Miracle-dz/UniFAR-FTUs huggingface dataset:
The absorption of very high frequency sound in dielectric solids

ABSTRACT A theoretical treatment is given of the absorption of longitudinally polarized sound in dielectric crystals of high symmetry, due to interaction with the thermal phonous. The Q value for the absorption is calculated in terms of the deviation from Hooke's law, the result being applicable at low temperatures when the mean free path of the phonons is greater than the wavelength of the acoustic wave. The theory is applied to cubic crystals, and in particular to solid argon, where a minimum Q value of about 108–109 is calculated. It is suggested that measurement of the absorption (at present somewhat beyond experimental techniques) would supply information on the deviation from linear elasticity, as well as providing a satisfactory verification of the basic interaction theory. The effect of isotopes, and, in more complicated structures, of optic modes, is shown to be negligible.
Soil Moisture Estimation Under Low Vegetation Cover Using a Multi-Angular Polarimetric Decomposition

The estimation of volumetric soil moisture under low agricultural vegetation from fully polarimetric synthetic aperture radar (SAR) data at L-band using a multi-angular polarimetric decomposition is investigated. Radar polarimetry provides the framework to decompose the backscattered signal into different canonical scattering mechanisms referring to scattering contributions from the underlying soil and the vegetation cover. Multi-angular observation diversity further increases the information space for soil moisture inversion enabling higher inversion rates and a stable inversion performance. The developed approach was applied on the multi-angular L-band data set acquired by German Aerospace Center's ESAR sensor as part of the OPAQUE campaign in 2008. The obtained results are compared against ground measurements collected by the OPAQUE team over a variety of vegetated agricultural fields. The validation of the estimated against ground measured soil moisture results in an root mean square error level of 6-8 vol.% including all test fields with a variety of crop types.
Financial time series forecasting based on wavelet kernel support vector machine

Financial time series forecasting is a hot research topic in the field of finance and it is of great significance to the study of finance market. Since the nonlinear characteristics of financial time series and the shortcomings of traditional forecasting methods, a new support vector machine (SVM) based on wavelet kernel function and its construct algorithms are proposed. Furthermore, the wavelet kernel functions have been proved to satisfy the admissible condition. The new SVM models are applied to forecast the Nasdaq composite index to test their forecasting performance. Compared with polynomial kernel SVM and Gaussian kernel SVM, experimental results show the wavelet kernel SVMs can increase the prediction accuracy, enhancing prediction model generalization performance.
Spatial joins using seeded trees

Existing methods for spatial joins assume the existence of indices for the participating data sets. This assumption is not realistic for applications involving multiple map layer overlays or for queries involving non-spatial selections. In this paper, we explore a spatial join method that dynamically constructs index trees called seeded trees at join time. This methods uses knowledge of the data sets involved in the join process. Seeded trees are R-tree like structures, and are divided into the seed levels and the grown levels. The nodes in the seed levels are used to guide tree growth during tree construction. The seed levels can also be used to filter out some input data during construction, thereby reducing tree size. We develop a technique that uses intermediate linked lists during tree construction and significantly speeds up the tree construction process. The technique allows a large number of random disk accesses during tree construction to be replaced by smaller numbers of sequential accesses. Our performance studies show that spatial joins using seeded trees outperform those using other methods significantly in terms of disk I/O. The CPU penalties incurred are also lower except when seed-level filtering is used.
The Drupal framework: a case study to evaluate variability testing techniques

Variability testing techniques search for effective but manageable test suites that lead to the rapid detection of faults in systems with high variability. Evaluating the effectiveness of these techniques in real settings is a must but challenging due to the lack of variability-intensive systems with available code, automated tests and fault reports. In this paper, we propose using the Drupal framework as a case study to evaluate variability testing techniques. First, we represent the framework variability as a feature model. Then, we report on extensive data extracted from the Drupal git repository and the Drupal issue tracking system. Among other results, we identified 378 faults in single features and 11 faults triggered by the interaction between two of the features of Drupal v7.23, reported during a one-year period. These data may give a new insight into the distribution of faults in variability-intensive systems and the fault propensity of features. To show the feasibility of our work, we used the case study to evaluate the effectiveness of a history-based test case prioritization criterion. Results suggest that this technique could contribute to accelerate the detection of faults of test suites based on combinatorial testing.
Oxygen diffusion in dislocations and grain boundaries in magnesium oxide

