Miracle-dz/UniFAR-FTUs huggingface dataset:
an Inhibitor of Protein Kinase C Target for the Anticancer and Radiosensitizing Agent PKC 412 ,-Kinase / Akt Survival Pathway Is a ′ The Phosphatidylinositide 3 Updated

Activation of the phosphatidylinositol 3 -kinase (PI3K)/Akt survival pathway protects against apoptotic stress stimuli. Therefore, compounds that down-regulate this pathway are of clinical interest for single and combined anticancer treatment modalities. Here we demonstrate that the cytotoxic effect of the protein kinase C (PKC)-inhibitor N-benzoylated staurosporine (PKC412) is mediated via the PI3K/Akt pathway. Dosedependent down-regulation of the proliferative activity, activation of the apoptotic machinery, and cell killing by PKC412 (0–1 M) in Rat1afibroblasts and H-ras-oncogene-transformed fibroblasts correlated with a decrease of Akt phosphorylation and a reduced phosphorylation of the endogenous Akt-substrate GSK3. Expression of the dominant-active myristoylated form of Akt abrogated this cytotoxic effect of PKC412. Experiments with Apaf-1-deficient cells revealed that PKC412-induced cytotoxicity depends on an intact apoptosome but that the decrease of Akt phosphorylation is not attributable to apoptosis execution. Comparative experiments indicate that PKC412 and the parent-compound staurosporine down-regulate this survival pathway upstream or at the level of Akt but by a different mechanism than the PI3K-inhibitor LY294002. Furthermore, inhibition of this pathway by PKC412 is relevant for sensitization to ionizing radiation. These results demonstrate the specific role of this signaling pathway for the PKC412-mediated down-regulation of an apoptotic threshold and its cytotoxicity.
A Trust Model Based on Similarity Evaluation in P2P Networks

Due to lack of effective trust management mechanism, there are a lot of deceptive behaviors in P2P networks, which seriously decrease the quality of network services. In order to improve the quality of services (or transactions), this paper proposes a novel trust and reputation model based on similarity evaluation in P2P environments. According to the different context of services, the model gives the similarity degree evaluation, and presents local reputation and global reputation computation. Experimental results demonstrate that this model can get more real trust value and deal with the malicious attacks.
Adaptive Analog VLSI Signal Processing and Neural Networks

PREFACE While the digital world frantically pursues ever-faster clock speeds to satisfy demanding signal processing applications, a quiet revolution in analog computing has been brewing, which promises to do more with less — more sophisticated signal processing delivered at less power in a smaller space. Novel application of a digital memory technology, the floating-gate MOS-FET (used in EEPROMs), as an analog memory and computation device provides the basic building block of this technology. Utilization of inherent device physics provides the adap-tivity and programmability needed to realize compact reconfigurable analog VLSI systems. Floating-gate charge storage provides non-volatile memory for a matrix of coefficients, while the nonlinear current-voltage relation of the MOSFET provides signal-coefficient multiplication. Summation of products is achieved simply using Kirckhoffs Current Law. Matrix coefficients adapt according to a correlation learning rule which utilizes physical device phenomena (electron tunneling and hot-electron injection) to program floating-gate charge. All of this functionality costs only four transistors per coefficient, each operating at nanowatts of power consumption. The resultant adaptive analog matrix-vector operations form the core of a novel analog VLSI signal-processing model, which is called computing in memory. Peripheral circuitry determines learning behavior, controls programmability, and expands core matrix functionality. iv ACKNOWLEDGEMENTS I wish to thank my colleagues in the Integrated Computational Electronics lab for their encouragement and support, particularly Venkatesh Srinivasan for assistance with the design and construction of the adaptive test board, as well as producing some of the simulation results in Chapter 6. Figure 1 Classic picture of a two-layer neural network from the perspective of im-plementating these networks in hardware. The neural networks are layers of simple processors, called neurons, interconnected through weighting elements, called synapses. The neurons aggregate the incoming inputs (including a threshold or offset) and are applied through a tanh(·) non-linearity. The synapse elements, which in general are far more numerous than neuron elements, must multiply the incoming signal by an internally stored value, called the weight, and must adapt this weight based upon a particular learning rule. Learning rules implemented in silicon are typically functions of correlations of signals passing through each synapse processor. 2 Figure 2 Typical architectures for neural network implementations. Although the routing looks complicated in Fig.
Energy detection spectrum sensing of M-ary QAM systems over AWGN channels

This article addresses energy detection for spectrum sensing of M-ary quadrature amplitude modulation (QAM) systems. Analytical expressions are developed for the average probability of detection in these systems. The analytical results are validated by numerical simulations and comparisons with different approximated approaches found in the literature are made. We see that the approximations usually found in existing literature are good for a large number of sensing samples or for very low SNR levels, but, otherwise, the use of a particular modulation scheme may have an impact on sensing performance.
Automating Areas of Interest Analysis in Mobile Eye Tracking Experiments based on Machine Learning

