Miracle-dz/UniFAR-FTUs huggingface dataset:
THERMAL CONTROL IN 3D LIQUID COOLED PROCESSORS VIA HOTSPOT SEPARATION AND THERMOELECTRIC COOLING

Microchannel liquid cooling is a promising technique to handling the high temperature problem of threedimensional (3D) processors. There have been a few works which made initial attempts to optimize liquid cooling by utilizing non-uniformly distributed channels, variable flow rate, wider channels, and Dynamic Voltage and Frequency Scaling (DVFS) combined with thread migration mechanisms. Although these optimizations could be better than a straightforward microchannel liquid cooling design, the cooling of 3D processors is limited due to design-time and run-time challenges. Moreover, in new technologies, the processor power density is continually increasing and this will bring more serious challenges to liquid cooling. In this paper, we propose two thermal control techniques to control hotspots in liquid cooled 3D processors: 1) Core Vertically Placed (CVP) technique. According to the architecture of a processor core, two schemes are given for placing a core vertically onto multilayers. The 3D processor with the CVP technique can be better cooled since its separate hotspot blocks have a larger contact area with the cooler surroundings. 2) Thermoelectric cooling (TEC) technique. We propose to incorporate the TEC technique into the liquid-cooled 3D processor to enhance the cooling of hotspots. Our experiments show the CVP technique reduces the maximum temperature up to 29.58 oC, and 13.77 oC on average compared with the baseline design. Moreover, the TEC technique effectively cools down a hotspot from 96.86 oC to 78.60 oC. Furthermore, the CVP technique supports a 30% increase in processor frequency which results in a 1.27 times speedup of processor performance.
New determinants of bilateral trade: An empirical analysis for developed and developing countries

In this dissertation, the pattern and direction of international trade flows will be analysed by taking into consideration different levels of development across countries in the world. A better understanding of the factors explaining trade will help authorities to define specific economic and industrial policies at macro and micro levels in order to promote trade and subsequently economic development and growth in countries at different stages of development.The dissertation analyses in greater detail the role of some of the variables recently considered as determinants of international trade flows. Technological innovation, geographical factors, cultural similarities and trade costs are the explanatory factors that will be investigated in depth. First, aggregated trade flows are modelled as a function of incomes, distance, technological innovation, geography and cultural similarities. Second, a disaggregated analysis is performed to investigate the effect of tariffs and transport costs on bilateral trade flows.Determinants of international trade flows may differ across both countries and sectors. Country and sector heterogeneity issues will therefore be considered when analysing international trade patterns.One of the main devices used to analyse the determinants of international trade flows is the gravity model of trade. Recently, some authors have referred to this model as the "workhorse" of empirical trade. In this dissertation, the gravity model is the main modelling framework used.
AODV Robust (AODVR): An Analytic Approach to Shield Ad-hoc Networks from Black Holes

Mobile ad-hoc networks are vulnerable to several types of malicious routing attacks, black hole is one of those, where a malicious node advertise to have the shortest path to all other nodes in the network by the means of sending fake routing reply. As a result the destinations are deprived of desired information. In this paper, we propose a method AODV Robust (AODVR) a revision to the AODV routing protocol, in which black hole is perceived as soon as they emerged and other nodes are alerted to prevent the network of such malicious threats thereby isolating the black hole. In AODVR method, the routers formulate the range of acceptable sequence numbers and define a threshold. If a node exceeds the threshold several times then it is black listed thereby increasing the network robustness.
Real Effects of the 2007-08 Financial Crisis Around the World

