Miracle-dz/UniFAR-FTUs huggingface dataset:
Translational Repression Mediates Activation of Nuclear Factor Kappa B by Phosphorylated Translation Initiation Factor 2

ABSTRACT Numerous stressful conditions activate kinases that phosphorylate the alpha subunit of translation initiation factor 2 (eIF2α), thus attenuating mRNA translation and activating a gene expression program known as the integrated stress response. It has been noted that conditions associated with eIF2α phosphorylation, notably accumulation of unfolded proteins in the endoplasmic reticulum (ER), or ER stress, are also associated with activation of nuclear factor kappa B (NF-κB) and that eIF2α phosphorylation is required for NF-κB activation by ER stress. We have used a pharmacologically activable version of pancreatic ER kinase (PERK, an ER stress-responsive eIF2α kinase) to uncouple eIF2α phosphorylation from stress and found that phosphorylation of eIF2α is both necessary and sufficient to activate both NF-κB DNA binding and an NF-κB reporter gene. eIF2α phosphorylation-dependent NF-κB activation correlated with decreased levels of the inhibitor IκBα protein. Unlike canonical signaling pathways that promote IκBα phosphorylation and degradation, eIF2α phosphorylation did not increase phosphorylated IκBα levels or affect the stability of the protein. Pulse-chase labeling experiments indicate instead that repression of IκBα translation plays an important role in NF-κB activation in cells experiencing high levels of eIF2α phosphorylation. These studies suggest a direct role for eIF2α phosphorylation-dependent translational control in activating NF-κB during ER stress.
Ensemble structure of evolutionary artificial neural networks

Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. Evolution can be introduced at various levels of ANNs. It can be used to evolve weights, architectures, and learning parameters and rules. The paper is concerned with the evolution of ANN architectures, where an evolutionary algorithm is used to evolve a population of ANNs. The current practice in evolving ANNs is to choose the best ANN in the last population as the final result. The paper proposes a novel approach to form the final result by combining all the individuals in the last generation in order to make best use of all the information contained in the whole population. This approach regards a population of ANNs as an ensemble of ANNs and use a method to combine them. We have used four simple methods in our computational studies. The first is the majority voting method. The second and third are linear combination methods over the whole population. The fourth is a linear combination method over a subset of the whole population. The near optimal subset is obtained by a genetic algorithm search. Our experiments have shown that all four methods have produced better results than those produced by the single best individual.
Estimating influence of data layout optimizations on SDRAM energy consumption

An important problem in extracting maximum benefits from an SDRAM-based architecture is to exploit data locality at the page granularity. Frequent switches between data pages can increase memory latency and have an impact on energy consumption. In this paper, we propose a mathematical formulation, using Presburger arithmetic and Ehrhart polynomials to-estimate the number of page breaks statically (i.e., at compile time). The results obtained using video codes indicate that the proposed framework can estimate the number of page breaks with good accuracy.
Leveraging frequency and diversity based ensemble selection to consensus clustering

Consensus clustering, also called aggregation of clustering (or partitions) is a method that desires to improve the robustness and quality in clustering of a dataset by optimally reconciling the results of different clusterings of the same dataset generated in different ways. This paper proposes a novel way of arriving at a consensus clustering by an ensemble selection strategy. The method avoids considering the entire ensemble and judiciously select few clusterings in the ensemble without compromising on the quality of the consensus. It begins with sorting the ensemble by prioritizing clusterings based on diversity and frequency. It is observed that considering jointly the diversity and frequency helps in identifying few representative partitions that have high potentiality to form qualitatively better consensus than that of the entire ensemble. Finally a greedy strategy is used to select the clusterings in an iterative consensus generation technique that ensures the internal quality of clustering to be monotonically non-decreasing. Empirical results show that the consensus clustering obtained by the proposed algorithm gives better clustering accuracy for many datasets.
Parallelizing State Space Plans Online

