Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Pain Recognition in Post-Operative Phases Using 3D-based Features From Video and Support Vector Machines

In this article first results are presented of our new method for vision based recognition of pain from facial expressions. Incorporating a series of image processing, low level computer vision and pattern recognition techniques the proposed method not only detects facial expressions of pain but also ones related to emotion or neutrally speaking subjects. In order to extract the facial features through image processing our approach uses color and gradient information along with a head contour model. In the 3D related part a camera model is included along with an initial registration step, in which we use method that automatically builds a person specific face model from stereo. By using this model information 3D geometric feature measures are determined and normalized through the application of photogrammetric techniques. A support vector machine based classifier is trained and applied to these features. The presented approach leads to minimal mixing between different expression classes. Also, our framework achieves robust and clear classification results while reaching high performance.
Quantitative analysis of WC stars: constraints on neon abundances from ISO-SWS spectroscopy

Neon abundances are derived in four Galactic WC stars - gamma(2) Vel (WR 11, WC8+O7.5III), HD 156385 (WR 90, WC7), HD 192103 (WR 135, WC8) and WR 146 (WC5+O8) - using mid-infrared fine-structure lines obtained with ISO-SWS. Stellar parameters for each star are derived using the non-local thermodynamic equilibrium model atmospheric code of Hillier & Miller, together with ultraviolet (IUE), optical (INT, AAT) and infrared (UKIRT, ISO) spectroscopy. In the case of gamma(2) Vel, we adopt very recent results from De Marco et al., who followed an identical approach.ISO-SWS data sets reveal the [Ne III] 15.5-mu m line in each of our targets, while [Ne II] 12.8 mu m, [S IV] 10.5 mu m and [S III] 18.7 mu m are observed solely in gamma(2) Vel. Using a method updated from Barlow et al. to account for clumped winds, we derive Ne/He = (3-4) x 10(-3) by number, plus S/He = 6 x 10(-5) for gamma(2) Vel. Neon is highly enriched, such that Ne/S in gamma(2) Vel is eight times higher than cosmic values. However, observed Ne/He ratios are a factor of 2 lower than predictions of current evolutionary models of massive stars. An imprecise mass loss and distance were responsible for the much greater discrepancy in neon content identified by Barlow et al.Our sample of WC5-8 stars span a narrow range in T-* (=55-71 kK), with no trend towards higher temperature at earlier spectral type, supporting earlier results for a larger sample by Koesterke & Hamann. Stellar luminosities range from 100 000 to 500 000 L. , while 10(-5.1) less than or equal to M/(M. yr(-1)) less than or equal to 10(-4.5) adopting clumped winds, in which volume filling factors are 10 per cent. In all cases, wind performance numbers are less than 10, significantly lower than recent estimates. Carbon abundances span 0.08 less than or equal to C/He less than or equal to 0.25 by number, while oxygen abundances remain poorly constrained.
Profile-guided program simplification for effective testing and analysis

Many testing and analysis techniques have been developed for inhouse use. Although they are effective at discovering defects before a program is deployed, these techniques are often limited due to the complexity of real-world code and thus miss program faults. It will be the users of the program who eventually experience failures caused by the undetected faults. To take advantage of the large number of program runs carried by the users, recent work has proposed techniques to collect execution profiles from the users for developers to perform post-deployment failure analysis. However, in order to protect users' privacy and to reduce run-time overhead, such profiles are usually not detailed enough for the developers to identify or fix the root causes of the failures. In this paper, we propose a novel approach to utilize user execution profiles for more effective in-house testing and analysis. Our key insight is that execution profiles for program failures can be used to simplify a program, while preserving its erroneous behavior. By simplifying a program and scaling down its complexity according to its profiles, in-house testing and analysis techniques can be performed more accurately and efficiently, and pragmatically program defects that occur more often and are (arguably) more relevant to users will be given preference during failure analysis. Specifically, we adapt statistical debugging on execution profiles to predict likely failure-related code and use a syntax-directed algorithm to trim failure-irrelevant code from a program, while preserving its erroneous behavior as much as possible. We conducted case studies on a testing engine, CUTE, and a software model checker, BLAST, to evaluate our technique. We used subject programs from the Aristotle Analysis System and the Software-artifact Infrastructure Repository (SIR). Our empirical results show that using simplified programs, CUTE and BLAST find more bugs with improved accuracy and performance: they were able to detect 20 and 21 (out of 139) more bugs respectively in about half of the time as they took on the original test programs.
Selection and characterization of brivudin resistant bovine herpesvirus type 5

