Estimating Waterbird Abundance on Catfish Aquaculture Ponds Using an Unmanned Aerial System

In this study, we examined the use of an unmanned aerial system (UAS) to monitor fish-eating birds on catfish (Ictalurus spp.) aquaculture facilities in Mississippi, USA. We tested 2 automated computer algorithms to identify bird species using mosaicked imagery taken from a UAS platform. One algorithm identified birds based on color alone (color segmentation), and the other algorithm used shape recognition (template matching), and the results of each algorithm were compared directly to manual counts of the same imagery. We captured digital imagery of great egrets (Ardea alba), great blue herons (A. herodias), and double-crested cormorants (Phalacrocorax auritus) on aquaculture facilities in Mississippi. When all species were combined, template matching algorithm produced an average accuracy of 0.80 (SD = 0.58), and color segmentation algorithm produced an average accuracy of 0.67 (SD = 0.67), but each was highly dependent on weather, image quality, habitat characteristics, and characteristics of the birds themselves. Egrets were successfully counted using both color segmentation and template matching. Template matching performed best for great blue herons compared to color segmentation, and neither algorithm performed well for cormorants. Although the computer-guided identification in this study was highly variable, UAS show promise as an alternative monitoring tool for birds at aquaculture facilities

Dataset for Controllable factors affecting accuracy and precision of human identification of animals from drone imagery

Dataset from the results of an experiment to determine how three controllable factors, flight altitude, camera angle, and time of day, affect human identification and counts of animals from drone images to inform best practices to survey animal communities with drones. We used a drone (unoccupied aircraft system, or UAS) to survey known numbers of eight animal decoy species, representing a range of body sizes and colors, at four GSD (ground sampling distance) values (0.35, 0.70, 1.06, 1.41 cm/pixel) representing equivalent flight altitudes (15.2, 30.5, 45.7, 61.0 m) at two camera angles (45° and 90°) and across a range of times of day (morning to late afternoon). Expert human observers identified and counted animals in drone images to determine how the three controllable factors affected accuracy and precision. Observer precision was high and unaffected by tested factors. However, results for observer accuracy revealed an interaction among all three controllable factors. Increasing flight altitude resulted in decreased accuracy in animal counts overall; however, accuracy was best at midday compared to morning and afternoon hours, when decoy and structure shadows were present or more pronounced. Surprisingly, the 45° camera enhanced accuracy compared to 90°, but only when animals were most difficult to identify and count, such as at higher flight altitudes or during the early morning and late afternoon. We provide recommendations based on our results to design future surveys to improve human accuracy in identifying and counting animals from drone images for monitoring animal populations and communities

Remote detection of invasive alien species

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail

Approaches to interpret the outcomes of a network meta-analysis on comparative efficacy of different targeted therapies plus fulvestrant for advanced breast cancer following progression on prior endocrine therapy

Rama Jayaraj,1 Chellan Kumarasamy,2 Shanthi Sabarimurugan,3 Suja Samiappan41College of Health and Human Sciences, Charles Darwin University, Casuarina, Northern Territory 0909, Australia; 2University of Adelaide, Adelaide, South Australia 5005, Australia; 3School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, India; 4Department of Biochemistry, Bharathiar University, Coimbatore, Tamil Nadu, IndiaZhang and colleagues have conducted a network meta-analysis regarding fulvestrant combined targeted therapies for breast cancer, which has been published in the Cancer Management and Research journal.1 The study itself is interesting in its approach.View the original paper by Zhang and colleagues

A Novel and Efficient square root Computation Quantum Circuit for Floating-point Standard

