Miracle-dz/UniFAR-FTUs huggingface dataset:
Building the science of research management - What can research management learn from education research?

Research management is an emerging field of study and its development is significant to the advancement of research enterprise. Developing the science of research management requires investigating social mechanisms involved in research management. Yet, studies on social mechanisms of research management is lacking in the literature. To address this gap, this paper proposes importing methodologies and theories from other social science disciplines to study the social mechanisms of research management and to build the science of research management. The paper first articulates what constitutes the science of research management, then proposes to appropriate Design-Based Research (DBR), a methodology in education research, for building the science of research management while at the same time strengthening the theory-practice nexus. A study of education research is then presented to illustrate how DBR is used to enact the theory of homophily which is imported from sociology. It reveals an opportunity to use social designs to develop social relationships among teachers from different schools for networked learning. Such a research endeavour also has potential to advance theories of relationship-building in sociology. Inferring from the example as an analogue to what is suggested for research management, the paper advocates a way to reciprocally connect research management as an emerging research field with more established social science disciplines at large and to advance both the theory and practice of research management.
Impeding Fuzzing Audits of Binary Executables

A general defense strategy in computer security is to increase the cost of successful attacks in both computational resources as well as human time. In the area of binary security, this is commonly done by using obfuscation methods to hinder reverse engineering and the search for software vulnerabilities. However, recent trends in automated bug finding changed the modus operandi. Nowadays it is very common for bugs to be found by various fuzzing tools. Due to ever-increasing amounts of automation and research on better fuzzing strategies, large-scale, dragnet-style fuzzing of many hundreds of targets becomes viable. As we show, current obfuscation techniques are aimed at increasing the cost of human understanding and do little to slow down fuzzing. In this paper, we introduce several techniques to protect a binary executable against an analysis with automated bug finding approaches that are based on fuzzing, symbolic/concolic execution, and taint-assisted fuzzing (commonly known as hybrid fuzzing). More specifically, we perform a systematic analysis of the fundamental assumptions of bug finding tools and develop general countermeasures for each assumption. Note that these techniques are not designed to target specific implementations of fuzzing tools, but address general assumptions that bug finding tools necessarily depend on. Our evaluation demonstrates that these techniques effectively impede fuzzing audits, while introducing a negligible performance overhead. Just as obfuscation techniques increase the amount of human labor needed to find a vulnerability, our techniques render automated fuzzing-based approaches futile.
Dipole Estimation Errors Due to Skull Conductivity Perturbations: Simulation Study in Spherical Head Models

Electroencephalogram (EEG) dipole source localization is a non-invasive technique used in the pre-surgical diagnosis of epilepsy. In the present study we investigated the dipole location and orientation errors due to skull conductivity perturbations, in seven 3-shell concentric spherical head models with brain-to-skull conductivity ratio (Rsigma) ranging from 10 to 40. Each head model was compared to the baseline head model with Rsigma = 20. It is noted that perturbations in the skull conductivity generate dipole location and orientation errors: the more Rsigma deviates from the baseline value the greater the errors and the larger the error ranges. Results show that the estimated dipole location is radially shifted away from the center of the head model if the skull conductivity is larger than that of the baseline head model (Rsigma = 10, 15), while it is radially shifted towards the center in case the skull conductivity is less than that of the baseline head model (Rsigma = 25, 30, 35, 40). The dipole orientation error due to skull conductivity perturbations is not significant (maximal mean < 1 degree) in this study, but the dipole location error is considerable (maximal mean > 6 mm, standard deviation = 3 mm), especially when the dipoles are near the skull the maximal mean can reach 8 mm. Therefore, accurate estimation of the skull conductivity of the head model is necessary to enhance the reliability in EEG dipole source localization.
Improved IR-Colorization using Adversarial Training and Current Deep Learning Design Patterns

This paper investigates deep learning based image translation techniques to perform a colorization of near-infrared (NIR) images. Current deep neural network design patterns like inception modules, skip-connections or multi-scalar processing are combined and examined. Adversarial training is used to improve the realism of the resulting image in the translated domain. The presented approach is trained and evaluated on NIR-RGB image pairs from a real-world dataset containing a large amount of road scene images in summer. The dataset was captured by a multi-CCD NIR/RGB camera to ensure a perfect pixel to pixel registration.
MORE THAN A GAME : A STUDY OF THE EFFECT OF SPORTS PARTICIPATION ON EDUCATION AND LABOR MARKET OUTCOMES

