Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep neural networks with local connectivity and its application to astronomical spectral data

The success of deep learning proves that deep models are able to achieve much better performance than shallow models in representation learning. However, deep neural networks with auto-encoder stacked structure suffer from low learning efficiency since common used training algorithms are variations of iterative algorithms based on the time-consuming gradient descent, especially when the network structure is complicated. To deal with this complicated network structure problem, we employ a “divide and conquer” strategy to design a locally connected network structure to decrease the network complexity. The basic idea of our approach is to force the basic units of the deep architecture, e.g., auto-encoders, to extract local features in an analytical way without iterative optimization and assemble these local features into a unified feature. We apply this method to process astronomical spectral data to illustrate the superiority of our approach over other baseline algorithms. Furthermore, we investigate visual interpretations of high level features and the model to demonstrate what exactly the model learn from the data.
Characterization of a Radish Nuclear Gene Expressed during Late Seed Maturation.

To study long-lived mRNAs stored in radish (Raphanus sativus) seed, we have selected clones from a dry seed cDNA library by differential screening. One of these clones, p8B6, whose mRNAs are abundant in the dry seed, was characterized. This clone hybridizes to an RNA class of approximately 600 nucleotides whose accumulation begins during the desiccation phase, reaches its maximum level in the dry seed, and is no longer detectable in 12 hour old seedlings. mRNAs hybrid-selected by p8B6 encode four polypeptides, but only two are compatible with the size class of RNAs detected by Northern analysis. Three of them have previously been identified as major ;early germination' polypeptides, and their synthesis has been shown to be induced prematurely in immature embryos by a desiccation treatment. The protein deduced from the p8B6 nucleotide sequence is 9 kilodaltons in size, highly hydrophilic, rich in Gly and Glu, and contains no Cys, Trp, and lie. The amino acid sequence shares good homology with that of two recently described seed proteins: a cotton late embryogenesis abundant protein and the wheat early methionine-labeled protein. Southern blot analysis suggests that the p8B6 sequence belongs to a very small gene family. The exact function of the product encoded by p8B6 remains to be determined.
RNR1, a 3′–5′ exoribonuclease belonging to the RNR superfamily, catalyzes 3′ maturation of chloroplast ribosomal RNAs in Arabidopsis thaliana

Arabidopsis thaliana chloroplasts contain at least two 3′ to 5′ exoribonucleases, polynucleotide phosphorylase (PNPase) and an RNase R homolog (RNR1). PNPase has been implicated in both mRNA and 23S rRNA 3′ processing. However, the observed maturation defects do not affect chloroplast translation, suggesting that the overall role of PNPase in maturation of chloroplast rRNA is not essential. Here, we show that this role can be largely ascribed to RNR1, for which homozygous mutants germinate only on sucrose-containing media, and have white cotyledons and pale green rosette leaves. Accumulation of chloroplast-encoded mRNAs and tRNAs is unaffected in such mutants, suggesting that RNR1 activity is either unnecessary or redundant for their processing and turnover. However, accumulation of several chloroplast rRNA species is severely affected. High-resolution RNA gel blot analysis, and mapping of 5′ and 3′ ends, revealed that RNR1 is involved in the maturation of 23S, 16S and 5S rRNAs. The 3′ extensions of the accumulating 5S rRNA precursors can be efficiently removed in vitro by purified RNR1, consistent with this view. Our data suggest that decreased accumulation of mature chloroplast ribosomal RNAs leads to a reduction in the number of translating ribosomes, ultimately compromising chloroplast protein abundance and thus plant growth and development.
Structural insights into enzymatic [4+2] aza-cycloaddition in thiopeptide antibiotic biosynthesis