This paper proposes a simple framework (a) to quantify the importance of the finance shock to non-financial firms in 45 countries by exploring cross-firm heterogeneity in dependence on external finance for working capital and investment, and (b) to study whether and how the type of financial system, the nature of monetary and exchange rate regime, and the magnitude of pre-crisis credit expansion affect the transmission of the finance shocks internationally by exploring cross-country heterogeneity in these dimensions. We find that the decline of stock price was more severe for firms with larger ex ante sensitivity to external finance over the period from July 2007 to August 2008. This finding thus provides convincing evidence that non-financial firms have indeed suffered from a strongly negative supply-of-finance shock. Moreover, this pattern is particularly pronounced in countries with rapid pre-crisis credit expansion and a monetary policy of inflation targeting.
Teachers’ reflections of instructional effectiveness: self-assessment through a standards-based appraisal process

ABSTRACT This paper explores teachers’ reflections on: (1) self-assessment of their own videotaped lesson using a standards-based appraisal system; (2) comparison to an external reviewer’s evaluation of the same lesson; and (3) effect of the appraisal system on their pedagogical views, professional development, and actual practice improvement. Findings indicate that teachers view the appraisal system as evaluative with little impact on their teaching practice and professional growth. Participating teachers indicated that the self-evaluative reflection process utilized in the study had a greater influence on their professional development than the appraisal system as it is currently structured.
A compressed sensing approach to 3D weak lensing

(Abridged) Weak gravitational lensing is an ideal probe of the dark universe. In recent years, several linear methods have been developed to reconstruct the density distribution in the Universe in three dimensions, making use of photometric redshift information to determine the radial distribution of lensed sources. In this paper, we aim to address three key issues seen in these methods; namely, the bias in the redshifts of detected objects, the line of sight smearing seen in reconstructions, and the damping of the amplitude of the reconstruction relative to the underlying density. We consider the problem under the framework of compressed sensing (CS). Under the assumption that the data are sparse in an appropriate dictionary, we construct a robust estimator and employ state-of-the-art convex optimisation methods to reconstruct the density contrast. For simplicity in implementation, and as a proof of concept of our method, we reduce the problem to one-dimension, considering the reconstruction along each line of sight independently. Despite the loss of information this implies, we demonstrate that our method is able to accurately reproduce cluster haloes up to a redshift of z=1, deeper than state-of-the-art linear methods. We directly compare our method with these linear methods, and demonstrate minimal radial smearing and redshift bias in our reconstructions, as well as a reduced damping of the reconstruction amplitude as compared to the linear methods. In addition, the CS framework allows us to consider an underdetermined inverse problem, thereby allowing us to reconstruct the density contrast at finer resolution than the input data.
Portfolio Level FVA Under Perfect Collateralization and Re-Hypothecation

This thesis concentrates on FVA computation for interest rate swaps under perfect collateralization and re-hypothecation. It also analyses the effect of FVA computation in a portfolio level. With a Hull-White set-up for interest rate, we are able to compute FVA for single swap and swap portfolios. It shows that the funding cost of transactions can be partially or entirely reduced in that sense.
Efficient GPU-based training of recurrent neural network language models using spliced sentence bunch

Copyright © 2014 ISCA. Recurrent neural network language models (RNNLMs) are becoming increasingly popular for a range of applications including speech recognition. However, an important issue that limits the quantity of data, and hence their possible application areas, is the computational cost in training. A standard approach to handle this problem is to use class-based outputs, allowing systems to be trained on CPUs. This paper describes an alternative approach that allows RNNLMs to be efficiently trained on GPUs. This enables larger quantities of data to be used, and networks with an unclustered, full output layer to be trained. To improve efficiency on GPUs, multiple sentences are "spliced" together for each mini-batch or "bunch" in training. On a large vocabulary conversational telephone speech recognition task, the training time was reduced by a factor of 27 over the standard CPU-based RNNLM toolkit. The use of an unclustered, full output layer also improves perplexity and recognition performance over class-based RNNLMs.
Range queries in natural language dictionaries with recursive lists of clusters

