Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial selection for structural color on butterfly wings and comparison with natural evolution

Significance Despite significant efforts to study structural colors in nature, little is known about how such colors and structures evolved in the first place. To address this key question, we performed the first artificial selection (to our knowledge) on a structural color using butterflies. We demonstrated rapid evolution of violet structural color from ultra-violet brown scales in Bicyclus anynana butterflies with only six generations of selection. Furthermore, we identified the structural changes responsible for color evolution, which involve changes in the thickness of a chitin lamina in individual wing scales. By examining other violet-banded species that occur naturally in the Bicyclus genus, we found the colors are produced via the same mechanism and thus may have evolved via similar scale modifications. Brilliant animal colors often are produced from light interacting with intricate nano-morphologies present in biological materials such as butterfly wing scales. Surveys across widely divergent butterfly species have identified multiple mechanisms of structural color production; however, little is known about how these colors evolved. Here, we examine how closely related species and populations of Bicyclus butterflies have evolved violet structural color from brown-pigmented ancestors with UV structural color. We used artificial selection on a laboratory model butterfly, B. anynana, to evolve violet scales from UV brown scales and compared the mechanism of violet color production with that of two other Bicyclus species, Bicyclus sambulos and Bicyclus medontias, which have evolved violet/blue scales independently via natural selection. The UV reflectance peak of B. anynana brown scales shifted to violet over six generations of artificial selection (i.e., in less than 1 y) as the result of an increase in the thickness of the lower lamina in ground scales. Similar scale structures and the same mechanism for producing violet/blue structural colors were found in the other Bicyclus species. This work shows that populations harbor large amounts of standing genetic variation that can lead to rapid evolution of scales’ structural color via slight modifications to the scales’ physical dimensions.
The effects of chronic lead exposure in taste-aversion conditioning in rats

Two experiments investigating the effect of chronic lead exposure on taste-aversion learning are reported. In Experiment 1 lead-exposed and non-lead-exposed animals received a single pairing of saccharin and lithium chloride. In Experiment 2 comparable groups received a single pairing of saccharin and rapid rotation. The results of both experiments indicate that significantly stronger aversions are developed by the lead-exposed animals. These results are attributed to the increased reactivity of the lead-exposed animals which allowed additional associations to be formed between the taste (conditioned stimulus, CS) and heightened reactivity, and between the taste-reactivity state stimuli and illness
Can the Market Fix a Wrong Administrative Decision? Massive Delisting on the Prague Stock Exchange

This research contributes to the investigation of the emerging stock markets in transition economies, namely in the Czech Republic. We estimate the impact of the various determinants of shares delisting e.g. exclusion from public trading on the Prague Stock Exchange (PSE) during the period 1993 – 2004. Unlike its counterparts in Poland or Hungary, exceptionally large amounts of shares were delisted from the PSE. Using the data on listed and delisted companies we show that the pre-privatization and privatization characteristics of the companies were decisive for delisting. This further indicates that it would have been possible to prevent massive delisting if these factors had been taken into account when deciding which companies to place on the stock exchange for public trading. Moreover, therefore companies that were not suitable for public trading were also not suitable for voucher privatization.
Eye gaze for reference resolution in multimodal conversational interfaces

Multimodal conversational interfaces allow users to carry a spoken dialogue with an artificial conversational agent while looking at a graphical display. The dialogue is used to accomplish purposeful tasks. Motivated by previous psycholinguistic findings, this dissertation investigates how eye gaze contributes to automated spoken language understanding in such a setting, specifically focusing on robust reference resolution---a process that identifies the referring expressions in an utterance and determines which entities these expressions refer to. As a part of this investigation we attempt to model user focus of attention during human-machine conversation by utilizing the users' naturally occurring eye gaze. We study which eye gaze and auxiliary visual factors contribute to this model's accuracy. Among the various features extracted from eye gaze, fixation intensity has shown to be the most indicative in reflecting attention. We combine user speech along with this gaze-based attentional model into an integrated reference resolution framework. This framework fuses linguistic, dialogue, domain, and eye gaze information to robustly resolve various kinds of referring expressions that occur during human-machine conversation. Our studies have shown that based on this framework, eye gaze can compensate for limited domain models and dialogue processing capability. We further extend this framework to handle recognized speech input acquired situated dialogue within an immersive virtual environment. We utilize word confusion networks to model the set of alternative speech recognition hypotheses and incorporate confusion networks into the reference resolution framework. The empirical results indicate that incorporating eye gaze significantly improves reference resolution performance, especially when limited domain model information is available to the reference resolution framework. The empirical results also indicate that modeling recognized speech via confusion networks rather than the single best recognition hypothesis leads to better reference resolution performance.
On-Disk Sequence Cache (ODSC): Using Excess Disk Capacity to Increase Performance

