Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning

This work explores the combination of free cloud computing, free open-source software, and deep learning methods to analyze a real, large-scale problem: the automatic country-wide identification and classification of surface mines and mining tailings dams in Brazil. Locations of officially registered mines and dams were obtained from the Brazilian government open data resource. Multispectral Sentinel-2 satellite imagery, obtained and processed at the Google Earth Engine platform, was used to train and test deep neural networks using the TensorFlow 2 application programming interface (API) and Google Colaboratory (Colab) platform. Fully convolutional neural networks were used in an innovative way to search for unregistered ore mines and tailing dams in large areas of the Brazilian territory. The efficacy of the approach is demonstrated by the discovery of 263 mines that do not have an official mining concession. This exploratory work highlights the potential of a set of new technologies, freely available, for the construction of low cost data science tools that have high social impact. At the same time, it discusses and seeks to suggest practical solutions for the complex and serious problem of illegal mining and the proliferation of tailings dams, which pose high risks to the population and the environment, especially in developing countries.
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Conducting text retrieval in a dense learned representation space has many intriguing advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires combination with sparse retrieval. In this paper, we identify that the main bottleneck is in the training mechanisms, where the negative instances used in training are not representative of the irrelevant documents in testing. This paper presents Approximate nearest neighbor Negative Contrastive Estimation (ANCE), a training mechanism that constructs negatives from an Approximate Nearest Neighbor (ANN) index of the corpus, which is parallelly updated with the learning process to select more realistic negative training instances. This fundamentally resolves the discrepancy between the data distribution used in the training and testing of DR. In our experiments, ANCE boosts the BERT-Siamese DR model to outperform all competitive dense and sparse retrieval baselines. It nearly matches the accuracy of sparse-retrieval-and-BERT-reranking using dot-product in the ANCE-learned representation space and provides almost 100x speed-up.
In-Distribution Interpretability for Challenging Modalities

It is widely recognized that the predictions of deep neural networks are difficult to parse relative to simpler approaches. However, the development of methods to investigate the mode of operation of such models has advanced rapidly in the past few years. Recent work introduced an intuitive framework which utilizes generative models to improve on the meaningfulness of such explanations. In this work, we display the flexibility of this method to interpret diverse and challenging modalities: music and physical simulations of urban environments.
PDE limits of stochastic SIS epidemics on networks

Stochastic epidemic models on networks are inherently high-dimensional and the resulting exact models are intractable numerically even for modest network sizes. Mean-field models provide an alternative but can only capture average quantities, thus offering little or no information about variability in the outcome of the exact process. In this article, we conjecture and numerically demonstrate that it is possible to construct partial differential equation (PDE)-limits of the exact stochastic susceptible-infected-susceptible epidemics on Regular, Erdős–Rényi, Barabási–Albert networks and lattices. To do this, we first approximate the exact stochastic process at population level by a Birth-and-Death process (BD) (with a state space of $O(N)$ rather than $O(2^N)$) whose coefficients are determined numerically from Gillespie simulations of the exact epidemic on explicit networks. We numerically demonstrate that the coefficients of the resulting BD process are density-dependent, a crucial condition for the existence of a PDE limit. Extensive numerical tests for Regular, Erdős–Rényi, Barabási–Albert networks and lattices show excellent agreement between the outcome of simulations and the numerical solution of the Fokker–Planck equations. Apart from a significant reduction in dimensionality, the PDE also provides the means to derive the epidemic outbreak threshold linking network and disease dynamics parameters, albeit in an implicit way. Perhaps more importantly, it enables the formulation and numerical evaluation of likelihoods for epidemic and network inference as illustrated in a fully worked out example.
The α1 subunit of the sodium pump could represent a novel target to combat non‐small cell lung cancers

