement is obtained.
An effective treatment for cerebral hemorrhage: minimally invasive craniopuncture combined with urokinase infusion therapy.

OBJECTIVES
To evaluate and compare the curative effect between the minimally invasive craniopuncture combined with urokinase infusion therapy and the clearance of hematoma by craniotomy with small bone flap in treating patients with 30-80 ml hemorrhage in the basal ganglion part of the brain.


METHODS
A multicenter, randomized control clinical trial was undertaken; it comprised of 22 hospitals in China. Three hundred and four patients with hemorrhage in the basal ganglion were randomly assigned to receive the craniopuncture combined with urokinase infusion therapy (n=159) or clearance of hematoma by craniotomy with small bone flap treatment (n=145). The main indexes of evaluation were the neurological impairment degree at day 14 after treatment, activities of daily living at day 90 and the case fatality by 90 days.


RESULTS
The main results were as follows: (1) there was a significant difference in favorable outcomes (Barthel index >or=95) between the two groups (chi(2)=3.95, p<0.05), which showed a better prognosis in the craniopuncture group, although there was no significant difference in improving the neurological functions and activities of daily living at day 90; (2) there was a remarkable decrease in case fatality by 90 days in the cranipuncture group, with statistically significant difference between the two groups (chi(2)=5.35, p=0.02); (3) the re-bleeding rate in cranipuncture group was 8.8%, significantly (chi(2)=9.51, p=0.002) lower than 21.4% in the craniotomy group.


CONCLUSION
The craniopuncture combined with urokinase infusion therapy could reduce the rate of re-bleeding after surgery and the case fatality by 90 days. It also could improve the activities of daily living (Barthel index >or=95) at day 90. Thus, this therapy was a safe and practical technique in treating cerebral hemorrhage (30-80 ml), especially suitable for hospitals in rural areas or developing countries.
Using mobile devices to leverage student access to collaboratively-generated resources: A case of WhatsApp instant messaging at a South African University

WhatsApp instant messaging has potential to bridge information divides between educators and students. Its capacity to create personalised environments was harnessed to share collectively generated educational resources among previously disadvantaged students (PDS) students at a South African university. Data analysis combined mobile instant messagingmediated (WhatsApp) interactions among students and educators and student evaluations of WhatsApp‟s value using blogs. Results suggest that students conceived WhatsApp as a lever for bridging access to peer-generated resources, heightening on-task behaviour and promoting meaningful context-free learning.
Predictors of the discharge dosage of an atypical antipsychotic agent among hospitalized, treatment-naive, first-episode psychosis patients in naturalistic, public-sector settings.

OBJECTIVE
Little is known about determinants of second-generation antipsychotic dosages during initial hospitalization of first-episode psychosis. This study examined potential predictors of dosage of an atypical antipsychotic agent, risperidone, at hospital discharge after initial evaluation and treatment of first-episode nonaffective psychosis in 3 naturalistic, public-sector treatment settings.


METHODS
The number of psychotropic agents prescribed and discharge antipsychotic dosage were abstracted from the medical record. Demographic and extensive clinical characteristics were assessed through a clinical research study conducted at the 3 sites. One-way analyses of variance, trend tests using specific linear combinations of estimates, and χ² tests assessed for associations between atypical antipsychotic dosage and 5 hypothesized predictors, as well as 12 exploratory variables.


RESULTS
Among 155 hospitalized first-episode patients, 121 (78.1%) were discharged on risperidone, and subsequent analyses focused on that subset. The mean risperidone dosage among those 121 patients was 4.26 mg; 31 received 1 to 2 mg, 45 received 3 to 4 mg, 37 received 5 to 6 mg, and 8 received more than 6 mg. Analyses suggested that older age at hospitalization, the number of psychotropic agents prescribed, excited symptoms, and premorbid social functioning may be predictors of the discharge dosage.