Bovine herpesvirus type 5 (BoHV-5) is the agent of meningoencephalitis, an important disease of cattle in South America. The neuropathogenesis of BoHV-5 infection is poorly understood and most previous research focused on the role of envelope glicoproteins in neurovirulence. Thymidine kinase (TK) is a viral enzyme necessary for virus replication in neurons and, therefore, represents a potential target for virus attenuation. The selection and characterization of BoHV-5 variants resistant to the nucleoside analog brivudin (BVDU), which selects TK-defective viruses is here described. Several BVDU-resistant clones were obtained after multiple passages in tissue culture in the presence of BVDU and one clone (BoHV-5/R-27) was further characterized. The selected clone replicated to similar titers and produced plaques with similar size and morphology to those of wild-type virus (SV507/99). The genetic stability of the resistant virus was demonstrated after ten passages in cell culture in the absence of the drug. Moreover, the drug-resistant virus showed reduced virulence in a rabbit model: virus inoculation in four rabbits did not result in disease, in contrast with 75% morbidity (3/4) and 50% mortality (2/2) among rabbits inoculated with the parental virus. These results demonstrate that BoHV-5 is sensitive to BVDU and that drug-resistant mutants can be readily selected upon BVDU treatment. BVDU-resistant mutants, likely defective in TK, retained their ability to replicate in tissue culture yet were attenuated for rabbits. This strategy to obtain TK-defective BoHV-5 may be useful to study the role of TK in BoHV-5 neuropathogenesis and for vaccine development.
Expressive Robotic Face for Interaction

This paper describes the current development status of a robot head with basic interactional abilities. On a theoretical level we propose an explanation for the lack of robustness implicit in the so-called social robots. The fact is that our social abilities are mainly unconscious to us. This lack of knowledge about the form of the solution to these abilities leads to a fragile behaviour. Therefore, the engineering point of view must be seriously taken into account, and not only insights taken from human disciplines like developmental psychology or ethology. Our robot, built upon this idea, does not have a definite task, except to interact with people. Its perceptual abilities include sound localization, omnidirectional vision, face detection, an attention module, memory and habituation. The robot has facial features that can display basic emotional expressions, and it can speak canned text through a TTS. The robot’s behavior is controlled by an action selection module, reflexes and a basic emotional module.
Effect of Thermal Properties on Delaminated Fibre Metal Laminate

An attempt is made to analyse the effect of variation in thermal properties in Fibre Metal Laminate with an implanted delamination. This work focuses to explore the variations in thermal contrast for the increase in values of thermal properties of delamination, Aluminium layers and glass reinforced epoxy layers. The paper projects the numerical investigations towards the thermal analysis of fibre metal laminates based on a type of infrared Thermography named Step Pulsed Active thermography. The results conclude that the strong dependency of thermal contrast is mainly based on thermal conductivity of delaminated material, and Aluminium layers but less dependent on specific heat and density for barely Aluminium layers. The supplementary conclusions are arrived that the specific heat and density of Aluminium layers only show less significant in reporting the changes in results but they do not make considerable changes for delamination. A complementary conclusion of the glass fibre epoxy layers confirms that none of thermal properties variations does make meaningful change in thermal contrast in both reflection mode and transmission mode. The empirical relationship is made to find the exact variation of thermal contrast with change in thermal properties to study the future case problems related to delaminated fibre metal laminates. Thus, the analyses conclude that step pulsed active thermography in both reflection and transmission modes are more sensitive with the variation in thermal conductivity of delamination and Aluminium layers.
MIMEFrame-a framework for statically and dynamically composed adaptable mobile browsers

The mobile environment sets new requirements for contents, browsers, and visualization. The capabilities and properties of mobile devices as well as networks vary a lot. As well as the browsing content, also, mobile browsers should be adaptable for specific users, use-contexts, and services to provide reasonable user experience. Because mobile usage is more spontaneous browsers need to be fast to download, install, and start. We describe a MIMEFrame framework that defines core parts for mobile user agents and browsers and present how adaptation tasks can dynamically compose browsers of the MIMEFrame components. In addition, we introduce a SKINS model that offers fine-grained methods for composing context- and content-driven presentations for (e.g. XML) contents and user interfaces described with element trees. We made Java implementations for these techniques that offer both core interfaces and a platform for adaptable mobile user agent and browser implementations that can illustrate various types of content and offer multimodal controls for browsing
Evaluation of optimal wavelet decomposition level for quantitative calibration of near infrared spectra

In order to avoid selecting decomposition level for quantitative calibration of near infrared spectra in discrete wavelet transform empirically or semi-empirically, a scheme which can be selected optimal decomposition level was proposed. In this scheme, the raw spectral was decomposed by wavelet transform, the approximation coefficients of each decomposition level as input set for partial least square (PLS) to built calibration model, root mean square error of validation (RMSEV) was employed as objective function to find the optimal decomposition level using the validation set, and the approximation coefficients which obtained lowest RMSEV is the optimal decomposition level. The proposed method was demonstrated in determination of moisture in wheat by near infrared spectroscopy.
Neural Bases of Talker Normalization

