Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Analysis of Light-Dependent Transcript Accumulation Patterns during Early Stages of Arabidopsis Seedling Deetiolation 1[W][OA]

Light is among the most important exogenous factors that regulate plant development. To sense light quality, intensity, direction, and duration, plants have evolved multiple photoreceptors that enable the detection of photons from the ultraviolet B (UV-B) to the far-red spectrum. To study the effect of different light qualities on early gene expression, dark-grown Arabidopsis ( Arabidopsis thaliana ) seedlings were either irradiated with continuous far-red, red, or blue light or received pulses of red, UV-A, or UV-A/B light. The expression proﬁles of seedlings harvested at 45 min and 4 h were determined on a full genome level and compared with the proﬁles of dark controls. Data were used to identify light-regulated genes and to group these genes according to their light responses. While most of the genes were regulated by more than one light quality, a considerable number of UV-B-speciﬁc gene expression responses were obtained. An extraordinarily high similarity in gene expression patterns was obtained for samples that perceived continuous irradiation with either far-red or blue light for 4 h. Mutant analyses hint that this coincidence is caused by a convergence of the signaling cascades that regulate gene expression downstream of cryptochrome blue light photoreceptors and phytochrome A. Whereas many early light-regulated genes exhibited uniform responses to all applied light treatments, highly divergent expression patterns developed at 4 h. These data clearly indicate that light signaling during early deetiolation undergoes a switch from a rapid, but unspeciﬁc, response mode to regulatory systems that measure the spectral composition and duration of incident light.
Intelligent aerodynamic/propulsion flight control for flight safety: a nonlinear adaptive approach

This paper presents an intelligent fault tolerant flight control system that blends aerodynamic and propulsion actuation for safe flight operation in the presence of actuator failures. Fault tolerance is obtained by a nonlinear adaptive control strategy based on on-line learning neural networks and actuator reallocation scheme. The adaptive control block incorporates a recently developed technique for adaptation in the presence of actuator saturation, rate limits and failure. The proposed integrated aerodynamic/propulsion flight control system is evaluated in a nonlinear flight simulation environment.
REGRESSION-BASED RESIDUAL ACOUSTIC ECHO SUPPRESSION

In this paper, we propose a novel regression-based algorithm for suppressing the residual echo present in the output of an acoustic echo canceller (AEC). We learn a functional relationship between the magnitudes of many frames of the speaker signal and the magnitude of the echo residual, per subband. We estimate and track the parameters of this function using adaptive algorithms (e.g. NLMS). We show that this approach can be interpreted as a rank-1 approximation to a more general regression model, and can address shortcomings of the earlier approaches based on correlation analysis. Preliminary results using linear regression on magnitudes of real audio signals in both mono and stereo situations demonstrate an average of 7 dB of echo suppression over the AEC output signal under a wide variety of conditions without near-end signal distortion. The framework is general enough to promise even further reductions in the future.
Anomaly Detection of Particle Orbit in Accelerator using LSTM Deep Learning Technology

A stable, reliable, and controllable orbit lock system is crucial to an electron (or ion) accelerator because the beam orbit and beam energy instability strongly affect the quality of the beam delivered to experimental halls. Currently, when the orbit lock system fails operators must manually intervene. This paper develops a Machine Learning based fault detection methodology to identify orbit lock anomalies and notify accelerator operations staff of the off-normal behavior. Our method is unsupervised, so it does not require labeled data. It uses Long-Short Memory Networks (LSTM) Auto Encoder to capture normal patterns and predict future values of monitoring sensors in the orbit lock system. Anomalies are detected when the prediction error exceeds a threshold. We conducted experiments using monitoring data from Jefferson Lab's Continuous Electron Beam Accelerator Facility (CEBAF). The results are promising: the percentage of real anomalies identified by our solution is 68.6%-89.3% using monitoring data of a single component in the orbit lock control system. The accuracy can be as high as 82%.
Survivability analysis of telephone access network

The telecommunications industry has achieved high reliability and availability for telephone service over decades of development. However, the current design does not aim at providing service survivability when a local switching office fails due to catastrophic damage. In this paper, several survivable architectures for telephone subscriber network are proposed based on common survivability principles. In order to quantitatively assess the effectiveness of design alternatives, a set of analytical models are developed to derive various survivability measures. Numerical results are provided to show how a comprehensive understanding of the system behavior after failure can be achieved through different survivability aspects.
Magnetism of Low-dimensional Metallic Structures

