Miracle-dz/UniFAR-FTUs huggingface dataset:
Adenoviral vector saturates Akt pro-survival signaling and blocks insulin-mediated rescue of tumor-necrosis-factor-induced apoptosis

Recombinant adenoviruses are used extensively as delivery vectors in clinical gene therapy and in molecular biology, but little is known about how the viral carrier itself contributes to cellular responses. Here we show that infection with an E1/E3-deleted adenoviral vector (Adv) sensitizes human epithelial cells to tumor necrosis factor (TNF)-induced apoptosis. To explore the mechanism of Adv-mediated sensitization, we measured activity time courses for three protein kinases (MK2, IKK and JNK1) centrally involved in the TNF-receptor signaling network, as well as two kinases (Akt and ERK) activated by growth factors. Both the pro-apoptotic signal MK2 and the anti-apoptotic signal Akt were upregulated when Adv-infected cells were stimulated with TNF, and MK2 and Akt each contributed significantly to TNF-induced cell fate. Surprisingly, further activation of Akt in Adv-infected cells via insulin treatment did not significantly reduce apoptosis or MK2 activity. We show that the ineffectiveness of insulin-mediated anti-apoptotic signaling through Akt is due to saturation of Akt-effector substrate phosphorylation in Adv-infected cells. Normalizing Akt signaling relative to its Adv-induced baseline activity identified a global dose-response curve that relates Akt signaling to cellular survival. Thus, the background Akt activity induced by Adv limits the transmission of anti-apoptotic signals in response to further cytokine or growth-factor stimulation. The phenotypic and intracellular synergy between Adv and TNF may have implications for interpreting cellular responses in gene-therapy and laboratory applications.
An XML-based framework for bidirectional transformation in model-driven architecture (MDA)

A model transformation in Model-Driven Architecture is the generation of a target model from a source model, which is normally based on different processes. These processes are described by a transformation definition, consisting of a number of transformation rules, and executed with the help of a transformational tool. In Model-Driven Architecture approach, bidirectionality is one of the most desirable features of the transformational process. Here bi-directionality means that a transformation can be applied from source to target as well as back from target to source model. Different technologies are available which provide bidirectionality between platform specific models to Code Generation but hardly any tool is providing bidirectionality between platform independent models to platform specific models. Here we proposed an XML-Based Bidirectional Transformation Model (as a framework) for Model-Driven Architecture that provides bidirectionality between platform independent model and platform specific model.
Asymmetric effects of speaking rate on the vowel/consonant ratio conditioned by coda voicing in English*

The vowel/consonant ratio is a well-known cue for the voicing of postvocalic consonants. This study investigates how this ratio changes as a function of speaking rate. Seven speakers of North American English read sentences containing target monosyllabic words that contrasted in coda voicing at three different speaking rates. Duration measures were taken for the voice onset time (VOT) of the onset consonant, the vowel, and the coda. The results show that the durations of the onset VOT and vowel are longer before voiced codas, and that the durations of all segments increase monotonically as speaking rate decreases. Importantly, the vowel/consonant ratio, a primary acoustic cue for coda voicing, was found to pattern asymmetrically for voiced and voiceless codas; it increases for voiced codas but decreases for voiceless codas with the decrease in speaking rate. This finding suggests that there is no stable ratio in the duration of preconsonantal vowels that is maintained in different speaking styles.
Biomedical Ontology Evolution in the EMBL-EBI Ontology Lookup Service

As ontologies are playing an increasingly important role in data annotation on today’s Semantic Web, there is a need to observe their constant evolution. At EMBL-EBI ontology preservation and curation is of growing value, and new tools are being developed to help undertake these tasks. One of these tools is the Ontology Lookup Service which holds 140 public bio-medical ontologies that are updated when new ontology version become available. To track changes in these ontologies we have utilized DIACHRON, a platform for tracking the evolution of RDF documents. With DIACHRON in OLS we can track and store the changes between ontology releases and view the differences through a graphical interface.
Flow processing-aware controller placement in wireless DenseNets

The traffic demand in wireless access networks has grown substantially in recent years and is expected to continue doing so, both in terms of total volume and data rate required by individual users. To overcome the current limitations of wireless access networks, operators already push for very dense and heterogeneous wireless networks, commonly known as DenseNets. Efficiently controlling DenseNets is a task for current research, as simply scaling existing networks by orders of magnitude brings along several problems, e.g. increased energy consumption and the explosion of signaling. Further, new innovations such as Network Functions Virtualization (NFV) which target the operation expenses for networks with a large variety of proprietary hardware appliances, reveal that data flow processing should not be neglected in this research domain. Software-Defined Networking (SDN), which separates the control plane and the data forwarding plane, has been identified as a promising approach for an efficient control of DenseNets. However, the controllers of classic SDN approaches are confined to the routing of data flows, while the support of sophisticated processing mechanisms, e.g. NFV or Coordinated Multi-Point transmission (CoMP), is not considered. Data flow processing imposes many requirements on data rate, latency and processing capacity. Hence, an adequate allocation of the locations for data processing in a network is a challenging task and crucial for network performance. In this paper we propose our flow processing-aware controller placement framework that takes into account data flow processing and control applications, both enhancing the SDN architecture specifically for DenseNets.
Switched-beam antenna array based on butler matrix for 5G wireless communication

