Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly Efficient and Consistent Gene Transfer into Dendritic Cells Utilizing a Combination of Ultraviolet-irradiated Adenovirus and Poly ( L-Lysine ) Conjugates 1

Dendritic cells (DCs) are capable of presenting tumor-associated anti gens and subsequently play an essential role in T-cell activation. The aim of this study was to develop an efficient method for gene transfer into DCs. These genetically transduced DCs can then be used as potent inducers of specific cell-mediated immune response. When compared with physical methods for gene transfer (lipofection and calcium phosphate precipita tion), adenovirus (AdV) vectors proved to be highly efficient for gene transfer into DCs. To overcome concomitant AdV gene expression and potential immunogenicity, AdVs were irradiated with I \. The UV dose was optimized to block AdV transcription without altering AdV receptor binding and endocytosis capacity. We subsequently used a polycationic amino acid compound, poly(L-lysine), to conjugate the irradiated AdVs to transgenes. The resulting complexes were found to mediate a highly efficient transfer of transgenes into DCs, without concomitant expression of AdV gene products. Low titers of irradiated AdVs were sufficient for a consistent gene transfer into DCs. This is the first study to demonstrate efficient, consistent, and practical gene transfer using an UV approach to irradiated AdV-poly(i.-lysine) conjugates and should be useful for the development of DC-based tumor vaccine therapies.
PENGARUH LATIHAN TRAINING RESISTENSE XANDER TERHADAP KEMAMPUAN TENDANGAN SABIT PENCAK SILAT

Penelitian ini bertujuan untuk mengetahui pengaruh latihan Training Resistense Xander (TRX) terhadap kemampuan tendangan sabit raga pencak silat.Metode yang digunakan dalam penelitian ini adalah metode experiment dengan desain rancangan blok lengkap One group pretest-post testdesign . Instrumen penelitian ini adalah tes tendangan pencak silat, denganteknik analisis data yang digunakan Uji-t. Kesimpulan penelitian ini adalah sebagai berikut: Terdapat pengaruh yang signifikan dari Metode Latihan TRX Terhadap kemampuan tendangan sabit, terbukti bahwa nilai t hitung 25,44 > t tabel 2,13. Kata kunci : latihan, Training Resistense Xander, tendangan sabit, pencak silat.
Systematic Construction of Real Lapped Tight Frame Transforms

We present a constructive algorithm for the design of real lapped equal-norm tight frame transforms. These transforms can be efficiently implemented through filter banks and have recently been proposed as a redundant counterpart to lapped orthogonal transforms, as well as an infinite-dimensional counterpart to harmonic tight frames. The proposed construction consists of two parts: First, we design a large class of new real lapped orthogonal transforms derived from submatrices of the discrete Fourier transform. Then, we seed these to obtain real lapped tight frame transforms corresponding to tight, equal-norm frames. We identify those frames that are maximally robust to erasures, and show that our construction leads to a large class of new lapped orthogonal transforms as well as new lapped tight frame transforms.
The CFT dual of AdS gravity with torsion

We consider the Mielke–Baekler model of three-dimensional AdS gravity with torsion, which has gravitational and translational Chern–Simons terms in addition to the usual Einstein–Hilbert action with cosmological constant. It is shown that the topological nature of the model leads to a finite Fefferman–Graham expansion. We derive the holographic stress tensor and the associated Ward identities and show that, due to the asymmetry of the left- and right-moving central charges, a Lorentz anomaly appears in the dual conformal field theory. Both the consistent and the covariant Weyl and Lorentz anomaly are determined, and the Wess–Zumino consistency conditions for the former are verified. Moreover we consider the most general solution with flat boundary geometry, which describes left- and right-moving gravitational waves on AdS3 with torsion, and show that in this case the holographic energy–momentum tensor is given by the wave profiles. The anomalous transformation laws of the wave profiles under diffeomorphisms preserving the asymptotic form of the bulk solution yield the central charges of the dual CFT and confirm the results that appeared earlier on in the literature. Finally we comment on some points concerning the microstate counting for the Riemann–Cartan black hole.
The Response of Hemostatic Marker Levels to Activated Factor VII in a Neonate following Cardiopulmonary Bypass

