Miracle-dz/UniFAR-FTUs huggingface dataset:
1,3-Diphenylethenylcarbazolyl-Based Monomer for Cross-Linked Hole Transporting Layers

A new cross-linkable monomer containing 1,3-diphenylethenylcarbazolyl-based hole-transporting moieties and four reactive epoxy groups, was prepared by a multistep synthesis route from 1,3-bis(2,2-diphenylethenyl)-9H-carbazol-2-ol and its application for the in situ formation of cross-linked hole transporting layers was investigated. A high concentration of flexible aliphatic epoxy chains ensures good solubility and makes this compound an attractive cross-linking agent. The synthesized compounds were characterized by various techniques, including differential scanning calorimetry, xerographic time of flight, and electron photoemission in air methods.
Compression of Microarray Images

DNA microarrays have become a tool of paramount importance in the study of gene function, regulation, and interaction across large numbers of genes, and even entire genomes (Hegde et al., 2000; Moore, 2001). Microarray experiments generate pairs of 16 bits per pixel grayscale images (see Fig. 1, for an example). These images, which may require several tens of megabytes in order to be stored or transmitted, are analyzed by software tools that extract relevant information, such as the intensity of the spots and the background level. This information is then used for evaluating the expression level of individual genes (Hegde et al., 2000; Moore, 2001).
Statistical modeling of speech signals based on generalized gamma distribution

In this letter, we propose a new statistical model, two-sided generalized gamma distribution (G/spl Gamma/D) for an efficient parametric characterization of speech spectra. G/spl Gamma/D forms a generalized class of parametric distributions, including the Gaussian, Laplacian, and Gamma probability density functions (pdfs) as special cases. We also propose a computationally inexpensive online maximum likelihood (ML) parameter estimation algorithm for G/spl Gamma/D. Likelihoods, coefficients of variation (CVs), and Kolmogorov-Smirnov (KS) tests show that G/spl Gamma/D can model the distribution of the real speech signal more accurately than the conventional Gaussian, Laplacian, Gamma, or generalized Gaussian distribution (GGD).
On the Spitzer-Härm Regime and Nonlocal Approximations: Modeling, Analysis, and Numerical Simulations

This paper is devoted to the derivation of the Spitzer–Harm limit from the coupled system of PDEs describing the evolution of charged particles and electromagnetic fields. We identify a relevant asymptotic regime which leads to a nonlinear diffusion equation for the electron temperature. Then, we discuss some intermediate models, which remain of hydrodynamic nature but involve a nonlocal coupling through integral or pseudodifferential operators. In particular, we exhibit important mathematical properties of the so-called Schurtz–Nicolai model like the well-posedness and the maximum principle. We also design numerical schemes for the nonlocal models and analyze their consistency and stability properties.
Probabilistic risk assessment of excavation performance in tunnel projects using Bayesian networks: A case study

A model for probabilistic assessment of excavation performance of tunnel projects is presented. The model is based on Dynamic Bayesian Networks (DBN) and enables to consider the quality of the design and construction process. It is applied on a case study, the excavation of a road tunnel by means of the New Austrian Tunnelling Method. The influence of main model parameters and assumptions (e.g. quality, distribution of unit time) is assessed through a sensitivity analysis.
Characterization of Salmonella Type III Secretion Hyper-Activity Which Results in Biofilm-Like Cell Aggregation

We have previously reported the cloning of the Salmonella enterica serovar Typhimurium SPI-1 secretion system and the use of this clone to functionally complement a ΔSPI-1 strain for type III secretion activity. In the current study, we discovered that S. Typhimurium cultures containing cloned SPI-1 display an adherent biofilm and cell clumps in the media. This phenotype was associated with hyper-expression of SPI-1 type III secretion functions. The biofilm and cell clumps were associated with copious amounts of secreted SPI-1 protein substrates SipA, SipB, SipC, SopB, SopE, and SptP. We used a C-terminally FLAG-tagged SipA protein to further demonstrate SPI-1 substrate association with the cell aggregates using fluorescence microscopy and immunogold electron microscopy. Different S. Typhimurium backgrounds and both flagellated and nonflagellated strains displayed the biofilm phenotype. Mutations in genes essential for known bacterial biofilm pathways (bcsA, csgBA, bapA) did not affect the biofilms formed here indicating that this phenomenon is independent of established biofilm mechanisms. The SPI-1-mediated biofilm was able to massively recruit heterologous non-biofilm forming bacteria into the adherent cell community. The results indicate a bacterial aggregation phenotype mediated by elevated SPI-1 type III secretion activity with applications for engineered biofilm formation, protein purification strategies, and antigen display.
Generalized Chaplygin gas as a unified scenario of dark matter/energy: Observational constraints