The chapter “Magnetism of low-dimensional metallic structures” reviews experiments on the magnetism of surface-supported low-dimensional structures of 3d metals. Controlling the static and dynamic magnetic behavior of both individual impurities and supported nanostructures on nonmagnetic surfaces represents a fundamental challenge as well as a prerequisite to design magnetic storage and logic devices of novel conception. We describe the governing principles of self-organized growth of metallic nanostructures at surfaces and outline approaches to drive and steer self-assembly processes. The controlled assembly of metal nanostructures on crystalline surfaces combined with scanning probe measurements and synchrotron radiation spectroscopy allows us to track the evolution of the magnetic properties from single atoms to finite-sized particles, atomic chains, and two-dimensional layers, highlighting the significance of size, coordination, and interface effects at the atomic scale. As examples, we report on the giant magnetic anisotropy and unquenched orbital moments observed in nanoparticles, unusual oscillations of the easy axis of magnetization in atomic chains of variable thickness, and metastable ferromagnetic order in one-dimension. We discuss the important role played by interactions with a nonmagnetic substrate and point out approaches to control and tune magnetism in nanoscale structures by taking advantage of coordination and hybridization effects. Keywords: epitaxial growth; self-assembly; magnetism; magnetic anisotropy; atomic chains; clusters; nanoparticles; Fe; Co; FePt alloy; STM; XMCD; MOKE
Pattern-driven engineering of interactive computing systems (PEICS)

Since almost over one decade, patterns have been gaining a lot of interest in the domain of Human-Computer-Interaction (HCI) engineering. It is generally agreed upon that patterns can be used to facilitate the exchange of best practices and knowledge between the interdisciplinary team members, involved in interactive systems design process. Despite intense research activities in the last years, HCI patterns still lack in a standardized description and organization. This makes it difficult for the developers to identify the relevant patterns for solving a problem as well as to apply them accordingly to the problem context. To fully benefit from HCI patterns within the engineering of interactive computer systems they have to be prepared for integration into a model-based user interface development process. Instead of guiding and advising the UI developers of which solution should be applied, HCI patterns should enable the easy reuse of already designed model or code fragments. To enable the integration of HCI patterns in the model-based development process the informal textual, or graphical notation of HCI patterns has to be overcome. HCI patterns have to support the formal description of their solution-part, which allows the direct integration of the solution-parts into the different models, like task-, dialog- and presentation-model.
Profiling Chinese Hong Kong consumers' attitudes on the atmospheric management strategies adopted by intimate apparel retailers

The atmosphere in a store is a crucial factor for inducing impulse shopping or providing an effect on perceived brand image and product quality. The atmosphere is especially important for aesthetic-related products, such as fashion. However, fashion becomes an inseparable element even in a function-oriented product, namely intimate apparel. In this study, the authors adopted a qualitative method, the grounded theory, to investigate the ways that the store atmosphere affects the attitudes of Chinese female consumers to intimate apparel. Attitudes with regards to cognitive and affective aspects are discussed and numerous strategic directions are presented.
Joint low-rank and sparse based image reconstruction for through-the-wall radar imaging

Through-the-wall radar uses electromagnetic waves to detect and discern targets behind opaque obstacles, such as doors and walls. Wall clutter mitigation and scene reconstruction are performed to produce the image of the behind-the-wall scene. These two problems, however, are often addressed separately, which may result in a suboptimal solution. In this paper, the wall clutter removal and image formation are unified as a joint low-rank and sparsity constrained optimization problem, which is solved using augmented Lagrange multiplier method. Experimental results shows that the proposed method produces clearer images than the existing method that uses a wall clutter mitigation method in conjunction with backprojection method for imaging.
Pioneering fungi from the Damma glacier forefield in the Swiss Alps can promote granite weathering

Fungi were isolated from fine granitic sediments, which were collected at 15 sampling points within a 20 m × 40 m area in front of the Damma glacier in the central Swiss Alps. From the 45 fungal isolates grown on nutrient‐rich agar media at 4 °C, 24 isolates were selected for partial sequencing and identification based on the small subunit ribosomal DNA. Sequencing data revealed that the isolated fungi represented three fungal phyla and 15 species. The weathering potential of 10 of the 15 fungal species was tested with dissolution experiments using powdered granite material (<63 μm). The results showed that the zygomyceteous species Mucor hiemalis, Umbelopsis isabellina and Mortierella alpina dissolved the granite powder most efficiently due to the release of a variety of organic acids, mainly citrate, malate and oxalate. In particular, the high concentrations of Ca, Fe, Mg and Mn in the solutions clustered well with the high amounts of exuded citrate. This is the first report on fungi that were isolated from a non‐vegetated glacier forefield in which the fungi’s capabilities to dissolve granite minerals were examined.
Very Low Bit Rate Facial Texture Coding

