Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of Nek11 Prevents G2/M Arrest and Promotes Cell Death in HCT116 Colorectal Cancer Cells Exposed to Therapeutic DNA Damaging Agents

The Nek11 kinase is a potential mediator of the DNA damage response whose expression is upregulated in early stage colorectal cancers (CRCs). Here, using RNAi-mediated depletion, we examined the role of Nek11 in HCT116 WT and p53-null CRC cells exposed to ionizing radiation (IR) or the chemotherapeutic drug, irinotecan. We demonstrate that depletion of Nek11 prevents the G2/M arrest induced by these genotoxic agents and promotes p53-dependent apoptosis both in the presence and absence of DNA damage. Interestingly, Nek11 depletion also led to long-term loss of cell viability that was independent of p53 and exacerbated following IR exposure. CRC cells express four splice variants of Nek11 (L/S/C/D). These are predominantly cytoplasmic, but undergo nucleocytoplasmic shuttling mediated through adjacent nuclear import and export signals in the C-terminal non-catalytic domain. In HCT116 cells, Nek11S in particular has an important role in the DNA damage response. These data provide strong evidence that Nek11 contributes to the response of CRC cells to genotoxic agents and is essential for survival either with or without exposure to DNA damage.
Fiscal Reaction Rules in Numerical Macro Models

To avoid exploding government debt, numerical macro models require ‘fiscal reaction rules’. Present rules impose arbitrary, backward-looking reaction of taxes to deviations of the debt ratio from a target. Arbitrary models may be poor guides to monetary policy. An optimising fiscal policy-maker would look forward, and maximise an objective function. A simple optimising model implies the future tax rate should be constant. I implement the constant-future-tax rule in the IMF’s MULTIMOD model. Simulations show model outcomes’ sensitivity to the choice of fiscal rule. A constant tax rate induces smoother and hence preferable consumption paths to MULTIMOD’s existing rule.
An adaptive algorithm for Internet multimedia delivery in a differentiated services environment

We present an adaptive class switching algorithm (ACSA) that provides good quality with good price for real-time multimedia applications running in a differentiated services (DiffServ) environment. The algorithm selects the most suitable class by taking both QoS and price into account. Class switching is based on both the QoS feedback received and the highest user utility. The user utility reflects the service quality and price tradeoff. The simulation results demonstrate that ACSA can react fast to the current class state and can control the tradeoff between price and quality.
A self-adaptive iterated local search algorithm on the permutation flow shop scheduling problem

Iterated local search (ILS) is a simple, effective and efficient metaheuristic, displaying strong performance on the permutation flow shop scheduling problem minimizing total flow time. Its perturbation method plays an important role in practice. However, in ILS, current methodology does not use an evaluation of the search status to adjust the perturbation strength. In this work, a method is proposed that evaluates the neighborhoods around the local optimum and adjusts the perturbation strength according to this evaluation using a technique derived from simulated-annealing. Basically, if the neighboring solutions are considerably worse than the best solution found so far, indicating that it is hard to escape from the local optimum, then the perturbation strength is likely to increase. A self-adaptive ILS named SAILS is proposed by incorporating this perturbation strategy. Experimental results on benchmark instances show that the proposed perturbation strategy is effective and SAILS performs better than three state of the art algorithms.
An ontological analysis of the UMLS Metathesaurus

Paper-based terminology systems cannot satisfy anymore the new desiderata of healthcare information systems: the demand for re-use and sharing of patient data, their transmission and the need of semantic-based criteria for purposive statistical aggregation. The unambiguous communication of complex and detailed medical concepts is now a crucial feature of medical information systems. Ontologies can support a more effective data and knowledge sharing in medicine. In this paper we briefly survey our ontological analysis and integration of various top-levels of terminologies and we report the main results of the ontological analysis of the UMLS Metathesaurus.
On Approximate Computer System Models