For an in-depth, AOI-based analysis of mobile eye tracking data, a preceding gaze assign-ment step is inevitable. Current solutions such as manual gaze mapping or marker-based approaches are tedious and not suitable for applications manipulating tangible objects. This makes mobile eye tracking studies with several hours of recording difficult to analyse quan-titatively. We introduce a new machine learning-based algorithm, the computational Gaze-Object Mapping (cGOM), that automatically maps gaze data onto respective AOIs. cGOM extends state-of-the-art object detection and segmentation by mask R-CNN with a gaze mapping feature. The new algorithm’s performance is validated against a manual fixation-by-fixation mapping, which is considered as ground truth, in terms of true positive rate (TPR), true negative rate (TNR) and efficiency. Using only 72 training images with 264 labelled object representations, cGOM is able to reach a TPR of approx. 80% and a TNR of 85% compared to the manual mapping. The break-even point is reached at 2 hours of eye tracking recording for the total procedure, respectively 1 hour considering human working time only. Together with a real-time capability of the mapping process after completed train-ing, even hours of eye tracking recording can be evaluated efficiently. (Code and video examples have been made available at: https://gitlab.ethz.ch/pdz/cgom.git)
Trace and revoke systems with short ciphertexts

Trace and revoke systems are motivated by content protection on various platforms such as DVD players, satellite radio receivers and PCs, which provide both broadcast encryption and traitor tracing mechanisms. So far, the best existing system requires ciphertext size sub-linear in the number of users. In communications, as system scale increases, it brings up a high bandwidth requirement which cannot be satisfied by current network condition. In this paper, we present a new fully collusion resistant trace and revoke system which has only constant size ciphertexts. The system is CPA secure against static adversaries with public broadcast key and secret tracing key. It can be efficiently applied in DRM fields where network bandwidth is limited.
Unattended consequences: how text responses alter alongside PISA’s mode change from 2012 to 2015

ABSTRACT In 2015, the Programme for International Student Assessment (PISA) introduced multiple changes in its study design, the most extensive being the transition from paper- to computer-based assessment. We investigated the differences between German students’ text responses to eight reading items from the paper-based study in 2012 to text responses to the same items from the computer-based study in 2015. Two response features – information quantity and relevance proportion – were extracted by natural language processing techniques because they are crucial indicators for the response process. Showcasing potential differential relationships, we additionally examined gender differences. Modelling effects of the round of assessment, gender, and response correctness on the response features, we analysed responses from 15-year-olds and ninth-graders in Germany. Results revealed differences in the text responses between the rounds of assessment in that students included more information overall in 2015, and the proportions of relevance varied substantially across items. As the study investigated the mode change in PISA’s natural (not experimental) setting, the differences could mirror cohort trends or design changes. However, with the evidence reported, we conclude that the differences could indicate mode effects.
The politics of pleasure in global drama: A case study of the TV series, The Magnificent Century (Muhteşem Yüzyıl)

This article is concerned with the ways in which local/national drama becomes a global success, which strategies are developed to appeal to viewers within different cultural settings and how far this shift is important when re/thinking audience reception studies. The study answers this question by exploring the television (TV) drama series, The Magnificent Century (2011–2014) by conducting in-depth interviews in the Greek capital Athens and the Moroccan capital Rabat with viewers and the production and distribution team of the series. The findings show that potentials for pleasure in the consumption of drama are designed from the very beginning when thinking globally, to reduce cultural differences to a minimum, to finally fuse audiences’ interpretative practices beyond cultural polarization to common understandings.
HitBoost: Survival Analysis via a Multi-Output Gradient Boosting Decision Tree Method

Survival analysis, in many areas such as healthcare and finance, mainly studies the probability of time to the event of interest. Among various methods that build survival predictive models, a class of methods combining with machine learning techniques make assumptions about hazard functions, while another class of methods directly exploit complex neural networks to learn the latent representation of hazard functions. For the traditional survival predictive models, the assumption about hazard functions restricts their performance to some extends. Similarly, the advanced survival predictive models built by complex neural networks also suffer from fairly poor interpretation in real applications. To solve these problems, in this paper, a novel survival analysis method named HitBoost is proposed to predict the probability distribution of the first hitting time (FHT). Instead of making any assumptions about the underlying stochastic process, the proposed HitBoost adopts the multi-output gradient boosting decision tree to implicitly capture the connections between the static covariate and the underlying stochastic process. Furthermore, in the process of tree boosting, the relevant statistics can be utilized to effectively measure the feature importance. The results of evaluations and case studies on benchmarks show that, in comparison to the classical methods, the proposed HitBoost is superior in prediction performance and risk discrimination. Therefore, the HitBoost can be utilized as an effective method to build survival predictive models or to find the important factors for cause-specific failure.
Phonetic Tonal Realization in Rugao Chinese 1 CONTEXTUAL AND PITCH RANGE EFFECTS ON TONAL REALIZATIONS IN