The primary function of recombinant activated factor VII (rFVIIa) is to increase thrombin formation which leads to increased fibrin and less “bleeding. ” As a result, most of literature utilizes “bleeding” as the outcome measure with respect to rFVIIa. However, we report the actual effect of rFVIIa on changes in hemostatic markers such as prothrombin activation peptide F1.2, thrombin antithrombin complex (TAT), D-dimer, tissue plasminogen activator (tPA), and plasminogen activator inhibitor (PAI) in a neonate after cardiopulmonary bypass. A single dose of rFVIIa caused a 5.5-fold increase in F1.2, 3.5-fold increase in TAT, and a small increase in d-dimer compared to only a 1.5-fold increase, no increase, and a decrease, respectively, in two neonates undergoing the same procedure having not received rFVIIa. The patterns of change for tPA and PAI were similar.
Neural Network Forecasting with High Performance Computers

Distributed computing allows to combine the computing power of miscellaneous computers. These computers may be at different locations as long as they are connected via a network, e. g. the Internet or an intranet. In this paper the development of a distributed computing version of the neurosimulator FAUN (F ast Approximation with U niversal Neural N etworks) is described. This offers the opportunity to use free computing resources, e. g. of a student and staff computer cluster. An easy to install client is part of the development work. The combined computation power is necessary for, e. g. , fast forecasting or fast simulation problems to be solved with FAUN which would otherwise take hours or days on a single processor computer. Problems which computation time can be shortened significantly by distributed computing with FAUN include, but are not limited to, dynamic games, robust optimal reentry guidance of a space shuttle and currency forecasting.
Corpus-Based Study of Language and Teacher Education

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. Corpus-based study of language and teacher education Alex Boulton, Henry Tyne
Interactive Virtual-Reality Driven Learning Framework for Engineering and Science Education

The University of Texas at San Antonio has established a cutting edge Advanced Visualization Lab ( http://vislab.utsa.edu ) that consists of a large-scale high-resolution VizWall powered by a hybrid CPU/GPU LINUX cluster with 6,000 processors, and various latest visualization technology including large screen 3D stereoscopic display, immersive 3D Oculus Rift virtual reality device, Google Glass, multi-touch visual control, Lean Motion gesture control, haptic control devices, Kinect enabled model control as well as laser scanner and 3D printers. It provides us a comprehensive visualization facility capable of building a simulation and visualization pipeline from start to finish. In this paper, we first present a general framework on how to develop and integrate some of the visualization devices into the large-scale (14.5 x 6 ft 2 ) high-resolution (98 Mpixels) VizWall for interactive learning. Then, we discuss a few application examples that are built on this platform include classical engineering beam deformation, biomedical virtual surgery simulation, artistic application with Kinect to track a dancer so that a live video mask can be interactively controlled by the dancer's movements, as well as a football kicking simulation system to provide interactive visual-based feedback to both players and coaches with model-based coaching techniques for performance improvement and injury mitigation. With rapid advancement of today's technology, it can make learning of various subjects of engineering and science more interesting and effective by designing interactive and visually stimulating curricula.
In vivo reconstitution of autophagy in Saccharomyces cerevisiae

Autophagy is a major intracellular degradative pathway that is involved in various human diseases. The role of autophagy, however, is complex; although the process is generally considered to be cytoprotective, it can also contribute to cellular dysfunction and disease progression. Much progress has been made in our understanding of autophagy, aided in large part by the identification of the autophagy-related (ATG) genes. Nonetheless, our understanding of the molecular mechanism remains limited. In this study, we generated a Saccharomyces cerevisiae multiple-knockout strain with 24 ATG genes deleted, and we used it to carry out an in vivo reconstitution of the autophagy pathway. We determined minimum requirements for different aspects of autophagy and studied the initial protein assembly steps at the phagophore assembly site. In vivo reconstitution enables the study of autophagy within the context of the complex regulatory networks that control this process, an analysis that is not possible with an in vitro system.
Gene Ontology Annotation Using Word Proximity Relationship