A new treatment of the boundary conditions of diffusionapproximations for interconnected queueing systems is presented.The results have applications to the study of the performance ofmultiple-resource computer systems. In this approximation method,additional equations to represent the behavior of the queues whenthey are empty are introduced. This reduces the dependence of themodel on heavy traffic assumptions and yields certain results whichwould be expected from queueing or renewal theory. The accuracy ofthe approach is evaluated by comparison with certain known exact ornumerical results.
Problems and Prospects of Development.

into five regional commands mitigates against a unified conspiracy or plot agalnst the government. Moreover, even in this extremely unIikely event of military takeover, the military would be faced by organized opposition of such proportions that the stability of any regime they might establish would be highly precarious. Thus, it will be suffice to conclude that India has cxystallised a reasonably stable pattern of civilian control which is not Iikely to be altered by the economic and political disruption in the foreseeable future. The main weakness of this book lies in its descriptive and factual orientations and the lack of indepth scholarly analysis. Besides, this study has lack of theoretical framework. The author also fails to explain how and why, with a common heritage of British Indian Army traditions, the Pakistani and Indian armed forces have moved to different paths. The Appendix of the book provide some useful information about the Indian Army and 'organisation defence of-India. In sum, on the whole, this is a descriptive short acc Indian Army reflecting its histoj, ethos and traditions and the role it is likely to play in the future and could be useful to the students of civil-military relations.
Epithelial Cells In Vivo II-Mediated Antigen Presentation by Cathepsin S Controls MHC Class

† Epithelial cells at environmental interfaces provide protection from potentially harmful agents, including pathogens. In addition to serving as a physical barrier and producing soluble mediators of immunity, such as cytokines or antimicrobial peptides, these cells are thought to function as nonprofessional APCs. In this regard, intestinal epithelial cells are particularly prominent because they express MHC class II molecules at the site of massive antigenic exposure. However, unlike bone marrow-derived professional APC, such as dendritic cells or B cells, little is known about the mechanisms of MHC class II presentation by the nonprofessional APC in vivo. The former use the lysosomal cysteine protease cathepsin S (Cat S), whereas thymic cortical epithelial cells use cathepsin L (Cat L) for invariant chain degradation and MHC class II maturation. Unexpectedly, we found that murine Cat S plays a critical role in invariant chain degradation in intestinal epithelial cells. Furthermore, we report that nonprofessional APC present a class II-bound endogenous peptide to naive CD4 T cells in vivo in a Cat S-dependent fashion. These results suggest that in vivo, both professional and nonprofessional MHC class II-expressing APC use Cat S, but not Cat L, for MHC class II-mediated Ag presentation. The Journal of Immunology, 2005, 174: 1205–1212. critical Ii class II Furthermore, we demonstrate that is essential for efﬁcient presentation of endogenous to CD4 T by APC in These results indicate that is a key enzyme regulating MHC class II presentation to CD4 T cells in both professional APC and in one of the most signif-icant nonprofessional APC of epithelial origin, IEC. cells, and it exhibits high afﬁnity for Cat L. Cystatin F mRNA is up-regulated in maturing dendritic cells (37), and we found cystatin F mRNA levels markedly increased in M (cid:1) upon treatment with IFN- (cid:8) , suggesting that it could be a Cat L inhibitor in these cells (data not shown). However, cystatin F mRNA was undetectable in IEC. Thus, an unknown mechanism responsible for Cat L inhibition in these cells will have to be further investigated.
Proteins associated with purified human cytomegalovirus particles