Searching for parallel solutions in state space planners is a challenging problem, because it would require the planners to branch on all possible subsets of parallel actions, exponentially increasing their branching factor. We introduce a variant of our heuristic state search planner AltAlt, which generates parallel plans by using greedy online parallelization of partial plans. Empirical results show that our online approach outperforms post-processing (offline) techniques in terms of the quality of the solutions returned.
A two-layered model for scalable, heterogeneous group communications

In peer-to-peer (P2P) applications, a group of multiple peer processes (peers) are required to cooperate with each other. In this paper, we discuss a heterogeneous hybridtime group communication (HHT) protocol which takes advantage of the linear time (LT) and physical time (PT) to causally order messages in a scalable heterogeneous group. It depends on accuracy of each physical clock and minimum delay time between a pair of peers how messages can be ordered. In this paper, we consider a heterogeneous type of group where the clock accuracy of each peer and the minimum delay time between every pair of peers are not the same. In group protocols, even if a pair of messages are ordered in the protocol, the messages may not be causally ordered. Thus, some messages are unnecessarily ordered in the protocols. In this paper, we show the number of messages to be unnecessarily ordered can be reduced in the HHT protocol. In a scalable group, it is not easy, maybe impossible for each peer to hold information on the clock accuracy and minimum delay time of every peer. In this paper, we newly consider a two-layered model of a heterogeneous group to reduce the information which each peer has to hold.
Thermoacoustic Instability Suppression by Gain-Delay and ${\cal H}_{\infty}$  Controllers Designed for Secondary Fuel Injection

This paper describes the suppression of thermoacoustic instabilities in a swirl-stabilized test rig. To that end, a high-bandwidth secondary fuel injector is installed and commanded with robust H infin and simpler gain-delay controllers. Depending on the operating condition, several distinct flame types occur, which are investigated with OH chemiluminescence. A model of the plant is obtained by means of closed-loop identification experiments. The model-based H infin approach confers more design freedom to the engineer and gives better results. In particular, the sensitivity can be distributed arbitrarily to target specific and separate frequency ranges. The pressure spectrum reductions achieved are compared with the predictions of the design process and are found to agree well. The influence of the injected natural gas on the flame is studied through OH chemiluminescence. Experiments show that the controlled flame assumes a position similar to the one of a flame being in a stable operating condition.
Comparison of immunohistochemistry with fluorescence in situ hybridization in determining the human epidermal growth factor receptor 2 status of breast cancer specimens: a multicenter study of 3 149 Chinese patients

Background Accurate detection of human epidermal growth factor receptor 2 (HER2) expression and gene amplification is crucial for the application of HER2‐specific therapy and for evaluating the response of patients with breast cancer. A uniform and standard procedure of immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) needs to be established for evaluating the HER2 status in breast cancer tissues for the treatment of patients with real HER2‐positive tumors. The present multicenter study was aimed to examine the HER2 status in breast cancer specimens from Chinese patients using both IHC and FISH methods. Methods A multicenter study was performed on the HER2 status in 3 149 breast cancer specimens from different ethnic populations and areas in China by IHC and FISH assays. The potential association of HER2 status with demographic and clinical characteristics was analyzed. Results The positive rates for HER2 over‐expression and HER2 amplification were 23.3% and 27.5% in this study, respectively. The concordance between IHC and FISH was 71.2% (&kgr;=0.494, P <0.001). Furthermore, 72.9% of specimens with IHC 2+ were negative to FISH. The discordance rates among laboratories were from 5% to 28% for IHC and 1% to 16% for FISH. HER2 amplification was associated significantly with advanced tumor stage (III or IV, P=0.002), large tumor size (>5 cm, P=0.002), moderate and poor histological grades (P <0.0001), post‐menopause (P <0.0001), ER‐PR‐ (P=0.002), and having ≥4 lymph nodes affected (P <0.0001) in this population. The positive rates of HER2 amplification in specimens from Man and Hui Chinese were significantly higher than that in other Chinese populations. There are slightly higher positive rates of HER2 expression and amplification in Chinese patients with breast cancer. Conclusion These findings may provide new insights into understanding the epidemiological features of HER2 expression and amplification, and may be valuable for clinical practice.
Cabozantinib in the treatment of advanced renal cell carcinoma: design, development, and potential place in the therapy