With an overall 5 year survival rate as low as 15% for non‐small cell lung cancer (NSCLC), even with surgical intervention and the use of newer molecules in adjuvant chemotherapy, there is an urgent need for new biological targets and associated novel anti‐cancer agents. The present study was undertaken to evaluate the potential of the Na+/K+‐ATPase α1 subunit as a novel target in NSCLC and revealed that α1 expression is markedly higher in a significant proportion of NSCLC clinical samples compared to normal lung tissue. Furthermore, reduction in α1 expression in A549 NSCLC cells by anti‐α1 siRNA resulted in markedly impaired proliferation and migration of these cancer cells. Finally, of three cardenolides investigated, UNBS1450, which is known to bind to Na+/K+‐ATPase and displays potent anti‐tumour activity in vivo in experimental models of human NSCLCs, is the most potent inhibitor of Na+/K+‐ATPase isozymes (α1β1, α2β1 and α3β1), most strikingly of α1β1. This was reflected in the compound's more potent anti‐proliferative activity in all NSCLC cell lines evaluated (A549, Cal‐12T, NCI‐H727 and A427); the first three of which over‐express α1. The marked impairment in A549 NSCLC cell proliferation and migration, and resulting similar morphology following anti‐α1 siRNA or UNBS1450 treatment, was associated with features of abnormal cytokinesis, mediated in the case of UNBS1450 by disorganization of the actin cytoskeleton. Collectively these data strongly suggest that targeting the Na+/K+‐ATPase α1 using specific cardenolides could represent a novel means to combat certain NSCLCs. Copyright © 2007 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Bayesian Low Rank Tensor Ring Model for Image Completion

Low rank tensor ring model is powerful for image completion which recovers missing entries in data acquisition and transformation. The recently proposed tensor ring (TR) based completion algorithms generally solve the low rank optimization problem by alternating least squares method with predefined ranks, which may easily lead to overfitting when the unknown ranks are set too large and only a few measurements are available. In this paper, we present a Bayesian low rank tensor ring model for image completion by automatically learning the low rank structure of data. A multiplicative interaction model is developed for the low-rank tensor ring decomposition, where core factors are enforced to be sparse by assuming their entries obey Student-T distribution. Compared with most of the existing methods, the proposed one is free of parameter-tuning, and the TR ranks can be obtained by Bayesian inference. Numerical Experiments, including synthetic data, color images with different sizes and YaleFace dataset B with respect to one pose, show that the proposed approach outperforms state-of-the-art ones, especially in terms of recovery accuracy.
Assessing ecosystem recovery in transplanted Posidonia australis at Southern Flats, Cockburn Sound

Following on from the large scale loss of seagrass in Cockburn Sound and extensive transplanting of Posidonia australis which had taken place on Southern Flats, assessment of the recovery of the seagrass benthic infauna ecosystems was undertaken. Samples from the outer, middle and centre edge zones of four different density transplant plots (1 m, 0.5 m, 0.25 m and 0.125 m spacing) located within a larger transplantation meadow were compared against two natural meadows and a bare sand site. Four years after transplantation the 0.25 and 0.125 m Plots had shoot densities comparable to those of the natural seagrass sites with a two-way ANOVA revealing significant effects of site and edge zone on the seagrass shoot density. Total infauna abundance and infauna assemblages within the 0.25 and 0.125 m Plots had reached equivalent level to the natural meadows but not at the 1 and 0.5 m Plots. A two-way ANOVA showed a significant difference in the total infauna abundance between the different sites but no significant edge effect was detected. Eusiridae, Solecurtidae, Diogenidae, Columbellidae, Fissurellidae, Oweniidae and Ischnochitonidae were found to occur in the two natural meadows and in the 0.25 and 0.125 m Plots and may be climax or K-species indicating the recovery of the transplanted seagrass to natural levels. The transplanted seagrass was also found to support small numbers of pipefish, seahorses and a sea lion. From this study it can be seen that the shoot densities and infauna abundances and assemblages of the 0.25 and 0.125 m Plots have reached levels comparable the nearby natural meadows and that those of the 1 and 0.5 m Plots are likely to reach comparable level another in one to two years.
The distribution of denitrifying bacteria in soils monitored by DNA-probing