Factors such as preceding or following tone, pitch range, and prosodic position have been found to have an impact on phonetic tonal realization (Gandour et al. 1994; Shih 1988; Liberman & Pierrehumbert 1984; Pierrehumbert & Beckman 1988; Peng 1997). The present study used Rugaohua, a Southern Mandarin dialect, as a testing ground for some of the theoretical claims and tonal realization models. It was found that preceding tone and pitch range, as well as underlying tonal specification for target syllable, were important factors in a tonal realization model for Rugaohua. In particular, a preceding tone with a L target downsteps a following tone, and different L targets may have different downstepping effects. When pitch range was manipulated by increasing and decreasing voice volume, high tones were affected more than low tones. The data suggest that there may also be following tone and prosodic position effects, calling for further investigation on these factors. SUBJECT
Investigation of TGFβ1-Induced Long Noncoding RNAs in Endothelial Cells

Objective. To evaluate the relationship between TGFβ signaling and endothelial lncRNA expression. Methods. Human umbilical vein endothelial cell (HUVECs) lncRNAs and mRNAs were profiled with the Arraystar Human lncRNA Expression Microarray V3.0 after 24 hours of exposure to TGFβ1 (10 ng/mL). Results. Of the 30,584 lncRNAs screened, 2,051 were significantly upregulated and 2,393 were appreciably downregulated (P < 0.05) in response to TGFβ. In the same HUVEC samples, 2,148 of the 26,106 mRNAs screened were upregulated and 1,290 were downregulated. Of these 2,051 differentially expressed upregulated lncRNAs, MALAT1, which is known to be induced by TGFβ in endothelial cells, was the most (~220-fold) upregulated lncRNA. Bioinformatics analyses indicated that the differentially expressed upregulated mRNAs are primarily enriched in hippo signaling, Wnt signaling, focal adhesion, neuroactive ligand-receptor interaction, and pathways in cancer. The most downregulated are notably involved in olfactory transduction, PI3-Akt signaling, Ras signaling, neuroactive ligand-receptor interaction, and apoptosis. Conclusions. This is the first lncRNA and mRNA transcriptome profile of TGFβ-mediated changes in human endothelial cells. These observations may reveal potential new targets of TGFβ in endothelial cells and novel therapeutic avenues for cardiovascular disease-associated endothelial dysfunction.
Direct active and reactive power control of inverter- based DGs using adaptive input-output feedback linearization

This paper presents a direct active and reactive power control (DPC) for the three-phase grid connected dc/ac converters. The proposed DPC strategy employs an adaptive nonlinear control scheme to directly calculate the required converter's control voltage so as to eliminate the instantaneous errors of active and reactive powers without involving any rotating coordinate transformations. The control is based on adaptive input-output feedback linearization control (AIOFLC) . With an appropriate Lyapunov function, the control law and the estimation laws for inductance and resistance of filter and line are achieved . Using space vector pulse width modulation (SV-PWM) a fixed switching frequency is achieved which simplifies harmonic design of ac filter. Simulation results show the capability of the proposed AIOFLC in direct active and reactive power control with uncertainties in filter/line impedance.
Delayed propagation of derivatives in a two-dimensional aircraft design optimization problem

In computational fluid dynamics (CFD), the use of high-performance computers is often indispensable, simply to manage the high request for computation time and storage. We consider a particular two-dimensional aircraft design problem and report on the use of automatic differentiation (AD) to obtain accurate derivatives rather than approximations based on numerical differentiation. More precisely, we apply the AD system ADIFOR to the large-scale CFD solver TFS and quantify the computational savings of a technique starting the derivative computations in a delayed manner over a black box AD approach.
Video browsing by direct manipulation

We present a method for browsing videos by directly dragging their content. This method brings the benefits of direct manipulation to an activity typically mediated by widgets. We support this new type of interactivity by: 1) automatically extracting motion data from videos; and 2) a new technique called relative flow dragging that lets users control video playback by moving objects of interest along their visual trajectory. We show that this method can outperform the traditional seeker bar in video browsing tasks that focus on visual content rather than time.
Supersymmetry breaking at the end of a cascade of Seiberg dualities

We study the IR dynamics of the cascading nonconformal quiver theory on $N$ regular and $M$ fractional D3 branes at the tip of the complex cone over the first del Pezzo surface. The horizon of this cone is the irregular Sasaki-Einstein manifold ${Y}^{2,1}$. Our analysis shows that at the end of the cascade supersymmetry is dynamically broken.
Mind the (Gender) Gap. Gender, Gender Role Types, and Their Effects on Objective Career Success over Time

