Miracle-dz/UniFAR-FTUs huggingface dataset:
Basic gray level aura matrices: theory and its application to texture synthesis

In this paper, we present a new mathematical framework for modeling texture images using independent basic gray level aura matrices (BGLAMs). We prove that independent BGLAMs are the basis of gray level aura matrices (GLAMs), and that an image can be uniquely represented by its independent BGLAMs. We propose a new BGLAM distance measure for automatically evaluating synthesis results w.r. t. input textures to determine if the output is a successful synthesis of the input. For the application to texture synthesis, we present a new algorithm to synthesize textures by sampling only the independent BGLAMs of an input texture. With respect to synthesis of textures and evaluation of the results, the performance of our approach is extensively evaluated and compared with symmetric GLAMs that are used in existing techniques and with gray level cooccurrence matrices (GLCMs). Experimental results have shown that (1) our approach significantly outperforms both symmetric GLAMs and GLCMs; (2) the new BGLAM distance measure has the ability to evaluate synthesis results, which can be used to automate the conventional visual inspection process for determining whether or not the output texture is a successful synthesis of the input; and (3) a broad range of textures can be faithfully synthesized using independent BGLAMs and the synthesis results are comparable to existing techniques
A Distributed-Parameter Approach to Dynamic Image Motion

The most elementary knowledge available in connection with image motion computation can be informally expressed as “structures do not jump”. We present a novel PDE-based representation of image motion exploiting this knowledge. Our distributed-parameter approach takes into account spatial context, unlike Kalman filters applied to point features separately. It performs spatio-temporal regularization in a recursive online fashion, unlike previous variational approaches evaluating entire spatio-temporal image volumes in a batch processing mode. Deviations from the expected velocity distribution generate vector fields that may serve as attentional mechanism for a superordinate processing stage. We briefly speculate about relations of our approach to perceptual phenomena like motion aftereffects.
Ieee Transactions on Aerospace and Electronic Systems 1 Multipath Exploitation in Through-the-wall Radar Imaging Using Sparse Reconstruction

Multipath exploitation and compressive sensing (CS) have both been applied independently to through-the-wall radar imaging. Fast and efficient data acquisition is desired in scenarios where multipath effects cannot be neglected. Hence, we combine the two methods to achieve good image reconstruction in multipath environments from few spatial and frequency measurements. Ghost targets appear in the scene primarily due to specular reflections from interior walls and multiple reflections within the front wall. Assuming knowledge of the room geometry, we can invert the multipath model and eliminate ghosts by means of CS. We develop effective methods for the reconstruction of stationary scenes which employ a group sparse CS approach. Additionally, we separate the target and wall contributions to the image by a sparse reconstruction approach joining wall and target models which allows suppression of the ghosts and increased signal-to-clutter ratio at the target locations. Effectiveness of the proposed approach is demonstrated using both simulated and real data.
Effects of severe dehydration on leaf photosynthesis in Quercus petraea (Matt.) Liebl.: photosystem II efficiency, photochemical and nonphotochemical fluorescence quenching and electrolyte leakage.

Leaf disks of oak (Quercus petraea (Matt.) Liebl. ) trees were subjected to rapid dehydration in air in the dark. Optimal photochemical efficiency of PS II (F(v)/F(M)), photochemical (q(P)) and nonphotochemical (q(NP)) quenchings of chlorophyll a fluorescence, and relative conductivity (C(r)) of leaf disk diffusate were measured in leaf disks with different water deficits (D). No effect of dehydration was detected before D reached values above 0.30. When D increased from 0.30 to 0.50, q(NP) increased without any change in q(P), which may indicate that thermal deexcitation of PS II increased, allowing reduced photochemical activity and maintenance of a large pool of oxidized primary acceptors (QA), although carbon reduction was impaired. Large changes in electron transport chain activity, leading to decreases in both q(P) and q(NP), appeared only in leaf disks subjected to severe water deficits (D > 0.60) and were correlated with a modification of membrane structure. However, stability of F(v)/F(M) indicated that the functional integrity of PS II was not altered until D reached values above 0.75. We conclude that the photosynthetic apparatus of Q. petraea is rather insensitive to leaf dehydration per se during drought under natural conditions.
Potentiation of Astrogliogenesis by STAT3-Mediated Activation of Bone Morphogenetic Protein-Smad Signaling in Neural Stem Cells

