Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised star, galaxy, QSO classification

Context. Classification will be an important first step for upcoming surveys aimed at detecting billions of new sources, such as LSST and Euclid, as well as DESI, 4MOST, and MOONS. The application of traditional methods of model fitting and colour-colour selections will face significant computational constraints, while machine-learning methods offer a viable approach to tackle datasets of that volume. Aims. While supervised learning methods can prove very useful for classification tasks, the creation of representative and accurate training sets is a task that consumes a great deal of resources and time. We present a viable alternative using an unsupervised machine learning method to separate stars, galaxies and QSOs using photometric data. Methods. The heart of our work uses Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to find the star, galaxy, and QSO clusters in a multidimensional colour space. We optimized the hyperparameters and input attributes of three separate HDBSCAN runs, each to select a particular object class and, thus, treat the output of each separate run as a binary classifier. We subsequently consolidated the output to give our final classifications, optimized on the basis of their F1 scores. We explored the use of Random Forest and PCA as part of the pre-processing stage for feature selection and dimensionality reduction. Results. Using our dataset of ∼50 000 spectroscopically labelled objects we obtain F1 scores of 98.9, 98.9, and 93.13 respectively for star, galaxy, and QSO selection using our unsupervised learning method. We find that careful attribute selection is a vital part of accurate classification with HDBSCAN. We applied our classification to a subset of the SDSS spectroscopic catalogue and demonstrated the potential of our approach in correcting misclassified spectra useful for DESI and 4MOST. Finally, we created a multiwavelength catalogue of 2.7 million sources using the KiDS, VIKING, and ALLWISE surveys and published corresponding classifications and photometric redshifts.
A Case of Slowly Progressive Purulent Pericarditis in Elderly Healthy Woman

A 67-year-old woman was admitted with dyspnea. The cheat X-ray showed marked cardiomegaly and the echocardiography revealed diffuse massive pericardial effusion but no finding of vegetation on valves. Clinical sign of cardiac tamponade was not observed. Values of white blood cell and C-reactive protein were 23,900/μL and 16.2 mg/dL, respectively. Immediately, pericardiocentesis was performed. Pericardial effusion was yellowish purulent exudate and Streptococcus pneumoniae was detected in culture. The early pericardial drainage and the effective doses of intravenous antibiotics and γ-globulin were successful for the treatment of this bacterial pericarditis, and no more surgical procedure was needed. Neither recurrence of inflammation nor constrictive pericarditis was developed after discontinuation of antibiotics during the follow-up period for over three years at the outpatient clinic. In this case, an infection route was unknown since pneumonia, empyema, or other focus of infection was not found. Although she had an upper respiratory infection one year prior to this pericarditis, their association was unclear. She was previously healthy and was not a compromised host. This case is thought to be rare bacterial pericarditis with slow progression in the recent antibiotic era.
Neural Networks for Option Pricing and Hedging: A Literature Review

Neural networks have been used as a nonparametric method for option pricing and hedging since the early 1990s. Far over a hundred papers have been published on this topic. This note intends to provide a comprehensive review. Papers are compared in terms of input features, output variables, benchmark models, performance measures, data partition methods, and underlying assets. Furthermore, related work and regularisation techniques are discussed.
Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement

Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cells have recently drawn significant attention due to their superior capability in manipulating electromagnetic waves. In particular, RIS-assisted wireless communications have the great potential to achieve significant performance improvement and coverage enhancement in a cost-effective and energy-efficient manner, by properly programming the reflection coefficients of the unit cells of RISs. In this article, free-space path loss models for RIS-assisted wireless communications are developed for different scenarios by studying the physics and electromagnetic nature of RISs. The proposed models, which are first validated through extensive simulation results, reveal the relationships between the free-space path loss of RIS-assisted wireless communications and the distances from the transmitter/receiver to the RIS, the size of the RIS, the near-field/far-field effects of the RIS, and the radiation patterns of antennas and unit cells. In addition, three fabricated RISs (metasurfaces) are utilized to further corroborate the theoretical findings through experimental measurements conducted in a microwave anechoic chamber. The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RISs, which may pave the way for further theoretical studies and practical applications in this field.
DRYING KINETICS OF BARU FRUITS (Dipteryx alata Vogel)

This study aimed to fit different mathematical models to the experimental data on drying of baru fruits (Dipteryx alata Vogel), determine and assess the effective diffusion coefficient, as well as obtain the activation energy and thermodynamic properties for the drying process under different air temperature conditions. Baru fruits with an initial moisture content of 0.429 ± 0.044 (dry basis, db) were dried in a forced air ventilation oven under four temperature conditions (40, 60, 80, and 100 °C) until reaching a moisture content of 0.065 ± 0.018 (decimal db). These data were fitted to mathematical models frequently used to represent the drying of vegetal products. The Logarithmic model presented the best fit to describe the phenomenon. The effective diffusion coefficient increased as temperature increased, being described by the Arrhenius equation, with an activation energy of 37.64 kJ mol. Enthalpy and entropy decreased, while Gibbs free energy increased as drying temperature increased.
Restoring dissolved organic carbon subsidies from floodplains to lowland river food webs: a role for environmental flows?

