Miracle-dz/UniFAR-FTUs huggingface dataset:
Using dogs to find cats: detection dogs as a survey method for wide-ranging cheetah

Rapid global large carnivore declines make evaluations of remaining populations critical. Yet landscape-scale evaluations of presence, abundance and distribution are difficult, as many species are wide-ranging, occur only at low densities and are elusive. Insufficient information-gathering tools for many large carnivore species compounds these challenges. Specially trained detection dogs have demonstrated effectiveness for carnivore surveys, but are untested on extremely sparse, wide-ranging species, such as cheetah Acinonyx jubatus. In this study, we conducted the first rigorous cheetah survey using detection dogs in a key transboundary area in the remote Liuwa–Mussuma Transfrontier Conservation Area (TFCA) in Western Zambia. We proposed to (1) evaluate the effectiveness of detection dog versus spoor surveys in detecting cheetah presence; (2) extract and analyze DNA from scat samples to estimate minimum population size and genetic effective population size; (3) determine the extent of cheetah occurrence in the unprotected transboundary corridor. Two detection dog teams surveyed 2432 km2 containing 74 randomly located transects in the transfrontier area. Twenty-seven cheetah scats were detected and confirmed by genetic analysis, while no cheetah spoor was detected, clearly demonstrating the superiority of detection dogs in detecting cheetah presence. Combining scat samples with opportunistically collected samples, we estimated 17–19 cheetahs, an effective population size of 8–14 and a density of 5.9–6.6 per 1000 km2. Cheetah utilized key transfrontier areas outside of the national park; however, because utilization appears low, improved connectivity and protection for these areas are critical. Approximately one third of Africa's estimated cheetah resides in protected areas, with 87% in transboundary areas. Our study demonstrates the efficacy of detection dog survey methods in providing information on cheetah across large landscapes. It will have particular value in areas where other survey means may be impossible, such as TFCAs, where size, remoteness and lack of accessibility often make traditional survey methods difficult or cost prohibitive.
The objects location from images binarized by means of self-learning neural network

The present work represents a first approach for the realization of a methodology for objects location and recognition. The choice objects was the starting point of the study; it has been decided to consider nuts and bolts of various dimensions. Then in order to eliminate the noise added to the images a neural network was designed. Once the desired pictures were obtained, an algorithm, based on the theory of the fuzzy sets, was applied, for detecting the position of each objects. The instruments used were low cost: a digital camera, one stand, equipped with four lamps assuring, for each acquisition, a diffused lighting system, one personal computer.
A comprehensive study on protection, control and communication techniques: a key concept for microgrid intelligent operation

Microgrid is an integrated network of renewable and non renewable resources to supply the green power to a small range of community. An effective communication technology is necessary to be implemented among the power generations, storages and loads of microgrid in order to manage the load sharing, shedding and protection issues. This paper provides the study on architecture, characteristics, load managements, protection schemes, communication techniques and research challenges of microgrid.
Using Growth Analysis to Interpret Competition between Cynodon dactylon (L.) Beauv. (Bermudagrass) and Newly Planted Olea europea L. (Olive Seedlings)

A greenhouse experiment was conducted to determine the effects of bermudagrass [Cynodon dactylon (L.) Beauv. ] on the growth of newly planted olive trees (Olea europea L. var. Chemlali) over a one-year period. C. dactylon and olive seedlings were grown individually and in competition with each other. Soil water content and growth period were evaluated weekly and nutrient content in the leaves was analyzed at the end of the experiment. Detailed growth analysis together with information on seedling growth was used to interpret competition between C. dactylon and olive seedlings. Competition reduced the growth of olive seedlings for different reasons. The decrease in the leaf area ratio was associated with an increase in the root/shoot ratio implying that olive seedlings were limited by competition for below-ground resources. Olive tree seedling leaf area was the most sensitive growth parameter measured in response to bermudagrass. Leaf area was reduced by 79% and specific leaf weight, a relative measure of leaf thickness, was reduced by 34.4%. Moreover, bermudagrass reduced olive tree seedling dry weight by 54%. Olive tree seedling trunk diameter relative growth rate and shoot length were reduced by 55 and 68%, respectively. In addition to visual symptoms of nutrient status, olive tree seedling nutrient status was reduced by bermudagrass. The negative effects of bermudagrass increased over time. This reduction in olive tree seedling growth cannot be explained entirely by competition for essential nutrients and water. However, a competitive interaction through allelopathy might be induced by C. dactylon.
The orbital ephemeris of HU Aquarii observed with OPTIMA. Are there two giant planets in orbit

