bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic and morphological characterization of a new genotype of nervous necrosis virus circulating among Nile tilapia in the south of Egypt
Authors: Gherbawy Youssuf Ahmed , Thabet Maha Aboelkassem , Sultan Serageldeen 
Published: July 2023

AbstractNervous necrosis virus (NNV) is the causative agent of viral nervous necrosis in freshwater and marine fishes. In this study, NNV circulating among wild and farmed Nile tilapia (Oreochromis niloticus) was genetically and morphologically characterized using reverse transcription polymerase chain reaction (RT-PCR), sequencing analysis, and transmission electron microscopy (TEM). Brain, eye, and other organ (spleen, kidney, heart, and liver) specimens were collected from 87 wild (66) and farmed (21) Nile tilapia fish during their adult or juvenile stage at different localities in Qena and Sohag governorates in southern Egypt. Among them, 57/87 fish showed suspected NNV clinical signs, and 30/87 were healthy. The results revealed that NNV was detected in 66 out of 87 fish (58.62% in the wild and 17.24% in farmed Nile tilapia by RT-PCR), and the prevalence was higher among diseased (55.17%) than in healthy (20.69%) fish. NNV was detected in the brain, eye, and other organs. Using TEM, virion size variations based on the infected organs were observed. Nucleotide sequence similarity indicated that NNVs had a divergence of 75% from other fish nodaviruses sequenced in Egypt and worldwide. Phylogenetic analysis distinguished them from other NNV genotypes, revealing the emergence of a new NNV genotype in southern Egypt. In conclusion, NNV is circulating among diseased and healthy Nile tilapia, and a new NNV genotype has emerged in southern Egypt.
Improved Resolution Estimate for the Two-Dimensional Super-Resolution and a New Algorithm for Direction of Arrival Estimation with Uniform Rectangular Array
Authors: Liu Ping , Ammari Habib 
Published: August 2023

AbstractIn this paper, we develop a new technique to obtain improved estimates for the computational resolution limits in two-dimensional super-resolution problems and present a new idea for developing two-dimensional super-resolution algorithms. To be more specific, our main contributions are fourfold: (1) Our work improves the resolution estimates for number detection and location recovery in two-dimensional super-resolution problems; (2) As a consequence, we derive a stability result for a sparsity-promoting algorithm in two-dimensional super-resolution problems [or direction of arrival Problems (DOA)]. The stability result exhibits the optimal performance of sparsity promoting in solving such problems; (3) Inspired by the new techniques, we propose a new coordinate-combination-based model order detection algorithm for two-dimensional DOA estimation and theoretically demonstrate its optimal performance, and (4) we also propose a new coordinate-combination-based MUSIC algorithm for super-resolving sources in two-dimensional DOA estimation. It has excellent performance and enjoys some advantages compared to the conventional DOA algorithms.
Heterologous gene expression system for the production of hydrolyzable tannin intermediates in herbaceous model plants
Authors: Oda-Yamamizo Chihiro , Mitsuda Nobutaka , Milkowski Carsten , Ito Hideyuki , Ezura Kentaro , Tahara Ko 
Published: August 2023

