Miracle-dz/UniFAR-FTUs huggingface dataset:
Defining Neuromarketing: Practices and Professional Challenges

&NA; Neuromarketing has recently generated controversies concerning the involvement of medical professionals, and many key questions remain—ones that have potentially important implications for the field of psychiatry. Conflicting definitions of neuromarketing have been proposed, and little is known about the actual practices of companies, physicians, and scientists involved in its practice. This article reviews the history of neuromarketing and uses an exploratory survey of neuromarketing Web sites to illustrate ethical issues raised by this new field. Neuromarketing, as currently practiced, is heterogeneous, as companies are offering a variety of technologies. Many companies employ academicians and professionals, but few list their clients or fees. Media coverage of neuromarketing appears disproportionately high compared to the paucity of peer‐reviewed reports in the field. Companies may be making premature claims about the power of neuroscience to predict consumer behavior. Overall, neuromarketing has important implications for academic‐industrial partnerships, the responsible conduct of research, and the public understanding of the brain. We explore these themes to uncover issues relevant to professional ethics, research, and policy. Of particular relevance to psychiatry, neuromarketing may be seen as an extension of the search for quantification and certainty in previously indefinite aspects of human behavior.
Hepatitis C virus infection in southwestern Saudi Arabia: Are we still in the plateau phase?

The aim was to study the seroprevalence of Hepatitis C virus (HCV) infection and related risk factors in Aseer region in southwestern Saudi Arabia, the region known to be of the highest endemicity of viral hepatitis. In a cross‐sectional study, all participants were interviewed using structured questionnaire. HCV infection was diagnosed using fourth‐generation ELISA. All positive and equivocal HCV serology results were further confirmed by using a qualitative confirmatory RT‐PCR. The study enrolled 10,234 participants. A seroprevalence of 2.2% (95%CI: 1.9–2.5%) was found. In multivariate logistic regression analysis, the study showed that males had significantly more risk to become seropositive for HCV (aOR = 1.437, 95%CI: 1.071–1.927) compared to females. Similarly, participants having history of blood transfusion had more than two times the risk of becoming seropositive for HCV (aOR = 2.079, 95%CI: 1.037–4.149). HCV infection in the study area is still high in the plateau phase. It is recommended to have an active educational and media campaign about the risks of HCV infections. Workshops and training of qualified laboratory staff related to blood banking seem mandatory. J. Med. Virol. 89:867–871, 2017. © 2016 Wiley Periodicals, Inc.
R peak delineation in ECG signal based on polynomial chirplet transform using adaptive threshold

R peak delineation is fundamental step in any application implicating electrocardiogram (ECG) signal. ECG is non stationary and non linear. Hence, linear transforms like short time fourier transform, wavelet transform and chirplet transform may be inadequate to represent ECG signal and consequently for R peak delineation. Polynomial chirplet transform (PCT) models the frequency into a higher order polynomial to enhance the representation of non stationary signals whose frequency vary non linearly with time. In this paper, PCT based R peak delineation method using adaptive threshold is proposed. The performance of the proposed algorithm is evaluated on ECG ID data base taken from physionet data bank. This work also presents a comparative study of QRS detection methods employing the uni scale family of time frequency analysis methods, short time fourier transform, chirplet transform, stockwell transform, wigner ville distribution, and pseudo wigner ville distribution out of which stockwell transform, pseudo wigner ville distribution along with adaptive threshold are applied to QRS detection for the first time. The results show that the proposed method outperforms the competitors in terms of sensitivity, specificity and detection error rate.
Multiprocessing neural network simulator

Over the last few years tremendous progress has been made in neuroscience by employing simulation tools for investigating neural network behaviour. Many simulators have been created during last few decades, and their number and set of features continually grows due to persistent interest from groups of researchers and engineers. A simulation software that is able to simulate a large-scale neural network has been developed and presented in this work. Based on a highly abstract integrate-and-fire neuron model a clock-driven sequential simulator has been developed in C++. The created program is able to associate the input patterns with the output patterns. The novel biologically plausible learning mechanism uses Long Term Potentiation and Long Term Depression to change the strength of the connections between the neurons based on a global binary feedback. Later, the sequentially executed model has been extended to a multi-processor system, which executes the described learning algorithm using the event-driven technique on a parallel distributed framework, simulating a neural network asynchronously. This allows the simulation to manage larger scale neural networks being immune to processor failure and communication problems. The multi-processor neural network simulator has been created, the main benefit of which is the possibility to simulate large scale neural networks using high-parallel distributed computing. For that reason the design of the simulator has been implemented considering an efficient weight-adjusting algorithm and an efficient way for asynchronous local communication between processors.
Compact ultrafast laser pulse shaping using chirped volume Bragg gratings