This paper examines the effect of high school athletic participation on education and labor market outcomes. Specifically, this papers aims to identify how athletic participation affects GPA, educational attainment and income. Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), OLS estimates were used to test the effect of high school athletic participation on the outcome variables. This paper uses propensity score matching to control for selection bias by generating a subsample of observations with similar characteristics. Supporting previous literature, this paper found significant impacts of athletic participation on GPA and educational attainment; however, there was no evidence that that high school athletics impacts income.
Characterization of Single-Unit Activity in the Mediodorsal Nucleus of the Thalamus during Expression of Differential Heart Rate Conditioning in the Rabbit

Much recent evidence has shown that the thalamic-prefrontal axis is involved in Pavlovian conditioning in rabbits. However, while single cell activity in the prefrontal cortex has been previously studied during classical conditioning in rabbits, that of its thalamic projection nucleus, the mediodorsal (MD) nucleus, has not. Consequently, in the present research we recorded neuronal activity from individual cells in MD during expression of conditioned bradycardia in rabbits that received differential Pavlovian conditioning in which tones served as conditioned stimuli and periorbital shock served as unconditioned stimuli. The pattern of firing in MD was similar to that evoked in the medial prefrontal cortex (mPFC). Of 84 cells sampled, approximately 35% showed CS-evoked activity. Ninety percent of these cells showed increases in activity, while the remainder were biphasic, showing an initial increase followed by a decrease. Also, like the mPFC, some cells showed initial increases, which declined during CS presentation, while others showed gradual increases which reached their maximum at CS offset. Also some cells were responsive to the CS+ and others to the CS-. Thus, MD cells, like mPFC cells, are somewhat heterogenous with regard to responding to conditional stimuli, although, unlike the mPFC, no strictly inhibitory cells were found.
Supplementary Material : Photorealistic Style Transfer with Screened Poisson Equation

For each content-style pair we produce four style transfer results using: NeuralStyle (NS) [2], NS with segmentation (NS+segment) [4], StyleSwap [1] and CNNMRF [3]. We then compare our post-processing based on Screened Poisson Equation (SPE) output with the post-processing of Matting Laplacian (MT) [4], on all four style transfer methods. Note that NS+Segment+ML is actually the Deep Photo Style Transfer (DPST) of Luan et al. [4].
Leaky Images: Targeted Privacy Attacks in the Web

Sharing files with specific users is a popular service provided by various widely used websites, e.g., Facebook, Twitter, Google, and Dropbox. A common way to ensure that a shared file can only be accessed by a specific user is to authenticate the user upon a request for the file. This paper shows a novel way of abusing shared image files for targeted privacy attacks. In our attack, called leaky images, an image shared with a particular user reveals whether the user is visiting a specific website. The basic idea is simple yet effective: an attacker-controlled website requests a privately shared image, which will succeed only for the targeted user whose browser is logged into the website through which the image was shared. In addition to targeted privacy attacks aimed at single users, we discuss variants of the attack that allow an attacker to track a group of users and to link user identities across different sites. Leaky images require neither JavaScript nor CSS, exposing even privacy-aware users, who disable scripts in their browser, to the leak. Studying the most popular websites shows that the privacy leak affects at least eight of the 30 most popular websites that allow sharing of images between users, including the three most popular of all sites. We disclosed the problem to the affected sites, and most of them have been fixing the privacy leak in reaction to our reports. In particular, the two most popular affected sites, Facebook and Twitter, have already fixed the leaky images problem. To avoid leaky images, we discuss potential mitigation techniques that address the problem at the level of the browser and of the image sharing website.
Computer-Aided Design of Diode Frequency Multipliers

This article describes a computational tool created to help with the design of reactive and resistive frequency multipliers. With the MultFreq program, calculation of all the inherent parts of this kind of circuit, such as filters and impedance matching networks, can be performed. We also present the multiplier layout, including all calculated dimensions. In a telecommunication system, the generation of high stability, low noise specific-frequency signals is important in many applications [1]. A signal of higher frequency is frequently obtained by generating harmonics from a signal of a lower frequency. This input signal usually comes from a very stable source such as crystal oscillator. Frequency multipliers can be characterized as devices able to realize this harmonic generation process. Usually, this kind of circuit uses the nonlinear characteristics of some element to provide multiples of a determined frequency. The desired frequency is selected through an appropriate filtering process. Frequency multiplication can be obtained through passive (diodes) or active (transistors) elements [2]. In this work, the approach used is valid only for reactive and resistive passive multipliers. The reactive multipliers have restricted use on narrow-band applications. In fact, the reactance is a property linked to the frequency. Consequently, any matching structure used will be efficient at only one frequency. The required nonlinear characteristics can be obtained through a varactor diode or a SRD (Step Recovery Diode). A SRD junction is characterized by a capacitance with a nonlinearity stronger than that shown by a varactor [3]. Reactive multipliers based on varactor diodes are used on low order multiplication of microwave signals. On the other hand, SRDs are useful to provide higher order harmonics in the UHF band and in a microwave narrow band, with an output frequency never higher than 20 GHz [3]. In the resistive case, multiplication through a Schottky diode is characterized by its nonlinear V/I relationship that creates harmonics from an excitation signal. Multiplication using these diodes is based on a nonlinear resistance. Since their characteristics do not vary with the frequency over a significantly wide band, they can be considered as wide-band devices. Unfortunately, because of their low efficiency, resistive multipliers are less used than the reac-
Fragment Anomaly Detection With Prediction and Statistical Analysis for Satellite Telemetry