ON-DISK SEQUENCE CACHE(ODSC): USING EXCESS DISK CAPACITY TO INCREASE PERFORMANCE Christopher R. Slade Department of Computer Science Master of Science We present an on-disk sequence cache (ODSC), which improves disk drive performance. An ODSC uses a separate disk partition to store disk data in the order that the operating system requests it. Storing data in this order reduces the amount of seeking that the disk drive must do. As a result, the average disk access time is reduced. Reducing the disk access time improves the performance of the system, especially when booting the operating system, loading applications, and when main memory is limited. Experiments show that our ODSC speeds up application loads by as much as 413%. Our ODSC also reduces the disk access time of the Linux boot by 396%, and speeds up a Linux kernel make by 28%. We also show that an ODSC improves performance when main memory is limited.
Foreign Research and Development in China: A Sectoral Approach

This study systematically examines foreign R&D in China's manufacturing industries, using the most recent census data published by China's State Council. It reveals that foreign firms are committing less R&D resource than China's domestic enterprises. Foreign R&D activities are far more active in high-tech industries than in labour-intensive industries. This study also demonstrates that China's dynamic domestic market and export, as well as its large pool of well-educated labour are the major drivers for foreign R&D, while the technology drive is not significant yet. Finally, the result shows that foreign firms are less likely to conduct R&D in sectors where they possess strong advantages. Such results suggest that the Chinese governments and domestic firms should focus on building up indigenous innovative capabilities in order to attract more foreign R&D: the majority of foreign firms will invest in R&D when they feel the competition from domestic firms.
Modeling and control of a flying robot for contact inspection

This paper focuses on the modeling and control of a flying robot. The complete system, composed of a quadrotor unmanned aerial vehicle and a custom-made manipulator, has been designed for remote inspection by contact of industrial plants. The goal of this paper is to show the dynamical characteristics of the flying robot during tasks that require physical interaction, and to determine a control strategy that allows to safely interact with unknown environments. The methodology has been implemented on a real prototype and tested in an indoor area. Experimental results validate the proposed controller and show its effectiveness.
Sensory reflex for biped humanoid walking

This paper proposes a walk control consist ng of a feedforward dynamic pattern and a feedback sensory reflex. The dynamic pattern is a rhythmic and periodic motion, and is generated assuming that the models of the humanoid and the environment are known. The sensory reflex is a simple, b t rapid motion programmed in respect to sensory information. The sensory reflex consis s f the ZMP (Zero Moment Point) reflex, the landing-phase reflex, and the body-posture reflex. With the dynamic pattern and the sensory reflex, it is possible for the humanoid to walk rhythmically and to adapt itself to the en ironmental uncertainties. The effectiveness of our proposed method was confirmed by dynamic simulation and walk experiments of an actual 33 DOF humanoid.
Stream cipher based on post-commutative quasigroups

A quasigroup (A, ⊙) is said to be post-commutative if a ⊙ b = c implies a ⊙ c = b for all a, b, c ∈ Q. In this paper, we design a stream cipher based on post-commutative quasigroups and analyse its security. A lower bound of the total number of post-commutative quasigroups of a given order, and constructions of post-commutative quasigroups are also given in this paper.
Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

Face alignment is a crucial step in face recognition tasks. Especially, using landmark localization for geometric face normalization has shown to be very effective, clearly improving the recognition results. However, no adequate databases exist that provide a sufficient number of annotated facial landmarks. The databases are either limited to frontal views, provide only a small number of annotated images or have been acquired under controlled conditions. Hence, we introduce a novel database overcoming these limitations: Annotated Facial Landmarks in the Wild (AFLW). AFLW provides a large-scale collection of images gathered from Flickr, exhibiting a large variety in face appearance (e.g., pose, expression, ethnicity, age, gender) as well as general imaging and environmental conditions. In total 25,993 faces in 21,997 real-world images are annotated with up to 21 landmarks per image. Due to the comprehensive set of annotations AFLW is well suited to train and test algorithms for multi-view face detection, facial landmark localization and face pose estimation. Further, we offer a rich set of tools that ease the integration of other face databases and associated annotations into our joint framework.
An Incremental Garbage Collection for an Object Heap on Flash Memory and A Memory Model For Flash