HU Aqr is an eclipsing CV system hosting a highly magnetic white dwarf orbited by a M4V dwarf with a period of about 125 min. Its orbital ephemeris has been followed with precision since 1993. Regular OPTIMA observations of eclipses of HU Aqr since 1999 can be used to follow the secular changes of the binary orbit. We report new modeling of the orbital ephemeris including recent 2008/2009 observations and find that a model including a linear and quadratic term as well as two sinusoidal oscillatory terms provides the best fit to the observed eclipses. We propose that the sinusoidal variations can be explained by the presence of two giant planets in orbit around HU Aqr.
An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO) algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR).
On the Competitive E ff ect of Informative Advertising

This paper challenges the robustness of the pro-competitive effect of informative advertising. In their seminal work Grossman and Shapiro (1984) find that informative advertising results in lower prices, and that firms may benefit from advertising restrictions. A crucial assumption in their model is that demand in the monopoly segment is perfectly price inelastic. Replicating their model in a Hotelling duopoly version, we show that results are in fact reversed if we allow for price elastic monopoly demand. The reason is that the marginal consumer informed about only one product is more price responsive than the marginal consumer informed about both products. We then use general demand (and advertising cost) functions and derive exact conditions for when informative advertising is pro-competitive.
Dispersion Properties of TM and TE Modes of Gyrotropic Magnetophotonic Crystals

This chapter discusses the propagation of TM and TE waves in the one-dimensional gyrotropic magnetophotonic crystals with ferrite and plasma-like layers. Elements of the transfer matrix are calculated in closed analytical form on the base of electrodynamic problem rigorous solution for arbitrary location of the gyrotropic elements on the structure period. Dispersion equation of the layered periodic structure with gyrotropic ele- ments is obtained. Dispersion properties of the structure for TE and TM modes are analyzed for different configurations of magnetophotonic crystals (ferrite and plasma- like layers). Existence areas of transmission bands for surface and bulk waves are obtained. The effect of problem parameters on the dispersion properties of magne- tophotonic crystals for TM and TE modes is investigated. Regimes of complete transmission of wave through limited magnetophotonic crystal are analyzed for bulk and surface waves.
ANAEROBIC CO-DIGESTION OF AQUEOUS LIQUID FROM BIOSOLIDS PYROLYSIS by Seyedehfatemeh Seyedi

ANAEROBIC CO-DIGESTION OF AQUEOUS LIQUID FROM BIOSOLIDS PYROLYSIS Seyedehfatemeh Seyedi Marquette University, 2018 Pyrolysis is a process to treat biosolids and recover energy. During pyrolysis, conversion of organic matter to energy-rich products yields biochar, py-gas, and pyrolysis liquids (aqueous phase and non-aqueous bio-oil). The aqueous pyrolysis liquid (APL), is a highCOD liquid with no apparent use that contains polycyclic aromatic hydrocarbons and nitrogen-containing compounds. One potential beneficial use of APL is as a co-digestate to produce more biogas for renewable energy from anaerobic digesters at municipal water resource recovery facilities. Some of the organics in APL may be converted to biomethane via anaerobic digestion under proper conditions. However, some APL organics are known to inhibit methane-producing microbes. Biosolids APL can also contain high concentrations of NH3-N that inhibit methane production. In this study, sustainable, unacclimated anaerobic digester organic loading rates for APL from biosolids pyrolysis were determined using anaerobic toxicity assays (ATA). APL loading rates higher than 0.5 gCOD/L for non-catalyzed APL and 0.10 g COD/L for catalyzed APL were not sustainable due to toxicity. By means of pretreatment by NH3-N air stripping, the potential toxicity exerted from NH3-N was decreased considerably (>80%). NH3-N was not the main inhibitory constituent and other organic constituents in APL caused considerable inhibition of methane production. In subsequent testing, continuous co-digestion of APL and synthetic wastewater primary sludge was performed while digester function and microbial community composition changes were evaluated. During quasi steady state operation, digesters that received catalyzed APL exhibited greater inhibition of methane production than digesters fed non-catalyzed APL. However, NH3-N stripping in non-catalyzed APL increased methane production rate; additional methane production was observed when non-catalyzed aerated APL was co-digested (1.5 ± 1.7 mL/day extra methane). Shifts in the Archaeal community composition in inhibited digesters (received catalyzed APL) versus uninhibited digesters (control digesters and digesters received non-catalyzed APL) was observed. The archaeal genus Methanosaeta dominated in uninhibited digesters, whereas in inhibited digesters hydrogenotrophic Methanobrevibacter was dominant and growth of acetate-consuming Archaea (i.e., Methanosaeta) was inhibited. Inhibited digesters had distinctly different Bacterial community composition from those in uninhibited digesters and Clostridium was the dominant Bacterial genus in all digesters. Results suggested that the microbes started to acclimate to the catalyzed APL; however, using an already acclimated biomass may be more efficient. A future study using acclimated biomass by bioaugmentation could be used to prove this hypothesis.
Patched-1 and smoothened, a hedgehog receptor and signal transducer are highly expressed in diffuse large B-cell lymphoma