In this paper we present two methods of enhancing the eigen face approach for the compression of images of human faces. In earlier work, a series of image basis functions (eigen faces) is created using the KarhunenLoeve transform on a large set of face images (the training set). The image to be encoded can then be approximated by a linear combination of these basis functions. We propose a reversible, non-linear geometrical normalization step to be performed on both the training set and the image before it is being encoded. To further increase quality, a partitioning step of the images into blocks can be performed before the KL transform. An improvement on JPEG of 4 dB has been measured on individual images for low bit rates.
Neonicotinoid Pesticide Reduces Bumble Bee Colony Growth and Queen Production

Bad News for Bees Neonicotinoid insecticides were introduced in the early 1990s and have become one of the most widely used crop pesticides in the world. These compounds act on the insect central nervous system, and they have been shown to be persistent in the environment and in plant tissues. Recently, there have been controversial connections made between neonicotinoids and pollinator deaths, but the mechanisms underlying these potential deaths have remained unknown. Whitehorn et al. (p. 351, published online 29 March) exposed developing colonies of bumble bees to low levels of the neonicotinoid imidacloprid and then released them to forage under natural conditions. Treated colonies displayed reduced colony growth and less reproductive success, and they produced significantly fewer queens to found subsequent generations. Henry et al. (p. 348, published online 29 March) documented the effects of low-dose, nonlethal intoxication of another widely used neonicotinoid, thiamethoxam, on wild foraging honey bees. Radio-frequency identification tags were used to determine navigation success of treated foragers, which suggested that their homing success was much reduced relative to untreated foragers. Bumble bee colonies produce many fewer queens after exposure to a widely used insecticide. Growing evidence for declines in bee populations has caused great concern because of the valuable ecosystem services they provide. Neonicotinoid insecticides have been implicated in these declines because they occur at trace levels in the nectar and pollen of crop plants. We exposed colonies of the bumble bee Bombus terrestris in the laboratory to field-realistic levels of the neonicotinoid imidacloprid, then allowed them to develop naturally under field conditions. Treated colonies had a significantly reduced growth rate and suffered an 85% reduction in production of new queens compared with control colonies. Given the scale of use of neonicotinoids, we suggest that they may be having a considerable negative impact on wild bumble bee populations across the developed world.
Workshop on programming languages and analysis for security (PLAS 2008)

The call for papers attracted 24 submissions from leading researchers at locations around the world. Overall, the submitted papers were very strong, and the program committee ultimately accepted 13 papers. The accepted papers at PLAS 2008 encompass a variety of topics, including: software verification, static and dynamic analysis for security policy enforcement, information flow, language-based security, and software protection.
Efficacy of Hepatoprotective Agents With or Without Antiviral Drugs on Liver Function and Fibrosis in Patients With Hepatitis B: A Meta-Analysis

Context: To systematically evaluate the effects of hepatoprotective agents, when delivered either alone or in combination with other antiviral or non-antiviral drugs in patients with hepatitis B and hepatic fibrosis. Objectives: The current randomized controlled clinical trials aimed to evaluate the efficacy of combinations of antiviral and non-antiviral hepatoprotective agents on indexes of liver function and liver fibrosis in patients with hepatitis B. Data Sources: Published literatures in Chinese and English on hepatoprotective treatment strategies for chronic hepatitis B and liver fibrosis were searched in three databases and randomized controlled clinical trials were selected. Study Selection: Data were extracted according to a variety of inclusion and exclusion criteria. Meta-analysis was employed to analyze the data. Results: A total of 22 randomized controlled trials encompassing 1,714 cases were considered in the meta-analysis. The obtained results indicated that the combination of antiviral drug and hepatoprotective agent was better than antiviral drug alone to improve liver function. Similarly, regarding liver fibrosis, using two different hepatoprotective agents was better than using one agent. The normalization rates of Aminotransferase (ALT) and total Bilirubin (TBil) were improved 25.7% by two hepatoprotective agents compared to the single agent. Acetylcysteine was superior to ursodeoxycholic acid or silibinin to reduce ALT. Ursodeoxycholic acid was superior to acetylcysteine or silibinin to reduce TBIL. Conclusions: Hepatoprotective agents combined with antiviral drugs can significantly improve liver function and liver fibrosis parameters in patients with hepatitis B.
High Intensity Neutron Beams for Small Samples