Virion-associated proteins isolated from purified human cytomegalovirus particles (strain AD169) were used as substrates for chemical sequence analysis. Extracellular virions, noninfectious enveloped particles, and dense bodies were purified by negative viscosity-positive density gradient centrifugation, and their component proteins were separated by denaturing polyacrylamide gel electrophoresis. The deduced amino acid sequence of individual protein bands was used to identify six corresponding viral genes whose products have not previously been identified as virion constituents: UL47, UL25, UL88, UL85, UL26, and UL48.5. In addition, a 45-kDa cellular protein was identified, and the protein fragments sequenced have a high degree of amino acid identity with actin. However, antiactin monoclonal and polyclonal antibodies did not react with a specific protein in the virus preparations, suggesting that this 45-kDa protein is an immunologically distinct isoform of actin. The newly identified viral and cellular proteins were resistant to protease treatment of purified virions, suggesting that they are unlikely to be contaminants of the viral preparations.
A semiparametric approach to mixed outcome latent variable models: Estimating the association between cognition and regional brain volumes

Multivariate data that combine binary, categorical, count and continuous outcomes are common in the social and health sciences. We propose a semiparametric Bayesian latent variable model for multivariate data of arbitrary type that does not require specification of conditional distributions. Drawing on the extended rank likelihood method by Hoff [Ann. Appl. Stat. 1 (2007) 265-283], we develop a semiparametric approach for latent variable modeling with mixed outcomes and propose associated Markov chain Monte Carlo estimation methods. Motivated by cognitive testing data, we focus on bifactor models, a special case of factor analysis. We employ our semiparametric Bayesian latent variable model to investigate the association between cognitive outcomes and MRI-measured regional brain volumes.
PARALLEL FDTD AND PARALLEL GA FOR MICROWAVE TOMOGRAPHY IN BREAST CANCER DETECTION

Asymptomatic screening methods are import to lower the mortality rate of breast cancer patients. Technologies available in clinics have weaknesses in terms of sensitivity and specificity. Microwave imaging technique uses the apparent dielectric property contrasts between different breast tissues at microwave frequencies and is a prospective direction to find small tumor at their early stage. Microwave tomography falls in one category of microwave imaging technique. There are two main components in microwave tomography to detect abnormalities in breasts: Genetic Algorithm (GA) and FiniteDifference Time-Domain (FDTD). Both GA and FDTD are time-consuming, but, they are data-parallel in nature. In this paper, we have designed a parallel framework for microwave tomography: parallel GA combined with parallel FDTD. The algorithms are implemented on distributed memory machines running MPI. It achieves a result of finding a 1.5cm tumor in a breast phantom of 12cm in diameter, with a speedup of 6.25 using 16 processors.
Privacy Preserving Naïve Bayes Classifier for Horizontally Distribution Scenario Using Un-trusted Third Party

The aim of the classification task is to discover some kind of relationship between the input attributes and the output class, so that the discovered knowledge can be used to predict the class of a new unknown tuple. The problem of secure distributed classification is an important one. In many situations, data is split between multiple organizations. These organizations may want to utilize all of the data to create more accurate predictive models or classifier while revealing neither their training data nor the tuples to be classified. The Naive Bayes classifier is a simple but efficient baseline classifier. In this paper, we present a privacy preserving Naive Bayes classifier for horizontally partitioned data. Our three layer protocol uses an Un-trusted Third Party (UTP). We study how to calculate model parameters for privacy preserving three-layer Naive Bayes classifier for horizontally partitioned databases and communicate their intermediate results to the UTP not their private data. In our protocol, an UTP allows to meet privacy constraints and achieve acceptable performance.
Combining Undersampled Dithered Images

Undersampled images, such as those produced by the HST WFPC‐2, misrepresent fine‐scale structure intrinsic to the astronomical sources being imaged. Analyzing such images is difficult on scales close to their resolution limits and may produce erroneous results. A set of “dithered” images of an astronomical source generally contains more information about its structure than any single undersampled image, however, and may permit reconstruction of a “superimage” with Nyquist sampling. I present a tutorial on a method of image reconstruction that builds a Nyquist superimage from a complex linear combination of the Fourier transforms of a set of undersampled dithered images. This method works by algebraically eliminating the high‐order satellites in the periodic transforms of the aliased images. The reconstructed image is an exact representation of the data set with no loss of resolution at the Nyquist scale. The algorithm is directly derived from the theoretical properties of aliased images and involves no arbitrary parameters, requiring only that the dithers are purely translational and constant in pixel space over the domain of the object of interest. I show examples of its application to WFC and PC images. I argue for its use when the best recovery of point sources or morphological information at the HST diffraction limit is of interest.
Potential functions and actions of Tori on Kähler manifolds