CONCLUSIONS
Although several factors emerged, in general, predictors of discharge dosages of second-generation agents, here exemplified by risperidone, in real-world practice settings remain to be clarified. Given the importance of antipsychotic initiation during first hospitalization, future research should test an even broader array of potential predictors.
Body shape by 3-D photonic scanning in Thai and UK adults: comparison of national sizing surveys

Background:Body mass index (BMI) cut-offs associated with increased risk of diabetes and cardiovascular disease differ between European and Asian populations, and among Asian populations. Within-population and ethnic variability in body shape has likewise been linked with variability in cardiovascular risk in western settings.Objectives:To explore differences between Thai and White UK adults in body shape and its associations with height, age and BMI.Methods:Data on weight and body shape by 3-D photonic scanning from National Sizing Surveys of UK (3542 men, 4130 women) and Thai (5889 men, 6499 women) adults aged 16–90 years, using a common protocol and methodology, were analysed.Results:Thai adults in both sexes had significantly smaller body girths than UK adults after adjusting for age and height. Matching for BMI, and adjusting for height and age, Thais in both sexes tended to have similar or greater limb girths, but significantly smaller torso girths (especially waist and hip) than UK individuals. These results were replicated within narrow BMI bands at ∼20 and ∼25 kg m−2. Shape-age associations also differed between the populations.Discussion:Young Thai adults have a significantly slighter physique than White UK adults, with a less central distribution of body weight. However these differences reduce with age, especially in males. The 3-D photonic scanning provides detailed digital anthropometric data capable of monitoring between- and within-individual shape variability. The technology merits further application to investigate whether variability in body shape is more sensitive to metabolic risk than BMI within and between-populations.
Security in multi-tenancy cloud

Cloud computing creates exciting opportunities like reduced costs and flexibility to the users. It also comprises of some risks like data security within the cloud. Several common security threats like data leakage, insecure API's, and malicious inside users are applicable to cloud computing environment as well. In this paper, the authors consider a cloud computing service where multiple Virtual Machines (VM's) are co-located on the same physical server. In such systems, physical resources are transparently shared by the VMs belonging to multiple users. In systems like these, a malicious user having control of a VM can try to gain control over other VM's resources or utilize all system resources leading to denial of resource attack over other VM users. A malicious user can also try to steal the data of other users located on the same server by compromising hypervisor file system (logical volumes). In this paper, security threats associated with cloud computing environment are evaluated. Authors also explore how such co-existent of VM's can be exploited to gain access over other user's data or deny service and propose constructive security measures that can be deployed to avoid such attacks.
The factor structure of the PHQ-9 in palliative care.

OBJECTIVES
The Primary Care Evaluation of Mental Disorders Patient Health Questionnaire (PRIME-MD PHQ-9) is a common screening tool designed to facilitate detection of depression according to DSM-IV criteria. However, the factor structure of the PHQ-9 within the palliative care population has not been evaluated.


METHODS
300 participants completed the PHQ-9 within one week of referral to a palliative care service. Participants completed the PHQ-9 again four weeks later (n=213). Confirmatory factor analysis (CFA) and multiple-group CFA were undertaken to test the factor structure of the PHQ-9 and evaluate model invariance over time.


RESULTS
A two-factor model comprising somatic and cognitive-affective latent factors provided the best fit to the data. Multiple-group CFA suggested model invariance over time. Structural equation modelling revealed that follow-up (time 2) cognitive-affective and somatic symptoms were predicted by their baseline (time 1) factors.


CONCLUSIONS
The PHQ-9 measures two stable depression factors (cognitive-affective and somatic) within the palliative care population. Studies are now required to examine the trajectories of these symptoms over time in relation to clinical intervention and events.
Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

UNLABELLED
The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data.


AVAILABILITY AND IMPLEMENTATION
Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl.
Variable On-time Control of the Critical Conduction Mode Boost Power Factor Correction Converter to Improve Zero-crossing Distortion

The critical conduction mode boost power factor correction converter operating at the boundary of continuous conduction mode and discontinuous conduction mode has been widely used in low power application. But in many applications, it is hard to make the total harmonic distortion(THD) less than 10% when the input line voltage is very high. The increase of THD comes from the zero-crossing distortion near the ac line zero crossing point. In this paper, the reason of the zero-crossing distortion is investigated and a new variable on-time control method is proposed to improve THD. The proposed method uses the voltage mode PWM changing the ramp slope according to the ac line voltage to control the switch on-time. The performance was verified with a 100W boost PFC converter. Using the proposed method, THD improved greatly and was lower than 10% even the load was half of the full load.
Mixed-Initiative Design of Game Levels: Integrating Mission and Space into Level Generation