In this paper, a switched-beam antenna array based on Butler matrix network at 25 GHz is demonstrated for 5G channel sounding system. In order to achieve beam switching, an 8×8 Butler matrix integrated with a 1×8 switch is designed as a feeding network to excite the patch antenna array. Owing to the linear phase distribution induced by the Butler matrix, the antenna array can generate different beams in specific directions. Experimental results show that the proposed array achieves the antenna gain of better than 10dB.
Distributed recycling of waste polymer into RepRap feedstock

– A low‐cost, open source, self‐replicating rapid prototyper (RepRap) has been developed, which greatly expands the potential user base of rapid prototypers. The operating cost of the RepRap can be further reduced using waste polymers as feedstock. Centralized recycling of polymers is often uneconomic and energy intensive due to transportation embodied energy. The purpose of this paper is to provide a proof of concept for high‐value recycling of waste polymers at distributed creation sites. , – Previous designs of waste plastic extruders (also known as RecycleBots) were evaluated using a weighted evaluation matrix. An updated design was completed and the description and analysis of the design is presented including component summary, testing procedures, a basic life cycle analysis and extrusion results. The filament was tested for consistency of density and diameter while quantifying electricity consumption. , – Filament was successfully extruded at an average rate of 90 mm/min and used to print parts. The filament averaged 2.805 mm diameter with 87 per cent of samples between 2.540 mm and 3.081 mm. The average mass was 0.564 g/100 mm length. Energy use was 0.06 kWh/m. , – The success of the RecycleBot further reduces RepRap operating costs, which enables distributed in‐home, value added, plastic recycling. This has implications for municipal waste management programs, as in‐home recycling could reduce cost and greenhouse gas emissions associated with waste collection and transportation, as well as the environmental impact of manufacturing custom plastic parts. , – This paper reports on the first technical evaluation of a feedstock filament for the RepRap from waste plastic material made in a distributed recycling device.
Quantum interference of multi-photon at beam splitter with application in measurement-device-independent quantum key distribution

Despite the relative simplicity of the traditional Hong–Ou–Mandel (HOM) interferometer setup, it is of fundamental interest in various quantum optics applications and quantum information technologies. In this article, multi-photon interference using the original HOM interferometer setup is analyzed. More specifically, for any photon number state with Gaussian spectral distribution entering the beam splitter, the general analytical solution is calculated. The result is then used to study the coincident probability for coherent sources (laser) and squeezed coherent state. We also look into the potential benefits of implementing the squeezed coherent state in discrete-variable Measurement-Device-Independent Quantum Key Distribution and find that by optimizing the squeezing parameter, the error rate can be significantly reduced. This in turn also enhances the secret key rate performance over the coherent state.
Pyramidal Neural Networks with Variable Receptive Fields Designed by Genetic Algorithms

Pyramidal Neural Networks (PNN) are computational systems inspired in the concept of receptive fields from the human visual system. In the original approach, the size of the receptive field within the same 2D layer is constant. However, their size is variable in the human visual system. This paper proposes a PNN with variable receptive fields, which might be determined by a Genetic Algorithm, called Variable Pyramidal Neural Network with Genetic Algorithms (VPNN-GA). We observed from preliminary experiments aiming at detecting faces in images that our approach can achieve better classification rates than the original.
Quality of Life and Associated Risk Factors in Caregivers of Patients with Obsessive Compulsive Disorder