This thesis concerns two issues regarding flash memories. The first one is improving an existing stop-the-world garbage collector for an object heap on flash memory and developing an incremental garbage collector for it. The second one is exploring the special characteristic of flash memories and how we can develop efficient algorithms when taking these characteristics into consideration. In the first issue, we present the design and implementation of two garbage collection algorithms for TINYSTORE. The first collector is an improvement to an existing stop-the-world collector and the second one is a new incremental collector. TINYSTORE is a persistent, transactional, garbage-collected memory-management system. The system is designed for flash-based implementations of Java Card, a variant of the Java platform for smart cards. In the Java Card platform, objects are persistent by default. TINYSTORE supports both explicit object deletions and automatic garbage collection, even with a small constant amount of RAM. TINYSTORE is improved in this thesis to efficiently collect garbage when stopping the program totally until the entire garbage collector’s work is finished, or by interleaving the running program and the collection of garbage. In the second issue, we define a new abstract model suitable to flash memories. We also present an efficient sorting algorithm for flash memories which is shown to be more efficient for flash than known I/O model optimal algorithms.
Click ! A study in automatic parameter selection for Computer Vision algorithms

This work investigates the possibility of designing a self-calibrating computer vision algorithm for given tracking or segmentation methods. We concentrate on a (suitably modified) segmentation algorithm, the meanshift segmentation of Comaniciu and Meer (2002). We show that even for a basic algorithm such as the one under study, the same set of parameter values cannot be universally optimal. However, we determine that within the same image (visual conditions) it is possible to have the same set of parameter values behaving in an optimal way for the majority of objects depicted. Furthermore, we show that it may be possible to classify the images by situations and use the same parameter values within a class. The conclusion indicates that it is possible to gather preliminary information about the image itself (e.g., degree of clutter, range of the color space, dispersion of colors, scene dynamics, etc.) which will indicate the best parameter values to use in the algorithm.
User Modeling by CLC and Feedback Behavior

The key of personalized recommendation system is to develop a user profile that describes the user's interests. We propose a method to establish the user profile based on Chinese Library Classification (CLC) and feedback behavior. The user interest profile is initialed by CLC, using its thesaurus to describe the user's interest. Then the feedback of user is classified and used, which allows us adjust the user's profile, having the user participate in as little as possible. Finally, based on the above ideas, we develop a document recommend system.
VALIDATION OF THE CORTICAL HOMUNCULUS USING FUNCTIONAL MRI

The motor strip in the frontal lobe of the Human Brain is responsible for all bodily movements or “motor functions”. In this paper we attempt to map the motor cortex of the Human Brain using fMRI data. The advantages of mapping it are several fold ranging from therapy to epilepsy and stroke patients, to understanding the development of these motor functions from birth. We try to recreate the homunculus, a concept which showed how the real estate of the motor cortex was distributed across these motor functions.
Cooperative Production of Public Input

A movement has ignited amongst government agencies to extend their efforts for obtaining wide input on contentious public issues. These projects face challenges related to scale and political capture. But new sociotechnical approaches that leverage nascent structures of distributed work and interaction exhibited in the social web may help address these issues. Instead of emphasizing the exchange of individual messages and voting, I propose that systems should be designed to support the cooperative synthesis, organization, and contextualization of public input.
Using Constraints to Query R-TreesJonathan Goldstein

The R-Tree index is a popular multidimensional index used in several extensible and GIS-oriented database systems. In this paper, we show that a simple reenement of the search algorithm of the R-Tree|which is common to all variants of the R-Tree|ooers signiicant speedups in most cases, with little or no worst-case performance penalty. The idea is essentially to use a conjunction of linear constraints (rather than a minimum bounding retangle) to approximate the query and to use this tighter bounding envelope to determine when the query overlaps with an R-Tree node. This raises an important question: How can we eeciently check whether the query envelope overlaps the minimum bounding box for a tree node? Linear Programming (LP) ooers one solution, but it is susceptible to numeric approximation errors. One of the contributions of this paper is a new algorithm for performing this check check that is more eecient than LP and free from numeric errors. We also present several theoretical results characterizing this algorithm. From a practical standpoint, adding the proposed constraint query reenement to existing R-Tree implementations is straightforward. Using implementations of R-Trees on top of the SHORE storage manager, we present experimental results (using TIGER census data for California and Wisconsin, and the Sequoia 2000 benchmark data set) that provide strong evidence in support of the proposed reenement. Our results demonstrate that the CPU overhead of our more complex overlap test, visa -vis the traditional minimum bounding box intersection test, is minor. On the other hand, the (CPU and I/O) gains can be considerable, especially for queries that are asymmetrically oriented with respect to the R-Tree axes. The results are especially surprising given that we make no changes at all to the insertion and deletion algorithms. Finally, linear constraints are a very powerful tool for formulating queries, and a very important application of our results is that we can eeciently support a broad new class of such queries on multidi-mensional datasets drawn from a variety of domains that go well beyond GIS and spatial applications. We illustrate this, with experimental results, using queries over a ve-dimensional projection of the widely used Compustat nancial database (which contains over 300 dimensions! ).
Computing the λ-Seeds of a String