Oxygen-18 gas exchange followed by concentration profile determination by Secondary Ion Mass Spectrometry (SIMS) was performed on single crystals, deformed single crystals andpolycrystals of MgO. The following results were obtained for the temperature range 1200 C-1 SO0 C for undoped MgO. +10.5 -6 3.45±0.17 eV 2 D=(3.9 -2. ) X 10 exp( kT ) cm /sec 1200-1500*C D'da 2 0-(1 5 .9±1.9) 3.20 ± 0.58 eV 4 d exp(kT ) cm /sec D' lo(6. 5±2. 2) 4.06 ± 0. 78 eV 3 bexp( kT ) cm /sec where D bulk diffusion coefficient D'd= diffusion coefficient within a dislocation a = dislocation core radius D'b= diffusion coefficient within a grain boundary b = grain boundary thickness Error intervals are for 68% confidence calculated from standard deviations from linear regression of Arrhenius plots. Activation energies for oxygen diffusion in the bulk, dislocations, and grain boundagesare the same within the experimental error. At 12000C it was found that D' b=D' d=1 0 D and that 6 and a are both less than 10 angstroms. Thesis Supervisor: W. D. Kingery Title: Professor of Ceramics
Pax6 Regulates Gene Expression in the Vertebrate Lens through miR-204

During development, tissue-specific transcription factors regulate both protein-coding and non-coding genes to control differentiation. Recent studies have established a dual role for the transcription factor Pax6 as both an activator and repressor of gene expression in the eye, central nervous system, and pancreas. However, the molecular mechanism underlying the inhibitory activity of Pax6 is not fully understood. Here, we reveal that Trpm3 and the intronic microRNA gene miR-204 are co-regulated by Pax6 during eye development. miR-204 is probably the best known microRNA to function as a negative modulator of gene expression during eye development in vertebrates. Analysis of genes altered in mouse Pax6 mutants during lens development revealed significant over-representation of miR-204 targets among the genes up-regulated in the Pax6 mutant lens. A number of new targets of miR-204 were revealed, among them Sox11, a member of the SoxC family of pro-neuronal transcription factors, and an important regulator of eye development. Expression of Trpm/miR-204 and a few of its targets are also Pax6-dependent in medaka fish eyes. Collectively, this study identifies a novel evolutionarily conserved mechanism by which Pax6 controls the down-regulation of multiple genes through direct up-regulation of miR-204.
Quantifying aspects in middleware platforms

Middleware technologies such as Web Services, CORBA and DCOM have been very successful in solving distributed computing problems for a large family of application domains. As middleware systems are getting widely adopted and more functionally mature, it is also increasingly difficult for the architecture of middleware to achieve a high level of adaptability and configurability, due to the limitations of traditional software decomposition methods. Aspect oriented programming has brought us new design perspectives because it permits the superimpositions of multiple abstraction models on top of one another. It is a very powerful technique in separating and simplifying design concerns. In this paper, we first show that, through the quantification of aspects in the legacy implementations, the modularity of middleware architecture is greatly hindered by the ubiquitous existence of tangled logic. We then go one step further by factoring out a number of aspects identified in the mining work and re-implementing them as aspect programs. The aspect oriented re-factorization allows us to apply a set of software engineering metrics to quantify the changes of the re-factored system in both the structural complexity and the runtime performance. The aspect oriented re-factoring proves that the aspect oriented programming is capable of composing orthogonal design requirements. The final "woven" system is able to correctly provide both the fundamental functionality and the "aspectized" functionality with negligible overhead and a leaner architecture. Further more, the configurability of middleware is dramatically increased because the "aspectized" features can be configured in and out during the compile-time
Nonlinear Boosting Projections for Ensemble Construction

In this paper we propose a novel approach for ensemble construction based on the use of nonlinear projections to achieve both accuracy and diversity of individual classifiers. The proposed approach combines the philosophy of boosting, putting more effort on difficult instances, with the basis of the random subspace method. Our main contribution is that instead of using a random subspace, we construct a projection taking into account the instances which have posed most difficulties to previous classifiers. In this way, consecutive nonlinear projections are created by a neural network trained using only incorrectly classified instances. The feature subspace induced by the hidden layer of this network is used as the input space to a new classifier. The method is compared with bagging and boosting techniques, showing an improved performance on a large set of 44 problems from the UCI Machine Learning Repository. An additional study showed that the proposed approach is less sensitive to noise in the data than boosting methods.
A comparison of bug finding tools for Java

Bugs in software are costly and difficult to find and fix. In recent years, many tools and techniques have been developed for automatically finding bugs by analyzing source code or intermediate code statically (at compile time). Different tools and techniques have different tradeoffs, but the practical impact of these tradeoffs is not well understood. In this paper, we apply five bug finding tools, specifically Bandera, ESC/Java 2, FindBugs, JLint, and PMD, to a variety of Java programs. By using a variety of tools, we are able to cross-check their bug reports and warnings. Our experimental results show that none of the tools strictly subsumes another, and indeed the tools often find nonoverlapping bugs. We discuss the techniques each of the tools is based on, and we suggest how particular techniques affect the output of the tools. Finally, we propose a meta-tool that combines the output of the tools together, looking for particular lines of code, methods, and classes that many tools warn about.
Isolation and Functional Validation of Salinity and Osmotic Stress Inducible Promoter from the Maize Type-II H+-Pyrophosphatase Gene by Deletion Analysis in Transgenic Tobacco Plants