A level designer typically creates the levels of a game to cater for a certain set of objectives, or mission. But in procedural content generation, it is common to treat the creation of missions and the generation of levels as two separate concerns. This often leads to generic levels that allow for various missions. However, this also creates a generic impression for the player, because the potential for synergy between the objectives and the level is not utilised. Following up on the mission-space generation concept, as described by Dormans [5], we explore the possibilities of procedurally generating a level from a designer-made mission. We use a generative grammar to transform a mission into a level in a mixed-initiative design setting. We provide two case studies, dungeon levels for a rogue-like game, and platformer levels for a metroidvania game. The generators differ in the way they use the mission to generate the space, but are created with the same tool for content generation based on model transformations. We discuss the differences between the two generation processes and compare it with a parameterized approach.
Antenna Module with New Wideband 5G-Antenna Array at 28 GHz in Combination with GNSS- and 4G/WLAN/DSRC in Automotive Environment

A new 5G-antenna module is presented consisting of a four radiator multiple input multiple output (MIMO) wideband antenna array at 24.25 – 29.5 GHz in combination with a 4G/WLAN/DSRC antenna at 0.7 – 6 GHz in close proximity. Additionally the antenna array is enclosed by a ring antenna for GNSS-satellite reception at Ll-band. The antenna array provides a wideband behaviour with an input reflection coefficient better than −10 dB in the complete frequency range and an omnidirectional behaviour with slight priority to driving- and back direction. Results of the 5G antenna are shown by measurement and simulation. Also in combination with the 4G/WLAN/DSRC antenna and a GNSS scarabaeus antenna surrounding the array, the 5G-antenna keeps its performance, showing also low mutual coupling of all the antenna elements.
Efficient reverse k-nearest neighbor estimation

The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing attention recently. Many industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces where the data objects are not Euclidean and only a metric distance function is given for specifying object similarity. Usually, these applications need a solution for the generalized problem where the value of k is not known in advance and may change from query to query. In addition, many applications require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate a fast answer with high recall. In this paper, we propose the first approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach uses the advantages of existing metric index structures but proposes to use an approximation of the nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall. In den letzten Jahren hat das Reverse k-Nearest Neighbor (RkNN) Problem eine vermehrte Aufmerksamkeit erfahren. Ziel ist es, alle Objekte in einer Datenbank zu finden, in deren k-nächster Nachbarumgebung ein gegebenes Anfrageobjekt enthalten ist. Viele industrielle und wissenschaftliche Anwendungen benötigen Lösungen des RkNN-Problems für beliebige metrische Räume. Dabei sind die Datenobjekte nicht mehr notwendigerweise euklidisch, die Ähnlichkeit dery Objekte wird lediglich durch eine metrische Distanzfunktion beschrieben. Üblicherweise benötigen diese Anwendungen eine Lösung für das verallgemeinerte RkNN-Problem, bei dem der Wert von k im voraus unbekannt ist und sich außerdem von Anfrage zu Anfrage ändern kann. Zusätzlich erfordern viele Applikationen eine schnelle, näherungsweise Antwort auf RkNN-Anfragen. In diesen Fällen ist es von besonderer Wichtigkeit, schnell eine Antwort mit hohem Recall zurückzuliefern. Wir schlagen den ersten Ansatz für eine effiziente, näherungsweise RkNN-Suche in beliebigen metrischen Räumen vor, wobei der Wert von k erst zur Anfragezeit angegeben werden muss. Unser Verfahren baut auf den Vorteilen existierender metrischer Indexstrukturen auf und verwendet eine Abschätzung der Nächsten-Nachbar-Distanzen, um den Suchraum zu beschränken. Wir zeigen, dass die von uns entwickelte Lösung signifikant besser skaliert als existierende nicht-approximative Verfahren und unsere Antwortmenge einen hohen Recall aufweist.