We evaluate the performance of range queries in the Recursive List of Clusters (RLC) metric data structure, when the metric spaces are natural language dictionaries with the Levenshtein distance. The study compares RLC with five data structures (GNAT, H-Dsatl, LAESA, LC, and vp-trees) and comprises six dictionaries. The natural language dictionaries (in English, French, German, Italian, Portuguese, and Spanish), are characterised according to the mean and the variance of the histograms of distances. The experimental results show that RLC has a good performance in all tested cases and, in some of them, it outperforms all the other data structures. In addition, RLC is the only data structure that always keeps its good performance, whether the space dimension is lower or higher, and whether the query radius is smaller or larger.
Responses of the Rhodobacter sphaeroides Transcriptome to Blue Light under Semiaerobic Conditions

ABSTRACT Exposure to blue light of the facultative phototrophic proteobacterium Rhodobacter sphaeroides grown semiaerobically results in repression of the puc and puf operons involved in photosystem formation. To reveal the genome-wide effects of blue light on gene expression and the underlying photosensory mechanisms, transcriptome profiles of R. sphaeroides during blue-light irradiation (for 5 to 135 min) were analyzed. Expression of most photosystem genes was repressed upon irradiation. Downregulation of photosystem development may be used to prevent photooxidative damage occurring when the photosystem, oxygen, and high-intensity light are present simultaneously. The photoreceptor of the BLUF-domain family, AppA, which belongs to the AppA-PpsR antirepressor-repressor system, is essential for maintenance of repression upon prolonged irradiation (S. Braatsch et al., Mol. Microbiol. 45:827-836, 2002). Transcriptome data suggest that the onset of repression is also mediated by the AppA-PpsR system, albeit via an apparently different sensory mechanism. Expression of several genes, whose products may participate in photooxidative damage defense, including deoxypyrimidine photolyase, glutathione peroxidase, and quinol oxidoreductases, was increased. Among the genes upregulated were genes encoding two σ factors: σE and σ38. The consensus promoter sequences for these σ factors were predicted in the upstream sequences of numerous upregulated genes, suggesting that coordinated action of σE and σ38 is responsible for the upregulation. Based on the dynamics of upregulation, the anti-σE factor ChrR or its putative upstream partner is proposed to be the primary sensor. The identified transcriptome responses provided a framework for deciphering blue-light-dependent signal transduction pathways in R. sphaeroides.
Antigens of herpes simplex virus of oral and genital origin.

The serological distinction between herpesviruses of oral or genital origin has been unequivocally shown by Schneweis (26), Plummer (21), and others (3, 20). Biological studies on the characterization of the 2 viruses have, in general, supported the idea of 2 discrete clusters. The 2 types behave differently in tissue culture held under particu lar conditions (5, 14, 15, 23) and the behavior of the 2 types on the chorioallantoic membranes of eggs of hens likewise supports the existence of 2 groups (19), but some studies indicate that there may be intermediate types (4). Clear-cut differences are obvious when comparing the acid-extractable proteins of the 2 types of virus (8) and some virus-speci fied enzymes appear to differ in their physical characteris tics (32). Indeed, differences can be detected in the DNA's
Data Quality in Very Large, Multiple-Source, Secondary Datasets for Data Mining Applications

The data mining research community is increasingly addressing data quality issues, including problems of dirty data. Hand, Blunt, Kelly and Adams (2000) have identified high-level and low-level quality issues in data mining. Kim, Choi, Hong, Kim and Lee (2003) have compiled a useful, complete taxonomy of dirty data that provides a starting point for research in effective techniques and fast algorithms for preprocessing data, and ways to approach the problems of dirty data. In this study we create a classification scheme for data errors by transforming their general taxonomy to apply to very large multiple-source secondary datasets. These types of datasets are increasingly being compiled by organizations for use in their data mining applications. We contribute this classification scheme to the body of research addressing quality issues in the very large multiple-source secondary datasets that are being built through today’s global organizations’ massive data collection from the Internet.
Cache Template Attacks: Automating Attacks on Inclusive Last-Level Caches