AbstractAluminum toxicity is the main factor limiting the elongation of plant roots in acidic soil. The tree species Eucalyptus camaldulensis is considerably more resistant to aluminum than herbaceous model plants and crops. Hydrolyzable tannins (HTs) accumulating in E. camaldulensis roots can bind and detoxify the aluminum taken up by the roots. However, in herbaceous model plants, HTs do not accumulate and the genes involved in the HT biosynthetic pathway are largely unknown. The aim of this study was to establish a method for reconstituting the HT biosynthetic pathway in the HT non-accumulating model plant Nicotiana benthamiana. Four E. camaldulensis enzymes were transiently expressed in N. benthamiana leaves via Agrobacterium tumefaciens-mediated transformation. These enzymes included dehydroquinate dehydratase/shikimate dehydrogenases (EcDQD/SDH2 and EcDQD/SDH3), which catalyze the synthesis of gallic acid, the first intermediate of the HT biosynthetic pathway that branches off from the shikimate pathway. The others were UDP-glycosyltransferases (UGT84A25 and UGT84A26), which catalyze the conversion of gallic acid to β-glucogallin, the second intermediate. The co-expression of the EcDQD/SDHs in transgenic N. benthamiana leaf regions promoted the synthesis of gallic acid. Moreover, the co-expression of the UGT84As in addition to the EcDQD/SDHs resulted in the biosynthesis of β-glucogallin, the universal metabolic precursor of HTs. Thus, we successfully reconstituted a portion of the HT biosynthetic pathway in HT non-accumulating N. benthamiana plants. This heterologous gene expression system will be useful for co-expressing candidate genes involved in downstream reactions in the HT biosynthetic pathway and for clarifying their in planta functions.
Precise orbit determination of LEO satellites: a systematic review
Authors: Selvan Kannan , Siemuri Akpojoto , Prol Fabricio S. , Välisuo Petri , Bhuiyan M. Zahidul H. , Kuusniemi Heidi 
Published: August 2023

AbstractThe need for precise orbit determination (POD) has grown significantly due to the increased amount of space-based activities taking place at an accelerating pace. Accurate POD positively contributes to achieving the requirements of Low-Earth Orbit (LEO) satellite missions, including improved tracking, reliability and continuity. This research aims to systematically analyze the LEO–POD in four aspects: (i) data sources used; (ii) POD technique implemented; (iii) validation method applied; (iv) accuracy level obtained. We also present the most used GNSS systems, satellite missions, processing procedures and ephemeris. The review includes studies on LEO–POD algorithms/methods and software published in the last two decades (2000–2021). To this end, 137 primary studies relevant to achieving the objective of this research were identified. After the investigation of these primary studies, it was found that several types of POD techniques have been employed in the POD of LEO satellites, with a clear trend observed for techniques using reduced-dynamic model, least-squares solvers, dual-frequency signals with undifferenced phase and code observations in post-processing mode. This review provides an understanding of the various POD techniques, dataset utilized, validation techniques, and accuracy level of LEO satellites, which have interest to developers of small satellites, new researchers and practitioners.
Factors influencing low incidence of double brooding in the Great Reed Warbler
Authors: Trnka Alfréd , Samaš Peter 
Published: July 2023

AbstractDouble brooding, the laying of a second clutch after successfully fledging young from a first nest in a season, is a common reproductive strategy among short-lived birds to increase annual breeding success. Nevertheless, there is widespread intra- and interspecific variation in the probability of producing a second clutch. Given that the frequency of double brooding could affect population growth rate, knowing what factors contribute to this phenomenon is also important in the conservation management of threatened facultative double-brooded species. Here, we examine the frequency of double brooding and the factors affecting the probability of this reproductive strategy in a population of the Great Reed Warbler, Acrocephalus arundinaceus, in south-western Slovakia. Results of a 15-year study (2008–2022) revealed low overall rate of double brooding in the Great Reed Warbler (5.6% per year, 0–15.4%). The length of breeding season, timing of the first clutch laying date and the size of the first broods were key factors influencing the female's decision to initiate a second clutch. On the other hand, successful brood parasitism did not affect second clutch initiation, which contrasts with our prediction. Given that only monogamous or primary females initiated a second clutch after successfully rearing a first one, we assume that producing two broods within the same season may be an alternative strategy for monogamous males to increase their annual reproductive output in this facultatively polygynous species. Therefore, due to relatively high rate of polygyny, we probably cannot expect higher rate of double broodings in the Great Reed Warbler in the future either.
A survey of uncertainty in deep neural networks
Authors: Gawlikowski Jakob , Tassi Cedrique Rovile Njieutcheu , Ali Mohsin , Lee Jongseok , Humt Matthias , Feng Jianxiang , Kruspe Anna , Triebel Rudolph , Jung Peter , Roscher Ribana , Shahzad Muhammad , Yang Wen , Bamler Richard , Zhu Xiao Xiang 
Published: July 2023