The shaping of ultrafast pulses is an area of great interest in the world of laser technology, due to the multiple possibilities and applications enabled by user-defined shaped pulses. Despite the success of the several existing techniques for pulse shaping, common problems still exist, such as the large dimensions of the associated experimental setups or the sensitivity of the alignment to mechanical vibrations, which limit their use in environments outside the laboratory, such as in industrial equipment. In this work we study the feasibility of a novel alternative to the optical element that performs the spatial dispersion inside a conventional pulse modulator. Our approach consists in using a chirped volume Bragg grating, and the goal is to study the properties of the transverse spatial chirp created when a laser pulse enters on the CVBG at a given angle. We developed a simplified theoretical model that allows the calculation of the diffraction efficiency at a given depth inside the CVBG and the associated spatial chirp. Using the model, the performance was studied for several parameters of the diffraction grating and of the incident pulse. We performed a number of laboratory measurements using different experimental setups for characterizing the performance of a specific CVBG operating at 1034 nm. We compare those with the theoretical model and determine the influence of each parameter. Finally, we analyze and discuss the future possibilities and limitations for the use of CVBG ultra-short pulse shaping.
Interaction design for nomadic devices in highly automated vehicles

Following the roadmaps of (inter)national committees, highly automated driving will be available in the next decade in production vehicles. This technology allows the driver to do some other tasks while driving and to remain only as a fallback in situations the automation is not capable to handle. This study tested if nomadic devices, that drivers might use while driving highly automated, can be integrated to support the driver in taking over control when requested. 33 drivers participated in a simulator study and drove in a highly automated vehicle on a motorway. The results showed that the takeover performance of drivers improve if the takeover request is displayed additionally on the nomadic device. Therefore, the integration of additional interfaces such as smartphones into a holistic interaction concept may be a key aspect for designing a secure and comfortable takeover process.
The protein phosphatase 2A B56γ regulatory subunit is required for heart development

Background: Protein Phosphatase 2A (PP2A) function is controlled by regulatory subunits that modulate the activity of the catalytic subunit and direct the PP2A complex to specific intracellular locations. To study PP2A's role in signal transduction pathways that control growth and differentiation in vivo, a transgenic mouse lacking the B56γ regulatory subunit of PP2A was made. Results: Lack of PP2A activity specific to the PP2A‐B56γ holoenzyme, resulted in the formation of an incomplete ventricular septum and a decrease in the number of ventricular cardiomyocytes. During cardiac development, B56γ is expressed in the nucleus of α‐actinin‐positive cardiomyocytes that contain Z‐bands. The pattern of B56γ expression correlated with the cardiomyocyte apoptosis we observed in B56γ‐deficient mice during mid to late gestation. In addition to the cardiac phenotypes, mice lacking B56γ have a decrease in locomotive coordination and gripping strength, indicating that B56γ has a role in controlling PP2A activity required for efficient neuromuscular function. Conclusions: PP2A‐B56γ activity is required for efficient cardiomyocyte maturation and survival. The PP2A B56γ regulatory subunit controls PP2A substrate specificity in vivo in a manner that cannot be fully compensated for by other B56 subunits. Developmental Dynamics 243:778–790, 2014. © 2014 Wiley Periodicals, Inc.
Advances in Diagnosis, Surveillance, and Monitoring of Zika Virus: An Update

Zika virus (ZIKV) is associated with numerous human health-related disorders, including fetal microcephaly, neurological signs, and autoimmune disorders such as Guillain-Barré syndrome (GBS). Perceiving the ZIKA associated losses, in 2016, the World Health Organization (WHO) declared it as a global public health emergency. In consequence, an upsurge in the research on ZIKV was seen around the globe, with significant attainments over developing several effective diagnostics, drugs, therapies, and vaccines countering this life-threatening virus at an early step. State-of-art tools developed led the researchers to explore virus at the molecular level, and in-depth epidemiological investigations to understand the reason for increased pathogenicity and different clinical manifestations. These days, ZIKV infection is diagnosed based on clinical manifestations, along with serological and molecular detection tools. As, isolation of ZIKV is a tedious task; molecular assays such as reverse transcription-polymerase chain reaction (RT-PCR), real-time qRT-PCR, loop-mediated isothermal amplification (LAMP), lateral flow assays (LFAs), biosensors, nucleic acid sequence-based amplification (NASBA) tests, strand invasion-based amplification tests and immune assays like enzyme-linked immunosorbent assay (ELISA) are in-use to ascertain the ZIKV infection or Zika fever. Herein, this review highlights the recent advances in the diagnosis, surveillance, and monitoring of ZIKV. These new insights gained from the recent advances can aid in the rapid and definitive detection of this virus and/or Zika fever. The summarized information will aid the strategies to design and adopt effective prevention and control strategies to counter this viral pathogen of great public health concern.
Towards Intelligent Crowdsourcing for Audio Data Annotation: Integrating Active Learning in the Real World