Although various cosmological observations congruously suggest that our universe is dominated by two dark com- ponents, the cold dark matter without pressure and the dark energy with negative pressure, the nature and origin of these components is yet unknow. The generalized Chaplygin gas (gCg), parametrized by an equation of state, p = −A/ρ α ,w as recently proposed to be a candidate of the unified dark matter/energy (UDME) scenarios. In this work, we investigate some observational constraints on it. We mainly focus our attention on the constraints from recent measurements of the X-ray gas mass fractions in clusters of galaxies published by Allen et al. (2002, MNRAS, 334, L11; 2003, 342, 257) and the dimensionless coordinate distances to type Ia supernovae and Fanaroff-Riley type IIb radio galaxies compiled by Daly & Djorgovski (2003, ApJ, 597, 9). We obtain the confidence region on the two parameters fully characterizing gCg, As ≡ A/ρ (1+α) gCg0 and α, from a combined analysis of these databases, where ρgCg0 is the energy density of gCg at present. It is found that As = 0.70 +0.16 −0.17 and α = −0.09 +0.54 −0.33 , at a 95% confidence level, which is consistent within the errors with the standard dark matter + dark energy model, i.e., the case of α = 0. Particularly, the standard Chaplygin gas (α = 1) is ruled out as a feasible UDME by the data at a 99% confidence level.
Wildfire Emission Modeling : Integrating BlueSky and SMOKE

Atmospheric chemical transport models are used to simulate historic meteorological episodes for developing air quality management strategies. Wildland fire emissions need to be characterized accurately to achieve these air quality management goals. The temporal and spatial estimates of emissions from fires, both wild and prescribed, have been problematic primarily because of uncertainty in the size and location of sources, and their temporal and spatial variability. Therefore, methods to estimate wildfire emissions that characterize their temporal and spatial variability are needed. The US Forest Service (USFS) and the US Environmental Protection Agency (EPA) have signed an interagency agreement to improve the episodic modeling of fires with improved fuel loading data, fire location information, and fire behavior modeling (including plume behavior), using meteorological inputs. The USFS has developed a tool known as BlueSky to predict cumulative impacts of smoke from forest, agricultural, and range fires. The BlueSky modeling framework combines state of the art emissions, meteorology, and dispersion models to generate predictions of smoke impacts across the landscape. The Sparse Matrix Operator Kernel Emission (SMOKE) processing system is a tool that creates gridded, speciated, and temporally allocated emission estimates for use in atmospheric chemical models. Portions of these tools have been combined to allow for an accurate characterization of fuel loading, temporal and spatial distribution of fire emissions, and a more accurate representation of fire plumes. By combining these two tools, the ability to simulate the impact of wildfires on air quality and develop air quality management strategies will be enhanced. This paper shows results from combining these two tools and an example from an air quality modeling simulation.
The "84/14/2" rule revisited : what drives choice, incidence and quantity elasticities?

A brand's total price elasticity, conditional on a purchase occasion, can be decomposed into three components: the brand choice, purchase incidence and purchase quantity elasticity. Gupta (1988) has analyzed this relationship within the context of a single product category. That study reported that the main impact of a price promotion falls on brand choice (84%), but to a lesser extent, purchase timing acceleration (14%) and stockpiling (2%), are also impacted. This research makes three new substantive contributions. First, while we confirm that the majority of the promotion effect is derived from choice, the relative emphasis on incidence and quantity varies systematically across categories. Storable products have relatively higher weight on quantity, perishable products have a higher weight on incidence. Second, we utilize a generalized least squares meta analysis procedure (Montgomery and Srinivasan, 1996) to show how factors such as marketing effort, category structure, brand franchise and consumer demographic variables influence elasticities. One key finding is that unpredictability of marketing effort has more influence on elasticity response than does relative levels of marketing effort. Third, we show that in several instances where important decision variables do not affect total elasticities, this is due to offsetting effects within two or more of the three behavioral components of elasticity. To calibrate our models, we use a multicategory scanner panel dataset to generate choice, incidence and quantity promotion elasticity estimates for 173 brands within 13 categories. Managerial implications for developing effective promotion strategies are discussed.
Damaris: How to Efficiently Leverage Multicore Parallelism to Achieve Scalable, Jitter-free I/O

With exascale computing on the horizon, the performance variability of I/O systems represents a key challenge in sustaining high performance. In many HPC applications, I/O is concurrently performed by all processes, which leads to I/O bursts. This causes resource contention and substantial variability of I/O performance, which significantly impacts the overall application performance and, most importantly, its predictability over time. In this paper, we propose a new approach to I/O, called Damaris, which leverages dedicated I/O cores on each multicore SMP node, along with the use of shared-memory, to efficiently perform asynchronous data processing and I/O in order to hide this variability. We evaluate our approach on three different platforms including the Kraken Cray XT5 supercomputer (ranked 11th in Top500), with the CM1 atmospheric model, one of the target HPC applications for the Blue Waters postpetascale supercomputer project. By overlapping I/O with computation and by gathering data into large files while avoiding synchronization between cores, our solution brings several benefits: 1) it fully hides jitter as well as all I/O-related costs, which makes simulation performance predictable, 2) it increases the sustained write throughput by a factor of 15 compared to standard approaches, 3) it allows almost perfect scalability of the simulation up to over 9,000 cores, as opposed to state-of-the-art approaches which fail to scale, 4) it enables a 600% compression ratio without any additional overhead, leading to a major reduction of storage requirements.
Learning Distinct and Complementary Feature Selectivities from Natural Colour Videos

