Miracle-dz/UniFAR-FTUs huggingface dataset:
Face Recognition Based on Covering Algorithm and PLS

This paper proposes a new approach of human face recognition using partial least square (PLS) and covering algorithm. PLS constructs the component so that the correlation between the class variable and themselves maximized. Covering algorithm is a kind of neural network method. The approach first processes the image with wavelet transform, and then eliminates the redundant features with PLS. It reduces the dimension of image by extracting the principal features. Finally, classifies the image by covering algorithm
Developing a PoS-tagged corpus using existing tools

In this paper, we describe the development of a new tagged corpus of Icelandic, consisting of about 1 million tokens. The goal is to use the corpus, among other things, as a new gold standard for training and testing PoS taggers. We describe the individual phases of the corpus construction, i.e. text selection and cleaning, sentence segmentation and tokenisation, PoS tagging with a combination method, error detection, and error correction. Furthermore, we discuss what problems have emerged, highlight which software tools have been found to be useful, and identify which tools are re-usable across different languages. Our preliminary evaluation results show that the error detection programs are effective and that our tagger combination method is crucial with regard to the amount of hand-correction that must be carried out in future work. We believe that our work will be of help to those wishing to develop similar resources for less-resourced languages.
New Detection of Peer-to-Peer Controlled Bots on the Host

Nowadays, Peer-to-Peer controlled (P2P-controlled) bots became an increasing threat to our network. Compared with traditional bots which rely on Internet Relay Chat (IRC) server, P2P-controlled bots spread much faster and construct the botnets with better robustness. The infected machine can be remotely controlled by the attacker to perform some malicious activities such as Distributed Denial of Service (DDoS) or email spamming. However, few bots detection techniques, especially aiming at P2P- controlled bots, have been developed to date. In this paper, we proposed a general way to detect P2P-controlled bots on the host. Our approach combines detections of malicious behaviors and P2P communication together. API function calls and P2P traffics generated by a specific bot are monitored dynamically during the specific time-window to achieve the detection. We perform a range of experiments with different dataset. The results show that our approach is effective to detect P2P-controlled bots on the host. Keywords-P2P-controlled bots, malicious behaviors, P2P communication, API function calls, P2P behavior model
14-3-3 Proteins Are Required for Maintenance of Raf-1 Phosphorylation and Kinase Activity

ABSTRACT By binding to serine-phosphorylated proteins, 14-3-3 proteins function as effectors of serine phosphorylation. The exact mechanism of their action is, however, still largely unknown. Here we demonstrate a requirement for 14-3-3 for Raf-1 kinase activity and phosphorylation. Expression of dominant negative forms of 14-3-3 resulted in the loss of a critical Raf-1 phosphorylation, while overexpression of 14-3-3 resulted in enhanced phosphorylation of this site. 14-3-3 levels, therefore, regulate the stoichiometry of Raf-1 phosphorylation and its potential activity in the cell. Phosphorylation of Raf-1, however, was insufficient by itself for kinase activity. Removal of 14-3-3 from phosphorylated Raf abrogated kinase activity, whereas addition of 14-3-3 restored it. This supports a paradigm in which the effects of phosphorylation on serine as well as tyrosine residues are mediated by inducible protein-protein interactions.
Genome-wide identification of in vivo protein–DNA binding sites from ChIP-Seq data

ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with ultra high-throughput massively parallel sequencing, is increasingly being used for mapping protein–DNA interactions in-vivo on a genome scale. Typically, short sequence reads from ChIP-Seq are mapped to a reference genome for further analysis. Although genomic regions enriched with mapped reads could be inferred as approximate binding regions, short read lengths (∼25–50 nt) pose challenges for determining the exact binding sites within these regions. Here, we present SISSRs (Site Identification from Short Sequence Reads), a novel algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments. The sensitivity and specificity of SISSRs are demonstrated by applying it on ChIP-Seq data for three widely studied and well-characterized human transcription factors: CTCF (CCCTC-binding factor), NRSF (neuron-restrictive silencer factor) and STAT1 (signal transducer and activator of transcription protein 1). We identified 26 814, 5813 and 73 956 binding sites for CTCF, NRSF and STAT1 proteins, respectively, which is 32, 299 and 78% more than that inferred previously for the respective proteins. Motif analysis revealed that an overwhelming majority of the identified binding sites contained the previously established consensus binding sequence for the respective proteins, thus attesting for SISSRs’ accuracy. SISSRs’ sensitivity and precision facilitated further analyses of ChIP-Seq data revealing interesting insights, which we believe will serve as guidance for designing ChIP-Seq experiments to map in vivo protein–DNA interactions. We also show that tag densities at the binding sites are a good indicator of protein–DNA binding affinity, which could be used to distinguish and characterize strong and weak binding sites. Using tag density as an indicator of DNA-binding affinity, we have identified core residues within the NRSF and CTCF binding sites that are critical for a stronger DNA binding.
CONTINUOUS SPEECH RECOGNITION WITH PHASE-CORRECTED RASTA

Phase-corrected RASTA is a new technique for channel normalisation that consists of classical RASTA filtering followed by a phase correction operation. In this manner, the channel bias is as effectively removed as with classical RASTA, without introducing a left-context dependency. The performance of the phase-corrected RASTA channel normalization technique was evaluated for a continuous speech recognition task. Using context-independenthidden Markov models we found that phase-corrected RASTA reduces the bestsentence word error rate (WER) by 10% compared to classical RASTA. Using a version of phase-corrected RASTA suited for real-time implementation WER was reduced by 7:5% compared to classical RASTA.
Constraint-based Design Critic for Flat-pack Furniture Design

This paper reports on the Flat-pack Furniture Design Critic (FFDC). By analyzing the literature of architecture education, we have identified critiquing methods: delivery types (interpretation, introduction, example, demonstration, and evaluation) and communication modalities (written comments, graphical annotations, and images). Our FFDC uses these methods to deliver feedback. This paper also presents how our FFDC system selects particular methods by considering a certain condition such as user’s knowledge level and the previously used methods.
Secure In-Session Attachment Predicts Rupture Resolution: Negotiating a Secure Base

Decades of work by Jeremy Safran and his colleagues have established that ruptures in the therapeutic alliance are not necessarily obstacles to the treatment, and that the process of repairing these events has the potential to deepen the therapeutic relationship and promote change. The field of alliance rupture research has largely focused on therapists’ role in repairing ruptures or patient characteristics associated with greater rupture frequency, with little research on how the patient contributes to rupture repair. This study examines the predictive relationship between patients’ attachment and the report of the rupture resolution process over the course of treatment. Patients’ attachment was measured with the Patient Attachment Coding System (PACS), which assesses patients’ attachment as different ways of communicating about present internal experience during the session. Alliance ruptures were measured via self-report items on a postsession questionnaire. Results show that secure in-session attachment is associated with higher ratings of rupture repair, according to both patients and therapists, and that the link between secure in-session attachment and repair increased when ruptures were more intense.
Development and Laboratory Testing of a Noninvasive Intracranial Focused Hyperthermia System

During the past two decades, a great deal of research has been carried out with the aim of developing effective techniques for hyperthermia treatment, primarily using RF, microwave, and ultrasound energy. A system for deep brain hyperthermia treatment, designed to also provide passive measurements of temperature and/or conductivity variations inside the human body, is presented in this paper. The proposed system comprises both therapeutic and diagnostic modules, operating in a totally contactless way, based on the use of an ellipsoidal beamformer to achieve focusing on the areas under treatment and monitoring. In previous publications, the performance of the system's diagnostic module in phantom, animal, and human studies has been reported. In the current research, new theoretical and experimental results using the therapeutic hyperthermia module of the system are presented. The main scope of the theoretical analysis is the improvement of the system's focusing attributes. Moreover, phantom experimental results verify the proof of concept. Both computation and phantom measurement results show that deep focused brain hyperthermia may be achievable with adequate spatial resolution and sensitivity using the proposed methodology, subject to the appropriate combination of operation frequency and low-loss dielectric material used as filling in the ellipsoidal.
INSIGHT Galway: Syntactic and Lexical Features for Aspect Based Sentiment Analysis