The treatment of metastatic renal cell carcinoma (mRCC) has markedly improved over the last few years with the introduction of several targeted agents in clinical practice. Nevertheless, either primary or secondary resistance to inhibition of VEGF and mTOR pathways has limited the clinical benefit of these systemic treatments. Recently, a better understanding of the involvement of MET and its ligand HGF in many biological processes made this signaling pathway an attractive therapeutic target in oncology, particularly in mRCC. Herein, we review the development of cabozantinib, a recently approved inhibitor of multiple tyrosine kinase receptors, including MET, VEGFRs, and AXL, which has proven to increase progression-free survival and overall survival when compared to everolimus in mRCC patients who had progressed after VEGFR-targeted therapy. Finally, we discuss the potential role of cabozantinib within the current treatment landscape for mRCC.
Improved FSMD partitioning for low power using Plackett-Burman

Finite State Machine with Datapath (FSMD) partitioning is an effective technique for isolating circuit components. The isolated components can be clock gated or power gated to achieve dramatic power savings. FSMD partitioning typically relies on a highly complex, parameterized model, making the impact of the various tunable parameters hard to understand, leading to suboptimal partitions. In this paper, we use the Plackett and Burman experiment design methodology, which provides a statistically rigorous approach, to study a technique which uses simulated annealing to efficiently partition a FSMD for power gating. A better understanding of the effects of the various parameters allows the partitioning model to be robustly tuned towards optimality.
A solar PV system controlled by least sum of exponentials algorithm

This study proposes a new control for grid-connected solar PV (Photovoltaic) system which simultaneously injects active power and improves the quality of power of a three-phase distribution grid. The system comprises of a solar PV array, a VSC (Voltage Source Converter), a RC ripple filter and interfacing reactors connected to the three-phase distribution grid and linear/nonlinear balanced/unbalanced loads. The proposed control for the VSC in addition to harmonics mitigation, reactive compensation and balancing of three-phase loads concurrently extracts the maximum available power from the PV array by means of a MPPT (Maximum Power Point Tracking) algorithm. Besides the MPPT algorithm, the VSC is controlled by the least sum of exponentials algorithm. The THDs (Total Harmonic Distortions) of grid currents and the voltages at the PCC (Point of Common Coupling) are found to be within the limits given by IEEE 519 and IEEE 929 standards. The system performance is experimentally tested for a variety of loads and solar insolation levels on a prototype developed in the laboratory.
The IKMC web portal: a central point of entry to data and resources from the International Knockout Mouse Consortium

The International Knockout Mouse Consortium (IKMC) aims to mutate all protein-coding genes in the mouse using a combination of gene targeting and gene trapping in mouse embryonic stem (ES) cells and to make the generated resources readily available to the research community. The IKMC database and web portal (www.knockoutmouse.org) serves as the central public web site for IKMC data and facilitates the coordination and prioritization of work within the consortium. Researchers can access up-to-date information on IKMC knockout vectors, ES cells and mice for specific genes, and follow links to the respective repositories from which corresponding IKMC products can be ordered. Researchers can also use the web site to nominate genes for targeting, or to indicate that targeting of a gene should receive high priority. The IKMC database provides data to, and features extensive interconnections with, other community databases.
A Two-Time-Scale Design for Edge-Based Detection and Rectification of Uncooperative Flows

