Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of a nuclear role for 'pebble', a gene required for cytokinesis in Drosophila / by Alyssa Harley.

Cellular division is a vital process that must be tightly regulated to ensure the faithful replication and segregation of the genetic material of a cell. Previous experiments have shown that the Drosophila gene pebble plays an essential role in this process, and is thought to be required for the activation of the Rho G protein and the stimulation of cytokinesis. However, in addition to the DH/PH domains deemed responsible for this activation of Rho, Pebble (PBL) also contains two highly conserved nuclear BRCT domains, and a third conserved region, named the RadECl region. BRCT domains have previously been implicated in the response to and repair of DNA damage. The presence of such domains within a Rho GEF protein is both unique and intriguing in that it could enable PBL to play a dual role in both cytokinesis and DNA repair. This would not only be a novel mechanism, but it could also provide a link between the sensing of DNA damage and cell cycle control. A potential nuclear role for PBL was therefore examined in this thesis. Through the use of a variety of biochemical and genetic techniques, the importance of the nuclear localisation of PBL was examined, as well as the function of its RadECl and BRCT domains. V/hile nuclear localisation was found to be non-essential for the role of PBL in cytokinesis, sequestering the protein to the nucleus at the appropriate time was found to be highly important for the maintenance of normal cellular processes. In a completely novel and exciting hnding, the RadECI/BRCT domains were found to be required in the cytoplasm for cytokinesis, extending the range of function attributed to these domains. PBL was also shown to shuttle between the nucleus and the cytoplasm, providing an explanation for the observed ability of nuclear PBL to influence cytoplasmic
Synthesis of four-phase asynchronous control circuits from pipeline dependency graphs

We propose a method of synthesizing pipeline controllers as four-phase asynchronous circuits from specifications described as two-phase dependency graphs. Pipeline two-phase dependency graphs are transformed into four-phase ones by applying a transformation rule to each simple loop in the graphs. Four-phase dependency graphs are easily mapped onto four-phase asynchronous control circuits. We also discuss some simplification of four-phase dependency graphs.
Image Super Resolution and Enhancement Using E-spline

E-splines (Exponential spline) polynomials represent the best smooth transition between continuous and discrete domains. As they are constructed from convolution of exponential segments, there are many degrees of freedom to optimally choose the most convenient E-spline, suitable for a specific application. In this paper, the parameters of these E-splines were optimally chosen, to enhance the performance of image zooming and interpolation schemes. The proposed technique is based on minimizing the total variation function of the detail coefficients of the E-spline based wavelet decomposition. In zooming applications, the quality of interpolated images are further improved and sharpened by applying ICA technique to them, in order to remove any dependency. Illustrative examples are given to verify image enhancement of the proposed E-spline scheme, when compared with the existing approaches.
SCALING THE WALLS OF HISTORY: THE PERILS AND PITFALLS OF MULTI-SCALE LAND COVER COMPARISON

The problem addressed is this: most environmental issues require context to solve them. Is the ocean getting warmer? Is the desert growing? Is the forest declining? Solution: measure the temperature / size / leaf area. But such measurements only have significance if there are other comparable historical measurements to compare them too. This paper is about that word comparable. Can we really compare landscape generalisations gathered at different times and at different spatial scales? Today we have the ability to produce land cover maps at a very high spatial resolution (grid cell sizes of 10, 5 or even 1 m). Historically, data has typically been collected at coarser spatial scales (grid cell sizes of 50, 100 or even 1000 m). To facilitate comparison, modern data is often re-scaled to match the historical data. To evaluate the validity of this process, a series of synthetic landscapes were created. These landscapes included the full range of possible dispersion from a random spatial distribution of scene elements to a highly clustered spatial pattern. Each simulated landscape was firstly classified and then degraded to four levels of generalisation (simulating a range of spatial resolutions). In parallel, the process was reversed and the simulated landscapes were degraded and then classified. The resultant classifications were then compared. In all cases the integrity of the data was best preserved when the image was more highly spatially autocorrelated. Changing the spatial scale (i.e. degrading) of classifications resulted in a rapid decline in information content, particularly in more random landscapes. The implications of these results are then discussed.
Covering orthogonal polygons with star polygons: the perfect graph approach