In this paper, we propose an approach for doing Gene Ontology (GO) annotation on full-text biomedical articles. This system explores the word proximity relationship between genes and GO terms. We associate genes and GO terms by considering the density function between gene-GO pairs in a paragraph. Different density models are built and several evaluation criteria are employed to assess the effects of the proposed methods. In the best case, we got a precision of < 88% and a recall of < 12%.
Redistributing Data Worlds: Open Data, Data Infrastructures and Democracy (Quand les mondes de données sont redistribués: Open Data, infrastructures de données et démocratie)

L’open data, defini comme un ensemble d’idees et de conventions qui transforment l’information en une ressource publique reutilisable, est promu pour des objectifs varies : ameliorer la transparence des institutions publiques, creer des projets qui renforcent la democratie, stimuler la croissance economique. Les infrastructures sociales et techniques qui soutiennent l’open data recomposent les « mondes de donnees » : de nouveaux collectifs sociaux se forment, de nouvelles pratiques creatrices de sens apparaissent. Des initiatives politiques transnationales voient le jour. Loin d’etre une simple « liberation » des donnees, cela ne va pas sans traduction, mediation, et de nouvelles pratiques sociales. Mais ce mouvement peut-il servir de base d’une deliberation democratique plus riche, ou est-il voue a institutionnaliser socialement diverses formes de bureaucratisation et de marchandisation ?
Speaker Identification Using Whispered Speech

The study of closed set text-independent speaker identification using whisper speech is presented in this paper. A new feature called temporal Teager energy based sub band cepstral coefficients (TTESBCC) is proposed. The work presented compares the performance of four feature sets: Mel frequency cepstral coefficients (MFCC), temporal energy of sub band cepstral coefficients (TESBCC), weighted instantaneous frequency (WIF) and TTESBCC. Next, outputs of three classifiers are combined and its performance is compared with that of the individual classifiers. The speaker identification system is trained using neutral speech and tested using neutral and whisper speech. The database of twenty five speakers containing speech utterances recorded in one of the Indian languages (Marathi) in the neutral and whisper environments is used for experimentation. Gaussian mixture model is used for classification. It is observed that performance of the speaker identification system degrades drastically when tested using whisper speech utterances. Fusion of classifiers enhances the speaker identification accuracy in both whisper and neutral environment.
LT3: Sentiment Analysis of Figurative Tweets: piece of cake #NotReally

This paper describes our contribution to the SemEval-2015 Task 11 on sentiment analysis of figurative language in Twitter. We considered two approaches, classification and regression, to provide fine-grained sentiment scores for a set of tweets that are rich in sarcasm, irony and metaphor. To this end, we combined a variety of standard lexical and syntactic features with specific features for capturing figurative content. All experiments were done using supervised learning with LIBSVM. For both runs, our system ranked fourth among fifteen submissions.
Assessing Reading Ability for Psychological Testing in Forensic Assessments: An Investigation with the WRAT-4 and MMPI-2-RF

ABSTRACT This study examined the association between two measures of WRAT-4 reading ability—Word Reading and Sentence Comprehension—and two well-validated measures of inconsistent responding—MMPI-2-RF Variable Response Inconsistency (VRIN-r) and True Response Inconsistency (TRIN-r) among 136 forensic inpatients (90 men, 46 women). It was hypothesized that WRAT-4 Sentence Comprehension would demonstrate stronger associations with VRIN-r than WRAT-4 Word Reading. It was also hypothesized that there may be a minimal association between Sentence Comprehension and TRIN-r. Although WRAT-4 Word Reading was not significantly correlated with VRIN-r (rs = −.17, p = .07) or TRIN-r (rs = −.10, p = .31), Sentence Comprehension was significantly correlated with VRIN-r (rs = −.27, p = .01). A hierarchical regression predicting VRIN-r scores indicated that WRAT-4 Sentence Comprehension significantly accounted for an additional 5.4% of the variance in VRIN-r scores after accounting for self-reported education level and Word Reading (p = .03). However, Word Reading did not significantly account for any additional variance in VRIN-r after accounting for Education and Sentence Comprehension (incremental R2 = .001, p = .74). These results suggest that Sentence Comprehension (rather than Word Reading) should be assessed prior to administering psychological testing, especially in forensic settings.
Advanced near field communication with resonant coupling