Existing Internet protocols rely on cooperative behavior of end users. We present a control-theoretic algorithm to counteract uncooperative users which change their congestion control schemes to gain larger bandwidth. This algorithm rectifies uncooperative users; that is, forces them to comply with their fair share, by adjusting the prices fed back to them. It is to be implemented at the edge of the network (e.g., by ISPs), and can be used with any congestion notification policy deployed by the network. Our design achieves a separation of time-scales between the network congestion feedback loop and the price-adjustment loop, thus recovering the fair allocation of bandwidth upon a fast transient phase
Reinforcement of composite laminate free edges with U-shaped caps

Generalized plane strain finite element analysis is used to predict reduction of interlaminar normal stresses when a U-shaped cap is bonded to the edge of a laminate. Three-dimensional composite material failure criteria are used in a progressive laminate failure analysis to predict failure loads of laminates with different edge cap designs. In an experimental program, symmetric 11-layer graphite-epoxy laminates with a one-layer cap of Kevlar-epoxy cloth are shown to be 130 to 140 percent stronger than uncapped laminates under static tensile and tension-tension fatigue loading. In addition, the coefficient of variation of the static tensile failure load decreases from 24 to 8 percent when edge caps are added. The predicted failure load calculated with the finite element results is 10 percent lower than the actual failure load. For both capped and uncapped laminates, actual failure loads are much lower than those predicted using classical lamination theory stresses and a two-dimensional failure criterion. Possible applications of the free edge reinforcement concept are described, and future research is suggested.
Prediction of magnetic orientation in driver gas associated -Bz events. [in interplanetary medium observed at earth when solar source is identified]

Can the magnetic orientation of driver gas in the interplanetary medium observed at Earth be predicted when its solar source is identified? Based on the exploratory assumption that the free magnetic energy present when a coronal mass ejection (CME) is initiated is transferred almost totally to other forms of energy by the time the CME stops acceleration, the potential field model can appropriately be used to calculate the magnetic orientation in the ejected plasma. As a first test of this hypothesis we have investigated the source regions of five strong −Bz events detected at 1 AU for which solar sources have been identified (Tang et al., 1989; Tsurutani et al., 1992). Three were traced to flare associated CMEs, one to an eruptive prominence associated CME, and one to three possible solar sources. The computed magnetic orientations at the candidate “release height” (the height where the front of a CME ceases to accelerate) above the flare sites associated with CMEs show the existence of the expected southward field component. On the other hand, the predicted field orientation at the candidate release height above the erupting prominence associated with a CME does not have a dominant southward field component. The result shows that the exploratory assumption may be proper only for the case of flare CMEs. With such a severely limited number of cases the results are only suggestive, but the magnetic orientation in flare associated CME generated driver gas may be predictable.
Application of Liquefied Wood to a New Resin System—Synthesis and Properties of Liquefied Wood/Epoxy Resins

Summary A new resin system was developed by reacting liquefied wood with various epoxy compounds. Examination of the optimum conditions for the synthesis of the resins, and the behavior of liquefied wood in the cured resins were undertaken. Generally, the compatibility and film forming performance of liquefied wood/epoxy resins became better as the wood content increased. The presence of only one broad dispersion peak, due to the glass transition, was observed during dynamic mechanical measurement of resin films suggesting that the different components of the resin were compatible. The glass transition temperature of the cured resins could be modified by changing the kinds of epoxy compounds and the wood contents of liquefied wood. The presence of rubber elasticity at higher temperatures suggests that the resin systems consisted of cross-linking polymer networks.
Mitogenic signaling by colony-stimulating factor 1 and ras is suppressed by the ets-2 DNA-binding domain and restored by myc overexpression