To recognize phonemes across variation in talkers, listeners can use information about vocal characteristics, a process referred to as talker normalization. The present study investigates the cortical mechanisms underlying talker normalization using fMRI. Listeners recognized target words presented in either a spoken list produced by a single talker or a mix of different talkers. It was found that both conditions activate an extensive cortical network. However, recognizing words in the mixed-talker condition, relative to the blocked-talker condition, activated middle/superior temporal and superior parietal regions to a greater degree. This temporal parietal network is possibly associated with selectively attending and processing spectral and spatial acoustic cues required in recognizing speech in a mixed-talker condition.
Hyperplastic Polyps Are Innocuous Lesions in Hereditary Nonpolyposis Colorectal Cancers

Aims. To compare methylation profiles, protein expression, and microsatellite instability (MSI) of sporadic, HNPCC, and familial hyperplastic polyps (HPs). Methods. Methylation-specific PCR (MSP) and pyrosequencing assessed p16, MGMT, hMLH-1, MINT 1, and MINT 31 methylation. IHC (Immunohistochemistry) assessed Ki67, CK20, hMLH-1, hMSH-2, and hMSH-6 protein expression. MSI analysis was performed on those polyps with adequate DNA remaining. Results. 124 HPs were identified 78 sporadic, 21 HNPCC, 25 familial, and the HNPCC group demonstrated no significant differences in overall methylation (P = .186 Chi2). The familial group demonstrated significantly less over all methylation levels (P = .004 Chi2). Conclusions. HPs that occur in HNPCC have no more worrying features at a molecular level than those patients with HPs in a sporadic setting.
The Challenge of Professional Development in Jewish Studies: Why the Conventional Wisdom May Not Be Enough

ABSTRACT This article examines the ways that Jewish studies teachers think about their teaching. It analyzes data from a three month teacher study group in which teachers read educational research articles as a framework for reflecting on their own teaching. The data suggest that Jewish studies teachers take one of two approaches in talking about their teaching: Half the teachers focused on the process of teaching, the specific modalities and teaching moves they employed, while the other half focused on the goals of teaching, the specific outcomes they wanted to see in their students. We also found that those teachers who were more focused on outcomes (rather than process) saw personal identity as an essential ingredient in effective Jewish education. This article raises questions about the efficacy of transferring professional development models from general education to Jewish education, without special attention to the specific cultural context of Jewish studies.
OQ-Quad: An efficient query processing for continuous k-nearest neighbor based on quad tree

With the growing popularity of mobile computing and wireless communications, managing the continuously changing information of the moving objects is becoming feasible, especially in LBS application which is characterized by a large number of moving objects and a large number of continuous queries. In this paper, we focus on continuous k-nearest neighbor (CkNN for short) query and propose a query method based on a quad tree to support continuous k-nearest neighbor query for moving objects, in which the main idea is to use a quad tree to divide the static spatial space for the moving objects. In the interested region, we use the quad tree and hash tables as an index to store the moving objects. Then we calculate the distances between the query point and the moving objects from inside to outside to get the result. Our comprehensive experimentation shows that the performance of the proposed method is better in memory consumption and processing time than the CMP algorithm.
Disparities in police proceedings and court sentencing for females versus males who commit sexual offences in New Zealand

ABSTRACT This study investigated whether there are disparities in the way in which police proceed against females and males who commit sexual offences. We explored whether there are discrepancies in the severity of court sentences handed down to female and male sexual offenders. Using police and sentencing data, we compared the proportion of females and males who proceeded to court action once charged with a sexual offence and, separately, the severity of sentencing handed down to both genders. In terms of police decision-making processes, compared to males, a smaller proportion of females proceeded to “court action” for their offences. Furthermore, the severity of sentences handed down to males was greater than those handed down to females, both generally and when the sexual offence could be directly matched. These findings are discussed in the context of gender differences in how these crimes are processed and implications for justice, intervention, and community safety.
Protecting Kernel Data through Virtualization Technology

Operating system security (OS) is the basis for trust computing. As the kernel rootkits become popular and lots of kernel vulnerabilities are exposed, the OS kernel suffers a large number of attacks. It is difficult to protect the kernel by its own module because the kernel rootkits has the same ability to cripple the security module within the same kernel space. Recently, with the virtualization renaissance, virtualization technology provides many new ways to improve the system security. Utilizing this new technology, we present a kernel protection system called VMhuko. By monitoring the kernel data access actively, VMhuko can defend the kennel data attacks on the fly. The intensive experiment shows that VMhuko can protect the kernel with moderate performance.
Detecting overlapping speech with long short-term memory recurrent neural networks

