Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards an Emotional Engagement Model: Can Affective States of a Learner be Automatically Detected in a 1: 1 Learning Scenario?

Existing Intelligent Tutoring Systems (ITSs) are unable to track affective states of learners. In this paper, we focus on the problem of emotional engagement, and propose to detect important affective states (i.e., ‘Satisfied’, ‘Bored’, and ‘Confused’) of a learner in real time. We collected 210 hours of data from 20 students through authentic classroom pilots. The data included information from two modalities: (1) appearance which is collected from the camera, and (2) context-performance that is derived from the content platform. In this paper, data from nine students who attended the learning sessions twice a week are analyzed. We trained separate classifiers for different modalities (appearance and context-performance), and for different types of learning sections (instructional and assessment). The results show that different sources of information are generically better representatives of engagement at different sections: For instructional sections, generic appearance classifier yields higher accuracy (55.79%); whereas context-performance classifier is more accurate for assessment sections (63.41%). Moreover, the results indicate that expression of engagement is person-specific through both of these sources, and personalized engagement models perform more accurately: When person-specific data are added to the training set, on instructional sections, 85.44% and 96.13% accuracies are achieved for appearance and context-performance, respectively. For assessment sections, the accuracies are 75.25% (appearance) and 90.24% (context-performance). When only person-specific data are employed during training, similar accuracies are achieved even with very limited data.
Contamination removal methods in cDNA microarray data

Our objective is to detect and remedy the contaminated spots for cDNA microarray data. To check the existence of unusual spots, single linkage clustering is used to assess the background intensities. Then, K-means clustering method is applied to identify the contaminated area. We estimate the amount of contamination, for background and foreground, through the use of nonparametric spline regression and empirical cumulative distribution approach, separately. A simulation study shows that the performance of the recommended approach is promising.
Molecular Characterization of c-Abl/c-Src Kinase Inhibitors Targeted against Murine Tumour Progenitor Cells that Express Stem Cell Markers

Background The non-receptor tyrosine kinases c-Abl and c-Src are overexpressed in various solid human tumours. Inhibition of their hyperactivity represents a molecular rationale in the combat of cancerous diseases. Here we examined the effects of a new family of pyrazolo [3,4-d] pyrimidines on a panel of 11 different murine lung tumour progenitor cell lines, that express stem cell markers, as well as on the human lung adenocarcinoma cell line A549, the human hepatoma cell line HepG2 and the human colon cancer cell line CaCo2 to obtain insight into the mode of action of these experimental drugs. Methodology/Principal Findings Treatment with the dual kinase inhibitors blocked c-Abl and c-Src kinase activity efficiently in the nanomolar range, induced apoptosis, reduced cell viability and caused cell cycle arrest predominantly at G0/G1 phase while western blot analysis confirmed repressed protein expression of c-Abl and c-Src as well as the interacting partners p38 mitogen activated protein kinase, heterogenous ribonucleoprotein K, cyclin dependent kinase 1 and further proteins that are crucial for tumour progression. Importantly, a significant repression of the epidermal growth factor receptor was observed while whole genome gene expression analysis evidenced regulation of many cell cycle regulated genes as well integrin and focal adhesion kinase (FAK) signalling to impact cytoskeleton dynamics, migration, invasion and metastasis. Conclusions/Significance Our experiments and recently published in vivo engraftment studies with various tumour cell lines revealed the dual kinase inhibitors to be efficient in their antitumour activity.
Motion detection using Horn Schunck algorithm and implementation

Use of unsuitable techniques and parameters in identifying optical flow movement produces poor segmentation and indirectly affects the optical flow pattern. In this paper, emphasis is focused on the production of optical flow image using Horn Schunck technique and finding the optimum parameters. Image flow movement using Horn Schunck technique and its implementation has been researched to comprehend more about the optical flow. Simulation was performed using the simulation software called MATLAB v7.6 by Mathworks Inc. There are three types of displacements used namely small, medium and large displacement. Several important parameters such as iteration, smoothness and density have been identified to achieve the research goal. This paper reports the study on three parameters previously mentioned in combination with three different types of displacements using Horn Schunck algorithm. Based on Horn Schunck algorithm, the results were obtained after considering the segmentation results, field of optical flow, standard derivation, error and processing time. It is then identified that the optimum values of parameters are when the iteration is between 1 to 6, the smoothing is between 0.0001 to 0.002 and the density is equal to 1.
Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort

