Miracle-dz/UniFAR-FTUs huggingface dataset:
Lethal control of eutherian predators via aerial baiting does not negatively affect female spotted-tailed quolls (Dasyurus maculatus maculatus) and their pouch young

Abstract Context. Outside its breeding season, the marsupial carnivore the spotted-tailed quoll (Dasyurus maculatus) is apparently largely unaffected by aerial baiting for dingoes and other wild dogs (Canis familiaris). However, the potential impact of aerial baiting during spring on female spotted-tailed quolls carrying and weaning young remains unquantified. Aim. The survivorship of female quolls and their pouch young was investigated after aerial baiting at two sites representing the northern and southern part of their New South Wales range. The null hypothesis was that aerial baiting would not lead to direct mortality of any adult females or higher pouch young mortality over that reported in the published literature under normal conditions. Methods. In total, nine female quolls with pouch young and eight male quolls were trapped, fitted with GPS/VHF collars containing mortality sensors and released at their point of capture. After trapping ceased, meat baits nominally containing 6 mg of 1080 and 50 mg of the biomarker rhodamine B were deployed by helicopter at both sites at the maximal permissible rate of 40 baits km−1. We monitored collared quolls daily for 4–5 weeks for mortality then retrapped animals and sampled whiskers for evidence of the biomarker. The fate of pouch young was also followed throughout our study by examining pouches of adult females and camera trapping at maternal den sites. Key results. No collared quolls died. After the daily monitoring period, 10 quolls, including all six collared female quolls, were trapped at the southern site, and whisker samples taken and assayed for Rhodamine B. Seven (4 females and 3 males) tested positive for rhodamine B, indicating consumption of baits. Separate bands of the biomarker in whisker samples indicated that most animals that tested positive had been exposed to multiple baits. At the northern site, four quolls (including two females and two males) tested positive for rhodamine B from the nine sampled. Post-baiting inspection of pouches of all trapped adult female animals, together with camera trapping at den sites, showed that the development of pouch young was unaffected by the baiting. Camera trapping arrays set across both sites continued to record the animals that were exposed to baits well beyond the baiting events, including evidence of breeding in a subsequent season. Conclusion. Our aerial baiting programs had no observable impact on the collared female quolls, or their ability to raise and wean young. These findings are consistent with results from all previous field-based experimental studies, which show no population-level impacts of 1080 baits on spotted-tailed quolls. Implications. Land managers should not be concerned about impacts of aerial baiting for wild dogs on spotted-tailed quolls, either in autumn or in spring during the breeding season.
ANTIOXIDANT ACTIVITY IN THE FOUR SPECIES OF CYANOBACTERIA ISOLATED FROM A SULFUR SPRING IN THE WESTERN GHATS OF KARNATAKA

In the present study, efforts were made to reveal the total phenolics and flavanoid contents and antioxidant activity in the four cyanobacterial species viz., Phormidium fragile, Lyngbya limnetica, Scytonema bohnerii and Calothrix fusca isolated from a sulfur spring in the Western Ghats of Karnataka. The cultures were maintained in BG11 medium. In vitro screening for antioxidant activity of ethanol and methanol extracts of these cultures was determined by total antioxidant capacity by phosphomolybdenum, DPPH free radical scavenging and ferric ion reducing assays. The study indicates the significant antioxidant potential in Lyngbya limnetica (P 0.05). Therefore, mass cultivation of such strains for the production of valuable bioproducts may be a good strategy for future use. The study has revealed the utilization of certain strains of cyanobacteria for the production of biologically active compounds particularly, antioxidants.
Effects of Induced Field Rotation From Rough Surface on H-Alpha Decomposition of Full-Polarimetric GPR