We consider the problem of covering simple orthogonal polygons with star polygons. A star polygon contains a point <italic>p</italic>, such that for every point <italic>q</italic> in the star polygon, there is an orthogonally convex polygon containing <italic>p</italic> and <italic>q</italic>. In general, orthogonal polygons can have concavities (dents) with four possible orientations. In this case, we show that the polygon covering problem can be reduced to the problem of covering a weakly triangulated graph with a minimum number of cliques. We thus obtain a <italic>&Ogr;</italic> (<italic>n</italic><supscrpt>10</supscrpt>) algorithm. Since weakly triangulated graphs are perfect, we also obtain an interesting duality relationship. In the case where the polygon has at most three dent orientations, we show that the polygon covering problem can be reduced to the problem of covering a triangulated (chordal) graph with a minimum number of cliques. This gives us an <italic>&Ogr;</italic> (<italic>n</italic><supscrpt>3</supscrpt>) algorithm.
The Influence of Learning Out of School Camping and Hiking Courses on Self-Control

This article discusses the effect of outdoor education Program camping and hiking on self control. The method used in this research is experiment. The pre-test post-test two treatment design. Using simple random sampling. which specified a group of structured games activities as a single experimental group and an unstructured games activity group as the two experimental groups. The results showed that the group of structured games activities and groups of unstructured games activities there are significant differences. After administering the test, this paper finds out that the group implementing outdoor education program of camping and hiking and unstructured games is better than the group which does not in terms of self-control.
A Procurement Auction Market to Trade Residual Cloud Computing Capacity

Currently in the cloud market resources are mainly allocated according to the fixed-price, direct selling model. Market principles such as the supply-demand rate are not taken into consideration by cloud providers. In the literature several market-based resource allocation models and algorithms have been proposed, showing that dynamic pricing models might result more convenient for both the providers and the consumers of cloud resources. In this paper, we discuss about the use of alternative auction-based mechanisms to sell the “residual” computing capacity, i.e., the capacity which the provider is not able to allocate through direct-selling. The design of a procurement market for computing resources is proposed: in such a market we devised an adaptive bidding strategy that suggests to the provider the right actions useful to attain its business objective. The resource overbooking mechanism is also proposed to overcome the problem of resource underutilization. A software simulator was implemented with the aim of testing and validating the proposed mechanisms. Results show that, by fine-tuning their own strategy, providers manage to pursue specific objectives.
Irregular low-density parity-check lattices

We construct lattices with high coding gains based on nested low-density parity-check (LDPC) codes by Construction D'. We generalize the LDPC lattices [1] to have irregular degrees and call them irregular LDPC lattices. To construct good irregular LDPC lattices, we optimize the degree distributions by using density evolution and a modified sequential quadratic programming (SQP) and show our optimized irregular LDPC lattice has a threshold 0.48 dB from the capacity, which is about 0.6 dB better than the regular one in [1]. To construct a Tanner graph corresponding to LDPC lattices, we generalize the progressive-edge growth (PEG) algorithm and show a lower bound on the girth of the graph. Simulation is performed using the sum-product algorithm. Also, we compare the performance of joint decoding and multi-stage decoding [2] and show the advantage of joint decoding.
Circuits for Local and Global Signal Integration in Primary Visual Cortex

Contrast-dependent changes in spatial summation and contextual modulation of primary visual cortex (V1) neuron responses to stimulation of their receptive field reveal long-distance integration of visual signals within V1, well beyond the classical receptive field (cRF) of single neurons. To identify the cortical circuits mediating these long-distance computations, we have used a combination of anatomical and physiological recording methods to determine the spatial scale and retinotopic logic of intra-areal V1 horizontal connections and inter-areal feedback connections to V1. We have then compared the spatial scales of these connectional systems to the spatial dimensions of the cRF, spatial summation field (SF), and modulatory surround field of macaque V1 neurons. We find that monosynaptic horizontal connections within area V1 are of an appropriate spatial scale to mediate interactions within the SF of V1 neurons and to underlie contrast-dependent changes in SF size. Contrary to common beliefs, these connections cannot fully account for the dimensions of the surround field. The spatial scale of feedback circuits from extrastriate cortex to V1 is, instead, commensurate with the full spatial range of center–surround interactions. Thus these connections could represent an anatomical substrate for contextual modulation and global-to-local integration of visual signals. Feedback projections connect corresponding and equal-sized regions of the visual field in striate and extrastriate cortices and cover anisotropic parts of visual space, unlike V1 horizontal connections that are isotropic in the macaque. V1 isotropic connectivity demonstrates that anisotropic horizontal connections are not necessary to generate orientation selectivity. Anisotropic feedback connections may play a role in contour completion.
Image Mining: Review and New Challenges