Background Uncertainty remains about the true extent by which alcohol consumption causes a number of health outcomes. Genetic variants, or combinations of variants built into a polygenic risk score (PGRS), can be used in an instrumental variable framework to assess causality between a phenotype and disease outcome of interest, a method known as Mendelian randomisation (MR). We aimed to identify genetic variants involved in the aetiology of alcohol consumption, and develop a PGRS for alcohol. Methods Repeated measures of alcohol consumption from mothers and their offspring were collected as part of the Avon Longitudinal Study of Parents and Children. We tested the association between 89 SNPs (identified from either published GWAS data or from functional literature) and repeated measures of alcohol consumption, separately in mothers (from ages 28–48) and offspring (from ages 15–21) who had ever reported drinking. We modelled log units of alcohol using a linear mixed model and calculated beta coefficients for each SNP separately. Cross-validation was used to determine an allelic score for alcohol consumption, and the AVENGEME algorithm employed to estimate variance of the trait explained. Results Following correction for multiple testing, one SNP (rs1229984) showed evidence for association with alcohol consumption (β = -0.177, SE = 0.042, p = <0.0001) in the mothers. No SNPs showed evidence for association in the offspring after correcting for multiple testing. The optimal allelic score was generated using p-value cut offs of 0.5 and 0.05 for the mothers and offspring respectively. These scores explained 0.3% and 0.7% of the variance. Conclusion Our PGRS explains a modest amount of the variance in alcohol consumption and larger sample sizes would be required to use our PGRS in an MR framework.
Trophic interactions between heterotrophic Protozoa and bacterioplankton in estuarine water analyzed with selective metabolic inhibitors

We estimated In si tu grazing rates of heterotrophic nanoplankton (HNAN) on bactenoplankton in a salt marsh estuary using a select~ve metabolic inhibitor technique. Seasonal experiments with prokaryohc inhibitors showed a significant, positive relation between bacterial abundance and HNAN grazing rates. On average, only 40 to 4 5 '/o of bacterioplankton produchon in the estuary appeared to be consumed by phagogrophic Protozoa <20 pm in size. Eukaryotic inhibitor experiments suggested that protozoan grazlng can have a positive feedback effect on bacterioplankton production, and that nitrogen regeneration by Protozoa may be of particular importance to bacterial growth. Although eukaryotic inhibitors did not prove to be rouhnely useful to estimate protozoan grazing rates on bacterioplankton, they may contribute to understanding qualitahve control mechanisms in the microbial food web.
Mobile reception of DVB-H : how to make it work?

This paper describes the conception and development of a solution for improved mobile reception of the digital video broadcast standard for handheld (DVB-H) at Philips Research. It includes a simple characterization of mobility-induced interference based on a suitable model for the doubly selective channel. We further describe estimation and interference cancellation algorithms explaining the trade-offs between complexity and performance. The presented algorithms have been implemented in an NXP chip.
An Effective Procedure for Computing "Uncomputable" Functions

We give an effective procedure that produces a natural number in its output from any natural number in its input, that is, it computes a total function. The elementary operations of the procedure are Turing-computable. The procedure has a second input which can contain the Goedel number of any Turing-computable total function whose range is a subset of the set of the Goedel numbers of all Turing-computable total functions. We prove that the second input cannot be set to the Goedel number of any Turing-computable function that computes the output from any natural number in its first input. In this sense, there is no Turing program that computes the output from its first input. The procedure is used to define creative procedures which compute functions that are not Turing-computable. We argue that creative procedures model an aspect of reasoning that cannot be modeled by Turing machines.
Moving Target Techniques: Leveraging Uncertainty for Cyber Defense

Securing critical computer systems against cyber attacks is a continual struggle for system managers. Attackers often need only find one vulnerability (a flaw or bug that an attacker can exploit to penetrate or disrupt a system) to successfully compromise systems. Defenders, however, have the technically difficult task of discovering and fixing every vulnerability in a complex system, which usually comprises an operating system, device drivers, numerous software applications, and hardware components. Within cyberspace, this imbalance between a simple, one-vulnerability attack tactic and a complicated, multipart defense strategy favors attackers. While defensive applications have grown significantly in complexity and size over many years, malicious software, i.e., malware, has remained relatively simple, computationally small, and still effective in bypassing defensive applications [1]. A major contributing factor to the imbalanced security of cyberspace is the static nature of systems and defenses. The same copy of a popular software application with the same internals developed by a major software vendor may run on millions of machines. As a result, an attack designed to infect that software application is likely to compromise millions of machines. Similarly, many defensive applications are static; they discover suspicious inputs by applying a set of rules and checks commonly used by software built to detect attacks. Therefore, clever cyber invaders can craft attacks to bypass existing defenses by analyzing local copies of readily available defensive applications and then exploiting the weaknesses within those applications. Cyber moving target techniques involve randomizing cyber system components to reduce the likelihood of successful attacks, adding dynamics to a system to shorten attack lifetime, and diversifying otherwise homogeneous collections of systems to limit attack damage. A review of five dominant categories of cyber moving target techniques assesses their benefits and weaknesses.
Eliminating trapping sets in low-density parity-check codes by using Tanner graph covers