The full-polarimetric ground-penetrating radar (FP-GPR) can obtain the polarimetric attributes of targets and achieve more accurate identification compared with traditional GPRs. However, in most cases, the polarimetric signals collected by GPRs are not only from the targets but also from the ground surface. According to the classical Fresnel formulas, the polarized directions of the waves will change after transmissions due to the difference in the transmission coefficients between horizontally and vertically polarized waves. This effect, called induced field rotation (IFR), will interfere with the acquisition of polarimetric attributes and also exists in the field measurements on a rough surface. In this study, we have derived the association between the measured FP-GPR data and transmission coefficients of the rough surface provided by the small perturbation method (SPM). The effects of IFRs from the rough surface on H-Alpha decomposition are analyzed later. The results show that the parameters of the rough surface will affect the values of components in the scattering matrix, but will not change the matrix and H-Alpha decomposition result; the incident angle and relative permittivity play main roles; for the H-Alpha decomposition results of three typical targets, the flat and dihedral are little influenced by IFRs, but the cylinder is seriously affected; simultaneously, a template for discriminating whether the calibration for H-Alpha decomposition is necessary is established. Both numerical and experimental tests validate the conclusions. Finally, a novel application strategy of H-Alpha decomposition is proposed, which has taken IFR from the rough surface into considerations.
An Image Processing Method: Edge-guided Directional Walk Mean Smoothing

Image denoising is an important computer vision task, it is also the basis of many other high-level vision tasks. Recently, various image denoising algorithms have proposed, such as BM3D, sparse representation and deep learning, that have achieved impressive performance in AWGN denoising or blind denoising tasks. However, when dealing with Dongba painting (A traditional painting from China’s ethnic minorities), there are problems that Dongba painting have blurred edges and faded colors, it is important to retain its original style when denoising. In this paper, we propose a novel image post-processing technique termed edge-guided directional walk mean smoothing (EDWMS), it can effectively calculate the mean of pixels along different directions then obtain denoised image with sharp edge. Experiments show that the proposed EDWMS outperforms compared algorithms in both edge sharpness and color saturation.
Resilience Training Efficacy by Instructor Specialization: A Program Evaluation with Army Recruits

Abstract A growing recognition of the importance of resilience skills for psychological health and optimal performance has led to the development of a wide array of resilience trainings. Across the military, resilience training has been implemented by military personnel and training experts. To date, no direct assessment of the comparative efficacy of instructor type on training outcomes has been conducted. To that end, we conducted a program evaluation that examined differences in the efficacy of a two-hour resilience training course for new recruits in Basic Combat Training on resilience-focused knowledge and skills as a function of instructor specialization. Soldiers (n = 401) received training from either a training specialist or a drill sergeant. Findings revealed that soldiers’ knowledge and perceived resilience skills improved regardless of instructor type. Soldiers preferred training specialists to drill sergeants; however, soldiers who received training from drill sergeants had greater improvements in knowledge as compared to soldiers instructed by training specialists. Soldiers with high levels of pre-training resilience who received training from drill sergeants showed the greatest improvements in knowledge. We conclude that drill sergeants, when provided with train-the-trainer preparation by subject matter experts, can efficaciously provide resilience training to new Army recruits during Basic Combat Training.
Deep learning for post‐hurricane aerial damage assessment of buildings

This study aims to improve post‐disaster preliminary damage assessment (PDA) using artificial intelligence (AI) and unmanned aerial vehicle (UAV) imagery. In particular, a stacked convolutional neural network (CNN) architecture is introduced and trained on an in‐house visual dataset from Hurricane Dorian. To account for the ordinality of damage level classes, the cross‐entropy classification loss function is replaced with the square of earth mover's distance (EMD2) loss. The trained model achieves 65.6% building localization precision and 61% (90% considering ±1 class deviation from ground‐truth) classification accuracy. It also exhibits a positive accuracy–confidence correlation, which is valuable for model assessment in situations where ground‐truth information is not readily available. Finally, the outcome of damage assessment is compared with the literature by examining the relationship between building size and number of stories, and severity of induced disaster damage.
Occurrence and Sources of Synthetic Musk Fragrances in the Sewage Treatment Plants and the Han River, Korea