DNA probes of dissimilatory NO2−- and N2O-reductases have been used to screen for the distribution of denitrifying bacteria in soils. In control experiments with known organisms, denitrifiers gave positive DNA-DNA hybridization signals in the dot-blot experiments whereas non-denitrifiers did not hybridize in almost all cases. Bacteria from soil of our institute garden were isolated, grown up and assayed for denitrification activity and for DNA-hybridizations with both gene probes. A correlation of about 75% was obtained between activities and signals. The remainder of the isolates gave a weak signal in the dot blots and only half of them expressed denitrification activities in the cultures. The confidence of about 75% was good enough to assay for the distribution of denitrifying bacteria in five different soil-types of the Dusseldorf area. In all cases, the percentage of bacteria which gave no hybridization signal was high in the plant-free, bulk soil, whereas bacteria with strong or very strong signals favourably associated with the roots of plants isolated from the different soils. The result that denitrifying bacteria predominantly occur at the surface of roots was obtained when the samples were taken both in June and November. The probes for either NO2−- or N2O-reductase gave essentially the same results. For comparison, a gene probe for nitrogenase was included in this investigation. N2-fixing bacteria showed a tendency to associate with the roots of plants in some but not in all soils. The overall number of bacteria was much higher at the roots of the plants than in the bulk soil in any of the samples assayed in the present investigation.
IIE-NLP-NUT at SemEval-2020 Task 4: Guiding PLM with Prompt Template Reconstruction Strategy for ComVE

This paper introduces our systems for the first two subtasks of SemEval Task4: Commonsense Validation and Explanation. To clarify the intention for judgment and inject contrastive information for selection, we propose the input reconstruction strategy with prompt templates. Specifically, we formalize the subtasks into the multiple-choice question answering format and construct the input with the prompt templates, then, the final prediction of question answering is considered as the result of subtasks. Experimental results show that our approaches achieve significant performance compared with the baseline systems. Our approaches secure the third rank on both official test sets of the first two subtasks with an accuracy of 96.4 and an accuracy of 94.3 respectively.
Boltzmann machine learning with a variational quantum algorithm

Boltzmann machine is a powerful tool for modeling probability distributions that govern the training data. A thermal equilibrium state is typically used for Boltzmann machine learning to obtain a suitable probability distribution. The Boltzmann machine learning consists of calculating the gradient of the loss function given in terms of the thermal average, which is the most time consuming procedure. Here, we propose a method to implement the Boltzmann machine learning by using Noisy Intermediate-Scale Quantum (NISQ) devices. We prepare an initial pure state that contains all possible computational basis states with the same amplitude, and apply a variational imaginary time simulation. Readout of the state after the evolution in the computational basis approximates the probability distribution of the thermal equilibrium state that is used for the Boltzmann machine learning. We actually perform the numerical simulations of our scheme and confirm that the Boltzmann machine learning works well by our scheme.
Second Order Accurate Hierarchical Approximate Factorization of Sparse SPD Matrices

We describe a second-order accurate approach to sparsifying the off-diagonal blocks in the hierarchical approximate factorizations of sparse symmetric positive definite matrices. The norm of the error made by the new approach depends quadratically, not linearly, on the error in the low-rank approximation of the given block. The analysis of the resulting two-level preconditioner shows that the preconditioner is second-order accurate as well. We incorporate the new approach into the recent Sparsified Nested Dissection algorithm [SIAM J. Matrix Anal. Appl. , 41 (2020), pp. 715-746], and test it on a wide range of problems. The new approach halves the number of Conjugate Gradient iterations needed for convergence, with almost the same factorization complexity, improving the total runtimes of the algorithm. Our approach can be incorporated into other rank-structured methods for solving sparse linear systems.
Keck Cosmic Web Imager (KCWI) spectra of globular clusters and ultracompact dwarfs in the halo of M87

