Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic variation at 27 y-strs in four regions of bahrain

Bahrain location in the Arabian Gulf contributed to the diversity of its indigenous population descended from Christian Arabs, Persians (Zoroastrians), Jews, and Aramaic-speaking agriculturalists. The aim of this study was to examine population substructure within Bahrain using the 27 Y-STRs (short tandem repeats) in the Yfiler Plus kit and to characterize the haplotypes of 562 unrelated Bahraini nationals, sub-divided into the four geographical regions - North, Capital, South and Muharraq. Yfiler Plus provided a significant improvement over the earlier 17-locus Yfiler kit in discrimination capacity, increasing it from 77% to 87.5%, but this value differed widely between regions from 98.4% in Muharraq to 75.2% in the Northern region, an unusually low value possibly as a consequence of the very rapid expansion in population size in the last 80 years. Clusters of closely related male lineages were seen, with only 79.4% of donors displaying unique haplotypes and 59% of instances of shared haplotypes occurring within, rather than between, regions. Haplogroup prediction indicated diverse origins of the population with a predominance of haplogroups J2 and J1, both typical of the Arabian Peninsula, but also haplogroups such as B2 and E1b1a originating in Africa and H, L and R2 indicative of migration from the east. Haplogroup frequencies differed significantly between regions with J2 significantly more common in the Northern region compared with the Southern possibly as a result of differential settlement with Baharna (descended from populations in which J2 predominates) and Arabs (both indigenous and migrant Huwala who are expected to have a higher frequency of J1). Our study illustrated the importance of encompassing geographical and social variation when constructing population databases and the need for highly discriminating multiplexes where rapid expansions have occurred within tightly bounded populations.
Hybrid Deep Neural Networks for Detection of Non-Technical Losses in Electricity Smart Meters

Non-technical losses (NTL) in electricity utilities are responsible for major revenue losses. In this paper, we propose a novel end-to-end solution to self-learn the features for detecting anomalies and frauds in smart meters using a hybrid deep neural network. The network is fed with simple raw data, removing the need of handcrafted feature engineering. The proposed architecture consists of a long short-term memory network and a multi-layer perceptrons network. The first network analyses the raw daily energy consumption history whilst the second one integrates non-sequential data such as its contracted power or geographical information. The results show that the hybrid neural network significantly outperforms state-of-the-art classifiers as well as previous deep learning models used in NTL detection. The model has been trained and tested with real smart meter data of Endesa, the largest electricity utility in Spain.
Soil Nitrification Potential Influences the Performance of Nitrification Inhibitors DCD and DMPP in Cropped and Non-Cropped Soils

The application of nitrification inhibitors (NIs) shows promise in prolonging the ammonium presence in soil with beneficial effects for agriculture ecosystems and climate change mitigation. Although the inhibitory effect (IE) of NIs has been studied in the presence of various environmental and edaphic conditions, little is known about the effect of soil nitrification potential (NP) on the effectiveness of NIs. Here, laboratory-scale experiments were conducted to investigate the effect of the variation in soil NP rates, among land-use type and temperature, on the performance of two nitrification inhibitors, dicyandiamide (DCD) and 3,4-dimethypyrazole phosphate (DMPP), at four NI application rates imposed upon eight cropland and non-cropland soils. We found that the IE of DCD and DMPP were organized according to soil NP rates. Nevertheless, NP was lower in non-cropped soil than in cropped systems, and DMPP-based inhibition was higher than DCD. The IE of both NIs decreased with NP and the amount of NI required to achieve an IE ≈ 50%, was significantly reduced for soils that exhibited the lowest NP rates, especially for DMPP. However, the temperature did not appear to have a major influence on IE of both DCD and DMPP, demonstrating the potential of NIs to inhibit nitrification for a wider temperature range, dependent on the NI application rate. Our findings provide evidence that change in soil NP rate has important influences on the efficacy of NI which required great consideration for N-fertilizer optimization with the application of nitrification inhibitors.
Fragility Functions for Displacement-based Seismic Design of Reinforced Masonry Wall Structures

ABSTRACT It is well understood that in the displacement-based seismic assessment of masonry shear wall structures, it is desirable to have an estimation for lateral deformation capacity of wall segments that are linked to their different damage levels. This study focuses on the development of experimental-based fragility functions for reinforced masonry shear walls subjected to in-plane seismic loading, which can be used in the next-generation displacement-based seismic design approaches. Hysteresis responses of 91 wall specimens and their damage progression patterns obtained from a series of experiments performed at The University of Texas at Austin and Washington State University are used to generate fragility functions for different demand levels. Various damage states are proposed within this study that are associated with commonly employed methods of repair, and these damage states represent different levels of flexure, diagonal shear, and sliding shear damage in reinforced masonry shear walls. Corresponding damage limit states are defined in terms of ratio of lateral deformations to the aspect ratio of wall segment as the demand parameter for flexural damage, while those limit states for diagonal and sliding shear damage is the normalized shear demand. This paper develops drift-based fragility functions for key damage states associated with the structural performance and reparability of reinforced masonry walls. This research also shows that the proposed demand parameters formulate a more accurate correlation between the demand parameters and the damage observed in the tests in masonry walls than does from story-drift ratio, which was previously the industry standard practice.
Cost Analysis of Chaff Harvesting Concepts in Germany