Besides new technology, a huge volume of data in various form has been available for people. Image data represents a keystone of many research areas including medicine, forensic criminology, robotics and industrial automation, meteorology and geography as well as education. Therefore, obtaining specific in-formation from image databases has become of great importance. Images as a special category of data differ from text data as in terms of their nature so in terms of storing and retrieving. Image Mining as a research field is an interdisciplinary area combining methodologies and knowledge of many branches including data mining, computer vision, image processing, image retrieval, statis-tics, recognition, machine learning, artificial intelligence etc. This review focuses researching the current image mining approaches and techniques aiming at widening the possibilities of facial image analysis. This paper aims at reviewing the current state of the IM as well as at describing challenges and identifying directions of the future research in the field.
Prenasalized and postoralized consonants: The diverse functions of enhancement

Abstract:We propose that contour nasals come from two principal sources. One source, articulatorily driven, comes from underlying voiced stops, as nasal venting in order to sustain voicing. The other, perceptually driven, comes from underlying nasal consonants, as shielding next to contrastively oral vowels. Although both processes are phonetically well motivated, we argue that the contoured allophones specifically arise in languages in which systemic or phonotactic restrictions allow for easy recoverability of the corresponding underlying segment. Finally, we present a few cases of contour nasals in preconsonantal contexts that seem to be neither venting nor shielding, and suggest that these arise due to place-of-articulation enhancement in clusters. We offer diagnostics for distinguishing nasal venting from shielding and present case studies from South American languages in which understanding such phenomena as enhancement involves analytical commitments to what is contrastive in the language.
An Anatomically Based Model of Transient Coronary Blood Flow in the Heart

An efficient finite difference model of blood flow through the coronary vessels is developed and applied to a geometric model of the largest six generations of the coronary arterial network. By constraining the form of the velocity profile across the vessel radius, the three-dimensional Navier--Stokes equations are reduced to one-dimensional equations governing conservation of mass and momentum. These equations are coupled to a pressure-radius relationship characterizing the elasticity of the vessel wall to describe the transient blood flow through a vessel segment. The two step Lax--Wendroff finite difference method is used to numerically solve these equations. The flow through bifurcations, where three vessel segments join, is governed by the equations of conservation of mass and momentum. The solution to these simultaneous equations is calculated using the multidimensional Newton--Raphson method. Simulations of blood flow through a geometric model of the coronary network are presented demonstrating phy.
Accelerated volume ray-casting using texture mapping

Acceleration techniques for volume ray-casting are primarily based on pre-computed data structures that allow one to efficiently traverse empty or homogeneous regions. In order to display volume data that successively undergoes color lookups, however, the data structures have to be re-built continuously. In this paper we propose a technique that circumvents this drawback using hardware accelerated texture mapping. In a first rendering pass we employ graphics hardware to interactively determine for each ray where the material is hit. In a second pass ray-casting is performed, but ray traversal starts right in front of the previously determined regions. The algorithm enables interactive classification and it considerably accelerates the view dependent display of selected materials and surfaces from volume data. In contrast to other techniques that are solely based on texture mapping our approach requires less memory and accurately performs the composition of material contributions along the ray.
Populus Tremula Plants with Reduced Expression of the 4-Coumarate-CoA Ligase Gene Demonstrate Defects of the Rhizogenesis

Changing expression of a single gene by introducing mutations or transformation often affects expression of other genes, which results in the modification of the plant phenotype. We have obtained aspen plants with reduced expression levels of 4CL gene (4-coumarate-CoA ligase). Change in qualitative composition and 11-23% reduced lignin content were observed in the wood of the greenhouse plants. In the study of rhizogenesis in vitro it was found that the micro shoots of transgenic plants formed a greater number of adventive roots than in the control, 30%. Studying the transgenic aspen plants grown in a greenhouse (3 months) and passed the semi-natural conditions trial (4 months) has revealed 5-10% reduction in the lignin content, alteration of the phenotype – decrease in biometrical values (height and diameter of stem). Analysis of RNA from the plants grown under semi-natural conditions indicated changed expression levels of monolignol biosynthesis genes, 4CL, CCR1 (cinnamoyl-CoA reductase), CAD6 (cinnamyl-alcohol dehydrogenase), and CCoAOMT (caffeoyl-CoA O-methyltransferase). For the lines PtXVI4CL9a and PtXIII4CL2c grown under semi-natural conditions, weight of the root system was 1.5-2 fold reduced in the transgenic plants as compared to the control. The conductive: feeding root ratio was increased. Morphology of the root system was changed.
Towards Robotic Semantic Segmentation of Supporting Surfaces

Perceiving the geometry of environmental structures surrounding is a crucial prerequisite for robotic understand the indoor environments autonomously. A new framework for parsing RGB-D images aimed at supporting surfaces segmentation is proposed. First, the surface normal is extracted from depth information using PCA and normal clusters with 3D mean shift clustering. Then the main planes such as floor, wall will be detected with gravity vector estimation. Finally supporting surface and its corresponding objects are segmented using graph optimization with energy functions. The approach can offer a robotic semantic segmentation for better understanding the indoor environment. The experiment results based on Berkeley 3D Object Dataset demonstrate that our framework works well on indoor RGB-D cluttered scenes.
Dynamic Adaptive Network Intelligence

