Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding Significant Subregions in Large Image Databases

Images have become an important data source in many scientific and commercial domains. Analysis and exploration of image collections often requires the retrieval of the best subregions matching a given query. The support of such content-based retrieval requires not only the formulation of an appropriate scoring function for defining relevant subregions but also the design of new access methods that can scale to large databases. In this paper, we propose a solution to this problem of querying significant image subregions. We design a scoring scheme to measure the similarity of subregions. Our similarity measure extends to any image descriptor. All the images are tiled and each alignment of the query and a database image produces a tile score matrix. We show that the problem of finding the best connected subregion from this matrix is NP-hard and develop a dynamic programming heuristic. With this heuristic, we develop two index based scalable search strategies, TARS and SPARS, to query patterns in a large image repository. These strategies are general enough to work with other scoring schemes and heuristics. Experimental results on real image datasets show that TARS saves more than 87% query time on small queries, and SPARS saves up to 52% query time on large queries as compared to linear search. Qualitative tests on synthetic and real datasets achieve precision of more than 80%.
Genetic Compatibility Determines Endophyte-Grass Combinations

Even highly mutually beneficial microbial-plant interactions, such as mycorrhizal- and rhizobial-plant exchanges, involve selfishness, cheating and power-struggles between the partners, which depending on prevailing selective pressures, lead to a continuum of interactions from antagonistic to mutualistic. Using manipulated grass-endophyte combinations in a five year common garden experiment, we show that grass genotypes and genetic mismatches constrain genetic combinations between the vertically (via host seeds) transmitted endophytes and the out-crossing host, thereby reducing infections in established grass populations. Infections were lost in both grass tillers and seedlings in F1 and F2 generations, respectively. Experimental plants were collected as seeds from two different environments, i.e., meadows and nearby riverbanks. Endophyte-related benefits to the host included an increased number of inflorescences, but only in meadow plants and not until the last growing season of the experiment. Our results illustrate the importance of genetic host specificity and trans-generational maternal effects on the genetic structure of a host population, which act as destabilizing forces in endophyte-grass symbioses. We propose that (1) genetic mismatches may act as a buffering mechanism against highly competitive endophyte-grass genotype combinations threatening the biodiversity of grassland communities and (2) these mismatches should be acknowledged, particularly in breeding programmes aimed at harnessing systemic and heritable endophytes to improve the agriculturally valuable characteristics of cultivars.
Thermal and Rheological Formulation and Evaluation of Synthetic Bitumen from Reprocessed Polypropylene and Oil

Bitumen from the catalytic cracking of petroleum is widely used in the construction industry as a binder for mineral aggregates paving asphalt cement (PAC). However, this material has serious limitations for use at different temperatures. Modifications with polymers have been widely studied to improve the properties of this material and increase its useful life. As a result of the increased environmental risk, the volume of solid waste (MSW) can be used as an alternative to the best use of this material. One of these is the formulation of synthetic bitumen (binders) from mixtures of lubricant oil/polymer that can show better when compared to traditional and modified bitumen. In this work, a mixture of lubricating oil and recycled polypropylene (PP) was made for the formulation of synthetic bitumens. The rheological analyses carried out on the material indicate that at low temperatures the formulated material shows high loading modulus values, indicating high mechanical strength, and the material also presented high resistance to permanent deformation; the viscosity profile indicates that the material is highly pseudoplastic presenting high viscosity at zero shear rate and low visibility at high shear rates, highlighting the samples containing 10 and 20% of polymer material in the formation as the best for use as one of the components of the pavement cement.
Multiset Codes for Permutation Channels

This paper introduces the notion of multiset codes as relevant to the problem of reliable information transmission over permutation channels. The motivation for studying permutation channels comes from the effect of out of order delivery of packets in some types of packet networks. The proposed codes are a generalization of the so-called subset codes, recently proposed by the authors. Some of the basic properties of multiset codes are established, among which their equivalence to integer codes under the Manhattan metric. The presented coding-theoretic framework follows closely the one proposed by Koetter and Kschischang for the operator channels. The two mathematical models are similar in many respects, and the basic idea is presented in a way which admits a unified view on coding for these types of channels.
Face Detection and Tracking in Dynamic Background of Street

The paper presents a novel face detection and tracking algorithm which could be part of human-machine interaction in applications such as intelligent cash machine. The facial feature extraction algorithm is based on discrete approximation of Gabor Transform, called Discrete Gabor Jets (DGJ), evaluated in edge points. DGJ is computed using integral image for fast summations in arbitrary windows and by FFT operations on short contrast signals. Contrasting is performed along radial directions while frequency analysis along angular directions. Fourier coefficients for a small number of rings create a feature vector which is next reduced to few LDA components and then compared to the reference facial feature vector. Detected eyes and nose corners are chosen to fit reference face by spatial relationships. Tracking is based on the same rule, but the corners are searched only within already detected facial features neighborhood. Optionally for face normalization eyes centers are found as centers of outer and inner eye corners. Comparison of manual and automatic eye center detection shows still significant advantage of manual approach, measured in terms of accuracy in face recognition by Linear Discriminant Analysis (LDA) and Dual Linear Discriminant Analysis (DLDA) algorithms.
Damping Control by Fusion of Reinforcement Learning and Control Lyapunov Functions