Salinity and drought severely affect both plant growth and productivity, making the isolation and characterization of salinity- or drought-inducible promoters suitable for genetic improvement of crop resistance highly desirable. In this study, a 1468-bp sequence upstream of the translation initiation codon ATG of the promoter for ZmGAPP (maize Type-II H+-pyrophosphatase gene) was cloned. Nine 5´ deletion fragments (D1–D9) of different lengths of the ZmGAPP promoter were fused with the GUS reporter and translocated into tobacco. The deletion analysis showed that fragments D1–D8 responded well to NaCl and PEG stresses, whereas fragment D9 and CaMV 35S did not. The D8 segment (219 bp; -219 to -1 bp) exhibited the highest promoter activity of all tissues, with the exception of petals among the D1–D9 transgenic tobacco, which corresponds to about 10% and 25% of CaMV 35S under normal and NaCl or PEG stress conditions, respectively. As such, the D8 segment may confer strong gene expression in a salinity and osmotic stress inducible manner. A 71-bp segment (-219 to -148 bp) was considered as the key region regulating ZmGAPP response to NaCl or PEG stress, as transient transformation assays demonstrated that the 71-bp sequence was sufficient for the salinity or osmotic stress response. These results enhance our understanding of the molecular mechanisms regulating ZmGAPP expression, and that the D8 promoter would be an ideal candidate for moderating expression of drought and salinity response genes in transgenic plants.
Hypoxia Inactivates the VHL Tumor Suppressor through PIASy-Mediated SUMO Modification

The hypoxic microenvironment contributes to embryonic development and tumor progression through stabilization of the potent transcriptional factor HIFα. In normoxia, the tumor suppressor protein VHL acts as an E3 ubiquitin ligase to target HIFα for proteolytic destruction. Increasing evidence shows that VHL is a multifunctional adaptor involved in inhibition of HIFα-dependent and independent cellular processes. However, the molecular effect of hypoxic stress on VHL functions remains elusive. Here we report that PIASy, a SUMO E3 ligase upregulated in hypoxia, interacts with VHL and induces VHL SUMOylation on lysine residue 171. Moreover, PIASy-mediated SUMO1 modification induces VHL oligomerization and abrogates its inhibitory function on tumor cell growth, migration and clonogenicity. Knockdown of PIASy by small interfering RNA leads to reduction of VHL oligomerization and increases HIF1α degradation. These findings reveal a unique molecular strategy for inactivation of VHL under hypoxic stress.
Moving Continuous K Nearest Neighbor Queries in Spatial Network Databases

One of the most important kinds of queries in Spatial Network Databases (SNDB) to support location-based services (LBS) is the shortest path query. Given an object in a network, e.g. a location of a car on a road network, and a set of objects of interests, e.g. hotels, gas station, car, etc., the k-NN query returns the k nearest neighbors from the query object to interested objects. This paper proposes a k-NN algorithm with a set of index structures to support the situation of moving objects. This algorithm can transform a dynamic problem to a static problem. In this paper we focus on road networks. However, our algorithms do not use any domain specific information, and therefore can be applied to any network. This algorithm's complexity is O(i2log2i), and traditional Dijkstra's complexity is O(i2 (i+n)2).
Formability Assessment of Prestrained Automotive Grade Steel Sheets Using Stress Based and Polar Effective Plastic Strain-Forming Limit Diagram

Accurate prediction of the formability in multistage forming process is very challenging due to the dynamic shift of limiting strain during the different stages depending on the tooling geometry and selection of the process parameters. Hence, in the present work, a mathematical framework is proposed for the estimation of stress based and polar effective plastic strain-forming limit diagram (σ- and PEPS-FLD) using the Barlat-89 anisotropic plasticity theory in conjunction with three different hardening laws such as Hollomon, Swift, and modified Voce equation. Two-stage stretch forming setup had been designed and fabricated to first prestrain in an in-plane stretch forming setup, and, subsequently, limiting dome height (LDH) testing was carried out on the prestrained blanks in the second stage to evaluate the formability. The finite element (FE) analysis of these two-stage forming process was carried out in ls-dyna for automotive grade dual-phase (DP) and interstitial-free (IF) steels, and the σ-FLD and PEPS-FLD were used as damage model to predict failure. The predicted forming behaviors, such as LDH, thinning development, and the load progression, were validated with the experimental results. It was found that the LDH in the second stage decreased with increase in the prestrain amount, and both the σ-FLD and PEPS-FLD could be able to predict the formability considering the deformation histories in the present multistage forming process with complex strain path.
Learning by Teaching a Robot: The Case of Handwriting