Introduction: The Hedgehog (Hh) signalling pathway is a developmental signalling pathway involved in normal mammalian developmental and homeostasis of adult renewable tissues. In most adult tissues, this pathway remains silent and previous studies have shown that constitutive activation of Hedgehog signalling pathway leads to various types of malignancies including medulloblastomas, basal cell carcinoma, gastrointestinal, breast and prostate cancer. The purpose of this study was to investigate the immunohistochemical expression of Hedgehog pathway proteins in Diffuse Large B-cell Lymphoma and determine their association with overall survival (OS). Methods: Positive control using normal tonsils were included in each batch of immunohistochemical staining procedure. Results: PTCH1 proteins were highly expressed in DLBCL and showed strong staining intensity in 107 (100%) cases and SMO proteins were expressed in 105 (98.1%) cases. PTCH1 proteins were localised in the nucleus of tumour cells, whereas SMO proteins were mainly localised in the cytoplasm of tumour cells. Positive expression of PTCH1 and SMO proteins and overall survival of DLBCL patients were correlated with age, gender, race and tumour location. There was no significant correlation between the expression of these two proteins with any of the parameters. PTCH1 expression showed significant association with SMO expression (P=0.03). Conclusions: Our findings suggest that high expression of both PTCH1 and SMO may be important in the pathogenesis of DLBCL. However, additional mechanisms that may contribute to the activation of HH signalling in DLBCL needs to be further explored.
Scene text detection based on probability map and hierarchical model

Scene text detection is an important step for the text-based information extraction system. This problem is challenging due to the var- iations of size, unknown colors, and background complexity. We present a novel algorithm to robustly detect text in scene images. To segment text candidate connected components (CC) from images, a text probability map consisting of the text position and scale information is estimated by a text region detector. To filter out the non-text CCs, a hierarchical model consisting of two classifiers in cascade is utilized. The first stage of the model estimates text probabilities with unary component features. The second stage classifier is trained with both probability features and similarity features. Since the proposed method is learning-based, there are very few manual parameters required. Experimental results on the public benchmark ICDAR dataset show that our algorithm outperforms other state-of-the-art methods. © 2012 Society of Photo-Optical Instrumentation Engi-
Structure, Photochromism and Liquid Crystal Properties of 1-Alkyl-2-(Arylazo)Imidazoles (Raai-CnH2n+1, n (Even) = 10 - 22)

Photochromism is the reversible structural change of the molecules upon light irradiation having different spectral pattern before and after irradiation. Liquid crystal (LC) is a long-range orientational order of the molecules in between solid and isotropic liquid phases which share the properties of the crystal and liquid phases. 1-Alkyl-2-(ary-lazo)imidazoles, (Raai-CnH2n+1, R = H, Me and n = 10, 12, 14, 16, 18, 20, 22) exhibits photochromism and two of them (Haai-C18H37 and Haai-C22H45) show Liquid crystal (LC) properties. One of these compounds, Meaai-C16H33 is structurally characterized by single crystal X-ray diffraction study. The compounds upon irradiation with UV light show E-to-Z isomerisation. Quantum yields (φE→Z) of E-to-Z isomerisation vary with the molar mass of the compounds. The reverse transformation, Z-to-E, is recorded in thermal condition. The activation energy (Ea) of isomerisation is determined by the controlled temperature reaction. Liquid crystal property of the molecules is examined by polarizing optical microscopy (POM) and DSC. The carbon chain length n = 18 shows nematic (N)-isotropic (I) phase transition and an unknown Smectic (Sm) phase is observed with n = 22 on heating cycle.
Better Estimates from Binned Income Data: Interpolated CDFs and Mean-Matching

Researchers often estimate income statistics from summaries that report the number of incomes in bins such as $0 to 10,000, $10,001 to 20,000, …, $200,000+. Some analysts assign incomes to bin midpoints, but this treats income as discrete. Other analysts fit a continuous parametric distribution, but the distribution may not fit well. We fit nonparametric continuous distributions that reproduce the bin counts perfectly by interpolating the cumulative distribution function (CDF). We also show how both midpoints and interpolated CDFs can be constrained to reproduce the mean of income when it is known. We evaluate the methods in estimating the Gini coefficients of all 3,221 U.S. counties. Fitting parametric distributions is very slow. Fitting interpolated CDFs is much faster and slightly more accurate. Both interpolated CDFs and midpoints give dramatically better estimates if constrained to match a known mean. We have implemented interpolated CDFs in the “binsmooth” package for R. We have implemented the midpoint method in the “rpme” command for Stata. Both implementations can be constrained to match a known mean.
CLASSIFICATION AND CLUSTERING OF WEB LOG DATA TO ANALYZE USER NAVIGATION PATTERNS