This work analyses various syntactic and lexical features for sentence level aspect based sentiment analysis. The task focuses on detection of a writer’s sentiment towards an aspect which is explicitly mentioned in a sentence. The target sentiment polarities are positive, negative, conflict and neutral. We use a supervised learning approach, evaluate various features and report accuracies which are much higher than the provided baselines. Best features include unigrams, clauses, dependency relations and SentiWordNet polarity scores.
Modelling Human Variation in Assembly Line Models

A method and container assembly for storing toxic material. An original container of toxic material is positioned within a first container and is insulated therefrom by sealant material. The first container is in turn inserted into an outside container and spaced therefrom by additional sealant material. Relief valves are positioned on the containers to allow complete filling of the space between containers with sealant material. A cap is sealingly mounted to the outside container and is fixedly secured to the first container.
Generating Molecular Database using BioComputing Approach

In this paper, case study of diabetes is taken and a new algorithm GIGC is proposed which is the modified form glucose insulin meal GIM model. Diabetes occurs when blood glucose levels are too higher than normal. Type two diabetes also known as mellitus has exceeded its growth to a large extent worldwide, and its impact on global health care problem has increased the interest of the scientific community to design algorithms that could be applied on real time patient and benefit the medical field.In this paper, variation in insulin sequence is combined to glucose insulin meal simulation model to develop a modified algorithm. Glucose insulin meal simulation software doesn’t simulate for T2D. The new algorithm GIGC has been implemented using glucose insulin meal software in which genetic variation along with insulin glucose secretion dynamically are combined.
Association between the PPARGC1A polymorphism and aerobic capacity in Japanese middle-aged men.

OBJECTIVE A lower frequency for the peroxisome proliferator-activated receptor γ coactivator 1α (PPARGC1A) Ser482 allele has been reported in elite-level endurance athletes among Caucasians, although this gene polymorphism has not been found to be associated with aerobic capacity in German, Dutch or Chinese populations. The purpose of the current study was to examine the associations between the Gly482Ser polymorphism and aerobic fitness in 112 Japanese middle-aged men. METHODS The PPARGC1A Gly482Ser polymorphism was identified according to a TaqMan(®) SNP genotyping assay. Habitual physical activity was objectively measured using an accelerometer. The lactate threshold (LT), an index of aerobic fitness, was measured based on a submaximal graded exercise test performed on an electric cycle ergometer. The association between the LT and the Gly482Ser polymorphism was assessed according to a multiple regression analysis and analysis of covariance, with adjustment for potential confounders (age, body mass index, cigarette smoking, physical activity level and regular exercise). RESULTS A significant association was observed between the PPARGC1A Gly482Ser polymorphism and LT, as carriers of the Ser482 had higher LT values than the Gly482 carriers. CONCLUSION The current results suggest that the PPARGC1A Ser482 allele is associated with a higher aerobic capacity in Japanese middle-aged men.
The NADPH Oxidase Inhibitor Imipramine-Blue in the Treatment of Burkitt Lymphoma