Environmental flows are managed events in river systems designed to enhance the ecological condition of aquatic ecosystems. Although not traditionally seen as important in lowland rivers, there is mounting evidence that terrestrial subsidies can be an important energy source in aquatic metazoan food webs. We argue that the apparent lack of importance of terrestrial subsidies to many lowland river food webs may reflect an artefact resulting from historical anthropogenic changes to lowland river–floodplain ecosystems, including the loss of lateral connectivity between rivers and their floodplains, changes in floodplain land use and carbon stores, and loss of sites of transformation within the main channel. The loss of floodplain subsidies to the main river channel can be partially redressed using environmental flows; however, this will require mimicking important aspects of natural high-flow events that have hitherto been overlooked when targeting environmental flows to a limited suite of biota. We suggest that key biotic targets for environmental flow releases may not be achievable unless river–floodplain subsidies are sufficiently restored. Environmental flows can go some way to addressing this shortfall, but only if floodplain subsidies to river channels are explicitly included in the design and management of environmental flows.
Gazing at the ultraslow magnetar in RCW 103 with NuSTAR and Swift

The results reported in this paper are based on observations obtained with Swift and NuSTAR. Swift is a NASA mission with participation of the Italian Space Agency and the UK Space Agency. The NuSTAR mission is a project led by the Californian Institute of Technology. AB, PE, and NR are supported by an NWO Vidi Grant (PI: Rea). FCZ and NR are supported by grants AYA2015-71042-P and SGR2014-1073. We thank the PHAROS COST Action (CA16214) for partial support and the referee for the comments.
The role of Aspergillus oryzae KKB4 in reducing and detoxifying aflatoxin B1 applied in moist-heated corn

Aims: The growth and metabolic activity of Aspergillus oryzae KKB4 in AFB1-contaminated corn and later coincided with AFB1 reduction and detoxification were investigated. Methodology and results: The decreasing of AFB1 amount by A. oryzae KKB4 could be clearly observed if the initial AFB1 concentration in corn was increased. Thus, moist-heated corn was artificially inoculated with Aspergillus flavus FNCC 62C7 to increase AFB1 content. AFB1-contaminated corn was applied as solid substrate and then inoculated with A. oryzae KKB4. During fermentation periods, the growth, metabolic activity, and AFB1 decline were investigated by glucosamine content, water content loss, and AFB1 concentration, respectively. The maximum growth was occurred in 4 th day at 1.499 ± 0.028 g glucosamine/ 100 g dry matter. The metabolic activity was going on up to the end of fermentation days, as shown as water content loss at 0.175 ± 0.007 g/g dry matter. In accordance with the growth and metabolic activity, the amount of AFB1 reduction was 37.04 ng AFB1/g dry matter during 5 days fermentation. According to toxicity analysis, it was found that the residues of AFB1 were not toxic to Bacillus megaterium cells. Conclusion, significance and impact of study: A. oryzae KKB4 is able to be applied in solid substrates as AFB1 reduction and detoxification agent. These lucrative effects are also important in relation with food and feed safety.
Effect of four commercial barley varieties on life table parameters of Sitotroga cerealella (Olivier) (Lepidoptera: Gelechiidae)

Angoumois grain moth, Sitotroga cerealella (Olivier) is one of the most important pests of stored products and known as factitious host for mass rearing of insect natural enemies. Effect of four commercial barely varieties including Fajr 30, Behrokh, Nik and Yousef on life table parameters of S. cerealella was determined at 26 ± 2 °C, 65 ± 5% RH and a photoperiod of 12:12 h (L: D). Data were analyzed based on the age-stage, two-sex life table theory. The results revealed that there were significant differences among various barely varieties regarding the developmental times, adult longevity and fecundity of S. cerealella. The longest developmental time (56.72 ± 0.29 days) was observed on Yousef. The longest and shortest male longevity were obtained on Behrokh (6.77 ± 0.27 days) and Yousef (5.79 ± 0.16 days). Moreover, female longevity ranged from 6.20 ± 0.18 to 7.23 ± 0.24 days on Yousef and Behrokh, respectively. The highest values of intrinsic rate of increase (r) were estimated 0.0719 ± 0.004 and 0.0717 ± 0.003 day -1 on Fajr 30 and Behrokh, respectively and the lowest values were 0.0539 ± 0.004 and 0.0542 ± 0.003 day -1 on Nik and Yousef, respectively. The longest generation time (T) was observed on Yousef. Furthermore, peaks of reproductive value occurred at ages of 45, 49, 48 and 53 days when reared on Fajr 30, Behrokh, Nik and Yousef, respectively. It can be concluded that Fajr 30 and Behrokh can be used for mass rearing programs of S. cerealella as an alternative host for natural enemies.
Changes in Biochemical Composition of the Gonads of Donax trunculus L. (Mollusca, Bivalvia) from the Gulf of Annaba (Algeria) in Relation to Reproductive Events and Pollution