ABSTRACT INTRODUCTION: Obsessive compulsive disorder (OCD) is a chronic disease that affects social relationships, and occupational and academic performance of patients and their relatives due to cognitive, emotional, and behavioural aspects of the disease. Quality of life (QoL) in relatives of patients with OCD has previously been reported and compared with caregivers of patients with other psychiatric conditions. However, there are few studies available in the literature regarding the causality of QoL in caregivers of patients with OCD. OBJECTIVE: The aim of this study was to evaluate QoL of caregivers of patients with OCD and predictors of QoL of the family caregivers. METHODS: The study population comprised of 68 patients with OCD and their caregivers. The dependent variable of this study is “QoL of caregivers” as assessed by the short version of the World Health Organization Quality of Life questionnaire (WHOQOL-BREF-TR). The Structured Clinical Interview for DSM-IV/Clinical Version (SCID-I/CV), Yale-Brown obsessive-compulsive scale (Y-BOCS), Y-BOCS symptom checklist, Hamilton Depression Rating Scale (HAM-D), and WHOQOL-BREF-TR were completed by the patients, whereas the SCID-I/CV, WHOQOL-BREF-TR, and Burden Assessment Scale (BAS) were completed by the caregivers. Student’s t-test, MWU, ANOVA, Kruskal–Wallis ANOVA, and Spearman’s correlations were used in univariate analyses, and multiple linear regression tests were run in multivariate analyses. Critical VIF values were taken as 5.0 for detecting collinearity among independent variables in the regression analyses. Type 1 error was taken as 0.05 in the analyses. RESULTS: Linear regression analysis showed that caregivers’ sex, education level, occupational status, disease burden, and patients’ sex, physical QoL, and disease severity were predictors of caregivers’ QoL. Moreover, disease burden was the only common predictor that affected all four dimensions (physical, psychological, social relations, environmental) of the caregiver’s QoL, and as the perceived disease burden increased, the caregiver’s QoL deteriorated.
Scalarized multi-objective reinforcement learning: Novel design techniques

In multi-objective problems, it is key to find compromising solutions that balance different objectives. The linear scalarization function is often utilized to translate the multi-objective nature of a problem into a standard, single-objective problem. Generally, it is noted that such as linear combination can only find solutions in convex areas of the Pareto front, therefore making the method inapplicable in situations where the shape of the front is not known beforehand, as is often the case. We propose a non-linear scalarization function, called the Chebyshev scalarization function, as a basis for action selection strategies in multi-objective reinforcement learning. The Chebyshev scalarization method overcomes the flaws of the linear scalarization function as it can (i) discover Pareto optimal solutions regardless of the shape of the front, i.e. convex as well as non-convex , (ii) obtain a better spread amongst the set of Pareto optimal solutions and (iii) is not particularly dependent on the actual weights used.
A Profile Based Network Intrusion Detection and Prevention System for Securing Cloud Environment

Cloud computing provides network based access to computing and data storage services on a pay per usage model. Cloud provides better utilization of resources and hence a reduced service access cost to individuals. Cloud services include software as a service, platform as a service, and infrastructure as a service. Cloud computing virtually and dynamically distributes the computing and data resources to a variety of users, based on their needs, with the use of virtualization technologies. As Cloud computing is a shared facility and is accessed remotely, it is vulnerable to various attacks including host and network based attacks (Brown 2012, and Grance 2009) and hence requires immediate attention. This paper identifies vulnerabilities responsible for well-known network based attacks on cloud and does a critical analysis on the security measures available in cloud environment. This paper focuses on a nonconventional technique for securing cloud network from malicious insiders and outsiders with the use of network profiling. With network profiling, a profile is created for each virtual machine (VM) in cloud that describes network behavior of each cloud user (an assigned VM). The behavior gathered is then used for determination (detection) of network attacks on cloud. The novelty of the approach lies in the early detection of network attacks with robustness and minimum complexity. The proposed technique can be deployed with minimal changes to existing cloud environment. An initial prototype implementation is verified and tested on private cloud with a fully functional implementation under progress.
Real-Time Link-Reliability Routing for QoS in Wireless Sensor Networks

This paper proposes a Real-Time Link Reliability Routing protocol for wireless sensor networks (WSNs). The protocol achieves to reduce packet deadline miss ratio while considering link reliability, two-hop velocity and power efficiency and utilizes memory and computational effective methods for estimating the link metrics. Numerical results provide insights that the protocol has a lower packet deadline miss ratio and improved sensor network lifetime. The results show that the proposed protocol is a feasible solution to the QoS routing problem in wireless sensor networks that support real-time applications.
Privacy-preserving Logarithmic-time Search on Encrypted Data in Cloud

Ideally, a privacy-preserving database-in-the-cloud environment would allow a database owner to outsource its encrypted database to a cloud server. The owner would retain control over what records can be queried and by whom, by granting each authorized user a search token and a decryption key. A user would then present this token to cloud server who would use it to find encrypted matching records, while learning nothing else. A user could then use its owner-issued decryption key to learn the actual matching
Reconstruction of carotid bifurcation hemodynamics and wall thickness using computational fluid dynamics and MRI