We study the λ-seed problem of a string in this paper. Given a string x of length n and an integer λ, the λ-seed problem is to find all the sets of λ substrings of x that cover a superstring of x, assuming that each element of the set is of equal length. We present an efficient algorithm that can compute all the λ-seeds of x in O(n) time.
Diffusion Tensor Imaging in Mild Traumatic Brain Injuries – Acute State and Short-Term Recovery

Mild traumatic brain injuries (MTBI), in most cases, cannot be detected using imaging modalities like CT or MRI. However, diffusion tensor imaging (DTI) reveals subtle changes in white matter integrity as a result of head trauma and plays an important role in refining diagnosis and management of MTBI. We use DTI to detect the microstructural changes in collegial football players induced by axonal injuries and to monitor their evolution during the recovery process. Three players suffered a MTBI during play or practice and underwent scanning within 24h with follow-ups after one and two weeks. Scalar diffusion indices were derived from diffusion tensors and analyzed using tract-based spatial statistics (TBSS) and voxel-wise t-tests to detect brain regions showing significant group differences between the injured subjects and controls. Both analyses revealed overlapping regions in the corticospinal tract with significant increase in fractional anisotropy and decreases in transverse and mean diffusivity within 24 hours. In voxel-wise t-tests strong indications for recovery were found spatially and temporally. For mean and transverse diffusivity, regions showing significant differences shrunk between the first and the follow-up scans. Although the sample size is small, these findings are remarkably consistent across all subjects and scans.
An improved hydrogen bond potential: Impact on medium resolution protein structures

A new semi‐empirical force field has been developed to describe hydrogen‐bonding interactions with a directional component. The hydrogen bond potential supports two alternative target angles, motivated by the observation that carbonyl hydrogen bond acceptor angles have a bimodal distribution. It has been implemented as a module for a macromolecular refinement package to be combined with other force field terms in the stereochemically restrained refinement of macromolecules. The parameters for the hydrogen bond potential were optimized to best fit crystallographic data from a number of protein structures. Refinement of medium‐resolution structures with this additional restraint leads to improved structure, reducing both the free R‐factor and over‐fitting. However, the improvement is seen only when stringent hydrogen bond selection criteria are used. These findings highlight common misconceptions about hydrogen bonding in proteins, and provide explanations for why the explicit hydrogen bonding terms of some popular force field sets are often best switched off.
Approximate Inference for Clusters in Solution Spaces

This work proposes new approximate (and exact) inference methods for reasoning about an important and hard-to-compute property of the solution space of combinatorial problems, namely clusters of solutions. Given a constraint satisfaction problem (CSP), we can think of two solutions as being "connected" if they differ in the value of only one variable. Clusters of solutions can thus be defined in a natural manner: two solutions s1 and s2 are in the same cluster if and only if there is a path of connected solutions from s1 to s2. The main question we seek to address is, given a CSP, how many solution clusters does it have?
Problems of Pedagogical Creativity Development.

This article provides analysis of research papers by different scholars, dedicated to topical issues of pedagogical creativity development in the educational process. The authors determined that pedagogical creativity could be considered at five levels: informationreproducing, adaptive-prognostic, innovative, research and creative-prognostic. In addition, this study highlights the main features of teachers’ creativity and describes the psychological and pedagogical factors that negatively influence creativity development in students of professional-pedagogical specialties. Practical significance of this paper is determined by the fact that the authors offered a pedagogical model describing creative potential development of the personality in the course of research activities.
Effect of heat shock protein 70 polymorphism on thermotolerance in Tharparkar cattle

Aim: Out of various members of heat shock protein (HSP) superfamily which act a molecular chaperon by binding to the denaturing protein thus stabilizing them and preserving their activity, HSP70 are of major importance in thermotolerance development. Thus, present investigation aimed at a screening of HSP70 gene for polymorphisms and possible differences in thermotolerance in Tharparkar breed of cattle. Materials and Methods: A 295 bp fragment of HSP70 gene was subjected to polymerase chain reaction-single-strand conformation polymorphism (SSCP) followed by sequencing of different SSCP patterns in 64 Tharparkar cattle. A comparative thermotolerance of identified genotypes was analyzed using heat tolerance coefficients (HTCs) of animals for different seasons. Results: Three SSCP patterns and consequently two alleles namely A and B were documented in one fragment of HSP70 gene. On sequencing, one single-nucleotide polymorphism with G > T substitution was found at a position that led to a change of amino acid aspartate to tyrosine in allele A. It was found that in maintaining near normal average rectal temperature, genotype AA was superior (p≤0.01). Genotype AA, thus, was found to be most thermotolerant genotype with the highest HTC (p≤0.01). Conclusion: The polymorphism at HSP70 is expected to be a potent determinant for heat tolerance in cattle, which may aid in selection for thermotolerance in cattle.