Significance Synthetic [4+2] cycloaddition reactions are prevalent and useful transformations employed in syntheses of valuable products. Coincidentally, nature also takes advantage of this transformation, and several cases of devoted enzymes have been found to facilitate this reaction in the production of small-molecule natural products. Prior examples have involved either carbocyclic or oxygen heterocycle products. Recently, an enzymatic, formal [4+2] aza-cycloaddition has been confirmed, featuring a nitrogen atom in the final pyridine structure central to a subset of thiopeptide natural products. The alternative synthetic route to substituted pyridines via cycloaddition has proven energetically challenging, highlighting the significance of these biocatalysts. Here, we report a detailed structural and mechanistic analysis of two such pyridine synthases from thiomuracin and GE2270 biosynthesis. The [4+2] cycloaddition reaction is an enabling transformation in modern synthetic organic chemistry, but there are only limited examples of dedicated natural enzymes that can catalyze this transformation. Thiopeptides (or more formally thiazolyl peptides) are a class of thiazole-containing, highly modified, macrocyclic secondary metabolites made from ribosomally synthesized precursor peptides. The characteristic feature of these natural products is a six-membered nitrogenous heterocycle that is assembled via a formal [4+2] cycloaddition between two dehydroalanine (Dha) residues. This heteroannulation is entirely contingent on enzyme activity, although the mechanism of the requisite pyridine/dehydropiperidine synthase remains to be elucidated. The unusual aza-cylic product is distinct from the more common carbocyclic products of synthetic and biosynthetic [4+2] cycloaddition reactions. To elucidate the mechanism of cycloaddition, we have determined atomic resolution structures of the pyridine synthases involved in the biosynthesis of the thiopeptides thiomuracin (TbtD) and GE2270A (PbtD), in complex with substrates and product analogs. Structure-guided biochemical, mutational, computational, and binding studies elucidate active-site features that explain how orthologs can generate rigid macrocyclic scaffolds of different sizes. Notably, the pyridine synthases show structural similarity to the elimination domain of lanthipeptide dehydratases, wherein insertions of secondary structural elements result in the formation of a distinct active site that catalyzes different chemistry. Comparative analysis identifies other catalysts that contain a shared core protein fold but whose active sites are located in entirely different regions, illustrating a principle predicted from efforts in de novo protein design.
Friction-Induced Vibrations and Self-Organization: Mechanics and Non-Equilibrium Thermodynamics of Sliding Contact

Introduction: Friction as a Fundamental Force of Nature in the History of Mechanics Historical Background Certain Philosophical Concepts of Mechanics Hilbert's Sixth Problem Noll's Axiomatic Mechanics P. Zhilin's Approach The Study of Friction Summary References Vibrations and Stability at the Bulk and at the Interface Linear Vibrations in Systems with Single, Multiple, and Infinite Number of Degrees of Freedom Stability Analysis Non-Linear Vibration and Stability Analysis Bifurcations, Catastrophes, and Chaos Multi-Scale Systems Self-Organization: Different Types Example: Benard Cells Self-Organization in Tribology Asymptotic Transition from a 3D (Bulk) to a 2D (Interface) System Summary References Principles of Non-Equilibrium Thermodynamics and Friction Thermodynamic Potentials and Equations Irreversible Processes and Non-Equilibrium Extremal Principles and Stability of Frictional Motion Stability Criterion for Frictional Sliding Summary References Bibliography Fundamentals of Friction Empirical Laws of Friction Mechanisms of Friction Non-Linear Character of Friction Thermodynamics of Friction Summary References Wear and Lubrication Mechanisms of Wear Empirical Laws of Wear Thermodynamics of Wear: Entropy Generation and Degradation Lubricated Contact Summary References Bibliography Friction-Induced Instabilities and Vibrations Mechanics of Elastic Contact and Stability of Frictional Sliding Velocity Dependency of Coefficient of Friction and Stability Criterion Thermoelastic Instabilities Adams-Martins Instabilities Radiation of Elastic Waves by Friction Interaction of Elastic Waves with Friction Friction Reduction and Self-Organized Patterns due to Friction-Induced Vibrations Summary References Bibliography Friction-Induced Vibrations and Their Applications Brakes and Vehicles Music and Sound Generation Nature Summary References From Frictional Instabilities to Friction-Induced Self-Organization Self-Organization, Instabilities, and Friction Stability of Frictional Sliding with Coefficient of Friction Dependent on Temperature Running-In as a Self-Organized Process Frictional Turing Systems Modeling of the Formation of Tribofilms Stick-Slip Motion and Self-Organization Summary References Self-Lubrication Principles of Self-Healing and Self-Lubricating Materials Various Approaches to Self-Lubrication Summary References Outlook Index
eid1: A New Arabidopsis Mutant Hypersensitive in Phytochrome A–Dependent High-Irradiance Responses

To identify specific mutants for components of phytochrome A (phyA) signaling in Arabidopsis, we established a light program consisting of multiple treatments with alternating red and far-red light. In wild-type seedlings, irradiation with multiple red light pulses can reduce the amount of phyA, which in turn decreases the high-irradiance responses (HIRs) mediated by the subsequent treatments with far-red light. Our mutants were able to avoid this red light–dependent reduction of the HIR. Here, we describe eid1, a new recessive mutant with increased sensitivity to far-red light. The eid1 mutation maps to the top of chromosome 4. The mutants showed no change in phenotype in darkness or under continuous white light, but they exhibited an increased sensitivity to red light and an increased persistence of HIR during prolonged dark phases after multiple short pulses of far-red light. The eid1 seedlings accumulated normal amounts of phytochrome and showed no alterations in the degradation or de novo synthesis of phyA. The expression of the Eid1 phenotype requires the presence of phyA. Our data provide evidence that EID1 is a negatively acting component in the phyA-dependent HIR-signaling pathway.
Investigation of lumen degradation mechanisms of mid-power LED by HAST