The main idea behind the concept, proposed in the paper, is the opportunity to make control systems with increased capabilities by synergetic fusion of the domain-specific knowledge and the methodologies from control theory and artificial intelligence. The particular approach considered combines Control Lyapunov Functions (CLF), a constructive control technique, and Reinforcement Learning (RL) in attempt to optimize a mix of system stability and performance. Two control schemes are proposed and the capabilities of the resulting controllers are illustrated on a control problem involving a thyristor controlled series capacitor (TCSC) for damping oscillations in a four-machine power system.
Hepatitis B vaccination in a high risk MSM population: the need for vaccine education

Editor,—Estimates of the prevalence of hepatitis B virus (HBV) markers among men who have sex with men (MSM) range from 5% to 81%, and the prevalence of HBV surface antigen varies from 1% to 11%. 1,2 Despite a safe and effective vaccine against HBV, sexually active MSM are not vaccinated adequately.2–5 Few empirical data describe the factors associated with HBV vaccination among MSM. We conducted a study to identify correlates of HBV vaccination among MSM that could inform future interventions designed to enhance HBV …
Self‐Insurance and Self‐Protection as Public Goods

Most pure public goods like lighthouses, dams, or national defense provide utility mainly by insuring against hazardous events. Our paper focuses on this insurance character of public goods. As for private actions against hazardous events, one can distinguish between self-insurance (SI) and self-protection (SP) also in the context of public goods. For both cases of SI and SP we analyze efficient public provision levels as well as provision levels resulting from Nash behavior in a private provision game. An interesting aspect of considering public goods as insurance devices is the interaction with market insurance. It turns out that the availability of market insurance reduces the provision level of the public good for both, the public and the private provision, regardless of whether we consider SI or SP. Moreover, we show that Nash behavior has always a larger impact than the availability of market insurance.
Cellz: a simple dynamic game for testing evolutionary algorithms

The game of Cellz has been designed as a test bed for evolutionary algorithms. The game has a minimal set of rules that nonetheless offer the possibility for complex behaviour to emerge. Computationally, the game is cheap to simulate, which leads to rapid runs of evolutionary algorithms. A key feature of the game is the cell division process, which can lead to evolution in situ without reference to any externally defined fitness function. This paper describes the rationale behind the development of Cellz, the rules of the game and the software interfaces for the cell controllers. The randomness in the game initialisation leads to extremely noisy fitness functions, which adds to the challenge of evolving high-performance controllers. Initial results demonstrate that an evolved perceptron-type controller can achieve mediocre performance on the single species game.
KICA for Face Recognition Based on Kernel Generalized Variance and Multiresolution Analysis

There are various outliers which influence the distributions of face samples (signals) and impact the performance of face recognition algorithms. A novel algorithm of kernel independent component analysis for face recognition based on kernel generalized variance and multiresolution analysis (KICA-MKGV) is proposed in this paper. The new algorithm is flexible and robust to a wide variety of signal distributions, and it could extract stable and robust independent features of face samples. According to the experiments on both Harvard face database and FERET face database, the new algorithm could cope with large variation of lighting direction and different illumination intensity very well, and outperform some famous algorithms (PCA, FLD and ICA) in face recognition
Social learning in otters

The use of information provided by others to tackle life's challenges is widespread, but should not be employed indiscriminately if it is to be adaptive. Evidence is accumulating that animals are indeed selective and adopt ‘social learning strategies’. However, studies have generally focused on fish, bird and primate species. Here we extend research on social learning strategies to a taxonomic group that has been neglected until now: otters (subfamily Lutrinae). We collected social association data on captive groups of two gregarious species: smooth-coated otters (Lutrogale perspicillata), known to hunt fish cooperatively in the wild, and Asian short-clawed otters (Aonyx cinereus), which feed individually on prey requiring extractive foraging behaviours. We then presented otter groups with a series of novel foraging tasks, and inferred social transmission of task solutions with network-based diffusion analysis. We show that smooth-coated otters can socially learn how to exploit novel food sources and may adopt a ‘copy when young’ strategy. We found no evidence for social learning in the Asian short-clawed otters. Otters are thus a promising model system for comparative research into social learning strategies, while conservation reintroduction programmes may benefit from facilitating the social transmission of survival skills in these vulnerable species.
Online Bayesian Models for Personal Analytics in Social Media