The information explosion in World Wide Web has increased the interest in Web usage mining techniques in both commercial and academic areas. Study of interested web users; provide valuable information for web designers to quickly respond to their individual needs and for the efficient organization of the website. Among the several approaches, like, Association rule mining, classification, clustering, to extract knowledge from users navigation data, this paper uses clustering and classification of log data to discover knowledge from web log files. The proposed algorithm uses Expectation Maximization (EM) clustering along with Maximum Likelihood classification for knowledge discovery from users navigation patterns. Experiments have been carried out in order to validate the proposed approach and evaluate the proposed algorithm.
A dynamic analysis of educational progression: Comparing children of immigrants and native Danes

This paper uses a parsimonious version of Cameron and Heckman’s (2001) model of educational progression to determine at what stages of their educational careers children of immigrants fall behind their native Danish peers and the magnitude of intergenerational transmission. Two barriers are identified: (1) high dropout rates, particularly from vocational upper secondary educations; and (2) children of Turkish origin have a low entry rate into upper secondary educations. Simulations show that weak socio-economic backgrounds explain the low entry rate but not the high dropout rates. The high dropout rates are thus due to behavioral differences and/or factors not controlled for.
Centennial-scale climate variability during the past 2000 years on the central Tibetan Plateau

It is currently suggested that climate change on the northeastern Tibetan Plateau (TP) was influenced alternately by the monsoon and the Westerlies. However, the mechanisms driving Holocene climate change on the TP remain unclear, since the extent of the influence of individual atmospheric circulation systems has not yet been clearly defined because of the shortage of high-quality paleoclimatic records. This is especially true in the central TP, where only a few ice core and paleolimnological records are available. Here, we present a decadal-resolution temperature record from Dagze Co in the central TP for the past 2000 years, based on the unsaturation index of long-chain alkenones, using an updated temperature calibration, and a record of precipitation isotopes from compound-specific isotope ratios of leaf waxes. The centennial-scale variation of the temperature and precipitation isotope records captures well-known climatic events over the past 1000 years, for example, the ‘Little Ice Age’, which was cooler and drier than the ‘Medieval Warm Period’. However, the relationship between temperature and the precipitation isotope records differed during the interval at 2000–1000 cal. yr BP compared to the past 1000 years, probably because of changes in precipitation seasonality and the additional influence of the Westerlies on the central TP. In addition, the temperature records exhibit a prominent 210-year cyclicity, suggesting a possible influence of solar radiation on temperature variability.
Melody extraction based on a source-filter model using pitch contour selection

This work proposes a melody extraction method which combines a pitch salience function based on source-filter modelling with melody tracking based on pitch contour selection. We model the spectrogram of a musical audio signal as the sum of the leading voice and accompaniment. The leading voice is modelled with a Smoothed Instantaneous Mixture Model (SIMM), and the accompaniment is modelled with a Non-negative Matrix Factorization (NMF). The main benefit of this representation is that it incorporates timbre information, and that the leading voice is enhanced, even without an explicit separation from the rest of the signal. Two different salience functions based on SIMM are proposed, in order to adapt the output of such model to the pitch contour based tracking. Candidate melody pitch contours are then created by grouping pitch sequences, using auditory streaming cues. Finally, melody pitch contours are selected using a set of heuristic rules based on contour characteristics and smoothness constraints. The evaluation on a large set of challenging polyphonic music material, shows that the proposed salience functions help increasing the salience of melody pitches in comparison to similar methods. The complete melody extraction methods also achieve a higher overall accuracy than state-of-the-art approaches when evaluated on both vocal and instrumental music.
Global meteorological drought – Part 2: Seasonal forecasts

Global seasonal forecasts of meteorological drought using the standardized precipitation index (SPI) are produced using two data sets as initial conditions: the Global Precipitation Climatology Centre (GPCC) and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (ERAI); and two seasonal forecasts of precipitation, the most recent ECMWF seasonal forecast system and climatologically based ensemble forecasts. The forecast evaluation focuses on the periods where precipitation deficits are likely to have higher drought impacts, and the results were summarized over different regions in the world. The verification of the forecasts with lead time indicated that generally for all regions the least reduction on skill was found for (i) long lead times using ERAI or GPCC for monitoring and (ii) short lead times using ECMWF or climatological seasonal forecasts. The memory effect of initial conditions was found to be 1 month of lead time for the SPI-3, 4 months for the SPI-6 and 6 (or more) months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value with skills at least equal to and often above that of climatological forecasts. Furthermore, it is very difficult to improve on the use of climatological forecasts for long lead times. Our results also support recent questions of whether seasonal forecasting of global drought onset was essentially a stochastic forecasting problem. Results are presented regionally and globally, and our results point to several regions in the world where drought onset forecasting is feasible and skilful.