Seasonal changes in biochemical composition of the bivalve Donax trunculus L. (Mollusca, Bivalvia) were studied during eight months from January to August 2009 in the gulf of Annaba. The samples were collected monthly at two sites: El Battah, a site far from any source of pollution, and Sidi Salem, a site located near human and industrial wastes. The amounts of carbohydrate, lipid, and protein were determined in gonad-visceral mass. The monthly amounts of the different components in gonads varied from 33.68 to 118.09 for carbohydrates, 6.68 to 44.45 for lipids and 3.56 to 36.72 µg/mg of wet tissue for proteins, respectively. A three-way ANOVA indicated significant effects of time, sex, and treatment. Lowest values of components were observed during the spawning phase. There was a significant difference in amounts of these gonad components between the two sites. Globally, the lowest values of carbohydrate and proteins, and the highest values of lipids were recorded in individuals sampled at Sidi Salem.
Influence of Entrepreneurial Orientation and Business Environment on Small and Medium Firm Performance: A PLS Approach

The purpose of this study is to investigate the relationship of entrepreneurial orientation and business environment on firm performance, underpinned by Resource based view. Their relationship receives a considerable scholarly attention in the literature, but few studies have been conducted among Nigerian SMEs. SMEs are considered as important to the economic growth of Nigeria and they constitute the major source of employment and significantly contribute to the gross domestic production. Based on the theoretical consideration, a model was proposed to examine this relationship. A quantitative method was used with a total of 640 questionnaires personally distributed to the owner/managers of SMEs in Nigeria. A total of 511 questions was duly completed and returned representing 79.8% response rate. The study finding is in support of previous researchers who have suggested the positive relationship of entrepreneurial orientation and firm performance in many organizations. The finding from the study indicated no relationship between the business environment and firm performance. The finding from this study will benefit SME owner/managers, regulatory agency ie small and medium enterprise development agency of Nigeria, it will also help in policy formulation and will serve as a frame of future reference.
The relaTionship beTween eservice qualiTy, evalue, esaTisfacTion and eloyalTy in online Tourism porTals

Customer satisfaction and loyalty are important drivers of business profits. In the online arena, acquisition costs are high, switching costs are low, the service encounter is non-personal and the Internet is often used only as a source of information. The aim of this article is to determine the relationship between critical eService quality elements utilised in online tourism portals in order to establish eLoyalty. The target population of this study was South African tourism accommodation establishments who advertised on online tourism portals during 2005. A personalised branded HTML email with a clickable link to the online survey was mailed to all respondents. One hundred and nine valid responses were received. A multi-item questionnaire was used to measure the relationship between eService quality, eValue, eSatisfaction and eLoyalty pertaining to online tourism portals utilised by the respondents. The findings imply that online tourism portals would increase their eLoyalty (and thus increase profits) if they first satisfied their suppliers’ needs by providing them with a secure, visually pleasing user interface with which they could identify. Secondly, there is a need for online tourism portals to provide services that add value, making it easy for suppliers to add and change details on their own pages, as well as ensuring that their suppliers receive a substantial income stream through the portal.
FEEDING HABITS OF SYMPATRIC MUSTELIDS IN AN AGRICULTURAL AREA OF HUNGARY

The feeding ecology of the badger (Meles meles) and its interspecific trophic relationship with the sympatric marten (Martes foina and M. martes) were investigated in a temperate climate agricultural area of southwestern Hungary. On the basis of food remains found in scats (over four years, badger n = 166, marten n = 545), both predators consumed the most abundant and accessible foods according to the season. No significant differences were found between predators concerning the consumption of small mammals as primary foods (mean; badger 59.3% and marten 48.0%) and other food types, except birds. Regarding plants as secondary foods, badgers consumed mainly maize, while martens ate predominately fruits. Both mustelids preferred open-field living common vole and avoided forest-living bank vole; both consumed primarily small (< 50 g) (97% vs 94%), open-field living (78% vs. 55%) and terrestrial (98% vs 86%) prey species, but marten preyed more on arboreal animals. Diets were diverse, but the trophic niche, especially of the badger, was very narrow. The mean food overlap between predators was high (67.1%). Considering that the chosen primary or secondary food resources are unlimited in central European agricultural areas, it is not possible to prove food resource partitioning between mustelids. Interspecific differences in feeding habits are rather the consequences of individual patterns than niche segregation.
CNN-BASED SINGLE IMAGE SUPER-RESOLUTION NETWORK AND BIOMEDICAL IMAGE APPLICATIONS