Accurate representational learning of both the explicit and implicit relationships within data is critical to the ability of machines to perform more complex and abstract reasoning tasks. We describe the efficient weakly supervised learning of such inferences by our Dynamic Adaptive Network Intelligence (DANI) model. We report state-of-the-art results for DANI over question answering tasks in the bAbI dataset that have proved difficult for contemporary approaches to learning representation (Weston et al., 2015).
Validation of the Emotiv EPOC EEG system for research quality auditory event-related potentials in children

Background. Previous work has demonstrated that a commercial gaming electroencephalography (EEG) system, Emotiv EPOC, can be adjusted to provide valid auditory event-related potentials (ERPs) in adults that are comparable to ERPs recorded by a research-grade EEG system, Neuroscan. The aim of the current study was to determine if the same was true for children. Method. An adapted Emotiv EPOC system and Neuroscan system were used to make simultaneous EEG recordings in nineteen 6- to 12-year-old children under “passive” and “active” listening conditions. In the passive condition, children were instructed to watch a silent DVD and ignore 566 standard (1,000 Hz) and 100 deviant (1,200 Hz) tones. In the active condition, they listened to the same stimuli, and were asked to count the number of ‘high’ (i.e., deviant) tones. Results. Intraclass correlations (ICCs) indicated that the ERP morphology recorded with the two systems was very similar for the P1, N1, P2, N2, and P3 ERP peaks (r = .82 to .95) in both passive and active conditions, and less so, though still strong, for mismatch negativity ERP component (MMN; r = .67 to .74). There were few differences between peak amplitude and latency estimates for the two systems. Conclusions. An adapted EPOC EEG system can be used to index children’s late auditory ERP peaks (i.e., P1, N1, P2, N2, P3) and their MMN ERP component.
A Synthetic Strategy for Conjugation of Paromomycin to Cell-Penetrating Tat(48-60) for Delivery and Visualization into Leishmania Parasites

A successful approach to deliver paromomycin, a poorly absorbed aminoglycoside antibiotic, to parasite cells is reported, based on selective protection of amino and hydroxyl groups followed by conjugation to a fluorolabeled, PEG-functionalized cell-penetrating Tat(48-60) peptide. The resulting construct is efficiently internalized into Leishmania cells, evidencing the fitness of cell-penetrating peptides as vectors for efficiently transporting low-bioavailability drugs into cells.
Scene Segmentation via Low-dimensional Semantic Representation and Conditional Random Field

In the past few years, significant progresses have been made in scene segmentation and semantic labeling by integrating informative context information with random field models. However, many methods often suffer the computational challenges due to training of the random field models. In this work, we present a fast approach to obtain semantic scene segmentation with high precision, which captures the local, regional and global information of images. The approach works in three steps as follows: First, an intermediate space with lowdimension semantic “topic” representation for image patches is introduced, by relying on the supervised Probabilistic Latent Semantic Analysis. Secondly, a concatenated pattern is taken to combine the vectors of posterior topic probabilities on different feature channels and to incorporate them into a conditional random field model. Finally, a fast max-margin training method is employed to learn the thousands of parameters quickly and to avoid approximation of the partition function in maximum likelihood learning. The comparison experiments on four multiclass image segmentation databases show that our approach can achieve more precise segmentation results and work faster than that of the state-of-the-art approaches.
A history-based matching approach to identification of framework evolution

In practice, it is common that a framework and its client programs evolve simultaneously. Thus, developers of client programs may need to migrate their programs to the new release of the framework when the framework evolves. As framework developers can hardly always guarantee backward compatibility during the evolution of a framework, migration of its client program is often time-consuming and error-prone. To facilitate this migration, researchers have proposed two categories of approaches to identification of framework evolution: operation-based approaches and matching-based approaches. To overcome the main limitations of the two categories of approaches, we propose a novel approach named HiMa, which is based on matching each pair of consecutive revisions recorded in the evolution history of the framework and aggregating revision-level rules to obtain framework-evolution rules. We implemented our HiMa approach as an Eclipse plug-in targeting at frameworks written in Java using SVN as the version-control system. We further performed an experimental study on HiMa together with a state-of-art approach named AURA using six tasks based on three subject Java frameworks. Our experimental results demonstrate that HiMa achieves higher precision and higher recall than AURA in most circumstances and is never inferior to AURA in terms of precision and recall in any circumstances, although HiMa is computationally more costly than AURA.