Many biological and artificial neural networks require the parallel extraction of multiple features, and meet this requirement with distinct populations of neurons that are selective to one property of the stimulus while being non-selective to another property. In this way, several populations can resolve a set of features independently of each other, and thus achieve a parallel mode of processing. This raises the question how an initially homogeneous population of neurons segregates into groups with distinct and complementary response properties. Using a colour image sequence recorded from a camera mounted on the head of a freely behaving cat, we train a network of neurons to achieve optimally stable responses, that is, responses that change minimally over time. This objective leads to the development of colour-selective neurons. Adding a second objective, decorrelating activity within the network, a subpopulation of neurons develops with achromatic response properties. Colour selective neurons tend to be non-oriented while achromatic neurons are orientation-tuned. The proposed objective thus successfully leads to the segregation of neurons into complementary populations that are either selective for colour or orientation.
Automatic Landing Control Law for Unmanned Helicopter using Lyapunov Approach

A globally stable tracking control law for automatic landing of unmanned helicopter is developed and validated using flight tests. To achieve both agile maneuver and precise landing, the near-minimum-time maneuver of a rigid body is used as reference trajectories. This approach enables a control law avoid large initial torque command. It also is shown that the control law is guaranteed to be globally stable in the sense of Lyapunov. Finally, flight test results utilizing the method are presented
Implementation of Occlusion Culling in Avango Virtual Environment Framework

Real-time visibility test is an attractive feature for Virtual Environment (VE) applications where large datasets should be interactively explored. In such scenes most of the objects are usually occluded by other ones, and their rejection from rendering can significantly accelerate the graphical performance. In this paper we present our implementation of occlusion culling in VE system Avango [1]. Visibility test module performs real-time update of the list of visible objects by means of color labeling and either hardware or software histogramming of corresponding color buffer. Exploiting the distribution capabilities of Avango, the main draw and visibility test processes are parallelized to different computers running Irix or Linux. Being applied to an architectural model containing 260,000 textured triangles, our method accelerates the graphical performance from 8 to 32 stereoimages/sec.
Workspace analysis of the underwater dexterous hand

This paper describes the present research work on IUDH underwater dexterous hand equipped with three fingers, six joints and four actuators, Which has been development at Anhui Polytechnic University and Hefei Institute of Intelligent Machine of Chinese Academy of Science. According to structure of IUDH, Every finger kinematics equations formulations for determining the boundary to manipulator are derived, by employing Denavit-Hartenberg representation. Further, every fingertip motion envelopment space is mapped. Moreover, volume and size of objects grasped by IUDH is certified. Thus, structure and geometric parameters of the hand are demonstrated and abilities for grasping objects are validated.
Detection, extraction and representation of tables

We are concerned with the extraction of tables from exchange format representations of very diverse composite documents. We put forward a flexible representation scheme for complex tables, based on a clear distinction between the physical layout of a table and its logical structure. Relying on this scheme, we develop a new method for the detection and the extraction of tables by an analysis of the graphic lines. To deal with tables that lack all or most of the graphic marks, one must focus on the regularities of the text elements alone. We propose such a method, based on a multi-level analysis of the layout of text components on a page. A general graph representation of the relative positions of blocks of text is exploited.
Entity based Programming Paradigm

Distributed systems are becoming increasingly important in order to scale services. However, these systems are complex with signiﬁcant concurrency and need for synchronization. Hence, these are diﬃcult to develop and we need better ways to program such systems. In this work, we present a new paradigm to program distributed systems based on real world distributed systems. We are social beings and are part of various teams and organizations or “real world” distributed systems. A fundamental approach we use to manage complexity of such real world systems is to abstract teams or organizations into single entities. We can use a similar approach in distributed systems to abstract a collection of nodes into an abstract entity and thus, make it easier to develop them. In this paper, we present this idea of entity abstraction and discuss various advantages of this approach.
Cytokine profiles in axial spondyloarthritis