In this contribution, we combine the advantages of traditional crowdsourcing with contemporary machine learning algorithms with the aim of ultimately obtaining reliable training data for audio processing in a faster, cheaper and therefore more efﬁcient manner than has been previously possible. We propose a novel crowdsourcing approach, which brings a simulated active learning annotation scenario into a real world environment creating an intelligent and gamiﬁed crowdsourcing platform for manual audio annotation. Our platform combines two active learning query strategies with an internally calculated trustability score to efﬁciently reduce manual labelling efforts. This reduction is achieved in a twofold manner: ﬁrst our system automatically decides if an instance requires annotation; second, it dynamically decides, depending on the quality of previously gathered annotations, on exactly how many annotations are needed to reliably label an instance. Results presented indicate that our approach drastically reduces the annotation load and is considerably more efﬁcient than conventional methods.
Concurrency Control in B-Trees with Batch Updates

In many applications it is important to be able to insert (or delete) keys into a B-tree as a batch, instead of inserting them one by one. Moreover, it may be necessary to search the B-tree concurrently with the batch update. An example of this is a text database system supporting a newspaper house: all words (keys) of each article obtained from a news agency should be inserted at once, and, at the same time, searches for documents containing certain words should be allowed as efficiently as possible. We have designed two solutions to the problem of concurrent batch update. The first solution-implemented in our commercial text database system-optimizes the speed of the batch update, and the second solution optimizes the average search time during the batch update.
Developing a Methodology for Online Service Failure Prevention: Reporting on an Action Design Research Project-in-Progress

The increasing use of online channels for service delivery raises new challenges in service failure prevention. This work-in-progress paper reports on the first phase of an action-design research project to develop a service failure prevention methodology. In this paper we review the literature on online services, failure prevention and failure recovery and develop a theoretical framework for online service failure prevention. This provides the theoretical grounding for the artefact (the methodology) to be developed. We use this framework to develop an initial draft of our methodology. We then outline the remaining phases of the research, and offer some initial conclusions gained from the project to date.
Fixed and Random Effects Selection in Mixed Effects Models

Summary We consider selecting both fixed and random effects in a general class of mixed effects models using maximum penalized likelihood (MPL) estimation along with the smoothly clipped absolute deviation (SCAD) and adaptive least absolute shrinkage and selection operator (ALASSO) penalty functions. The MPL estimates are shown to possess consistency and sparsity properties and asymptotic normality. A model selection criterion, called the ICQ statistic, is proposed for selecting the penalty parameters ( Ibrahim, Zhu, and Tang, 2008 , Journal of the American Statistical Association 103, 1648–1658). The variable selection procedure based on ICQ is shown to consistently select important fixed and random effects. The methodology is very general and can be applied to numerous situations involving random effects, including generalized linear mixed models. Simulation studies and a real data set from a Yale infant growth study are used to illustrate the proposed methodology.
Histomorphometric Analysis of a Biopsy Harvested 10 Years After Maxillary Sinus Augmentation With Anorganic Bovine Bone Matrix and Plasma Rich in Growth Factors: A Case Report

Purpose:To evaluate the histologic and histomorphometric data 10 years after grafting of maxillary sinus in a case using anorganic bovine bone matrix (ABBM) and plasma rich in growth factors (PRGF). Materials and Methods:Histomorphometric measures were performed for newly formed bone, ABBM particles remnants, marrow spaces, and the presence of osteoblastic and osteoclastic activity. Results:Histologic analysis showed ABBM particles surrounded by new compact and mature vital bone. Osteocytes were noted within lacunae. Some osteoblastic and osteoclastic activity could be identified. The histomorphometric results were 21.7% of newly formed bone, 33.9% of ABBM, and 44% was composed of marrow spaces. Conclusions:After 10 years postoperatively, the histologic evaluation of this case report demonstrated slow replacement of the ABBM particles by newly formed bone, even with the addition of PRGF. The residual ABBM particles were found in close contact to the newly formed bone.
Statistical Learning With Time Series Dependence: An Application to Scoring Sleep in Mice