Recent work on cache attacks has shown that CPU caches represent a powerful source of information leakage. However, existing attacks require manual identification of vulnerabilities, i.e., data accesses or instruction execution depending on secret information. In this paper, we present Cache Template Attacks. This generic attack technique allows us to profile and exploit cache-based information leakage of any program automatically, without prior knowledge of specific software versions or even specific system information. Cache Template Attacks can be executed online on a remote system without any prior offline computations or measurements. Cache Template Attacks consist of two phases. In the profiling phase, we determine dependencies between the processing of secret information, e.g., specific key inputs or private keys of cryptographic primitives, and specific cache accesses. In the exploitation phase, we derive the secret values based on observed cache accesses. We illustrate the power of the presented approach in several attacks, but also in a useful application for developers. Among the presented attacks is the application of Cache Template Attacks to infer keystrokes and--even more severe--the identification of specific keys on Linux and Windows user interfaces. More specifically, for lowercase only passwords, we can reduce the entropy per character from log2(26) = 4.7 to 1.4 bits on Linux systems. Furthermore, we perform an automated attack on the T-table-based AES implementation of OpenSSL that is as efficient as state-of-the-art manual cache attacks.
A Naphthalenic Derivative ND-1 Inhibits Thrombus Formation by Interfering the Binding of Fibrinogen to Integrin αIIbβ3

Integrin αIIbβ3 plays a crucial role in the process of platelet aggregation. Three integrin αIIbβ3 antagonists (abciximab, eptifibatide, and tirofiban) have been approved by FDA for clinical use. Unfortunately, they all showed severe side effects such as thrombocytopenia and bleeding risk. Thus, researches on the development of more effective and safer antiplatelet agents are needed. In this manuscript we reported a novel naphthalenic derivative compound ND-1 with potent antithrombotic effect and lower bleeding risk. ND-1 inhibited ADP-, collagen-, thrombin-, and U46619-induced platelet aggregation with IC50 values of 1.29, 14.46, 12.84, and 40.24 μM, respectively. Mechanism studies indicated that ND-1 inhibited the binding of fibrinogen to integrin αIIbβ3 in a dose-dependent manner with an IC50 value of 3.12 μM. ND-1 inhibited P-selectin expression induced by ADP, collagen, thrombin, and U46619 on the surface of platelets. Additionally, this compound reduced platelets spreading to the immobilized fibrinogen. In vivo, ND-1 potently decreased thrombus formation in an arteriovenous shunt thrombosis model in rats and slightly prolonged bleeding time in a tail cutting model in mice. Taken together, our results reveal that ND-1 is a novel antagonist of αIIbβ3 with strong antithrombotic effect and lower bleeding risk.
Catecholamines Abrogate Antimitogenic Effects of 2-Hydroxyestradiol on Human Aortic Vascular Smooth Muscle Cells

Catechol-O-methyltransferase (COMT)-mediated methylation of 2-hydroxyestradiol (endogenous estradiol metabolite) to 2-methoxyestradiol (angiogenesis inhibitor) may be responsible for the antimitogenic effects of 2-hydroxyestradiol on vascular smooth muscle cells (VSMCs). Catecholamines are also substrates for COMT, and increased levels of catecholamines are associated with vasoocclusive disorders. We hypothesize that catecholamines may abrogate the vasoprotective effects of 2-hydroxyestradiol by competing for COMT and inhibiting 2-methoxyestradiol formation. To test this hypothesis, we investigated the antimitogenic effects of 0.001 to 0.1 &mgr;mol/L of 2-hydroxyestradiol on human aortic VSMC proliferation (cell number and DNA synthesis), collagen synthesis, and migration in the presence and absence of catecholamines. Norepinephrine, epinephrine, and isoproterenol concentration-dependently abrogated the inhibitory effects of 2-hydroxyestradiol on cell number, DNA synthesis, collagen synthesis, and cell migration. These modulatory/attenuating effects of catecholamines were not abrogated in the presence of the &agr;- and &bgr;-adrenergic receptor antagonists, phentolamine mesylate and propranolol, respectively. In contrast to 2-hydroxyestradiol, the antimitogenic effects of 2-methoxyestradiol (0.1 &mgr;mol/L) were not attenuated by isoproterenol (1 &mgr;mol/L) or quercetin (competitive inhibitor of COMT, 10 &mgr;mol/L). Norepinephrine, epinephrine, and isoproterenol concentration-dependently (10 to 500 &mgr;mol/L) inhibited the metabolism of 2-hydroxyestradiol (0.25 to 2 &mgr;mol/L) to 2-methoxyestradiol, and the potency of the catecholamines to reverse 2-hydroxyestradiol-induced inhibition of VSMC proliferation, collagen synthesis, and migration was correlated with their ability to inhibit 2-methoxyestradiol formation. Our findings suggest that catecholamines within the vasculature may abrogate the anti-vaso-occlusive effects of estradiol and 2-hydroxyestradiol by blocking 2-methoxyestradiol formation.
The National Register of Historic Places