In this paper, the degradation modes and degradation mechanisms of mid-power LEDs were presented. For this study, commercially available mid-power LED packages were aged by method of accelerated temperature and humidity stress test (HAST). During ageing test, the ambient temperature and relative humidity was hold at 105 C and 100 %RH separately, which is so-called 105 C/100 %RH. As a result, little lumen decay was found in LED packages aged that is not stressed by current, while sharp lumen decay was observed in LED packages stressed by constant current. Physics analysis indicated that sharp lumen decay of the LED packages was mainly due to carbonization of the silicone plate, which was resulted from either the self-heating of phosphors or over-absorption of blue lights. The degradation trend observed in 105 C/100 %RH was different from that in 85 C/90%RH, indicating that different degradation mechanisms were triggered in HAST other than that in the steady-state humidity life test. Though a few researchers had demonstrated HAS T was a potential method for fast lifetime assessment of white light LED packages, experiments should be carefully designed to prevent improper lifetime prediction.
Deriving E-Assessment from a Competency Model

Self-assessment is a crucial component of learning. Creating effective questions is time-consuming, however, because it may require considerable resources and the skill of critical thinking. Questions need careful construction to accurately represent the intended learning outcome and the subject matter involved. There are very few systems currently available which generate questions automatically, and these are confined to specific domains. This paper presents a system for automatically generating questions from a competency framework, based on question templates, criteria for effective questions, and the instructional content and ability matrix. This makes it possible to guide learners in developing questions for themselves, and to provide authoring templates which speed the creation of new questions for self-assessment.
Theory and analysis of peel adhesion : adhesive thickness effects

Abstract The existing assumptions concerning boundary stress concentrations in peel adhesion are extended to treat the effects of adhesive thickness. In adhesive bonds involving the all-angle peeling of a flexible elastic adherend from a rigid substrate the varying of adhesive thickness is shown theoretically to predict a proportional increase of peel force (P) with adhesive interlayer thickness (a) when the product (βCa) of the cleavage stress concentration β, cavitation scale factor C, and adhesive thickness a is less than unity. When the product (βCa) becomes greater than unity the new theory predicts that cleavage stresses concentrate within a fractional layer of the total adhesive thickness f(a) and the peel force P tends to achieve a constant value Pmax. This new theory is verified by experimental studies and the experimental analysis suggests new optimizations in the design and measurement of the peel adhesive bond.
A class of interval type-2 fuzzy neural networks illustrated with application to non-linear identification

Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function. Recent research shows that embedding T1FLS on an NN or embedding IT2FLS on an NN can be very effective for a wide number of non-linear complex systems, especially when handling imperfect information. In this paper we show that an Interval Type-2 Fuzzy Neural Network (IT2FNN) is a universal approximator with some precision using a set of rules and Interval Type-2 membership functions (IT2MF) and the Stone-Weierstrass Theorem.
Application of intelligence of swarm in architecture

Last two decades some architects have used tools, which are based on nature principles. Thanks to globalization and multidisciplinary, contemporary architecture uses principles based on computing design, engineering, sociology or nature systems. Implementation of these principles brings new possibilities to architecture and design and new ways how to develop it. This paper focuses on intelligence of swarm (SI) in architecture and describes several principles and examples which are using intelligence of nature systems like ants, birds, locusts etc. Contemporary Architecture should count with many changes which are still in progress. It is very difficult to predict, what will be tomorrow. Using of the dynamic principles in architecture, design and civil engineering could help us to be ready for these changes. Like ant colony or schooling of fish can adapt on non-predicted changes, also city or building should be capable of this. This is not useful just for dynamic and kinetic architecture, but also for finding a form of static building or city. In this paper several SI algorithms and four types of SI use in architecture are described: space optimization, swarm urbanism, swarm modelling and swarm robotics.
Controlling RNA self-assembly to form filaments

Fundamental control over supra-molecular self-assembly for organization of matter on the nano-scale is a major objective of nanoscience and nanotechnology. ‘RNA tectonics’ is the design of modular RNA units, called tectoRNAs, that can be programmed to self-assemble into novel nano- and meso-scopic architectures of desired size and shape. We report the three-dimensional design of tectoRNAs incorporating modular 4-way junction (4WJ) motifs, hairpin loops and their cognate loop–receptors to create extended, programmable interaction interfaces. Specific and directional RNA–RNA interactions at these interfaces enable conformational, topological and orientational control of tectoRNA self-assembly. The interacting motifs are precisely positioned within the helical arms of the 4WJ to program assembly from only one helical stacking conformation of the 4WJ. TectoRNAs programmed to assemble with orientational compensation produce micrometer-scale RNA filaments through supra-molecular equilibrium polymerization. As visualized by transmission electron microscopy, these RNA filaments resemble actin filaments from the protein world. This work emphasizes the potential of RNA as a scaffold for designing and engineering new controllable biomaterials mimicking modern cytoskeletal proteins.
User Analytics with UbeOne: Insights into Web Printing