As novel materials of excellent homogeneity can often only be grown in small quantities it is important to optimize the transport of neutrons from the moderator to the sample while keeping the background low. Using elliptically or parabolically tapered guides the losses can be strongly reduced such that 50% – 90% of the useful neutrons arrive at the sample. If not properly designed, however, the divergence at the sample becomes inhomogeneous. In contrast, pairs of nested Kirkpatrick-Baez mirrors in Montel geometry yield well focused beams with a compact phase space. The mirrors extract only the useful neutrons from the moderator and effectively interrupt the line of sight leading to a very low background. As the focal distances are typically several meters, the extraction of the neutrons and the installation of bulky sample environment is facilitated.
New non-asymptotic random channel coding theorems

New non-asymptotic random coding theorems (with error probability ϵ and finite block length n) based on Gallager parity check ensemble are established for binary input arbitrary output channels. The resulting non-asymptotic achievability bounds, when combined with non-asymptotic equipartition properties, can be easily computed. Analytically, these non-asymptotic achievability bounds are shown to be asymptotically tight up to the second order of the coding rate as n goes to infinity with either constant or sub-exponentially decreasing ϵ. Numerically, they are also compared favourably, for finite n and ϵ of practical interest, with existing non-asymptotic achievability bounds in the literature in general.
Guidelines for using multiple views in information visualization

A multiple view system uses two or more distinct views to support the investigation of a single conceptual entity. Many such systems exist, ranging from computer-aided design (CAD) systems for chip design that display both the logical structure and the actual geometry of the integrated circuit to overview-plus-detail systems that show both an overview for context and a zoomed-in-view for detail. Designers of these systems must make a variety of design decisions, ranging from determining layout to constructing sophisticated coordination mechanisms. Surprisingly, little work has been done to characterize these systems or to express guidelines for their design. Based on a workshop discussion of multiple views, and based on our own design and implementation experience with these systems, we present eight guidelines for the design of multiple view systems.
Design development and utilisation of conducting polymer sensors

The aim of this thesis is to implement a comprehensive study of conducting polymer sensor array for detection of species in both liquid and gas phase. The research area includes design of the sensor array configuration, development of conducting polymer sensors and carrying out some applications. Sensor configurations have been designed towards different applications using inexpensive substrate materials such as polyvinylchloride with screen printed carbon electrodes (C/PVC), transparencies, glossy papers and photo films. Conducting polymer films were then deposited onto the base electrodes to form sensor arrays. Different fabrication processes involving chemical deposition, electrochemical deposition, inkjet and contact printing were applied for each type of sensor in order to achieve the most effective CP sensor array in terms of analytical performance as well as production procedure. For amperometric detection of species in solution, an eight C/PVC electrode array was produced using screen-printing method. Conducting polymers were electrochemically deposited onto individual carbon electrode to form the array. Of many polypyrrole based CP sensors studied, eight sensors with the best performance were selected to produce sensor array for detection of species. The obtained results indicated that the eight CP sensors array could be used to detect and discriminate between four electroinactive cations, namely, Na, K, Ca and Mg, using pulsed amperometry and pattern recognition techniques.
Computerized Medical Imaging and Graphics Automatic Localization of the Optic Disc by Combining Vascular and Intensity Information

Keywords: Retinal image analysis Optic disc localization Retinal vessel segmentation Entropy a b s t r a c t This paper describes a new methodology for automatic location of the optic disc in retinal images, based on the combination of information taken from the blood vessel network with intensity data. The distribution of vessel orientations around an image point is quantified using the new concept of entropy of vascular directions. The robustness of the method for OD localization is improved by constraining the search for maximal values of entropy to image areas with high intensities. The method was able to obtain a valid location for the optic disc in 1357 out of the 1361 images of the four datasets.
Bayesian analysis of generalized frequency-modulated signals

General frequency-modulated (GFM) signals can be used to characterize many vibrations in dynamic environments, with applications to engine monitoring and sonar. Most work into parameter estimation of such signals assumes knowledge of the number of carrier frequencies. In this paper, we make no such assumption and use Bayesian techniques to address jointly the problem of model selection and parameter estimation. Following the work of Andrieu and Doucet (see ibid., vol.47, p.2667-76, 1999), who addressed the problem for nonmodulated sinusoids, a posterior distribution for the parameters and model order is obtained. This distribution is too complicated for analytical extraction of moments and to sample from directly; therefore, we use a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to draw samples from the distribution. Some simulated examples are presented to illustrate the algorithm's performance.