United States Department of the Interior National Park Service D"ZG 2 11990" National Register of Historic Places Multiple Property Documentation Form NATIONAL REGISTER This form is for use in documenting multiple property groups relating to one or several historic contexts. See instructions in Guidelines tor Completing National Register Forms (National Register Bulletin 16). Complete each item by marking "x" in the appropriate box or by entering the requested information. For additional space use continuation sheets (Form 10-900-a). Type all entries.
Bounds On The Sum Of A Divergent Series

Given a truncated perturbation expansion of a physical quantity, one can, under certain circumstances, obtain lower or upper bounds (or both) to the sum of the full perturbation series by using the Borel transform and a variational conformal map. The method is illustrated by applying it to various mathematical toy-models for which exact results are known. One of these models is used to exemplify how non-perturbative contributions supplement the sum of a Borel-nonsummable series to give the final exact and unambiguous result. Finally, the method is applied to some physical problems. In particular, some speculations are made on the phase of quantum electrodynamics at super-high temperatures from a study of its perturbative free-energy density.
Classification of proteins in intracellular and secretory pathway using global descriptors of amino acid sequence

It is widely recognized that the information from the amino acid sequence can serve as crucial pointers in predicting subcellular location of proteins. We introduce a new feature vector for predicting proteins targeted to various compartments in the intracellular and secretory pathway from protein sequence. Features are based on the global Composition, Transition and Distribution (CTD) of amino acid attributes such as hydrophobicity, normalized van der Waals volume, polarity, polarizability, charge, secondary structure and solvent accessibility. Sequences are considered in three equal parts and the features are extracted separately for all the three parts. Based on the feature vectors, we have trained a Support Vector Machine to classify intracellular and secretory proteins. Our method gives an accuracy of 92% in human, 88% in plant and 95% in fungi with independent dataset at root level of the protein sorting pathway.
The Universe and Parallel Radiosity

Radiosity provides an effective method for modelling a diffuse environment. Unfortunately this method is computationally expensive. The main cost of the radiosity method is the calculation of form factors which takes approximately 95% of the computation time. Through the use of a task farm the computation of form factors can be parallelised, on a Massively Parallel Processor (MPP) super computer like the CRAY-T3D. This creates a relatively good linear speed up. A different approach is to use a Symmetric Multi-Processing (SMP) model. Threads, instead of processes, are used to perform the work using a task farm. Apart from the thread’s stack space all memory is global. Communication and synchronisation takes place using semaphores and conditions instead of message passing. This model reduces the amount of communication and synchronisation required between the master and the slaves. The size of the environment is limited only by the total amount of virtual memory available to the process. Both models provide effective linear speed up solutions to a computationally expensive problem. The task that follows is to improve the algorithm itself and possibly reduce the prohibitively expensive O(n2) scaling of the problem.