Levels of synthetic musk fragrances (SMFs) and various personal care products (PCPs) were measured in the Han River and its tributaries in Seoul, Korea. The most abundant SMF in all river and PCP samples was 4,6,6,7,8,8-hexamethyl-1,3,4,7-tetrahydrocyclopenta(g)sochromene (HHCB), followed by 1-(3,5,5,6,8,8-hexamethyl-6,7-dihydronaphthalen-2-yl)ethanone (AHTN), musk ketone (MK), and 1,1,2,3,3-pentamethyl-2,5,6,7-tetrahydroinden-4-one (DPMI). The most abundant SMF in both PCPs and the Han River samples was HHCB, followed by AHTN. Moving from upstream to downstream in the Han River, the median SMF concentration was 6.756, 2.945, 0.304, and 0.141 μg/L in the sewage treatment plant (STP) influents, effluents, tributaries, and mainstream, respectively, implying that effective SMF removal was achieved during the sewage treatment process, followed by dilution in the receiving water. Four STPs using advanced biological treatment processes had removal efficiencies of 58.5%, 56.8%, and 38.1% for HHCB, AHTN, and MK, respectively. The highest SMF concentrations in the tributaries were observed at locations close to the STPs. Our study confirmed that the main source of SMFs in the receiving water were sewage effluents containing untreated SMFs, which largely originate from household PCPs, especially hair care products (e.g., shampoo) and perfumes.
The utilization of machine learning techniques in the building design stage: a qualitative review

This item is part of: Boarin, P., Haarhoff, E. , Manfredini, M. , Mohammadzadeh, M. , Premier, A. , (2021). Rethinking Sustainable Pacific Rim Territories. Proceedings of the 2020 APRU Sustainable Cities and Landscapes Hub PhD Symposium, Future Cities Research Hub, School of Architecture and Planning of the University of Auckland. ISBN: 978-0-473-53616-9ABSTRACTMachine learning (ML) is a subdivision of artificial intelligence (AI) technology that has been extensively researched and applied in the building and construction industry for the past few years, particularly in the building design process. It yields significant benefits to the sector through its learning method that not only offers automation for repetitive complex design tasks and evaluation for decision-making functions but also optimization of building performances. This study investigates the existing exploration of the machine learning techniques utilized in the building design process to improve both the performance and result of the building design in the early design stage. From the 27 publications discussed in this paper, the Genetic Algorithm was the most utilized technique in the building design research area, followed by Neural Network. However, the employment of machine learning in this area mostly focused on particular building aspects, creating an opportunity for further studies to develop comprehensive building design solutions through the machine learning approach
A Critical Review of Osmosis-Associated Imbibition in Unconventional Formations

In petroleum engineering, imbibition is one of the most important elements for the hydraulic fracturing and water flooding processes, when extraneous fluids are introduced to the reservoir. However, in unconventional shale formations, osmosis has been often overlooked, but it can influence the imbibition process between the working fluid and the contacting formation rocks. The main objective of this study is to understand effects of fluid–rock interactions for osmosis-associated imbibition in unconventional formations. This paper summarizes previous studies on imbibition in unconventional formations, including shale, tight carbonate, and tight sandstone formations. Various key factors and their influence on the imbibition processes are discussed. Then, the causes and role of osmotic forces in fluid imbibition processes are summarized based on previous and recent field observations and laboratory measurements. Moreover, some numerical simulation approaches to model the osmosis-associated imbibition are summarized and compared. Finally, a discussion on the practical implications and field observations of osmosis-associated imbibition is included.
Seasonal variations in some quality parameters of milk produced in Khorasan Razavi Province, Iran