Objectives Current studies concentrate on the cytokine network and its role in the pathogenesis of spondyloarthritis (SpA). In this study, we analyzed whether the serum cytokine profile (interleukins: IL-10, IL-11, IL-12, IL-15, IL-17, IL-23 and IL-33) correlates with demographic data, clinical manifestations, disease activity and treatment outcome in a group of patients with axial spondyloarthritis. Material and methods Forty-nine patients with an established diagnosis of axial spondyloarthritis (aSpA) and 19 healthy volunteers as controls were enrolled in the study. Clinical evaluation included patient's medical history, 44 joint count, back pain intensity and global disease activity in the preceding week (VAS), the duration of morning stiffness and blood tests. Disease activity was assessed using BASDAI and ASDAS-CRP. Serum concentration of IL-10, IL-11, IL-12, IL-15, IL-17, IL-23 and IL-33 was determined. Results In patients with aSpA, elevated serum concentration of IL-10, IL-15, IL-17 and IL-23 was detected. In the aSpA group we detected higher values of serum concentration of IL-23 and IL-33 in the subgroup with anterior uveitis (83.1 ±184.0 pg/ml vs. 14.0 ±17.1 pg/ml, p < 0.0001 and 45.5 ±71.9 pg/ml vs. 18.4 ±14.3 pg/ml, p < 0.0001, respectively). Additionally, in the subgroup with peripheral arthritis, elevation of serum concentration of IL-12 (249.3 ±246.9 pg/ml vs. 99.9 ±105.9 pg/ml, p = 0.0001) was detected. Patients with preradiological SpA had higher serum concentration of IL-17 than patients with established diagnosis of AS (6.37 ±8.50 pg/ml vs. 2.04 ±2.98 pg/ml, p = 0.0295). No differences in serum concentration of analyzed cytokines were found between the subgroup with low to moderate disease activity and the subgroup with high to very high disease activity. Conclusions We report that in aSpA patients, compared to controls, elevated serum concentrations of IL-10, IL-15, IL-17 and IL-23 were observed. Some cytokines may predispose to a more severe course of aSpA.
Conceptual Search And Text Categorization

The most fundamental problem in information retrieval is that of interpreting information needs of users, typically expressed in a short query. Using the surface level representation of the query is especially unsatisfactory when the information needs are topic speciflc such as \US politics" or \Space Science", that seem to require understanding of what the query mean rather than what it is. We suggest that a newly proposed semantic representation of words [4] can be used to support Conceptual Search. Namely, it allows retrieving documents on a given topic even when existing keyword-based search approaches fail. The method we develop allows us to categorize and retrieve documents topically on-the-∞y, without looking at the data collection ahead of time, without knowing a-priori the topics of interest and without training topic categorization classiflers. We compare our approach experimentally to state-of-theart IR techniques and to machine learning based text categorization techniques and demonstrate signiflcant improvement in performance. Moreover, as we show, our method is intrinsically adaptable to new text collections and domains.
Penny Wise, Dollar Foolish: The Left-Digit Effect in Security Trading

The left-digit effect is defined as when a change in the left-most digit of a price (e.g., 7 to 6 when $7.00 drops to $6.99) dramatically affects the perception of the magnitude. Using a random sample of more than 100 million stock transactions, we find excess buying by liquidity demanders when the price starts above an integer and then drops below the integer. Conversely, we find excess selling by liquidity demanders when the price starts below an integer and then rises to the integer or above it. This is true under three buy-sell ratio measures, in multivariate regressions with various controls, and in multiple robustness checks. We consider the left-digit effect and two other possible explanations that are not mutually exclusive. We test which of the three explanations predominates. We find that liquidity demanders who buy when the price falls below an integer or who sell when the price rises to an integer earn lower 24-hour returns than other benchmark liquidity demanders and, in aggregate, lose $350 million per year. This finding plus two other findings suggest that the left-digit effect predominates over the two other explanations.
Pedigree Dog Breeding in the UK: A major welfare concern?

1. Purpose and scope of the report This is a summary of an independent report, which was commissioned by the RSPCA in order to help inform all those committed to protecting and improving the welfare of pedigree dogs. It addresses the impact on pedigree dog welfare of traditional selective breeding practices. Specifi cally, it focuses on welfare issues associated with exaggerated anatomical features and inherited disease. Whilst conclusions are centred on the specifi c situation in the UK, the report reviews what is well recognised as an international problem. As an independent report, its contents are the fi ndings, views and conclusions of its authors and contributors, who are recognised experts in the fi elds of animal welfare science, genetics, epidemiology and veterinary science. It contains a review of the scientifi c literature and proposes, in brief, possible ways forward to improve the welfare of pedigree dogs. The RSPCA is fi rmly committed to helping protect the welfare of dogs and recognises that solving the welfare problems associated with exaggerated anatomical features and inherited disease presents a very complex challenge. It hopes that this report will be seen as a constructive contribution to the current debate into the welfare of pedigree dogs and that it will help stimulate and focus essential wider discussion amongst all relevant stakeholders in order to identify and implement practical, evidencebased, effective solutions.