This work assesses the costs of exploiting the biomass feedstock chaff. Chaff is a harvest residue generated during the conventional grain harvesting process and usually remains on the field. In this paper, the costs of collecting and supplying chaff to the end user with different harvesting methods and supply chains are analyzed. The costs are estimated for a base case defining a set of general assumptions. The impact of these assumptions is analyzed in a sensitivity analysis by means of tornado diagrams. A full costing method based on the VDI guideline 2067 part 1 is applied for the cost estimation. The cost analysis reveals that ceasing the fractioning of grain, straw and chaff during harvesting and transporting them as a mixture reduces the harvesting costs significantly. The costs are decreased due to a reduction in agricultural operations and processing large amounts of material. The lowest total costs originate from the production of chaff-straw bales. Harvesting chaff as a single fraction leads to the highest costs with the investigated supply chains. Comparing the costs of chaff supply to potential revenues shows that an exploitation of the harvest residue can be economically feasible.
Environmental Profile of the Manufacturing Process of Perovskite Photovoltaics: Harmonization of Life Cycle Assessment Studies

The development of perovskite solar cell technology is steadily increasing. The extremely high photoconversion efficiency drives factor that makes these devices so attractive for photovoltaic energy production. However, the environmental impact of this technology could represent a crucial matter for industrial development, and the sustainability of perovskite solar cell is at the center of the scientific debate. The life cycle assessment studies available in the literature evaluate the environmental profile of this technology, but the outcomes vary consistently depending on the methodological choices and assumptions made by authors. In this work, we performed the harmonization of these life cycle assessment results to understand which are effectively the environmental hotspots of the perovskite solar cell fabrication. The outcomes of this analysis allowed us to outline an environmental ranking of the profiles of the several cell configurations investigated and, most importantly, to identify the material and energy flows that mostly contribute to the technology in terms of environmental impact.
The Biodiversity of Saccharomyces cerevisiae in Spontaneous Wine Fermentation: The Occurrence and Persistence of Winery-Strains

Saccharomyces cerevisiae populations occurring in spontaneous wine fermentations display a high polymorphism, although few strains are generally able to dominate the fermentative process. Recent studies have suggested that these indigenous S. cerevisiae strains are representative of a specific oenological ecosystem, being associated to a given wine-producing area or a single winery. In contrast, according to other ecological studies, no correlation between genotypic and phenotypic groups of the native S. cerevisiae strains and their origin was found. In this work, several S. cerevisiae strains were isolated in consecutive years from spontaneous fermentations carried out in the same wineries located in different oenological areas in Tuscany, and their persistence was assessed by molecular methods. Some predominant S. cerevisiae strains persisted in different fermentations in the same winery from one year to another and they seemed to be representative of a single winery rather than of an oenological area. Therefore, data suggested the idea of the “winery effect” or a microbial terroir at a smaller scale. The use of these typical strains as starter yeasts could provide wines with the distinctive characteristics of a particular winery or sub-zone.
Studies on growth and development of golden plum

The experimental results indicated that the growth and development of Golden plum was trable S-shaped curves: slow-fast-slow-fast-slow. The whole growth and development course was divided into five periods: the slow growth period of infant fruit, the first fast growth period of fruit, the second slow growth period of fruit, the second fast growth period of fruit and the third slow growth period of fruit at the beginning of ripening. The second slow growth period of fruit inosculated with the rigidification period of stone, and the first and the second fast growth period of fruit were two pivotal periods for fruit to grow. The variational curves of fresh fruit weight and fruit volume were almost semblable with that of vertical diameter, horizontal diameter, side diameter and pulp thickness of fruit. After relatively analyzed, we found that the relative coefficients among vertical diameter, horizontal diameter, side diameter, respectively pulp thickness of fruit and fresh fruit weight were 0.9421**, 0.9442**, 0.9413** and 0.9843**, and the relative coefficients among vertical diameter, horizontal diameter, side diameter, pulp thickness of fruit and fruit volume were respectively 0.9391**, 0.9462**, 0.9373** and 0.9824**, and those indicated that they rose synchronously. The growth and development of stone was about T-shaped curves: fast-slow-stopping. Before thirty-one days after Golden plum shattered, it was the fast growth period of stone. After that it was the slow growth period of stone, and at the same time, stone started to scleroses and change color. It was fifty-nine days after Golden plum shattered that stone attained the inherent size and color, and at the same time, stone stopped sclerosesing. After that stone stopped growing.
Cobalt Oxide Catalysts in the Form of Thin Films Prepared by Magnetron Sputtering on Stainless-Steel Meshes: Performance in Ethanol Oxidation