ABSTRACT Astrocytes play important roles in brain development and injury response. Transcription factors STAT3 and Smad1, activated by leukemia inhibitory factor (LIF) and bone morphogenetic protein 2 (BMP2), respectively, form a complex with the coactivator p300 to synergistically induce astrocytes from neuroepithelial cells (NECs) (K. Nakashima, M. Yanagisawa, H. Arakawa, N. Kimura, T. Hisatsune, M. Kawabata, K. Miyazono, and T. Taga, Science 284:479-482, 1999). However, the mechanisms that govern astrogliogenesis during the determination of the fate of neural stem cells remain elusive. Here we found that LIF induces expression of BMP2 via STAT3 activation and leads to the consequent activation of Smad1 to efficiently promote astrogliogenic differentiation of NECs. The BMP antagonist Noggin abrogated LIF-induced Smad1 activation and astrogliogenesis by inhibiting BMPs produced by NECs. NECs deficient in suppressor of cytokine signaling 3 (SOCS3), a negative regulator of STAT3, readily differentiated into astrocytes upon activation by LIF not only due to sustained activation of STAT3 but also because of the consequent activation of Smad1. Our study suggests a novel LIF-triggered positive regulatory loop that enhances astrogliogenesis.
The Stable Homology of Congruence Subgroups

In a previous paper, the author (together with Matthew Emerton) proved that the completed cohomology groups of SL_N(Z) are stable in fixed degree as N goes to infinity (Z may be replaced by the ring O_F of integers of any number field). In this paper, we relate these completed cohomology groups to K-theory and Galois cohomology. Various consequences include showing that Borel's stable classes become infinitely p-divisible up the p-congruence tower if and only if a certain p-adic zeta value is non-zero. We use our results to compute H_2(Gamma_N(p),F_p) (for sufficiently large N) where Gamma_N(p) is the full level-p congruence subgroup of SL_N(Z).
CD4-Specific Designed Ankyrin Repeat Proteins Are Novel Potent HIV Entry Inhibitors with Unique Characteristics

Here, we describe the generation of a novel type of HIV entry inhibitor using the recently developed Designed Ankyrin Repeat Protein (DARPin) technology. DARPin proteins specific for human CD4 were selected from a DARPin DNA library using ribosome display. Selected pool members interacted specifically with CD4 and competed with gp120 for binding to CD4. DARPin proteins derived in the initial selection series inhibited HIV in a dose-dependent manner, but showed a relatively high variability in their capacity to block replication of patient isolates on primary CD4 T cells. In consequence, a second series of CD4-specific DARPins with improved affinity for CD4 was generated. These 2nd series DARPins potently inhibit infection of genetically divergent (subtype B and C) HIV isolates in the low nanomolar range, independent of coreceptor usage. Importantly, the actions of the CD4 binding DARPins were highly specific: no effect on cell viability or activation, CD4 memory cell function, or interference with CD4-independent virus entry was observed. These novel CD4 targeting molecules described here combine the unique characteristics of DARPins—high physical stability, specificity and low production costs—with the capacity to potently block HIV entry, rendering them promising candidates for microbicide development.
Dynamic Mesh Refinement on GPU using Geometry Shaders

This paper presents a real-time rendering technique for dynamic, incremental 3D mesh refinement. The technique can be applied to any triangulated 3D mesh with arbitrary topology and connectivity. The functionality relies on geometry shaders that are used to amplify or remove geometry based on precalculated refinement patterns. For each triangle, the instantiated refinement pattern is selected dynamically. Due to limitations of current hardware, on-the-fly pattern instantiation cannot be implemented on the GPU. Instead, the complete refined mesh must be generated through pattern copying. We propose an incremental approach where the refined mesh is generated by using the previous refined mesh as primitive source. This algorithm runs exclusively on the GPU and requires no continuous data exchange between CPU and GPU. Due to the necessary mesh generation, the approach is particularly suitable for applications with small refinement levels. It complements traditional pattern-based refinement approaches that deliver high throughput for large refinement levels, but incur a substantial CPU-GPU communication overhead otherwise. Interesting applications include view-dependent mesh smoothing and interactive non-planar projections. In these areas, our algorithm enables efficient vertex-based implementations due to adaptive refinement.
Three-dimensional independent control of multiple magnetic microrobots via inter-agent forces

This article presents a method to independently control the position of multiple microscale magnetic robots in three dimensions, operating in close proximity to each other. Having multiple magnetic microrobots work together in close proximity is difficult due to magnetic interactions between the robots, and here we aim to control those interactions for the creation of desired multi-agent formations in three dimensions. Based on the fact that all magnetic agents orient to the global input magnetic field, the local attraction–repulsion forces between nearby agents can be regulated. For the first time, 3D manipulation of two microgripping magnetic microrobots is demonstrated. We also mathematically and experimentally prove that the center-of-mass external magnetic pulling of the multi-agent system is possible in three dimensions with an underactuated magnetic field generator. Here we utilize the controlled interaction magnetic forces between two spherical agents to steer them along two prescribed paths. We apply our method to independently control the motion of a pair of magnetic microgrippers as functional microrobot candidates each equipped with a five-degree-of-freedom motion mechanism and a grasp–release mechanism for targeted cargo delivery. A proportional controller and an optimization-based controller are introduced and compared, with potential to control more than two magnetic agents in three dimensions. Average tracking errors of less than 141 and 165 micrometers are accomplished for the regulation of agents’ positions using optimization-based and proportional controllers, respectively, for spherical agents with approximate nominal radius of 500 micrometers operating within several body-lengths of each other.
Avoiding the second year slump : a transition framework for students progressing through university