In aerospace engineering, condition monitoring is an important reference for evaluating the performance of complex systems. Especially, effective anomaly detection, based on telemetry data, plays an important role for the system health management of a spacecraft. With the advantages of easy-to-use, high efficiency, and data-driven, the predicted model has been applied for anomalous point detection for monitoring data. However, compared with the point abnormal mode, fragment anomaly is more attractive and meaningful for the system identification. Therefore, the detection strategy of fragment anomaly is proposed based on the uncertainty estimation of least square support vector machine and statistical analysis. Moreover, some effective estimation indicators are presented to evaluate the performance of the detection method. Experimental validations are also carried out for some typical simulation data sets and open source data sets. In particular, relied on the analysis of fragment anomaly modes, experiments are conducted with the real satellite telemetry data and different anomaly modes are injected to examine the applicability of the proposed framework.
Nitric oxide generation from sodium nitroprusside and hydroxylamine in brain

WE aimed to demonstrate different modes of in situ nitric oxide (NO) generation from two NO donors in cerebral cortex of halothane anesthetized cats. NO donors were delivered by in vivo microdialysis into the cortical tissue where an NO electrode measured real-time changes in extracellular NO concentration. In vitro testing in Ringer's solution revealed that sodium nitroprusside (SNP) liberates NO spontaneously in the presence of light, whereas hydroxylamine does not generate any NO under these conditions. Supplementation with 200 mM of the NO donors SNP and hydroxylamine evoked dose-related increases in NO concentration (52.0 ± 6.7 nM, n = 5, and 14.0 ± 3.8 nM, n = 5, respectively). The increase in NO concentration was significantly greater during SNP than during hydroxylamine delivery (p < 0.001). In contrast, CBF increased similarly under the influence of both NO donors. Electrocorticogram and cortical direct current potential remained unaffected. In conclusion, hydroxylamine is degraded into NO intracellularly and efficiently dilates cerebral blood vessels. SNP, in contrast, generates NO mainly in the extracellular space.
WCDMA Downlink Load Sharing with Dynamic Control of Soft Handover Parameters

In this article, we address the problem of auto-tuning of soft handover (SHO) parameters in WCDMA networks. The auto-tuning process uses a fuzzy Q-learning controller to adapt SHO parameters to varying network situations such as traffic fluctuation. The fuzzy Q-learning controller combines both fuzzy logic theory and reinforcement learning method. The cooperation of these two mechanisms simplifies the task of the online optimization of fuzzy logic rules and consequently leads to a better online SHO parameterization of each base station in the network. The proposed scheme improves the system capacity compared to a classical network with fixed parameters, balances the load between base stations and minimizes human intervention in network management and optimization tasks
ADAPTATION FOR VIDEO OBJECT SEGMENTATION 3 from the last frame is used as an additional input channel to the neural network , enabling it to use temporal context

We tackle the task of semi-supervised video object segmentation, i.e. segmenting the pixels belonging to an object in a video using the ground truth pixel mask for the first frame. We build on the recently introduced one-shot video object segmentation (OSVOS) approach which uses a pretrained network and fine-tunes it on the first frame. While achieving impressive performance, at test time OSVOS uses the fine-tuned network in unchanged form and is not able to adapt to large changes in object appearance. To overcome this limitation, we propose Online Adaptive Video Object Segmentation (OnAVOS) which updates the network online using training examples selected based on the confidence of the network and the spatial configuration. Additionally, we add a pretraining step based on objectness, which is learned on PASCAL. Our experiments show that both extensions are highly effective and improve the state of the art on DAVIS to an intersection-over-union score of 85.7%.
Indexing Techniques for Spatiotemporal Databases

of spatiotemporal databases needs new data models and query languages and novel access structures for storing and accessing information. In Güting, Bohlen, Erwig, Jensen, Lorentzos, Schneider, and Vazirgiannis (2000) a data model and a query language capable of handling such time-dependent geometries, including those changing continuously that describe moving objects, were proposed; the basic idea was to represent time-dependent geometries as attribute data types and to provide an abstract data type extension to the traditional database data models and query languages. In that paper, it was also discussed how various temporal and spatial models could possibly be extended to be spatiotemporal models.
Facet-based trend modeling for cold start of recommendation in social media