Thomas (all children's names have been changed) is five and a half years old and has been diagnosed with visuoconstructive deficits. He is under the care of an occupational therapist and tries to work around his inability to draw letters in a consistent manner. Vincent is six and struggles at school with his poor handwriting and even poorer self-confidence. Whereas Thomas is lively and always quick at shifting his attention from one activity to another, Vincent is shy and poised. Two very different children, each one facing the same difficulty to write in a legible manner. Additionally, hidden beyond these impaired skills, psychosocial difficulties arise: they underperform at school. Thomas has to go for follow-up visits every week, and they both live under the label of "special care. " This is a source of anxiety for the children and for their parents alike.
A user supported tracking framework for interactive video production

We present a user supported tracking framework that combines automatic tracking and extended user input to create error free tracking results that are suitable for interactive video production. The goal of our approach is hereby to keep the necessary user input as small as possible. In our framework, the user can select between different tracking algorithms and if he/she wants automatically fuse the results of different trackers with our robust fusion approach. The tracked object can be marked in more than one frame, which can significantly improve the tracking result. After tracking, the user can validate the results in an easy way, thanks to the support of a powerful interpolation technique. The tracking results are interactively improved until the complete track has been found. After the interactive editing process, the tracking result of each object is stored in an external file in order to create the interactive video.
Neuronal activity related to saccadic eye movements in the monkey's dorsolateral prefrontal cortex.

1. Single-neuron activity was recorded from the prefrontal cortex of monkeys performing saccadic eye movements in oculomotor delayed-response (ODR) and visually guided saccade (VGS) tasks. In the ODR task the monkey was required to maintain fixation of a central spot throughout the 0.5-s cue and 3.0-s delay before making a saccadic eye movement in the dark to one of four or eight locations where the visual cue had been presented. The same locations were used for targets in the VGS tasks; however, unlike the ODR task, saccades in the VGS tasks were visually guided. 2. Among 434 neurons recorded from prefrontal cortex within and surrounding the principal sulcus (PS), 147 changed their discharge rates in relation to saccadic eye movements in the ODR task. Their response latencies relative to saccade initiation were distributed between -192 and 460-ms, with 22% exhibiting presaccadic activity and 78% exhibiting only postsaccadic activity. Among PS neurons with presaccadic activity, 53% also had postsaccadic activity when the monkey made saccadic eye movements opposite to the directions for which the presaccadic activity was observed. 3. Almost all (97%) PS neurons with presaccadic activity were directionally selective. The best direction and tuning specificity of each neuron were estimated from parameters used to fit a Gaussian tuning curve function. The best direction for 62% of the neurons with presaccadic activity was toward the contralateral visual field, with the remaining neurons having best directions toward the ipsilateral field (23%) or along the vertical meridian (15%). 4. Most postsaccadic activity of PS neurons (92%) was also directionally selective. The best direction for 48% of these neurons was toward the contralateral visual field, with the remaining neurons having best directions toward the ipsilateral field (36%) or along the vertical meridian (16%). Eighteen percent of the neurons with postsaccadic activity showed a reciprocal response pattern: excitatory responses occurred for one set of saccade directions, whereas inhibitory responses occurred for roughly the opposite set of directions. 5. Sixty PS neurons with saccade-related activity in the ODR task were also examined in a VGS task. Forty of these neurons showed highly similar profiles of directional specificity and response magnitude in both tasks, 13 showed saccade-related activity only in the ODR task, and 7 changed their response characteristics between the ODR and VGS tasks. (ABSTRACT TRUNCATED AT 400 WORDS)
Thin film thickness measurement error reduction by wavelength selection in spectrophotometry

Fast and accurate volumetric profilometry of thin film structures is an important problem in the electronic visual display industry. We propose to use spectrophotometry with a limited number of working wavelengths to achieve high-speed control and an approach to selecting the optimal working wavelengths to reduce the thickness measurement error. A simple expression for error estimation is presented and tested using a Monte Carlo simulation. The experimental setup is designed to confirm the stability of film thickness determination using a limited number of wavelengths.
A Watermarking Algorithm Based on MA and DWT

To efficiently protect the ownership of multimedia data with watermarking technology, a novel image watermarking algorithm based on discrete wavelet transform (DWT) and memetic algorithm (MA) is proposed in this paper. The watermark is embedded to subband coefficients of subimage which is extracted from the original image with DWT, and watermark extraction is efficiently performed via MA. Experimental results show that the proposed watermarking algorithm results in almost invisible difference between the watermarked image and the original image, and is robust to common image processing operations and JPEG lossy compression.