The ‘Sophomore Slump’ is a lack of engagement that can be experienced by students entering their second year at University. It has been a recognized phenomenon in American universities for many years but has gone largely unrecognized within Australian Universities. In 2009 a program called ‘Welcome to Second Year’ was introduced at a Metropolitan Australian University for Science students returning as second years or articulating straight into second year. The one day program took place during the week before trimester 1 classes commenced. The aim of the program was to re-engage students both socially with their peers, and academically with their course, and also to introduce them to professionals in their field. This paper provides a description of the program as well as student evaluation of the program over the three years it has now been run.
Estimating Incentive and Selection Effects in the Medigap Insurance Market: An Application with Dirichlet Process Mixture Model

This paper presents an empirical study of endogenous treatment effects in the presence of heterogeneous responses. We estimate the incentive and selection effects of having prescription drug coverage on total drug expenditures using a sample from the Medicare Current Beneficiary Survey (MCBS). A Dirichlet process mixture (DPM) model is used to model the heterogeneity in treatment effects. Rather than estimating a finite mixture model with a fixed number of components, we specify a DP prior on the parameters, thus allowing the data and prior knowledge to determine the number of components. Endogeneity is modeled by the covariance of the error terms of the selection and the outcome equations in a two-equation selection model. We find that there are strong incentive and advantageous selection effects, with the average treatment effect and the average treatment effect for the treated estimated at $1132 and $858, respectively. Substantial heterogeneity is found to exist in the selection effects, particularly for those having lower drug expenditures.
The hard state of black hole candidates: XTEJ1752-223

We present a 2-day long Rossi X-ray Timing Explorer observation and simultaneous Swift data of the bright X-ray transient XTE J1752–223. Spectral and timing properties were stable during the observation. The energy spectrum is well described by a broken power law with a high-energy cut-off. A cold disc (? 0.3 keV) is observed when Swift/X-Ray Telescope data are considered. The fractional root mean square amplitude of the aperiodic variability (0.002–128 Hz) is 48.2 ± 0.1 per cent, and it is not energy dependent. The continuum of the power density spectrum can be fitted by using four broad-band Lorentzians. A high-frequency (? 21 Hz) component and two weak quasi-periodic oscillation-like features are also present. Time lags between soft and hard X-rays roughly follow the relation ? t? 0.7, with delays dropping from ? 0.5 (0.003 Hz) to ? 0.0015 (? 10 Hz) s. Our results are consistent with XTE J1752–223 being a black hole candidate, with all timing and spectral components very similar to those of Cyg X-1 during its canonical hard state.
Notes on Foreign Aid Selectivity Based on Human Capital

In order to achieve developmental goals more effectively, international communities have paid increasing attention to the pros and cons of "Aid Selectivity. " However, the empirical results on the effects of international aid on economic growth in the recipient countries are mixed. This note proposes a theoretical framework to reconcile those mixed findings on aid effectiveness. In particular, I focus on the growth consequences of a poverty-efficient aid allocation in the recipientâ€™s economy, and theoretically illustrate that an important determinant of aid efficacy is the achieved growth of human capital accumulation in recipient countries.
The use of Internet in public relations and its impact on the practice: a New Zealand perspective

This study explores the trends in the application of various Internet tools in the public relations practice of New Zealand and the impact these have on certain key aspects of the practice such as skills, encroachment, gender balance and ethics. A mixed methods approach including an online survey and semi-structured indepth interviews has been followed. An attempt has been made to answer the research questions with the aid of the data collected from 133 survey respondents and ten interview participants. The findings revealed that there are considerable variations in the use and application of the different online tools in the New Zealand public relations practice. This discrepancy was found to have been influenced by the area of work and experience of the practitioners along with their knowledge of the Internet and the organisational environment they operated in. Further, it appears that practitioners do not have a full grasp of the nature of online tools and their scope of utilization in the practice. Areas of further investigation have been highlighted and recommendations have been made for the future researchers to help aid a better understanding of online public relations.
Spatial Resolutions of the Broadband Nonredundant and Minimum Redundancy Arrays