Using the Keck Cosmic Web Imager, we obtain spectra of several globular clusters (GCs), ultracompact dwarfs (UCDs), and the inner halo starlight of M87, at a similar projected galactocentric radius of ∼5 kpc. This enables us, for the first time, to apply the same stellar population analysis to the GCs, UCDs, and starlight consistently to derive ages, metallicities, and alpha-element abundances in M87. We find evidence for a dual stellar population in the M87 halo light, i.e. an ∼80 per cent component by mass that is old and metal-rich and a ∼20 per cent component that is old but metal-poor. Two red GCs share similar stellar populations to the halo light suggesting they may have formed contemporaneously with the dominant halo component. Three UCDs, and one blue GC, have similar stellar populations, with younger mean ages, lower metallicities, and near solar alpha-element abundances. Combined with literature data, our findings are consistent with the scenario that UCDs are the remnant nucleus of a stripped galaxy. We further investigate the discrepancy in the literature for M87’s kinematics at large radii, favouring a declining velocity dispersion profile. This work has highlighted the need for more self-consistent studies of galaxy haloes.
SJSU ScholarWorks

Micro-expressions are short-lived, rapid facial expressions that are exhibited by individuals when they are in high stakes situations. Studying these micro-expressions is important as these cannot be modified by an individual and hence offer us a peek into what the individual is actually feeling and thinking as opposed to what he/she is trying to portray. The spotting and recognition of micro-expressions has applications in the fields of criminal investigation, psychotherapy, education etc. However due to micro-expressions’ short-lived and rapid nature; spotting, recognizing and classifying them is a major challenge. In this paper, we design a hybrid approach for spotting and recognizing micro-expressions by utilizing motion magnification using Eulerian Video Magnification and Spatiotemporal Texture Map (STTM). The validation of this approach was done on the spontaneous micro-expression dataset, CASMEII in comparison with the baseline. This approach achieved an accuracy of 80% viz. an increase by 5% as compared to the existing baseline by utilizing 10-fold cross validation using Support Vector Machines (SVM) with a linear kernel.
STUDY OF NORMAL DEVELOPMENT AND EXTERNAL MORPHOLOGY OF TADPOLES OF MICROHYLA ORNATA AND UPERODON GLOBULOSUS OF THE FAMILY MICROHYLIDAE (AMPHIBIA: ANURA) FROM NORTH EAST INDIA

Normal developmentaltable and external morphology of stage38 tadpolesofUperodonglobulosusandMicrohyla ornata has been described . The development rate of U.globulosushas been found to be slowerin comparison toM. ornatain laboratory condition. Larva hatches at stage 20 in both M.ornataandU.globulosus.Clutch sizeinU.globulosusis larger (750-900 eggs) thaninM. ornata(300-510 eggs), but hatching success of larvae are less inU.globulosus(66.6-80%)in comparison toM.ornata(91.1-93.3%). The tadpole of M.ornataistransparentdorsally withoval shaped body andthin tailmusculature. On the other hand tadpole of U.globulosushas dark pigmentation with roughly oval body andmoderate tail musculature. Atstage 38Pinealocellusis visibleinM.ornatawhereasit isabsentinU.globulosus. Spiracle is median in both the species . Oral disc isdeveloped inU.globulosusthaninM. ornata. Toe pads arewell developed in metamorphosingstages in both the species at stage 40 where astoe pads are absent in the adult of U.globulosus.
No whirlwind romance: typhoons, temperature and the failure of reproduction in Caulacanthus okamurae (Gigartinales, Rhodophyta)

The red alga Caulacanthus okamurae Yamada occurs commonly on the coasts of South Korea, but reproductive plants have rarely been found in the field. Seasonality of field populations was examined and the temperature responses of growth and reproduction were determined in laboratory cultures. In the field, monthly average temperatures of surface seawater ranged from 12·7°C±0·73 (SD) to 21°C±1·19. Monthly mean biomass in 25×25 cm quadrats (n=3) ranged from 11·2±9·6 g m−2 (SD) to 148·8±19·2 g m−2 in wet weight with minimal biomass in February 1995 and maximal values in August. In culture, the growth of vegetative plants and germination of tetraspores of C. okamurae occurred at temperatures from 13 to 27°C. Tetrasporangia, gametangia and cystocarps were formed at 19°C and above, but not at 13 or 16°C, indicating that reproduction is directly affected by seawater temperature. On the basis of these data, seawater temperature was above the critical temperature for reproduction from August to October (20–21°C) yet only three plants with tetrasporangial branches were found in the field. In September the biomass of C. okamurae declined sharply following severe storm damage. Thus, the absence of reproductive organs in field populations of C. okamurae may occur because they inhabit a seasonally stressful habitat, in which typhoon damage removes branches before the water temperature becomes favourable for reproduction.
Pest categorisation of potato virus X (non‐EU isolates)