Catalytic total oxidation is an effective procedure to minimize emissions of volatile organic compounds (VOC) emissions in industrial gases. Catalysts in the form of meshes are remarkable as they minimize the internal diffusion of reactants during the reaction as well as the need of expensive active components. In this paper, various conditions of radio frequency magnetron sputtering of cobalt on stainless-steel meshes was applied during catalyst preparation. Properties of the supported Co3O4 catalysts were characterized by SEM, XRD, temperature programmed reduction (H2-TPR), FTIR, XPS, and Raman spectroscopy. Catalytic activity was examined in deep oxidation of ethanol chosen as a model VOC. Performance of the catalysts depended on the amount of Co3O4 deposited on the supporting meshes. According to specific activities (the amounts of ethanol converted per unit weight of Co3O4), smaller Co3O4 particle size led to increased catalytic activity. The catalyst prepared by sputtering in an Ar+O2 atmosphere without calcination showed the highest catalytic activity, which decreased after calcination due to enlargement of Co3O4 particles. However, specific activity of this catalyst was more than 20 times higher than that of pelletized commercial Co3O4 catalyst used for comparison.
Wireless sensor network energy efficient coverage method based on intelligent optimization algorithm

As a basic and fundamental problem in wireless sensor network (WSN), the network coverage greatly reflects the performance of information transmission in WSN. In order to achieve a good balance between target coverage and energy consumption, in this paper, we propose a novel wireless sensor network energy efficient coverage method based on genetic algorithm. Particularly, the goal of this work is cover a 2D sensing area via selecting a minimum number of sensors. Moreover, the deployed wireless sensors should be connected to let each sensor be connected a path to the base station. Afterwards, genetic algorithm is used to compute the minimum number of potential position to let all target be k-covered and all sensor nodes be m-connected, and each chromosome is set to be the number of potential positions. Finally, we provide a simulation to test the performance of the proposed method, and simulation results demonstrate that the proposed method can achieve high degree of target coverage without wasting extra energy.
Assessing patterns of bird roadkills in a high Andean Ecuadorian national park

ABSTRACT Animal mortality due to collisions with vehicles in roads are a major threat to biodiversity; however, there is still much to learn about this problem in the tropical Andes hot spot. We describe general patterns of bird mortality associated with the presence of a road that bisects Cajas National Park (CNP), in the southern high Andes of Ecuador. We use a published study of the abundance of species in the study area, and explored if there were particular ecological traits that predisposed species to collisions with vehicles. Roadkill data were gathered by collecting carcasses on 15 km of a main road that crosses páramo grasslands. Overall we found carcasses of 23 species. Bird mortality rate was four individuals per km per year. We found an association between roadkills and the abundance of species in areas close to the road. Moreover, forest species were less likely to be road-killed than species with other habitat preferences. Our results can be used to ameliorate roadkills in CNP and to raise concern on the direct effects of roads in the páramo of the Tropical Andes.
The development of a Niemann-Pick gene-based marker in common bean (Phaseolus vulgaris L.) for the selection of common bacterial blight resistance

THE DEVELOPMENT OF A NIEMANN-PICK GENE-BASED MARKER IN COMMON BEAN (PHASEOLUS VULGARIS L.) FOR THE SELECTION OF COMMON BACTERIAL BLIGHT RESISTANCE Emily Morneau Advisor: University of Guelph, 2019 Dr. K. Peter Pauls Common bacterial blight (CBB) is a major disease in common bean (Phaseolus vulgaris) caused by Xanthomonas axonopodis pv. phaseoli and Xanthomonas fuscans subsp. fuscans. By characterizing alleles in three candidate genes within white bean line OAC Rex, a codominant molecular marker for resistance was created. The Niemann-Pick polymorphism (NPP) marker was developed to screen common beans for CBB resistance, and is anchored in a candidate resistance gene (Niemann-Pick like gene). Individuals in two segregating populations were screened for allelic state and disease susceptibility. It was found that the NPP marker is significantly more efficient (8% decrease in error rate) in comparison to other markers. Within the OAC Rex pedigree, the resistant allele for the NPP marker was found solely within progeny from the introgression of Phaseolus acutifolius into P. vulgaris. Lastly, the two additional candidate resistance genes investigated (R-genes 231733-8-004 and 231733-8-005), were found to have no exploitable polymorphisms.
An Opportunistic Thresholding Detector for IoT Random Access in Massive MIMO