Latent author attribute prediction in social media provides a novel set of conditions for the construction of supervised classification models. With individual authors as training and test instances, their associated content (“features”) are made available incrementally over time, as they converse over discussion forums. We propose various approaches to handling this dynamic data, from traditional batch training and testing, to incremental bootstrapping, and then active learning via crowdsourcing. Our underlying model relies on an intuitive application of Bayes rule, which should be easy to adopt by the community, thus allowing for a general shift towards online modeling for social media.
Experimental investigation on effects of varying volume fractions of SiC nanoparticle reinforcement on microstructure and mechanical properties in friction-stir-welded dissimilar joints of AA2024-T351 and AA7075-T651

Effects of varying volume fractions of SiC nanoparticle (SiC_NP) reinforcement on microstructure and mechanical properties of dissimilar AA2024-T351 and AA7075-T651 joints by friction stir welding (FSW) have been investigated experimentally. A rectangular section edge groove was prepared at the adjoining surfaces of the two plates with the butt configuration before FSW. Initially, four fractional volumes with 0, 5, 8, and 13% of SiC_NP are reinforced into the grooves of width, 0, 0.2, 0.3, and 0.5 mm and the FSW was performed with the first and second pass to obtain metal matrix nanocomposite (MMNC) at the weld nugget zone (WNZ). The characterization of microstructure specimens was investigated using optical microscopy (OM), scanning electron microscopy (SEM) and X-ray diffraction technique (XRD). The FSW joint specimen produced with 5 vol% fraction of SiC_NP for second pass processing observes a defect-free, homogeneous distribution of SiC_NP with a mean grain size of about 2–3 µm at the WNZ and weld joints higher in tensile strength, 411 MPa, yield strength, 252 MPa, and percentage elongation, 14.3. The result shows that varying volume fractions (5, 8, 13%) of the SiC_NP after the FSW second pass led to significant grain refinement at the WNZ and higher mechanical properties compared with FSW specimens prepared without SiC_NP. Higher hardness of 150 Hv was observed in the WNZ for specimen produced with 13 vol% fraction SiC_NP.
Effect of Solar Spectrum on the Performance of Various Thin-Film PV Module Technologies in Tropical Singapore

The spectral influence on the performance of four different thin-film photovoltaic (PV) modules (single-junction amorphous Si, CdTe, CIGS, and double-junction “micromorph” Si) is studied. Two methods are used to quantify the effective irradiance intensity for the investigated four modules. The first is based on spectral mismatch factors calculated from the measured outdoor spectrum and the spectral responses of the PV modules. The second is based on the measured short-circuit currents of the modules. The effective irradiance ratio (EIR) of a PV module technology, for a given time period, is defined as the ratio between the cumulative effective irradiance intensity received by the module and the cumulative irradiance intensity measured by a c-Si reference cell. We find that the average photon energy of the spectrum in Singapore is higher than that of the AM1.5G reference spectrum, indicating that the spectrum is “blue-rich. ” Compared with the AM1.5G spectrum, this blue-rich spectral irradiance results in an annual EIR of 1.07 and 1.03 for the single-junction a-Si module and the CdTe module, respectively. An EIR larger than 1 indicates energetic irradiance gain. CIGS is not significantly affected by the blue-rich spectrum, while micromorph Si shows an annual EIR of less than 1.
Transitions in a Metastable Neuronal Network

Recent experimentation has found that while newborn rats follow an exponential distribution for wake bout distributions, older rats follow a power law distribution. Understanding possible explanations for this phenomenon requires understanding how transitions occur in metastable systems. Here we review some useful mathematical results and terminology in relation to networks and explore how several different network structures affect the dynamics of this sleep-wake system. We also employ several methods to identify possible transition mechanisms to help uncover biological and mathematical reasons for the change in bout distributions. Studying each mechanism, we relate the most prevalent transition mechanism for a system with a given network architecture to the type of bout distribution observed and correlate power law behavior to a gradual degradation mechanism and exponential behavior to a mechanism involving the firing of well-connected nodes.
Myocyte Enhancer Factor 2 and Microphthalmia-associated Transcription Factor Cooperate with NFATc1 to Transactivate the V-ATPase d2 Promoter during RANKL-induced Osteoclastogenesis*