In this thesis, we propose a convolutional neural network (CNN) based single image super-resolution network model with sparse representation by combining three existing state-of-the-art methods SC [1], SRCNN [2] and SCN [3] models with a modified pre-processing step. Firstly, standard gaussian box filter is applied to test image, which is a low-resolution image (LR), to remove low-frequency noises. After that, the given low-resolution image is up-scaled by bicubic interpolation method to the same size with desired output high-resolution image (HR). Secondly, a convolutional neural network based dictionary learning method is employed to train input low-resolution image to obtain LR image patches. Also, a rectified linear unit (ReLU) thresholds the output of the CNN to get a better LR image dictionary. Thirdly, to get optimal sparse parameters, we adopted Learned Iterative Shrinkage and Thresholding Algorithm (LISTA) [4] [5] network to train LR image patches. LISTA is a sparse-based network that generates sparse coefficients from each LR image patches. Finally, in the reconstruction step, corresponding high-resolution image patches are obtained by multiplying low-resolution image patches with optimal sparse coefficients. Then corresponding high-resolution image patches are combined to get final HR image. The experimental results show that our proposed method demonstrates outstanding performance compare to other state-of-the-art. The proposed method generates clear and better-detailed output high-resolution images since it is important in real life applications. The advantage of the proposed method is to combine convolutional neural network based dictionary learning and sparse-based network training with better preprocessing to create efficient and flexible single-image-super-resolution network.
WIND-GENERATED CURRENT AND PHASE SPEED OF WIND WAVES

Measurements of drift were made in a wind and wave facility at different elevations below the mean water level. The drift profiles were obtained for reference wind speeds, Ur = 3.1, 5.7 and 9.6 m/sec. The measurement technique involved tracing the movement of small paper discs which were soaked in water to become neutrally buoyant at the elevation of release. A logarithmic drift profile is proposed. The water shear velocity, U*w, predicts a surface stress, TS = pw U*S, in agreement with that obtained from the wind shear velocity, Ts = Pa U*li where pa and pw refer to air and water densities, respectively. The influence of wind on phase speeds of waves was investigated by solving the first order perturbation problem of the coupled shear flows in air and water. The air velocity profile was described by a logarithmic distribution and the drift profile was described by the proposed drift profile. Adequate agreement is found between the calculated and measured phase speed using Doppler radar in the wave number range 1.9 - 10 cm-1. In the wave number range 0.05 - 0.5 cm-1, measurements of phase speeds were obtained by using two wave gages. The waves were mechanically generated without wind and the wave gages were spaced to obtain coherent signals. The wind was then allowed to blow over the waves and the distance between wave gages was increased to maintain coherence. The wave length and frequency were obtained from the distance between the gages and from the generator frequency, respectively. The measured phase speeds were found to increase with wind speed consistent with theoretical computations.
Open Archive TOULOUSE Archive Ouverte (OATAO)

Energy savings are among the most important topics concerning Cloud and HPC infras- tructures nowadays. Servers consume a large amount of energy, even when their computing power is not fully utilized. These static costs represent quite a concern, mostly because many datacenter managers are over-provisioning their infrastructures compared to the actual needs. This results in a high part of wasted power consumption. In this paper, we proposed the BML ( “Big,Medium,Little” ) infrastructure, composed of heterogeneous architectures, and a scheduling framework dealing with energy proportionality. We introduce heterogeneous power processors inside datacenters as a way to reduce energy consumption when processing variable workloads. Our framework brings an in- telligent utilization of the infrastructure by dynamically executing applications on the architecture that suits their needs, while minimizing energy consumption. In this paper we focus on distributed stateless web servers scenario and we analyze the energy savings achieved through energy proportionality.
Should African Rural Development Strategies Depend on Smallholder Farms? An Exploration of the Inverse Productivity Hypothesis

In Africa, most development strategies include efforts to improve the productivity of staple crops grown on smallholder farms. An underlying premise is that small farms are productive in the African context and that smallholders do not forgo economies of scale -- a premise supported by the often observed phenomenon that staple cereal yields decline as the scale of production increases. This paper explores a research design conundrum that encourages researchers who study the relationship between productivity and scale to use surveys with a narrow geographic reach, when policy would be better served with studies based on wide and heterogeneous settings. Using a model of endogenous technology choice, the authors explore the relationship between maize yields and scale using alternative data. Since rich descriptions of the decision environments that farmers face are needed to identify the applied technologies that generate the data, improvements in the location specificity of the data should reduce the likelihood of identification errors and biased estimates. However, the analysis finds that the inverse productivity hypothesis holds up well across a broad platform of data, despite obvious shortcomings with some components. It also finds surprising consistency in the estimated scale elasticities.