We develop methodology that combines statistical learning methods with generalized Markov models, thereby enhancing the former to account for time series dependence. Our methodology can accommodate very general and very long-term time dependence structures in an easily estimable and computationally tractable fashion. We apply our methodology to the scoring of sleep behavior in mice. As methods currently used to score sleep in mice are expensive, invasive, and labor intensive, there is considerable interest in developing high-throughput automated systems which would allow many mice to be scored cheaply and quickly. Previous efforts at automation have been able to differentiate sleep from wakefulness, but they are unable to differentiate the rare and important state of rapid eye movement (REM) sleep from non-REM sleep. Key difficulties in detecting REM are that (i) REM is much rarer than non-REM and wakefulness, (ii) REM looks similar to non-REM in terms of the observed covariates, (iii) the data are noisy, and (iv) the data contain strong time dependence structures crucial for differentiating REM from non-REM. Our new approach (i) shows improved differentiation of REM from non-REM sleep and (ii) accurately estimates aggregate quantities of sleep in our application to video-based sleep scoring of mice. Supplementary materials for this article are available online.
Archaeology and the Ordnance Survey

The Ordnance Survey of Great Britain is now in its 167th year. Founded in 1791, it has provided a map coverage of this country which is unexcelled in its completeness and in the range of its scales. All the most important towns are now being mapped on a 1/1250 (50-in,) scale in a new survey, over 60 per cent of which have now been completed. Only a few mountainous and uninhabited regions are excluded from the 1/2500 (25-in.) scale which otherwise covers the whole country. Consequential from this scale is a further series of maps at scales of 1/10,560 (6-in.), 1/25,000 (2½-in.), 1/63,360 (1-in.), 1/126,720 (½-in.), and 1/253,440(¼-in.). Except for the north-west of Scotland the 1/25/000 (2½-in.) scale map covers the whole of the country, but the 1/126,720 (½-in.) scale has only recently been started and will take some years to complete. An unusual feature of the whole of these map series when compared with other national surveys is the attention it pays to the mapping of antiquities. This is not confined to the delineation of those ancient features which have size and bulk which make it impossible to omit them from any map. A big range of antiquities is shown. The current list shows 107 different types ranging in date from the earliest times down to the 18th century. Some, like burial mounds, are small; others, like major hill-forts or Roman town sites, cover many acres, while others of linear type like Hadrian’s Wall or Offa’s Dyke approach or exceed 100 miles in length. Apart from this kind of antiquity which can still be recognized on the ground, there are many places indicated where important finds of portable objects have been made, and the sites of battles and other historic events are shown.
Handbook of Elliptic and Hyperelliptic Curve Cryptography

Preface Introduction to Public-Key Cryptography Mathematical Background Algebraic Background Background on p-adic Numbers Background on Curves and Jacobians Varieties Over Special Fields Background on Pairings Background on Weil Descent Cohomological Background on Point Counting Elementary Arithmetic Exponentiation Integer Arithmetic Finite Field Arithmetic Arithmetic of p-adic Numbers Arithmetic of Curves Arithmetic of Elliptic Curves Arithmetic of Hyperelliptic Curves Arithmetic of Special Curves Implementation of Pairings Point Counting Point Counting on Elliptic and Hyperelliptic Curves Complex Multiplication Computation of Discrete Logarithms Generic Algorithms for Computing Discrete Logarithms Index Calculus Index Calculus for Hyperelliptic Curves Transfer of Discrete Logarithms Applications Algebraic Realizations of DL Systems Pairing-Based Cryptography Compositeness and Primality Testing-Factoring Realizations of DL Systems Fast Arithmetic Hardware Smart Cards Practical Attacks on Smart Cards Mathematical Countermeasures Against Side-Channel Attacks Random Numbers-Generation and Testing References
Reactive biped walking control for a collision of a swinging foot on uneven terrain

This paper describes a biped walking control method for a collision of a swinging foot on uneven terrain. Because a swing leg moves to a desired landing position, an unexpected collision on a terrain may be happened by a distance error between a foot and a terrain. A swing foot has to not only absorb a impact force, but also changes a trajectory as long as a swing foot contacts on a terrain. Furthermore it is required to keep a balance against a contact force. To prevent a trip over and a losing balance by contact on a terrain, two reactive key components are installed: 1) Set appropriate impedance gains of the feet according to a walking phase, 2) Update the desired landing position to the COG (Center of Gravity) pattern generation immediately as a detecting/releasing contact. In this paper, focused on a swing motion, a robust biped walking with a collision of a swinging foot on a uneven terrain is realized. The proposed method is validated through simulation results with the HRP-2 humanoid robot.