Let M be a Kaehler manifold with a free, holomorphic and Hamiltonian action of the standard n-torus T. We give a simple, explicit and canonical formula for the Kaehler potential on the Kaehler reduction of M. As a consequence we can derive improvements of several classical results known for more general Hamiltonian reductions. Among these are a forms-level proof of the Duistermaat-Heckman theorem; an elementary proof of Atiyah's proof of the convexity of the moment image of a complexified T-orbit; another formula due to Biquard-Gauduchon for the Kaehler potential; and a formula in terms of moment data for the Kaehler metric on a toric variety, due originally to the second author.
Database of RNA binding protein expression and disease dynamics (READ DB)

RNA Binding Protein (RBP) Expression and Disease Dynamics database (READ DB) is a non-redundant, curated database of human RBPs. RBPs curated from different experimental studies are reported with their annotation, tissue-wide RNA and protein expression levels, evolutionary conservation, disease associations, protein–protein interactions, microRNA predictions, their known RNA recognition sequence motifs as well as predicted binding targets and associated functional themes, providing a one stop portal for understanding the expression, evolutionary trajectories and disease dynamics of RBPs in the context of post-transcriptional regulatory networks. Database URL: READ DB is freely available on the web at http://darwin.soic. iupui.edu/ with all major browsers supported.
The effects of cognitive dissonance on inappropriate emotional reactions.

In most emotionally arousmg situations, the mdividual is usually aware of the cause of his emotional reaction He probably would feel confident that his reaction is justified if it were obvious that the stimulus situation should evoke such a response m most people most of the tnne. However, there may be mstances when an mdividual experiences an emotional reaction that does not seem appropriate for the situation In other words, an mdividual might become aware that his reaction to a certam situation IS different from what is normally expected. In terms of dissonance theory, it might be said m such mstances that the mdividual's awareness of his reaction is dissonant with his appraisal that there might not be adequate reason for such a reaction He might try to reduce such dissonance by dismissmg the importance of his "mappropnate" reaction, perhaps by explammg his reaction on the basis of past expenence For example, the lnappropnateness of bemg fnghtened of a small dog might be dismissed on the grounds that he was bitten by a dog as a child Or the mdividual might try to explam his reaction by attnbutmg it to a general upset state, that is, by saymg "I'm worried about an exam, so everythmg is bothermg me today "
A Component-Oriented Reliability Model Using Back-Propagation Neural Networks

Most of the component-based software reliability models suffer from the evaluating complexity for the software system with high complex structures. A component-based back-propagation reliability model (CBPRM) for the high complex software system reliability evaluation is presented in this paper with a low complexity. The novel scheme is based on the artificial neural networks and the component reliability sensitivity analyses. The component reliability sensitivity analyses are performed dynamically and assigned to the neurons to optimize the reliability evaluation. Based on the experiment results and analyses, it shows that CBPRM outperforms the contrast models and the reliability evaluating accuracy is acceptable in the complex software system.
BuDDI: Bug detection, debugging, and isolation middlebox for software-defined network controllers

Despite tremendous software quality assurance efforts made by network vendors, chastising software bugs is a difficult problem especially, for the network systems in operation. Recent trends towards softwarization and opensourcing of network functions, protocols, controls, and applications tend to cause more software bug problems and pose many critical challenges to handle them. Although many traditional redundancy recovery mechanisms are adopted to the softwarized systems, software bugs cannot be resolved with them due to unexpected failure behavior. Furthermore, they are often bounded by common mode failure and common dependencies (CMFD). In this paper, we propose an online software bug detection, debugging, and isolation (BuDDI) middlebox architecture for software-defined network controllers. The BuDDI architecture consists of a shadow-controller based online debugging facility and a CMFD mitigation module in support of a seamless heterogeneous controller failover. Our proof-of-concept implementation of BuDDI is on the top of OpenVirtex by using Ryu and Pox controllers and verifies that the heterogeneous controller switchover does not cause any additional performance overhead.
Automatic Run-time Parallelization and Transformation of I/O