Introduction of internet of things (IoT) into the massive MIMO random access scheme has generated many complications. Specifically, the number of IoT devices is significantly greater than mobile broadband. On the other hand, their traffic is intermittent. Given the different nature of IoT traffic, on-off random access channel can model it accurately. An extension of this access model has been recently applied to massive MIMO scenarios where it was demonstrated to entail common support recovery in a jointly sparse multiple measurement vector (MMV) problem. Several sparse recovery algorithms have also been proposed. However, we are not particularly bothered by the choice of algorithm but pose a new question which has been previously overlooked. While measurements size is severely constrained and dictated by the environment and the physical nature of communication channel, which is out of our control, the number of antennas is at our disposal to increase at will. The question is can we relieve the burden on number of measurements by increasing number of antennas and still maintain a satisfactory recovery performance. The so-called trivial pursuit (TP) gives a positive answer for independent sensing matrices. Motivated by TP, we introduce a novel opportunistic thresholding detector (OTD) which exploits partial de-correlation of sensing matrices to improve support recovery performance with minimum modifications and thus keeping the low-complexity nature of the algorithm. Extensive simulations has corroborated the superior performance of OTD compared to ordinary thresholding.
Intravitreal Silicone Oil Migration Into the Lateral Cerebral Ventricles

Purpose: Silicone oil (SO) is often used as an intraocular tamponade in repairs of retinal detachments. It may be associated with complications such as cataract, glaucoma, keratopathy, subretinal migration of oil, fibrous epiretinal and sub retinal proliferations, and oil emulsification. The purpose of this report is to describe a rare phenomenon of intraocular silicone oil migration into the cerebral ventricles, which may later be mistaken for intraventricular hemorrhages on neuroimaging. Methods: Case report with literature review. Results: A patient with a history of retinal detachment repair with intraocular SO presented with headaches. Neuroimaging revealed SO migration to the cerebral ventricles. The patient was treated conservatively with symptom management and headaches resolved. Conclusions: We present a case of intraocular SO migration to the cerebral ventricles and review the current literature. We also propose two mechanisms for this phenomenon.
Effect of Individual vs. Combined Supplementation of Tamarind Seed Husk and Soapnut on Methane Production, Feed Fermentation and Protozoal Population in vitro

Increasing concentration of greenhouse gas in the atmosphere is leading to the prompt shifts in climate across the globe. Intergovernmental Panel on climate change (IPCC) has listed six gases namely carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride [1]. Among agriculture sector, enteric fermentation is the single largest source of methane emission [2]. Livestock contribute up to 18% of global greenhouse gas emissions in the form of methane [3]. Livestock are annually emitting about 90Tg of methane due to the enteric fermentation [4]. The contribution of Indian livestock to global enteric methane emission is 9.25Tg per year [5]. Methane is listed as one of the important greenhouse gases not because of abundance, but also due to its global warming potential. Due to the massive negative environmental impacts and reduce animal feed efficiency, a search for developing suitable and effective methane mitigation strategy in ruminants is underway. Since last two decades, many strategies have been developed and tested for the reduction in enteric methane emission; however, most of them could not be implemented at the field level. The factors such as variable reduction, cost of test materials, transitory effect, impact on host animal and denizen microbes pose hindrances in the adoption of such approaches at the farmer’s doorstep [6]. For example, ionophores such as monensin and lasalocid have been largely used for the reduction of enteric methane emission; however, the results always Crimson Publishers Wings to the Research Research Article
Screening of chemical composition of essential oil, mineral elements and antioxidant activity in Pulicaria Undulata (L.) C. A. Mey from Iran

Pulicaria undulata (L.) C.A. Mey is a medicinal plant used to treat inflammation. It is also an insect repellent and herbal tea. In this study, concentration of macro minerals (that is, Ca, K and Mg) and micro minerals (major and trace elements) (that is, Fe, Cu, Na and Mn) and P, were estimated in Pulicaria undulata from the Sistan and Baluchestan province. Sample preparation using microwave digestion was used for mineralization of this plant. Atomic absorption spectrophotometry (AAS) and UV-Visible spectrophotometry were used to quantify metal levels and Phosphorus, respectively. Essential oil from aerial parts of P. undulata was obtained by hydrodistillation. The chemical constituents of essential oil of aerial parts were analyzed by GC-FID and GC/MS techniques. The main components identified in the oil were 4-Terpineole (20.12%), alpha terpinene (4.02%), gamma terpinene (7.00%), cis-sabinene hydrate (8.29%), Linalool (5.60%), 1S-cis-calamenene (13.37%) and Junipene (8.66%). In addition, antioxidant activity of ethanolic extract was evaluated by 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging method. Key words: Macro and micro minerals, microwave digestion, Pulicaria undulata, antioxidant activity.