We discuss error floor asympotics and present a method for improving the performance of low-density parity-check (LDPC) codes in the high SNR (error floor) region. The method is based on Tanner graph covers that do not have trapping sets from the original code. The advantages of the method are that it is universal, as it can be applied to any LDPC code/channel/decoding algorithm and it improves performance at the expense of increasing the code length, without losing the code regularity, without changing the decoding algorithm, and, under certain conditions, without lowering the code rate. The proposed method can be modified to construct convolutional LDPC codes also. The method is illustrated by modifying Tanner, MacKay and Margulis codes to improve performance on the binary symmetric channel (BSC) under the Gallager B decoding algorithm. Decoding results on AWGN channel are also presented to illustrate that optimizing codes for one channel/decoding algorithm can lead to performance improvement on other channels.
An Efficient Fingerprint Based Gender Classification System Using Dominant Un-decimated Wavelet Coefficients

Gender classification is the major and challenging task in the field of forensic anthropology which minimizes the list of suspects search. The existing systems use the availability of bones, teeth and other identifiable body parts having physical features that allow gender and age estimation by conventional methods. The different biometrics traits such as face, gait, iris, speech and fingerprint are used to identify the gender and age. Among the biometrics, fingerprint is most commonly available in any crime scene. In this study, an efficient algorithm to identify the gender of a given fingerprint into male or female is proposed. The two most efficient techniques are utilized to enhance the performance of the gender classification system. As the first step, Un-decimated Wavelet Transform (UWT) is employed to extract the features from the fingerprints by applying ranking. Secondly, Gaussian Mixture Models (GMMs) technique is used as classifier for the process of gender classification. The proposed system is carried out with the database of 180 persons finger prints of all fingers in which 80 are female and 100 are male. The results show the satisfactory classification accuracy of over 90%.
Characterization of PbPga1, an Antigenic GPI-Protein in the Pathogenic Fungus Paracoccidioides brasiliensis

Paracoccidioides brasiliensis is the etiologic agent of paracoccidioidomycosis (PCM), one of the most prevalent mycosis in Latin America. P. brasiliensis cell wall components interact with host cells and influence the pathogenesis of PCM. Cell wall components, such as glycosylphosphatidylinositol (GPI)-proteins play a critical role in cell adhesion and host tissue invasion. Although the importance of GPI-proteins in the pathogenesis of other medically important fungi is recognized, little is known about their function in P. brasiliensis cells and PCM pathogenesis. We cloned the PbPga1 gene that codifies for a predicted GPI-anchored glycoprotein from the dimorphic pathogenic fungus P. brasiliensis. PbPga1 is conserved in Eurotiomycetes fungi and encodes for a protein with potential glycosylation sites in a serine/threonine-rich region, a signal peptide and a putative glycosylphosphatidylinositol attachment signal sequence. Specific chicken anti-rPbPga1 antibody localized PbPga1 on the yeast cell surface at the septum between the mother cell and the bud with stronger staining of the bud. The exposure of murine peritoneal macrophages to rPbPga1 induces TNF-α release and nitric oxide (NO) production by macrophages. Furthermore, the presence of O-glycosylation sites was demonstrated by β-elimination under ammonium hydroxide treatment of rPbPga1. Finally, sera from PCM patients recognized rPbPga1 by Western blotting indicating the presence of specific antibodies against rPbPga1. In conclusion, our findings suggest that the PbPga1gene codifies for a cell surface glycoprotein, probably attached to a GPI-anchor, which may play a role in P. brasiliensis cell wall morphogenesis and infection. The induction of inflammatory mediators released by rPbPga1 and the reactivity of PCM patient sera toward rPbPga1 imply that the protein favors the innate mechanisms of defense and induces humoral immunity during P. brasiliensis infection.
Profit Measurement of Menu Items

The long-time calculation for gross profit of a menu item is selling price less food cost, but such other inputs as labor and energy are not negligible. Moreover, not only are labor and energy usually not included in the calculation, but food costs are often not updated frequently as menu items and recipes change, owing to the complexity of making the update. A survey of operators of Chinese restaurants in Hong Kong (freestanding chain restaurants, as well as restaurants in hotels and clubs) found that the respondents support the idea of updating menu costs and considering labor and energy expenses. However, the difficulties of measuring the inputs, including numerous uninventoried food items typical of Chinese cooking, undermine a more precise profit calculation of menu items in Chinese restaurants in Hong Kong.
Role of repair protein Rad51 in regulating the response to gefitinib in human non-small cell lung cancer cells