Near Field Communication (NFC) applied with resonant coupling would lead to an innovative improvements such as power transfer efficiency and robustness, which can be most suitable for medical applications. However, there are several technical issues of the conventional NFC system that makes it difficult to apply resonant coupling. One of the critical issues is that the system performance becomes excessively sensitive to impedance matching and bandwidth of its antenna. In this paper, we propose a novel high-Q NFC system that overcomes the limitations of applying resonant coupling to conventional NFC system. As a result, the high-Q NFC system showed remarkable improvement in energy efficiency. Moreover, the high-Q NFC system showed perfect compatibility with conventional NFC system, while it quadrupled the power transmission efficiency.
Detection of Tick-Borne Pathogens in the Korean Water Deer (Hydropotes inermis argyropus) from Jeonbuk Province, Korea

The objective of this study was to investigate the prevalence of tick-borne pathogens in the Korean water deer (Hydropotes inermis argyropus). Pathogens were identified using PCR which included Anaplasma, Ehrlichia, Rickettsia, and Theileria. Rickettsia was not detected, whereas Anaplasma, Ehrlichia, and Theileria infections were detected in 4, 2, and 8 animals, respectively. The most prevalent pathogen was Theileria. Of the 8 Theileria-positive animals, 2 were mixed-infected with 3 pathogens (Anaplasma, Ehrlichia, and Theileria) and another 2 animals showed mixed-infection with 2 pathogens (Anaplasma and Theileria). Sequencing analysis was used to verify the PCR results. The pathogens found in this study were identified as Anaplasma phagocytophilum, Ehrlichia canis, and Theileria sp. To the best of our knowledge, this is the first report identifying these 3 pathogens in the Korean water deer. Our results suggest that the Korean water deer may serve as a major reservoir for these tick-borne pathogens, leading to spread of tick-borne diseases to domestic animals, livestock, and humans. Further studies are needed to investigate their roles in this respect.
Scaled factorial hidden Markov models: A new technique for compensating gain differences in model-based single channel speech separation

In model-based single channel speech separation, factorial hidden Markov models (FHMM) have been successfully applied to model the mixture signal Y(t) = X(t) + V(t) in terms of trained patterns of the speech signals X(t) and V(t). Nonetheless, when the test signals are scaled versions of the trained patterns (i.e. gxX(t) and gvV(t)), the performance of FHMM degrades significantly. In this paper, we introduce a modification to FHMM, called scaled FHMM, which compensates gain difference. In this technique, first, the scale factors are expressed in terms of the target-to-interference ratio (TIR). Then, an iteration quadratic optimization approach is coupled with FHMM to estimate TIR which with the decoded HMM sequences maximize the likelihood of the mixture signal. Experimental results, conducted on 180 mixtures with TIRs from 0 to 15 dB, show that the proposed technique significantly outperforms unscaled FHMM, and scaled/unscaled vector quantization speech separation techniques.
Does Television Cultivate Narcissism? Relationships Between Television Exposure, Preferences for Specific Genres, and Subclinical Narcissism