Recommendation systems have been widely used in social media. One of recommendation tasks in social media is to provide relevant messages for users. Although many models have been proposed, how to make accurate recommendation for new users with little historical information still remains a big challenge, which is called the cold start problem. In order to address this problem, many models have been proposed, which use information of social media to improve the recommendation performance. However, lack of such versatility limits the successful application of these models. In this study, we propose an effective facet-based trend model to describe the trend interests of the entire user community in social media. Trend facet is the probability distribution of all users' preference to an attribute. In contrast to the general feature, the facet stems from the users' history and captures the interests to the attribute in social media. We evaluate our models in the context of personalized ranking of microblogs. Experiments on real-world data show that trend modeling can alleviate the cold start problem significantly. In addition, we compare the performance of user modeling and trend modeling, and find that user modeling outperforms trending model and the impact is slightly negative when combining trend modeling with user modeling.
Computed tomography for pancreatic injuries in pediatric blunt abdominal trauma.

AIM To evaluate the efficacy of computed tomography scan in diagnosing and grading the pattern of pancreatic injuries in children. METHODS We conducted a retrospective study to review medical files of children admitted with blunt pancreatic injuries to the Maternity and Children Hospital Al-Madina Al-Munawwarah, Kingdom of Saudi Arabia. The demographic details and mechanisms of injury were recorded. From the database of the Picture Archiving and Communication System of the radiology department, multidetector computed tomography (MDCT) images of the pancreatic injuries, severity, type of injuries and grading of pancreatic injuries were established. RESULTS Seven patients were recruited in this study over a period of 5 years; 5 males and 2 females with a mean age of 7 years (age range 5-12 years). Fall from height was the most frequent mechanism of injury, reported in 5 (71%), followed by road traffic accident (1 patient, 14%) and cycle handlebar (1 patient, 14%) injuries. According to the American Association for the Surgery of Trauma grading system, 1 (14%) patient sustained Grade I, 1 (14%) Grade II, 3 (42%) Grade III and 2 (28%) patients were found to have Grade V pancreatic injuries. This indicated a higher incidence of severe pancreatic injuries; 5 (71.4%) patients were reported to have Grade III and higher on the injury scale. Three (42%) patients had associated abdominal organ injuries. CONCLUSION Pediatric pancreatic injuries due to blunt abdominal trauma are rare. The majority of the patients sustained extensive pancreatic injuries. MDCT findings are helpful and reliable in diagnosing and grading the pancreatic injuries.
Risk and Return in International Corporate Bond Markets

Corporate bond returns in the major developed economies increase with risk, as measured by maturity and ratings. From a pricing perspective, we find little to no evidence against the World CAPM model, where the market consists out of equity, sovereign and corporate bonds. However, from a factor model perspective, local factors contribute substantially more to the variation of corporate bond returns than global factors. The factor exposures show intuitive patterns: as ratings worsen, equity betas show a hockey stick pattern, sovereign betas decline monotonically and corporate bond betas increase steeply. JEL Classification: G10, G11, G15
Topological phenomena in quantum gases

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Topological phenomena in quantum gases Jérôme Beugnon
Identification and functional characterisation of a novel dopamine beta hydroxylase gene variant associated with attention deficit hyperactivity disorder

Objectives. Dysregulation in neurotransmitter signalling has been implicated in the aetiology of attention deficit hyperactivity disorder (ADHD). Polymorphisms of the gene encoding dopamine beta hydroxylase (DBH) have been reported to be associated with ADHD; however, small sample sizes have led to inconsistency. Methods. We conducted transmission disequilibrium test analysis in 794 nuclear families to examine the relationship between DBH and ADHD. The effects of the ADHD-associated polymorphisms on gene expression were assessed by luciferase reporter assays in a human neuroblastoma cell line, SH-SY5Y. Results. A SNP within the 3′ untranslated region of DBH rs129882 showed a significant association with ADHD (χ2 = 9.71, p = 0.0018, OR = 1.37). This association remained significant after Bonferroni correction for multiple testing (p = 0.02). Further, allelic variation in rs129882 significantly impacted luciferase expression. Specifically, the C allele of the ADHD-associated rs129882 SNP produced a 2-fold decrease (p < 0.001) in luciferase activity. Conclusions. These data demonstrate for the first time that a DBH gene variant, rs129882, which confers risk to ADHD is also associated with reduced in vitro gene expression. Reduced DBH expression would be consistent with decreased conversion of dopamine to noradrenaline and thus with a relative hypo-noradrenergic state in ADHD.