A thorough understanding of the relationship between local hemodynamics and plaque progression has been hindered by an inability to prospectively monitor these factors in vivo in humans. In this study a novel approach for noninvasively reconstructing artery wall thickness and local hemodynamics at the human carotid bifurcation is presented. Three‐dimensional (3D) models of the lumen and wall boundaries, from which wall thickness can be measured, were reconstructed from black‐blood magnetic resonance imaging (MRI). Along with time‐varying inlet/outlet flow rates measured via phase contrast (PC) MRI, the lumen boundary was used as input for computational fluid dynamic (CFD) simulation of the subject‐specific flow patterns and wall shear stresses (WSSs). Results from a 59‐year‐old subject with early, asymptomatic carotid artery disease show good agreement between simulated and measured velocities, and demonstrate a correspondence between wall thickening and low and oscillating shear at the carotid bulb. High shear at the distal internal carotid artery (ICA) was also colocalized with higher WSS; however, a quantitative general relationship between WSS and wall thickness was not found. Similar results were obtained from a 23‐year‐old normal subject. These findings represent the first direct comparison of hemodynamic variables and wall thickness at the carotid bifurcation of human subjects. The noninvasive nature of this image‐based modeling approach makes it ideal for carrying out future prospective studies of hemodynamics and plaque development or progression in otherwise healthy subjects.
Evaluation of Signaling Cascades Based on the Weights from Microarray and ChIP-seq Data

In this study, we combined the ChIP-seq and the transcriptome data and integrated these data into signaling cascades. Integration was realized through a framework based on data- and model-driven hybrid approach. An enrichment model was constructed to evaluate signaling cascades which resulted in specic cellular processes. We used ChIP-seq and microarray data from public databases which were obtained from HeLa cells under oxidative stress having similar experimental setups. Both ChIP-seq and array data were analyzed by percentile ranking for the sake of simultaneous data integration on specic genes. Signaling cascades from KEGG pathway database were subsequently scored by taking sum of the individual scores of the genes involved within the cascade. This scoring information is then transferred to en route of the signaling cascade to form the nal score. Signaling cascade model based framework that we describe in this study is a novel approach which calculates scores for the target process of the analyzed signaling cascade, rather than assigning scores to gene product nodes.
A DCC Analysis of Stock Market and Exchange Rates: An Evidence Study of the South Korea Country

This paper studies the relatedness and the model construction of exchange rate volatility and the South Korea stock market returns. Empirical results show that we can construct a bivariate EGARCH(1, 2) model with a dynamic conditional correlation (DCC) to analyze the relationship of exchange rate volatility and Korea stock market returns. The average estimation value of the DCC coefficient for these two markets equals to -0.1961, this result indicates that the exchange rate volatility negatively affects the South Korea stock market. Empirical result also shows that there exists an asymmetrical effect on the South Korea stock market, but the exchange rate volatility does not have the asymmetrical effect. Based on the good news and bad news (Nelson, 1991) of the stock market, the bivariate EGARCH(1, 2) model with a DCC has the better explanation ability compared to the bivariate GARCH(1, 1) model.
The Condorcet Jury Theorem under Cognitive Hierarchies : Theory and Experiments

Cognitive hierarchy models have been developed to explain systematic deviations from the equilibrium behavior in certain classes of games. This paper introduces an endogenous cognitive hierarchy model, which better explains the behavioral heterogeneity of the strategies in games for which the standard cognitive hierarchy model provides an unreasonable prediction. As in the previous models, each player in the endogenous cognitive hierarchy model is assumed to best-reply to the other players holding a belief induced by the cognitive hierarchy. Contrary to the previous models, however, players are allowed to consider the presence of opponents at their own level of cognitive hierarchy. This extension is shown to eradicate the incompatibility of cognitive hierarchy models in the classes of games. We employ the model to explain voting behavior in information aggregation problems of the Condorcet Jury Theorem. Behavioral assumption of the strategic thinking turns out to be a crucial factor in whether the asymptotic efficiency is obtained or not. We conducted laboratory experiments which show that the endogenous cognitive hierarchy model provides significant improvements upon symmetric Bayesian Nash equilibrium and the previous cognitive hierarchy models in explaining the observed behavior of voters.
Students' Spiritual Integration Into Bible Colleges: A Grounded Theory Study

The purpose of this grounded theory study was to explain how undergraduate students integrate spiritually into Bible colleges in the Midwestern and Southeastern United States and discern the role spiritual integration plays in persistence. Spiritual integration of Bible college undergraduate students occurs when they perceive that their spirituality, whether possessed by them upon their enrollment and/or formed during their attendance, has aligned with the spiritual environment of their college and therefore have accepted their place in that environment. A total of 35 participants, 28 students and seven faculty members, were interviewed to obtain their perceptions of how students experience the process of spiritual integration within the unique environments found in Bible colleges in the Midwestern and Southeastern United States. The analysis of data collected in the study produced The Spiritual Integration Model which shows how students undergo the process of seeking God and a spiritual education, discovering a college family within an appealing college environment, developing relationally and spiritually, applying their knowledge and skills through participating in their college and contributing to God and their community, and finally accepting their place in the college’s spiritual environment. The alignment of students’ spirituality with a Bible college’s spiritual environment as well as their acceptance, or refusal, of their place in the college was found to influence decisions to persist.