The V-ATPase d2 protein constitutes an important subunit of the V-ATPase proton pump, which regulates bone homeostasis; however, currently little is known about its transcriptional regulation. Here, in an attempt to understand regulation of the V-ATPase d2 promoter, we identified the presence of NFATc1, microphthalmia-associated transcription factor (MITF)- and myocyte enhancer factor 2 (MEF2)-binding sites within the V-ATPase d2 promoter using complementary bioinformatic analyses, chromatin immunoprecipitation, and electromobility shift assay. Intriguingly, activation of the V-ATPase d2 promoter by NFATc1 was enhanced by either MEF2 or MITF overexpression. By comparison, coexpression of MITF and MEF2 did not further enhance V-ATPase d2 promoter activity above that of expression of MITF alone. Consistent with a role in transcriptional regulation, both NFATc1 and MITF proteins translocated from the cytosol to the nucleus during RANKL-induced osteoclastogenesis, whereas MEF2 persisted in the nucleus of both osteoclasts and their mononuclear precursors. Targeted mutation of the putative NFATc1-, MITF-, or MEF2-binding sites in the V-ATPase d2 promoter impaired its transcriptional activation. Additionally retroviral overexpression of MITF or MEF2 in RAW264.7 cells potentiated RANKL-induced osteoclastogenesis and V-ATPase d2 gene expression. Based on these data, we propose that MEF2 and MITF function cooperatively with NFATc1 to transactivate the V-ATPase d2 promoter during RANKL-induced osteoclastogenesis.
Molecular Dynamics Simulations for Resolving Scaling Laws of Polyethylene Melts

Long-timescale molecular dynamics simulations were performed to estimate the actual physical nature of a united-atom model of polyethylene (PE). Several scaling laws for representative polymer properties are compared to theoretical predictions. Internal structure results indicate a clear departure from theoretical predictions that assume ideal chain statics. Chain motion deviates from predictions that assume ideal motion of short chains. With regard to linear viscoelasticity, the presence or absence of entanglements strongly affects the duration of the theoretical behavior. Overall, the results indicate that Gaussian statics and dynamics are not necessarily established for real atomistic models of PE. Moreover, the actual physical nature should be carefully considered when using atomistic models for applications that expect typical polymer behaviors.
Database Management for Interactive Display of Large Architectural Models

This paper describes algorithms for predictive database management used in The UC Berkeley Building Walkthrough System The algorithms fore cast a range of possible observer viewpoints during upcoming frames and use precomputed cell visibil ity information to determine a set of objects likely to be visible to the observer in the near future For each of these objects detail elision techniques de termine which levels of detail must be stored in a memory resident cache Cache management algo rithms determine which objects to load into mem ory from disk and which to replace when the cache is full Using these algorithms the system is able to maintain real time frame rates during interactive visualization of large building models with furniture and radiosity illumination
To model or not to model: Controlling Pac-Man ghosts without incorporating global knowledge

The creation of interesting opponents for human players in computer games is an interesting and challenging task. In contrast to up-to-date computer games, e.g. real time strategy games, learning of non-player-character strategies for older games seems to be easier and not that time-consuming. This way, older games, like the famous arcade game Pac-Man, serve as a test bed for the creation of strategies that are fun to play against. The paper at hand uses computational intelligence methods to accomplish this challenge, namely evolutionary algorithms (EA) and artificial neural networks (ANN). The latter are trained on a model of the game whereas the EA learn good behavior by playing. The performance of these two approaches is compared on the original Pac-Man level as well as on other maps with different properties to test the ability of generalizing the learned strategies.
(Pro)renin Receptor Mediates Both Angiotensin II-Dependent and -Independent Oxidative Stress in Neuronal Cells

The binding of renin or prorenin to the (pro)renin receptor (PRR) promotes angiotensin (Ang) II formation and mediates Ang II-independent signaling pathways. In the central nervous system (CNS), Ang II regulates blood pressure via inducing oxidative stress; however, the role of PRR-mediated Ang II-independent signaling pathways in oxidative stress in the CNS remains undefined. To address this question, Neuro-2A cells were infected with control virus or an adeno-associated virus encoding the human PRR. Human PRR over-expression alone increased ROS levels, NADPH oxidase activity, as well as NADPH oxidase (NOX) isoforms 2 and 4 mRNA expression levels and these effects were not blocked by losartan. Moreover, the increase in NOX 2 and NOX 4 mRNA levels, NADPH oxidase activity, and ROS levels induced by PRR over-expression was prevented by mitogen activated protein kinase/extracellular signal-regulated kinase 1 and 2 (MAPK/ERK1/2) inhibition, and phosphoinositide 3 kinase/Akt (IP3/Akt) inhibition, indicating that PRR regulates NOX activity and ROS formation in neuro-2A cells through Ang II-independent ERK1/2 and IP3/Akt activation. Interestingly, at a concentration of 2 nM or higher, prorenin promoted Ang II formation, and thus further increased the ROS levels in cultured Neuro-2A cells via PRR. In conclusion, human PRR over-expression induced ROS production through both angiotensin II-dependent and -independent mechanisms. We showed that PRR-mediated angiotensin II-independent ROS formation is associated with activation of the MAPK/ERK1/2 and PI3/Akt signaling pathways and up-regulation of mRNA level of NOX 2 and NOX4 isoforms in neuronal cells.