Cow’s milk as the most important product of dairy systems is among the main foods for human consumption all over the world (Pereira, 2014). Because of its high nutritional value, milk offers excellent conditions for microbial growth, thus requiring proper conservation to avoid rapid deterioration by spoilage microorganisms and pathogenic bacteria (Lee et al., 2019). One of the most important contaminants of milk and dairy products are mesophilic bacteria, including several types of pathogens like Salmonella spp. and Mycobacterium spp. (Lee et al., 2012; Moosavy et al., 2019; Mullan, 2019). Moreover, milk may also contain increased somatic cell counts (SCC), mainly formed by leukocytes from blood origin and epithelial cells from scaling-off as a consequence of inflammation of the mammary gland (Fagundes et al., 2011). In this context, total mesophilic count (TMC) and SCC have been defined as the most reliable indicators for evaluating the quality of raw milk received in dairy processing factories worldwide, especially in the developed countries (Coelho et al., 2017). In the Iranian milk production system, raw milk is categorized into four grades (excellent, A, B and C), depending on maximum permitted levels (MPL) for SCC and TMC (Institute of Standard and Industrial Research of Iran, 2014). The higher MPLs were established for grade C milk, which should contain maximum SCC and TMC levels of 105 cells/mL (Log 5.69 cells/mL) and 106 colony forming units (CFU)/mL (Log 6.0 CFU/mL), respectively (Institute of Standard and Industrial Research of Iran, 2014). The main contributing factors for microbial contamination of raw milk are related to milking hygiene and parlous conditions, cow udder soundness, raw milk collection, reserving and handling to the processing factories (Tassew & Seifu, 2011; Kara & Aslan, 2020). Additionally, milk and dairy products are exposed to different chemical contaminants such as antibiotics and other drug residues, neutralizing and preservatives residues (Iqbal, 2017; Müller et al., 2020). Among these contaminants, antibiotics residues represent a worldwide concern, since they are broadly used to control, treat or prevent different diseases, increase growth rate, regulate reproduction, or even improve the production efficiency of the dairy animals (Oliveira et al., 2020). The issue of antibiotic residues in milk is not a new problem. In the early 1960’s, over 6% of the raw milk marketed in the United States were contaminated with antibiotic residues, although recent surveys indicated that the contamination percentage in the country decreased to 3.7% (Grunwald & Petz, 2003). Previous studies conducted in Iran indicated that antibiotic residues have been occasionally detected in raw cow’s milk (Ghanavi et al., 2013; Moghadam et al., 2016).
N-Carbon coated P-W2C composite as efficient electrocatalyst for hydrogen evolution reactions over the whole pH range

Development of a highly efficient and stable hydrogen evolution reaction (HER) electrocatalyst based on non-precious-metal remains a great challenge. Herein, we report P-modified tungsten carbide encapsulated in N-doped carbon (P-W2C@NC) as an efficient and stable HER electrocatalyst over the whole pH range (0–14), prepared by annealing polyoxometalate (H3PW12O40·xH2O) and dicyandiamide at a high temperature. To achieve a current density of 10 mA cm−2, P-W2C@NC required an overpotential of 89 mV in acid, 63 mV in alkaline solution and 185 mV in neutral solution. This is the first case of a tungsten-carbide-based HER electrocatalyst operating at all pH values with high activity and stability, and might provide some new routes for the exploration of tungsten-based Pt-like electrocatalysts for the HER.
Bayesian analysis of a multivariate spatial ordered probit model

Abstract Many phenomena are correlated and spatially dependent. In addition, some of them are ordinal discrete responses. Thus, a model is needed to capture the interactions of multivariate ordinal outcomes and spatial dependences. Following Smith and LeSage (2004) and Jeliazkov et al. (2008), this study proposes a new algorithm for a multivariate spatial ordered probit (MSOP) model to address this need. In applying this model, the parameters are calculated using the Bayesian inference based on Markov chain Monte Carlo (MCMC) sampling. The validity and accuracy of the MSOP model is verified by simulated datasets, and the model performs very well with the simulated data. In addition, this study illustrates the model by applying it to two response variables, self-rated health, and life satisfaction of elderly people in 18 representative provinces in mainland China. The empirical results show that the spatial dependences are indispensable on the response variables.
Numerical and Experimental Investigation on the Combustion of Premixed Propane – Air Mixtures