A survey of 565 college students was conducted to examine the hypothesis that daily TV exposure is associated with scores on the Narcissistic Personality Inventory (NPI), as well as to answer the research question whether preferences for various TV genres are associated with narcissism. Additionally, effect testing was used to replicate meta-analytic evidence that narcissism has increased over time. Participants reported their daily TV exposure, preferences for specific TV genres (e.g., drama, sports), and completed the NPI. Daily TV exposure was positively associated with narcissism. Preferences for reality TV, sports, suspense/thriller/horror shows, and political talk shows were positively associated with narcissism. Preference for news was negatively associated with narcissism. Effect testing revealed that narcissism in college students has continued to increase over time. Results are interpreted according to cultivation theory, which suggests that TV is an aspect of culture that may be responsible for cultivating greater narcissism in college students.
Control of a swept-wing boundary layer using ring-type plasma actuators

Application of ring-type plasma actuators for control of laminar–turbulent transition in a swept-wing boundary layer is investigated thorough direct numerical simulations. These actuators induce a wall-normal jet in the boundary layer and can act as virtual roughness elements. The flow configuration resembles experiments by Kim et al. (2016 Technical Report. BUTERFLI Project TR D3.19, http://eprints.nottingham.ac.uk/id/eprint/46529). The actuators are modelled by the volume forces computed from the experimentally measured induced velocity field at the quiescent air condition. Stationary and travelling cross-flow vortices are triggered in the simulations by means of surface roughness and random unsteady perturbations. Interaction of vortices generated by actuators with these perturbations is investigated in detail. It is found that, for successful transition control, the power of the actuators should be increased to generate jet velocities that are one order of magnitude higher than those used in the experiments by Kim et al. (2016) mentioned above.
Technology for Mining the Big Data of MOOCs.

Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in detail, how students behave and how learning takes place. We chart an agenda that starts with data standardization. It identifies crowd sourcing as a means to speed up data analysis of forum data or predictive analytics of student behavior. It also points to open source platforms that allow software to be shared and visualization analytics to be discussed. Massi ve Open Online Courses (MOOCs) are college courses offered on the Internet. Lectures are conveyed by videos, textbooks are digitized, and problem sets, quizzes and practice questions are web–based. Students communicate with one another and faculty via discussion forums. Grading, albeit constrained by somewhat restrictive assessment design, is automated. The popularity of MOOCs has made a high volume of learner data available for analytic purposes. Some MOOC data is just like that which comes from the classroom. This can include teaching material, student demographics and background data, enrollment information, assessment scores and grades. But very important differences arise between MOOC and classroom in how behavioral data is collected and what is observable. The platform records, unobtrusively, through input, capture every mouse click, video player control use, and every submission to the platform such as problem solution choice selection, solution composition or text entry for a forum discussion. The level of recorded detail of behavior in a MOOC vastly surpasses that recorded in conventional settings. Very directly, this data can provide a count of problem attempts and video replays. It can reveal how long a student stayed on a textbook page or the presence of very short, quick patterns of resource consultation. It can inform an individualized or aggregated portrait of how a student solves problems or accesses resources. It presents opportunities to identify and compare different cohorts of students in significant quantities, thus enabling us to personalize how content is delivered. It allows us to study learner activities not exclusive to problem-solving, such as forum interactions and video-watching habits (Thille et al., 2014). It also facilitates predictive analytics based on modeling and machine learning. This data also contains large samples. Large sample sizes enable us to …
Two discursive frameworks concerning ideology in Australian industrial relations

There are two discursive frameworks concerning ideology in Australian industrial relations. In many disciplines concerned with aspects of industrial relations, including political science, law and history, it is the traditional political ideologies of the industrial era which take centre stage: liberalism (classical, social and neoliberalism), socialism (Marxism, social democracy and labourism) and conservatism. By contrast, ideological issues in the discipline of employment relations are chiefly addressed in terms of Fox’s three analytical perspectives: unitarism, pluralism and radicalism. The disjunction between these parallel discourses goes largely unnoted in the literature of the relevant disciplines, which all tend to proceed using their own preferred approach without making reference to the other. This article critically explores the relationship between these two discourses and investigates the broader implications that the existence of the two different discursive traditions has for the analysis of industrial relations phenomena in Australia.