Approximate formulations for the 3-dB beamwidth are derived in this letter to measure the spatial resolution of the broadband nonredundant array (NRA) and minimum redundancy array (MRA), which assume the ideal continuous-time, infinite-length filters with the frequency responses obtained by the linearly constrained minimum variance (LCMV) optimization. By these formulations, the beamwidths of NRA and MRA are compared with that of the uniform linear array (ULA). Moreover, the accuracy of the derived formulations is assessed by numerical studies.
Why Do Managers Explain Their Earnings Forecasts

Managers often explain their earnings forecasts by linking forecasted performance to their internal actions and the actions of parties external to the firm. These attributions potentially aid investors in the interpretation of management forecasts by confirming known relationships between attributions and profitability or by identifying additional causes that investors should consider when forecasting earnings. We investigate why managers choose to provide attributions with their forecasts and whether the attributions are related to security price reactions to management earnings forecasts. Using a sample of 951 management earnings forecasts issued from 1993 to 1996, we find that attributions are more likely for larger firms, less likely for firms in regulated industries, less likely for forecasts issued over longer horizons, more likely for bad news forecasts, and more likely for forecasts that are maximum type. Furthermore, attributions are associated with greater absolute price reactions to management forecasts, more negative price reactions to management forecasts (forecast news held constant), and a greater price reaction per dollar of unexpected earnings. Our findings hold after control for the aforementioned determinants of attributions and after control for other firm- and forecast-specific variables that are often associated with security prices.
What if firms adjust their debt-equity ratios toward a target range?

We estimate optimal target-ranges of capital structure controlling for a series of rm-speci c characteristics and accounting for the serial correlation that arises from the dynamic component of the leverage choice. Then, we empirically examine if rms adjust their leverages toward the estimated optimal ranges. Our analysis suggests that the observed behavior of rms is consistent with the notion of rangeadjustment. JEL classi cation: G32 EFM classi cation: 140
Occupational Therapy and Management of Multiple Chronic Conditions in the Context of Health Care Reform

One in four individuals living in the United States has multiple chronic conditions (MCCs), and the already high prevalence of MCCs continues to grow. This population has high rates of health care utilization yet poor outcomes, leading to elevated concerns about fragmented, low-quality care provided within the current health care system. Several national initiatives endeavor to improve care for the population with MCCs, and occupational therapy is uniquely positioned to contribute to these efforts for more efficient, effective, client-centered management of care. By integrating findings from the literature with current policy and practice, we aim to highlight the potential role for occupational therapy in managing MCCs within the evolving health care system.
Haplotype Block Partitioning using a Normalized Maximum Likelihood Model

This paper proposes a new method for finding block structure in haplotypes. The new method belongs to the family of minimum description length (MDL) methods, which were intensively investigated in connection with this problem also in the past. Within MDL paradigm we evaluate the code length by using the normalized maximum likelihood (NML) model, as opposed to two part codes used in the past, resulting in a more compact conditional description. Also we propose a new joint clustering and encoding algorithm which selects the cluster centers by minimizing the overall code length when encoding the cluster centers (block prototypes) and the blocks conditional on the block prototypes. The minimized description length provided by the new algorithm is shown to be smaller than that obtained by previous methods when applied to real haplo-type data. The inference of the block boundaries using this better code length measure produces different results than the previous methods, reducing significantly the description length of the overall haplotype partition.
A robot to study the development of artwork appreciation through social interactions

In this work, we present a model based on social referencing mechanisms for the artwork appreciation development. We show that trying to reach autonomous robot artwork preferences is an interesting framework for developmental robotics. Therefore, we present an application of our model in a natural environment. The museum as an experiment place, helps us to benefit from a large number of visitors with different backgrounds and personal interests, as well as provides the challenge of the learning and recognition of an important number of artefacts (heterogeneous set of objects in terms of size, culture). To overcome some limitations like the autonomy in the learning, we proposed a first model for cumulative learning using a second-order conditioning approach with very encouraging results.
Large-scale Multi-class and Hierarchical Product Categorization for an E-commerce Giant

In order to organize the large number of products listed in e-commerce sites, each product is usually assigned to one of the multi-level categories in the taxonomy tree. It is a time-consuming and difficult task for merchants to select proper categories within thousands of options for the products they sell. In this work, we propose an automatic classification tool to predict the matching category for a given product title and description. We used a combination of two different neural models, i.e., deep belief nets and deep autoencoders, for both titles and descriptions. We implemented a selective reconstruction approach for the input layer during the training of the deep neural networks, in order to scale-out for large-sized sparse feature vectors. GPUs are utilized in order to train neural networks in a reasonable time. We have trained our models for around 150 million products with a taxonomy tree with at most 5 levels that contains 28,338 leaf categories. Tests with millions of products show that our first predictions matches 81% of merchants’ assignments, when “others” categories are excluded.