As web and mobile applications become more sensitive to the user context, there is a shift from purely off-line processing of user actions (log analysis) to real-time user analytics that can generate information about the user context to be instantly leveraged by the application. Ubeone is a system that enables both real-time and aggregate analytics from user data. The system is designed as a set of lightweight, composeable mechanisms that can progressively and collectively analyze a user action, such as pinning, saving or printing a web page. We will demonstrate the system capabilities on analyzing a live feed of URLs printed through a proprietary, web browser plug-in. This is in fact the first analysis of web printing activity. We will also give a taste of how the system can enable instant recommendations based on the user context.
Adaptive zero-crossing digital phase-locked loop for packet synchronization

This paper describes the design and performance analysis of a new approach for frequencysynchronization and transfer over packet networks. The proposed system utilizestimestamps-based with raised cosine pulse shaping first order adaptive zero-crossing digital phase-locked loop (AZC-DPLL). The system is designedto recover frequency as well as packets, independently of the input signal level in the presence of noise. This technique provides reliable locking by adjusting the loop gain, with the aid of finite state machine (FSM), and hence both system locking range and acquisition are improved.
Approximating Sparse PCA from Incomplete Data

We study how well one can recover sparse principal components of a data matrix using a sketch formed from a few of its elements. We show that for a wide class of optimization problems, if the sketch is close (in the spectral norm) to the original data matrix, then one can recover a near optimal solution to the optimization problem by using the sketch. In particular, we use this approach to obtain sparse principal components and show that for \math{m} data points in \math{n} dimensions, \math{O(\epsilon^{-2}\tilde k\max\{m,n\})} elements gives an \math{\epsilon}-additive approximation to the sparse PCA problem (\math{\tilde k} is the stable rank of the data matrix). We demonstrate our algorithms extensively on image, text, biological and financial data. The results show that not only are we able to recover the sparse PCAs from the incomplete data, but by using our sparse sketch, the running time drops by a factor of five or more.
Asynchronous stream modeling for large vocabulary audio-visual speech recognition

Addresses the problem of audio-visual information fusion to provide highly robust speech recognition. We investigate methods that make different assumptions about asynchrony and conditional dependence across streams and propose a technique based on composite HMMs that can account for stream asynchrony and different levels of information integration. We show how these models can be trained jointly based on maximum likelihood estimation. Experiments, performed for a speaker-independent large vocabulary continuous speech recognition task and different integration methods, show that best performance is obtained by asynchronous stream integration. This system reduces the error rate at a 8.5 dB SNR with additive speech "babble" noise by 27 % relative over audio-only models and by 12 % relative over traditional audio-visual models using concatenative feature fusion.
Effect of crumb rubber modifiers (CRM) on performance-related properties of asphalt binders

The purpose of this paper is to summarize the results of the first phase of a project to evaluate the effect of Crumb Rubber Modifiers (CRM) produced by different processes on basic rheological, failure, and aging properties of asphalt binders. The study also addressed the high-temperature stability of the asphalt rubbers as well as the aging characteristics of these binders as reflected by the Thin Film Oven Test (TFOT) and Pressure Aging Vessel (PAV) aging procedures. This paper also includes analysis of the effect of high-temperature storage on rheological response at high and intermediate temperatures, the effect of rubber on the properties used for grading using the new Strategic Highway Research Program (SHRP) specifications, and an evaluation of the change in aging characteristics of the selected asphalts as a result of adding the CRM.
Learning by Reading: Two Experiments

This paper addresses the challenge of learning information by reading natural language text. The major aim is to map natural language input into logical expressions anchored upon concise and speci c theories underlying the domains, in such a way that a reasoning engine can be used to answer questions about the input. We de ne a 3-step procedure, including parsing and abduction, and explore different implementations for the steps. Experiments were conducted in two domains, chemistry and biology, and the versatility of the approach suggests that extension to other domains is possible when the underlying theories are suitably speci ed.
An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks

In wireless sensor networks, almost all geographic routing algorithms assume that sensors are accurately located. In this paper, we propose an energy efficient geographic routing algorithm (EEG-Routing). In our method, before the deployment of sensors in their environment, sensor positions are known with position error bounds which are potentially larges. According to this knowledge, it is possible to compute, before the deployment the probability that two sensors communicate. EEG-Routing introduces a new metric which defines, regarding to communication probabilities, energy consumptions and realized progress, communication costs between neighbors. EEG-Routing simultaneously optimizes two criteria: the energy consumption and the delivery rate, in networks where sensors are inaccurately located. Performances are validated by simulations which compare EEG-Routing with an energy-optimal algorithm.