Burkitt lymphoma is a rare malignancy arising from B cells. Current chemotherapeutic regimens achieve excellent overall survival rates in children, but less impressive rates in adults. There are cases with poor outcome caused by toxic effects of the therapy, tumor lysis syndrome, or metastatic spread of lymphomas to the central nervous system. Modulators of reactive oxygen species are currently discussed as potential drugs for the treatment of cancer. The NADPH oxidase 4 inhibitor imipramine-blue might satisfy the aforementioned requirements, and was studied here. We used MTT assay, crystal violet assay, and thymidine 3H-incorporation assay to analyze the effects of imipramine-blue on Burkitt lymphoma (BL2, BL2B95, BL30B95, BL41B95), neuroblastoma (KELLY, SH-SY5Y, SMS-KAN), cervix carcinoma (HeLa), breast cancer (MDA-MB231), angiosarcoma (AS-M), human embryonic kidney (HEK293WT), and nonmalignant (FLP1) cell lines. The effects of imipramine-blue on BL2B95 cells in vivo were investigated in xenografts on the chick chorioallantoic membrane (CAM). We report that imipramine-blue is a potent growth inhibitor for several cancer cell lines in vitro with IC50 values comparable to those of doxorubicin (0.16–7.7 μmol/L). Tumor size of BL2B95 cells inoculated in the CAM was reduced significantly (P < 0.05) after treatment with 10 μmol/L imipramine-blue. Lymphogenic dissemination of BL2B95 and the formation of blood and lymphatic vessels in experimental tumors were not affected. We show that imipramine-blue can be used to decrease the viability of cancer cell lines in vitro and in vivo. Imipramine-blue reduces the size of experimental Burkitt lymphoma significantly but does not affect the dissemination of BL2B95 cells, angiogenesis, and lymphangiogenesis. Mol Cancer Ther; 13(4); 833–41. ©2014 AACR.
Interactive volume visualization and editing methods for surgical applications

Volumetric imaging modalities are increasingly being used in surgical applications. However, visualizing the 3D information contained in these datasets effectively on a 2D display is a challenging problem. Most important issues to overcome are the occlusion of different anatomical features of each other and the difficulty of visualizing the depth information of a given pixel in a 2D image. Moreover, the resulting image is aimed to be used to guide actions performed on the patient, therefore the mental registration of real and virtual spaces has to be considered when designing visualization and interaction approaches. This work proposes an interactive focus + context visualization method that uses the Magic Lens interaction scheme to select important parts of volumetric datasets while displaying the rest of the dataset to provide context for the mental registration process. The Magic Lens paradigm is extended to handle arbitrarily shaped selection volumes, enabling interactive volume editing to visualize different anatomical structures from multiple datasets in a single coherent view. Capabilities of modern graphics hardware are used to achieve real time frame rates. The implementation of these methods introduces novel technical contributions to view and to select arbitrarily shaped sub-volumes in real-time using polygon-assisted raycasting using meshes as proxies to store selection information. These approaches enable sub-voxel accuracy in selecting and rendering volumetric regions using significantly smaller storage space compared to using lookup volume textures for selection. Proposed methods are applied to a gesture-based interaction interface, and user studies are undertaken to evaluate the effectiveness and intuitiveness of this interface in volume rotation and target localization tasks.
Mass and inertia optimization for natural motion in hands-on robotic surgery

In hands-on robotic surgery, the surgeon controls the motion of a tool mounted on the end effector by applying forces directly to the robot. The mass and inertia properties of the robot at the end effector thus contribute to the ability of the surgeon to move the tool and consequently, the performance of the surgery. As redundant robots have varying mass/inertia properties for different configurations at the same position and orientation of the end effector, we present optimizations which affect the inertial properties to improve the surgeon's movement capabilities. A method for optimizing the overall belted mass/inertia ellipsoids based on the determinant of the inverse pseudo kinetic energy matrices is presented, along with a method for optimizing the effective mass/inertia in a particular direction. Using a gradient based controller operating in the null-space of the end effector position and orientation, the measures are optimized to the local optima without affecting the surgeon's desired tool pose. Through simulation, the efficacy of the method is demonstrated and a comparison with two standard approaches to redundancy resolution is performed. Lastly, a pre-optimized solution is shown to be effective for heavily constrained environments which prevent active optimization.
Luminal Breast Cancer Cell Lines Overexpressing ZNF703 Are Resistant to Tamoxifen through Activation of Akt/mTOR Signaling