Detecting segments of overlapping speech (when two or more speakers are active at the same time) is a challenging problem. Previously, mostly HMM-based systems have been used for overlap detection, employing various different audio features. In this work, we propose a novel overlap detection sys-tem using Long Short-Term Memory (LSTM) recurrent neural networks. LSTMs are used to generate framewise overlap predictions which are applied for overlap detection. Furthermore, a tandem HMM-LSTM system is obtained by adding LSTM predictions to the HMM feature set. Experiments with the AMI corpus show that overlap detection performance of LSTMs is comparable to HMMs. The combination of HMMs and LSTMs improves overlap detection by achieving higher recall.
Image super-resolution reconstruction by sparse decomposition and scale-invariant feature retrieval in micro-UAV stereo vision

To meet the need of micro-UAV vision system for navigation task, this paper introduces a new single image super resolution approach, based on the sparse decomposition and wavelet transform scale invariant features of captured images. Through the training of high resolution natural image and the blurred and down sampled low resolution image, the approach learns the overcomplete dictionaries that could represent their respective images sparsely. Based on the sparse representation at low resolution and the wavelet transform scale invariant features, the approach could automatically retrieves the high resolution patches for the super resolution reconstruction. Compared with the celebrated algorithms proposed in the literature, this approach improves both PSNR of the recovered image and appearance which would improve the stereo vision for scene depth estimat ion.
Efficient lookahead resource allocation for stored video delivery in multi-cell networks

Novel transmission mechanisms are imperatively needed to cope with the exponential growth of mobile traffic and its associated power consumption. To address such challenges, we present lookahead video delivery schemes that jointly improve the streaming experience and reduce BS power consumption. This is accomplished by exploiting knowledge of future wireless rates users are anticipated to face. Such an approach is useful for delivering stored videos that can be strategically buffered in advance at the users' devices. For instance, a user leaving the cell center may have content prebuffered efficiently before poor channel conditions prevail. This will save energy as transmission will not be needed during poor conditions. In this paper, we first formulate Lookahead Resource Allocation (LRA) as a multi-cell optimization problem that leverages predictions of user mobility rates. Then, we present centralized and distributed algorithms that closely follow the benchmark results of the optimal solution. Numerical results demonstrate that significant improvements in video streaming and BS power consumption are achievable by the LRA strategies.
Multi-Domain Adaptation for SMT Using Multi-Task Learning

Domain adaptation for SMT usually adapts models to an individual specific domain. However, it often lacks some correlation among different domains where common knowledge could be shared to improve the overall translation quality. In this paper, we propose a novel multi-domain adaptation approach for SMT using Multi-Task Learning (MTL), with in-domain models tailored for each specific domain and a general-domain model shared by different domains. The parameters of these models are tuned jointly via MTL so that they can learn general knowledge more accurately and exploit domain knowledge better. Our experiments on a largescale English-to-Chinese translation task validate that the MTL-based adaptation approach significantly and consistently improves the translation quality compared to a non-adapted baseline. Furthermore, it also outperforms the individual adaptation of each specific domain.
Data distribution for failure correlation management in a Peer to Peer storage system

This article presents a dynamic data distribution method for data storage in a P2P system. In our system (named Us), peers are arranged in groups called metapeers to deal with account failure correlation. To minimize end user traffic according to the reconstruction process, distribution must take into account a new measure: the maximum disturbance cost of a peer. In a previous work, we defined a static distribution scheme which minimizes this reconstruction cost derived from affine plan theory. In this paper, we extend this distribution scheme to deal with the dynamic behaviour of peer to peer systems
Word sense disambiguation using HMM tagger

In Natural Language Processing, it is necessary to take into account the polysemy of some words. In all the domains of language management, stochastic methods have shown their efficiency. To what extent is i t possible to use probabilities for word sense disambiguation? What are the available resources and do they fit such a task? In this article, we evaluate the difficulty of a semantic disambiguation task and present different statistic methods for sense assignation, based on WordNet and using the SemCor to train and test the models.
Adding Value to Biodiversity Images through Community Annotation

Morphbank, an on-line collection of museum-quality biological images, is an NSF funded project designed to facilitate the on-line collaboration of biologists from around the world [3]. Our primary focus is to aid in the collection and management of images that are useful in phylogenetic research. Morphbank users are actively collaborating on the creation of information that represents the associations among images and related biodiversity data objects. This paper describes the Morphbank annotation tool and data models and gives examples of how users create structured information in the system. Schematized annotation provides biologists with a flexible framework to create semantically-rich annotations using their own data models.