As the size of computational clusters grows, one can expect that I/O will consume an increasing portion of wall-clock time as the problem and node sizes are scaled up, unless parallel I/O is introduced. Unfortunately, using parallel I/O is non-trivial, so few applications developed by individual researchers enjoy its benefits. In this paper, we describe our novel method for analyzing I/O and communication operations at run-time. When nodes perform I/O or communication operations, our technique protects the memory associated with the requests from the application. Subsequent operations are analyzed for overlap between communication and I/O operations. When found, the I/O operation is automatically transformed, by our injected library, from an individual operation to a collective and shared MPI I/O operation. This allows users to benefit from parallel file systems without redesigning or recompiling their applications, and we demonstrate speedup for common usage patterns.
Thriving in Complexity? The OECD System's Role in Energy and Taxation

The purpose of this article is to reveal how two organizations from the OECD system—the Organisation for Economic Co-operation and Development and the International Energy Agency—are maneuvering strategically to retain their focal places in the regime complexes that developed around taxation and energy, respectively. It argues that their bid for leadership and centralization is built on the comparative advantages they enjoy as institutions; namely, their historically accumulated expertise and distinct working methods, their close ties with the Group of 8, and their rapidly developing relationships with emerging powers. Notwithstanding these institutional assets, a revision of the OECD's membership could further cement and legitimize the central role of the OECD system in these regime complexes.
Evaluation of a-Synuclein Degradation Pathways in a Budding Yeast Model

The nervous system controls and finely tunes most of the behaviors exhibited by animals. This system is made up of two parts: the central nervous system, consisting of the brain and spinal cord and the peripheral nervous system, which coordinates sensory input to the brain and motor output from the brain. The brain, in particular, contains approximately a hundred billion neurons that make several trillion connections to perform daily activities as diverse as sensation, perception, action, thought, motivation, emotions, memory, and homeostasis. However, what happens when these complex connections become dysfunctional or damaged? Unlike most other cells in our bodies, the brain and spinal cord neurons have severely limited abilities to recover from damage and disease, leading to permanent damage. Disorders that lead to irreversible and progressive deterioration of the nervous system are categorized as neurodegenerative diseases or NDDs (Ross & Poirier, 2004). The most well known of these diseases include Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington disease (HD), multiple sclerosis (MS), amyotrophic lateral sclerosis or Lou Gehrig's disease (ALS) and prion diseases. NDDs are an enormous economic burden to society. For instance, the annual cost for AD patients alone is 183 billion US dollars (Alzheimer’s Disease Facts and Figures Report, 2011). Despite years of extensive research, cures for these neurodegenerative diseases remain elusive yet imperative for overcoming the human loss and economic burden. Regardless of the diversity of symptoms that NDDs exhibit as a group, they have several important features in common. Firstly, in each NDD, a distinct group of cells die in an age-progressive manner responsible for that specifically cause the unique symptoms for that disease. Secondly, in those dying neurons, one or more proteins misfold and form fibrous aggregates that accumulate inside or outside the cells. This unifying pathology has laid the foundation for the current molecular understanding of NDDs, which are now also called proteinopathies or proteinmisfolding diseases (Taylor et al., 2002). Due to such shared pathology, understanding the mechanisms of protein misfolding-linked toxicity in one disease may unlock mysteries for the other NDDs. My thesis focuses on understanding the molecular mechanisms of protein misfolding-linked toxicity of one such major NDD: Parkinson’s disease (PD).