Background Selective estrogen receptor modulators, such as tamoxifen, play a pivotal role in the treatment of luminal-type breast cancer. However, in clinical applications, nearly half of breast cancer patients are insensitive to tamoxifen, a small number of whom have early recurrence or disease progression when receiving tamoxifen. The underlying mechanism of this resistance has not been determined. ZNF703 is a novel oncogene in the 15% of breast cancers that harbor 8p12 amplifications. Therefore, the goal of our study was to explore the role of ZNF703 in tamoxifen resistance. Methodology/Principal Findings We used immunohistochemistry techniques to examine ZNF703 expression in stage I-III primary breast cancer specimens and found a positive expression rate of 91.3%. All patients were divided into either high or low ZNF703 expression groups. We found that high ZNF703 expression mainly occurred in ER+ and PR+ breast cancers. Furthermore, 4-hydroxytamoxifen had different modes of action in breast cancer cell lines with high or low ZNF703 expression. ZNF703 overexpression in MCF-7 breast cancer cells activated the Akt/mTOR signaling pathway, downregulated ERα, and reduced the antitumor effect of tamoxifen. Low-dose tamoxifen did not suppress, but rather, stimulated the growth of cells overexpressing ZNF703. ZNF703 knockdown in MDA-MB-134 and HCC1500 luminal B-type breast cancer cell lines by siRNA significantly decreased survival rates when cells were treated with tamoxifen. Furthermore, targeting ZNF703 with a mTOR inhibitor increased the inhibitory effects of tamoxifen in ZNF703-overexpressing cells. Conclusion/Significance Our study suggests that ZNF703 expression levels may predict tamoxifen sensitivity. Tamoxifen should be administered with caution to those patients bearing tumors with ZNF703 overexpression. However, large clinical trials and prospective clinical studies are needed to verify these results.
Neutrino mass hierarchy and three-flavor spectral splits of supernova neutrinos

It was recently realized that three-flavor effects could peculiarly modify the development of spectral splits induced by collective oscillations, for supernova neutrinos emitted during the cooling phase of a protoneutron star. We systematically explore this case, explaining how the impact of these three-flavor effects depends on the ordering of the neutrino masses. In inverted mass hierarchy, the solar mass splitting gives rise to instabilities in regions of the (anti)neutrino energy spectra that were otherwise stable under the leading two-flavor evolution governed by the atmospheric mass splitting and by the 1-3 mixing angle. As a consequence, the high-energy spectral splits found in the electron (anti)neutrino spectra disappear, and are transferred to other flavors. Imperfect adiabaticity leads to smearing of spectral swap features. In normal mass hierarchy, the three-flavor and the two-flavor instabilities act in the same region of the neutrino energy spectrum, leading to only minor departures from the two-flavor treatment.
Energy consumption-based performance tuning of software and applications using Particle Swarm Optimization

Software development is increasing amidst of various emerging concerns for new technological trends, namely, grids, clouds, and HPC. However, Software developers of such technologies, to be more specific, are concerned about the performance aspects of their code - for instances, the developers are worried about the memory leakage, pipeline stalls, cache misses, and so forth. Recently, energy consumption analysis and tuning of software/applications have enabled a wide research spectrum among HPC research community. This research is crucial for developing an eco-friendly compute machines. In this scenario, our paper reveals a methodology which does energy consumption-based tuning of software and applications when Particle Swarm Optimization (PSO) algorithm was used in EnergyAnalyzer. EnergyAnalyzer is an online-based energy analysis tool which is a Department of Science and Technology, India, funded ongoing project. The research study was carried out in HPCCLoud Research Laboratory of our premise which comprises of a HP ProLiant 48 core compute machine.