The behaviour of a premixed propane flame in three dimensions was studied numerically and experimentally in a jet flow combustor at different equivalence ratio, Reynolds numbers and turbulent intensity. The detailed attract here has come up with data of propane -air mixtures flame propagation over a range of equivalence ratios (e) between 0.6 lean flame to 1.3 rich flame on environmental conditions of temperature and atmospheric pressure. The instantaneous flame was visualized using a high-speed camera on the domain of the burner of 100 mm diameter. From 174 to 472 images were recorded for each experimental test. Flame surface density was obtained from the instantaneous image of the flame. The influence of the flame area density in the evaluation of the flame propagation will be discussed. The study shows that the increase in turbulent intensity leads to increase the turbulent flame propagation speed subsequently increase in flame area density at a constant an equivalence ratio value. Also, it was shown that the wrinkling flame shape is the dominant characteristic leading to the increased turbulence intensity. The research results are expected to be used for developing jet flow combustor burners.
Effects of Marsh Migration on Flooding, Saltwater Intrusion, and Crop Yield in Coastal Agricultural Land Subject to Storm Surge Inundation

Low‐lying coastlines are vulnerable to sea‐level rise and storm surge salinization, threatening the sustainability of coastal farmland. Most crops are intolerant of salinity, and minimization of saltwater intrusion is critical to crop preservation. Coastal wetlands provide numerous ecosystem services, including attenuation of storm surges. However, most research studying coastal protection by marshes neglects consideration of subsurface salinization. Here, we use two‐dimensional, variable‐density, coupled surface‐subsurface hydrological models to explore how coastal wetlands affect surface and subsurface salinization due to storm surges. We evaluate how marsh width, surge height, and upland slope impact the magnitude of saltwater intrusion and the effect of marsh migration into farmland on crop yield. Results suggest that along topographically low coastlines subject to storm surges, marsh migration into agricultural fields prolongs the use of fields landward of the marsh while also protecting groundwater quality. Under a storm surge height of 3.0 m above mean sea level or higher and terrestrial slope of 0.1%, marsh migration of 200 and 400 m protects agricultural yield landward of the marsh‐farmland interface compared to scenarios without migration, despite the loss of arable land. Economic calculations show that the maintained yields with 200 m of marsh migration may benefit farmers financially. However, yields are not maintained with migration widths over 400 m or surge height under 3.0 m above mean sea level. Results highlight the environmental and economic benefits of marsh migration and the need for more robust compensation programs for landowners incorporating coastal wetland development as a management strategy.
Theoretical Investigation of a Pin Fin Heat Sink Performance for Electronic Cooling using Different Alloys Materials

Electronic cooling plays a role in removing the electronic equipment’s heat rate to prevent failure from occurring. Electronic cooling performance is based on many parameters, such as thermal characteristics and material type design. Pure aluminium, copper – aluminium, and aluminium - beryllium are selected for predicting the performance of a heat sink. It was observed that the presence of Aluminium-copper alloy raises the performance of the heat sink compared with that of the pure aluminium. In contrast, the heat sink performance using aluminium - beryllium alloy was less than that of the reference material (pure aluminium). It was found that the heat dissipated from the heat sink increases by 1.4 % with using aluminium-copper alloy instead of using pure aluminium while the heat dissipated drops by 2% with using aluminium - beryllium alloy compared with that of using pure aluminium. Further, the heat sink mass decreases with the use of the aluminium-beryllium and increases with using copper - aluminium instead of pure aluminium. Whereas the mass of the heat sink using aluminium-copper alloy is higher than that of the pure aluminium by 2.3% while the mass of the heat sink using aluminium - beryllium alloy is less than that of the pure aluminium by 2.4%.