The activity of p21ras is required for the proliferative response to colony-stimulating factor 1 (CSF-1), and signals transduced by both the CSF-1 receptor (CSF-1R) and p21ras stimulate transcription from promoter elements containing overlapping binding sites for Fos/Jun- and Ets-related proteins. A sequence encoding the DNA-binding domain and nuclear localization signal of human c-ets-2, which lacked portions of the c-ets-2 gene product necessary for trans activation, was fused to the bacterial lacZ gene and expressed from an actin promoter in NIH 3T3 cells expressing either the v-ras oncogene or human CSF-1R. Nuclear expression of the Ets-LacZ protein, confirmed by histochemical staining of beta-galactosidase, inhibited the activity of ras-responsive enhancer elements and suppressed morphologic transformation by v-ras as well as CSF-1R-dependent colony formation in semisolid medium. When CSF-1R-bearing cells expressing the Ets-LacZ protein were stimulated by CSF-1, induction of c-ets-2, c-jun, and c-fos ensued, but the c-myc response was impaired. Enforced expression of the c-myc gene overrode the suppressive effect of ets-lacZ and restored the ability of these cells to form colonies in response to CSF-1. NIH 3T3 cells engineered to express a CSF-1R (Phe-809) mutant similarly cannot form CSF-1-dependent colonies in semisolid medium and exhibit an impaired c-myc response, but expression of an exogenous myc gene resensitizes these cells to CSF-1 [M. F. Roussel, J. L. Cleveland, S. A. Shurtleff, and C. J. Sherr, Nature (London) 353:361-363, 1991]. The ability of these cells to respond to CSF-1 was also rescued by enforced expression of an endogenous c-ets-2 gene. The ets family of transcription factors therefore plays a central role in integrating both CSF-1R and ras-induced mitogenic signals and in modulating the myc response to CSF-1 stimulation.
Partially Supervised Classification of Text Documents

We investigate the following problem: Given a set of documents of a particular topic or class P , and a large set M of mixed documents that contains documents from class P and other types of documents, identify the documents from class P in M . The key feature of this problem is that there is no labeled nonP document, which makes traditional machine learning techniques inapplicable, as they all need labeled documents of both classes. We call this problem partially supervised classification. In this paper, we show that this problem can be posed as a constrained optimization problem and that under appropriate conditions, solutions to the constrained optimization problem will give good solutions to the partially supervised classification problem. We present a novel technique to solve the problem and demonstrate the effectiveness of the technique through extensive experimentation.
Label-Based Access Control: An ABAC Model with Enumerated Authorization Policy

There are two major techniques for specifying authorization policies in Attribute Based Access Control (ABAC) models. The more conventional approach is to define policies by using logical formulas involving attribute values. Examples in this category include ABAC, HGABAC and XACML. The alternate technique for expressing policies is by enumeration. Policy Machine (PM) and 2-sorted-RBAC fall into the later category. In this paper, we present an ABAC model named LaBAC (Label-Based Access Control) which adopts the enumerated style for expressing authorization policies. LaBAC can be viewed as a particularly simple instance of the PolicyMachine. LaBAC uses one user attribute (uLabel) and one object attribute (oLabel). An authorization policy in LaBAC for an action is an enumeration using these two attributes. Thus, LaBAC can be considered as a bare minimum ABAC model. We show equivalence of LaBAC and 2-sorted-RBAC with respect to theoretical expressive power. Furthermore, we show how to configure the traditional RBAC (Role-Based Access Control) and LBAC (Lattice-Based Access Control) models in LaBAC to illustrate its expressiveness.
Continuous Attractor Neural Networks

In this chapter a brief review is given of computational systems that are motivated by information processing in the brain, an area that is often called `neurocomputing’ or `artificial neural networks’. While this is now a well studied and documented area, specific emphasis is given to a subclass of such models, called continuous attractor neural networks, which are beginning to emerge in a wide context of biologically inspired computing. The frequent appearance of such models in biologically motivated studies of brain functions gives some indication that this model might capture important information processing mechanisms used in the brain, either directly or indirectly. Most of this chapter is dedicated to an introduction to this basic model and some extensions that might be important for their application, either as model of brain processing, or in technical applications. Direct technical applications are only emerging slowly, but some examples of promising directions are highlighted in this chapter.