Gefitinib (Iressa, ZD1839) is a selective epidermal growth factor receptor tyrosine kinase inhibitor that can block growth factor-mediated cell proliferation and extracellular signal-regulated kinases 1/2 (ERK1/2) activation. High-level Rad51 expression has been reported in chemoresistant or radioresistant carcinomas. In this study, we examined the role of Rad51 in regulating the response to gefitinib among different human lung cancer cell lines. The H520 line (human squamous cell carcinoma) was less sensitive to gefitinib compared with the H1650 (human adenocarcinoma) or A549 (human bronchioloalveolar carcinoma) lines. In H1650 and A549 cells but not in H520 cells, gefitinib decreased cellular levels of phospho-ERK1/2 and Rad51 protein and message levels. Moreover, gefitinib decreased Rad51 protein levels by enhancing Rad51 protein instability through 26S proteasome-mediated degradation. Inhibition of endogenous Rad51 levels by si-Rad51 RNA transfection significantly enhanced gefitinib-induced cytotoxicity. In contrast, transfection with constitutively active MKK1 vector could restore both Rad51 protein levels and cell survival inhibited by gefitinib. The MKK1/2-ERK1/2 signaling pathway constitutes the upstream signaling for maintaining Rad51 message and protein levels. Rad51 protein can protect lung cancer cells from cytotoxic effects induced by gefitinib. Suppression of Rad51 may be a novel lung cancer therapeutic modality to overcome drug resistance to gefitinib. [Mol Cancer Ther 2008;7(11):3632–41]
Methods for the semantic analysis of document markup

We present an approach on how to investigate what kind of semantic information is regularly associated with the structural markup of scientific articles. This approach addresses the need for an explicit formal description of the semantics of text-oriented XML-documents. The domain of our investigation is a corpus of scientific articles from psychology and linguistics from both English and German online available journals.For our analyses, we provide XML-markup representing two kinds of semantic levels: the thematic level (i.e.\ topics in the text world that the article is about) and the functional or rhetorical level. Our hypothesis is that these semantic levels correlate with the articles' document structure also represented in XML. Articles have been annotated with the appropriate information. Each of the three informational levels is modelled in a separate XML document, since in our domain, the different description levels might conflict so that it is impossible to model them within a single XML document.For comparing and mining the resulting multi-layered\linebreak XML annotations of one article, a Prolog-based approach is used. It focusses on the comparison of XML markup that is distributed among different documents. Prolog predicates have been defined for inferring relations between levels of information that are modelled in separate XML documents. We demonstrate how the Prolog tool is applied in our corpus analyses.
Individual and Combined Effects of Methamphetamine and Ketamine on Conditioned Place Preference and NR1 Receptor Phosphorylation in Rats

Methamphetamine (MA), a commonly abused psychostimulant, induces the drug dependence by enhancing the dopamine-mediated neurotransmission. Ketamine (KET) is a non-competitive N-methyl-D-aspartate receptor antagonist, which can be actually mixed with MA for polydrug abuse. In the present study, the individual and combined effects of KET (10 mg/kg, i.p.) and MA (1 mg/kg, i.p.) on conditioned place preference in rats were investigated. The alterations of serine 897 phosphorylations of NR1 receptors in the striatum and ventral tegmental area of after-conditioning rats were measured immunochemically. The results showed repeated administrations of MA, KET and their combination, at the doses studied, all could induce psychological dependences evaluated by conditioned place preference. KET was not able to suppress the MA-induced place preference. The modulations of NR1 phosphorylations in basal ganglia were partly responsible to place preference. Although the alterations induced by KET were not significant in most areas we studied, MA showed a significant increase in the ventral tegmental area but a marked decrease in caudate putamen and nucleus accumbens. Such alterations were much more significant when KET and MA were combined. These results have important implications for public awareness of harm with combined drug abuse. Further investigations toward the specific interaction of the two drugs are necessary.
The 5th international workshop on pervasive eye tracking and mobile eye-based interaction

Previous work on eye tracking and eye-based human-computer interfaces mainly concentrated on making use of the eyes in traditional desktop settings. With the recent growth of interest in smart eyewear and low-cost mobile eye trackers, gaze-based techniques for mobile computing is becoming increasingly important. PETMEI 2015 focuses on the pervasive eye tracking paradigm as a trailblazer for mobile eye-based interaction and eye-based context-awareness. We want to stimulate and explore the creativity of these communities with respect to the implications, key research challenges, and new applications for pervasive eye tracking in ubiquitous computing. The long-term goal is to create a strong interdisciplinary research community linking these fields together and to establish the workshop as the premier forum for research on pervasive eye tracking.
OPEED: Optimal energy-efficient neighbor discovery scheme in opportunistic networks

In opportunistic networks, it is difficult to predict when a node encounters others and how long it keeps in contact with another. Nodes continually attempt to explore neighbor nodes in the vicinity to transmit data. In battery-operated devices, this persistent exploration consumes a great deal of energy. In this paper, we propose an optimal energy-efficient neighbor discovery scheme (OPEED) that guarantees neighbor discovery within a delay bound. Through performance evaluation, we show that the OPEED scheme consumes 33%-83% less energy than other schemes.