Abstract Following a request from the EU Commission, the Panel on Plant Health has addressed the pest categorisation of non‐EU isolates of potato virus X (PVX). The information currently available on geographical distribution, biology, epidemiology, potential entry pathways, potential additional impact and availability of control measures of non‐EU isolates of PVX has been evaluated with regard to the criteria to qualify as a potential Union quarantine pest. Because non‐EU isolates of PVX are absent from the EU, they do not meet one of the requirements to be regulated as a regulated non‐quarantine pest (RNQP) (presence in the EU); as a consequence, the Panel decided not to evaluate the other RNQP criteria for these isolates. On the basis of their ability to overcome potato resistance genes, PVX isolates can be divided into several pathotypes. PVX isolates that are not able to overcome resistance genes and PVX isolates that are able to overcome the Nb and/or Nx resistance genes are already present in the EU. Isolates able to overcome the Rx resistance gene have only been reported from South America. These Rx breaking isolates could potentially have an additional impact over the current situation in the EU and therefore meet all the criteria to qualify as a potential Union quarantine pest. All other non‐EU isolates, should they be introduced, are not expected to have additional impact and therefore do not meet this criterion to qualify as a potential Union quarantine pest.
Pyrethrum Flowers: A Quantitative Study Of Their Development

Summary. 1An account is given of the examination of the flowers of pyrethrum plants (C. cinerariafoolium) grown upon a bed in Harpenden. The plants were divided into blocks and randomised, the flowers being harvested from a dozen plants each week over a period of 81/2 weeks, the flower heads ranged from the small bud stage in the first week to the overblown stage in the last week. The categories into which the flowers were divided to indicate maturity are defined and illustrated. 2The yield in numbers and weight of heads per plant, the diameters of the receptacles and the content of pyrethrin I and II were determined. There was a considerable amount of variation in all these factors in the flowers from different plants. 3A statistical analysis showed in this experiment: (a) That there was no significant variation in the numbers of the flowers with time, but that position of the plant in the bed had a significant effect. (b) That the time of harvesting had a significant effect upon the content of the pyrethrins whether taken separately or together and whether expressed in percentages, parts per flower head or parts per plant. The effect due to- position was only definitely significant in the case of pyrethrin I when expressed in parts per flower head. (c) That there was on the different dates a significant correlation between the contents of pyrethrin I and II expressed in parts per flower head or plant. (d) That there was, for the blocks of material examined, a significant correlation between the contents of pyrethrin I and II, whether expressed in percentages, parts-per head or parts per plant, but that owing to the heterogeneity of the material the correlation was only significant for individual plants when the pyrethrias were expressed in parts per plant. 4The data in this experiment indicate that for the material examined, there is a quantitative development of the active principles in the flower heads from the small bud stage up to the time of maturity of the flowers, which more than keeps pace on the whole with the increase in weight of the flowers. Thus the content of pyrethrins, both relatively and absolutely, rises to a maximum at the maturity of the flowers. The mean percentage content of pyrethrins fell after pollination and the fading of the flowers; this corresponds with the rapid increase in weight of the heads on the formation of seed. There would thus appear to be a loss, which might be serious, both in percentage content of active principles and in yield of flowers if harvested before being fully open. There seems to be no useful purpose served in leaving the flowers to the overblown condition. I wish to express my great indebtedness to Dr R. A. Fisher and Dr J. Wishart for carrying out the greater part of the statistica.1 analyses incorporated in this paper and for much helpful advice. I am also indebted to Mr J. T. Martin for checking many of the analyses by an alternative method.