Drawing on ideas by Pierre Bourdieu, this paper analyzes the effects of gender and gender role type (GRT) for objective career success (i.e., income) over time. Empirically, data from two cohorts of business school graduates were analyzed with mixed linear models. Gender and GRT, both perceived as career capital, progressively affect objective career success over time, with feminine GRT hampering objective career success for both sexes. Remaining results vary between the two cohorts: findings for the younger cohort deviate more strongly from the hypotheses derived.
Explaining the Intention to Use Pre-Exposure Prophylaxis among HIV-negative Men who have Sex with Men in Switzerland: Testing an extended explanatory model drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT)

 Men who have sex with men (MSM) continue to be disproportionally affected by HIV/AIDS. In Switzerland, almost half of the HIV infections yearly diagnosed are in MSM [1].  Although HIV Pre-Exposure Prophylaxis (PrEP) has not been approved in Switzerland, there is a discussion about its potential and adequacy as an additional prevention option especially for MSM.  In the USA, where PrEP was approved in 2012, there is evidence that MSM are not keen to use it [2, 3, 4].  Against this background, it is important to learn more about factors influencing the acceptability of PrEP. For an in-depth understanding comprehensive explanatory models will be essential. The aim of this study was to explain the intention to use PrEP among MSM living in Switzerland by developing and testing a model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) [5].
EigenCrime: An Algorithm for Criminal Network Mining Based on Trusted Computing

The searches on criminal network have become a key issue recent years, as the criminal activities are becoming grouping and networking. Most researches mainly focus on network of criminals, few on network of suspects and the traditional method is studying the static structure of the network, without explaining the behaviours among the nodes. In this paper, we are motivated by the ideal of EigenTrust algorithm to calculate the suspicion score of every member in the network of suspects and figure out the activists in the network by the score, supporting decision making for the police. Experiment results show high rank of criminals and low rank of innocents in a practical suspect network and prove the efficiency and accuracy of EigenCrime.
Model Selection for Anomaly Detection in Wireless Ad Hoc Networks

Anomaly detection has been actively investigated to enhance the security of wireless ad hoc networks. However, it also presents a difficulty on model determination, such as feature selection and algorithm parameter optimization. In this paper, we address the issue of parameter selection for one-class support vector machine (1-SVM) based anomaly detection. We have investigated the performance of existing approaches, and also proposed a skewness-based outlier generation approach for parameter selection in the 1-SVM based anomaly detection model
Isolation of Symbiotically Expressed Genes From the Dinoflagellate Symbiont of the Solitary Radiolarian Thalassicolla nucleata

Symbiotic associations are fundamental to the survival of many organisms on Earth. The ability of the symbiont to perform key biochemical functions often allows the host to occupy environments that it would otherwise find inhospitable. This can have profound impacts upon the diversification and distribution of the host. Cellular organelles (chloroplasts and mitochondria) represent the final stages of integration of endosymbionts. These organelles were of critical importance to the evolution and success of eukaryotic lineages on our planet because they allowed the host cells to harness light energy and to thrive in the presence of oxygen. The marine photosymbiotic associations that we study represent an earlier stage in the process of symbiont integration—one in which the photobiont can still be removed from the host and exist on its own. These systems are of interest to us for two reasons. First, they are ecologically important in the marine environment where they occur. These organisms form zones of photosynthetic production in oceanic regions typically low in nutrients. Second, investigation of these interactions may shed light on the molecular and evolutionary mechanisms involved in the integration of cells and their genomes.
FPGA architecture for a videowall image processor

This paper proposes an FPGA architecture for a videowall image processor. To create a videowall, a set of high resolution displays is arranged in order to present a single large image or smaller multiple images. An image processor is needed to perform the appropriate format conversion corresponding to the required output configuration, and to properly enhance the image contrast. Input signals either in the interlaced or in the progressive format must be managed. The image processor we propose is integrated into two different blocks: the first one implements the deinterlacing task for a YCbCr input video signal, then it converts the progressive YCbCr to the RGB data format and performs the optional contrast enhancement; the other one performs the format conversion of the RGB data format. Motion-adaptive vertico-temporal deinterlacing is used for the luminance signal Y; the color difference signals Cb and Cr instead are processed by means of line average deinterlacing. Image contrast enhancement is achieved via a modified Unsharp Masking technique and involves only the luminance Y. The format conversion algorithm is the bilinear interpolation technique employing the Warped Distance approach and is performed on the RGB data. Two different subblocks have been considered in the system architecture since the interpolation is performed column-wise and successively row- wise.