It is imperative that quantum computing devices perform floating-point arithmetic operations. This paper presents a circuit design for floating-point square root operations designed using classical Babylonian algorithm. The proposed Babylonian square root, is accomplished using Clifford+T operations. This work focuses on realizing the square root circuit by employing the bit Restoring and bit Non-restoring division algorithms as two different approaches. The multiplier of the proposed circuit uses an improved structure of Toom-cook 2.5 multiplier by optimizing the T-gate count of the multiplier. It is determined from the analysis that the proposed square root circuit employing slow-division algorithms results in a T-count reduction of 80.51% and 72.65% over the existing work. The proposed circuit saves a significant number of ancillary qubits, resulting in a qubit cost savings of 61.67 % When compared to the existing work.peerReviewe

Estimating technical and irrigation water productivities in rice production in Tamil Nadu, India

The overall measure of farm-level technical efficiency is generally used to derive recommendations for the use of individual inputs. In this paper, joint estimation is made of technical and individual input-use (e.g. irrigation water productivity) efficiencies. This indicates that overall technical efficiency is not an indication of the efficiency level of all the individual inputs used. This is because the efficiency of individual inputs may vary and suggests that greater effort should be made to improve such efficiencies in comparison with overall technical efficiency. The model is applied to rice production in four tank-irrigated districts in Tamil Nadu, India, which is one of the most important tank-irrigated areas in India. The average technical efficiency is 62.8%, which indicates that in order to achieve the present level of production, 62.8% of the current level of input resources is sufficient. Average irrigation water productivity is estimated at ~34%, indicating that current output levels could be achieved with 66% less irrigation water. These findings also suggest the need for improvements in crop and water productivity. Thus, the paper makes a contribution in the form of a methodology development for possible adoption in future irrigation water productivity studies

T-Count optimized quantum circuit designs for single-precision floating-point division

The implementation of quantum computing processors for scientific applications includes quantum floating points circuits for arithmetic operations. This work adopts the standard division algorithms for floating-point numbers with restoring, non-restoring, and Goldschmidt division algorithms for single-precision inputs. The design proposals are carried out while using the quantum Clifford+T gates set, and resource estimates in terms of numbers of qubits, T-count, and T-depth are provided for the proposed circuits. By improving the leading zero detector (LZD) unit structure, the proposed division circuits show a significant reduction in the T-count when compared to the existing works on floating-point division

Molecular Investigation of miRNA Biomarkers as Chemoresistance Regulators in Melanoma: A Protocol for Systematic Review and Meta-Analysis

Introduction: Melanoma is a global disease that is predominant in Western countries. However, reliable data resources and comprehensive studies on the theragnostic efficiency of miRNAs in melanoma are scarce. Hence, a decisive study or comprehensive review is required to collate the evidence for profiling miRNAs as a theragnostic marker. This protocol details a comprehensive systematic review and meta-analysis on the impact of miRNAs on chemoresistance and their association with theragnosis in melanoma. Methods and analysis: The articles will be retrieved from online bibliographic databases, including Cochrane Review, EMBASE, MEDLINE, PubMed, Scopus, Science Direct, and Web of Science, with different permutations of ‘keywords’. To obtain full-text papers of relevant research, a stated search method will be used, along with selection criteria. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Protocols 2015 (PRISMA-P) standards were used to create this study protocol. The hazard ratio (HR) with a 95% confidence interval will be analyzed using Comprehensive Meta-Analysis (CMA) software 3.0. (CI). The pooled effect size will be calculated using a random or fixed-effects meta-analysis model. Cochran’s Q test and the I2 statistic will be used to determine heterogeneity. Egger’s bias indicator test, Orwin’s and the classic fail-safe N tests, the Begg and Mazumdar rank collection test, and Duval and Tweedie’s trim and fill calculation will all be used to determine publication bias. The overall standard deviation will be evaluated using Z-statistics. Subgroup analyses will be performed according to the melanoma participants’ clinicopathological and biological characteristics and methodological factors if sufficient studies and retrieved data are identified and available. The source of heterogeneity will be assessed using a meta-regression analysis. A pairwise matrix could be developed using either a pairwise correlation or expression associations of miRNA with patients’ survival for the same studies