AbstractOver the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more and more important. However, basic neural networks do not deliver certainty estimates or suffer from over- or under-confidence, i.e. are badly calibrated. To overcome this, many researchers have been working on understanding and quantifying uncertainty in a neural network’s prediction. As a result, different types and sources of uncertainty have been identified and various approaches to measure and quantify uncertainty in neural networks have been proposed. This work gives a comprehensive overview of uncertainty estimation in neural networks, reviews recent advances in the field, highlights current challenges, and identifies potential research opportunities. It is intended to give anyone interested in uncertainty estimation in neural networks a broad overview and introduction, without presupposing prior knowledge in this field. For that, a comprehensive introduction to the most crucial sources of uncertainty is given and their separation into reducible model uncertainty and irreducible data uncertainty is presented. The modeling of these uncertainties based on deterministic neural networks, Bayesian neural networks (BNNs), ensemble of neural networks, and test-time data augmentation approaches is introduced and different branches of these fields as well as the latest developments are discussed. For a practical application, we discuss different measures of uncertainty, approaches for calibrating neural networks, and give an overview of existing baselines and available implementations. Different examples from the wide spectrum of challenges in the fields of medical image analysis, robotics, and earth observation give an idea of the needs and challenges regarding uncertainties in the practical applications of neural networks. Additionally, the practical limitations of uncertainty quantification methods in neural networks for mission- and safety-critical real world applications are discussed and an outlook on the next steps towards a broader usage of such methods is given.
DynaQ: online learning from imbalanced multi-class streams through dynamic sampling
Authors: Sadeghi Farnaz , Viktor Herna L. , Vafaie Parsa 
Published: July 2023

AbstractOnline supervised learning from fast-evolving data streams, particularly in domains such as health, the environment, and manufacturing, is a crucial research area. However, these domains often experience class imbalance, which can skew class distributions. It is essential for online learning algorithms to analyze large datasets in real-time while accurately modeling rare or infrequent classes that may appear in bursts. While methods have been proposed to handle binary class imbalance, there is a lack of attention to multi-class imbalanced settings with varying degrees of imbalance in evolving streams. In this paper, we present the Dynamic Queues (DynaQ) algorithm for online learning in multi-class imbalanced settings to fill this knowledge gap. Our approach utilizes a batch-based resampling method that creates an instance queue for each class to balance the number of instances. We maintain a queue threshold and remove older samples during training. Additionally, we dynamically oversample minority classes based on one of four rate parameters: recall, F1-score, $$\kappa _m$$

κ
m

, and Euclidean distance. Our learning algorithm consists of an ensemble that uses sliding windows and a soft voting schema while incorporating a drift detection mechanism. Our experimental results demonstrate the superiority of the DynaQ approach over state-of-the-art methods.
The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain
Authors: Lehner Manuela , Rotach Mathias W. 
Published: July 2023

AbstractEddy-covariance data from five stations in the Inn Valley, Austria, are analyzed for stable conditions to determine the gap scale that separates turbulent from large-scale, non-turbulent motions. The gap scale is identified from (co)spectra calculated from different variables using both Fourier analysis and multi-resolution flux decomposition. A correlation is found between the gap scale and the mean wind speed and stability parameter z/L that is used to determine a time-varying filter time, whose performance in separating turbulent and non-turbulent motions is compared to the performance of constant filter times between 0.5 and 30 min. The impact of applying different filter times on the turbulence statistics depends on the parameter and location, with a comparatively smaller impact on the variance of the vertical wind component than on the horizontal components and the turbulent fluxes. Results indicate that a time-varying filter time based on a multi-variable fit taking both mean wind speed and stability into account and a constant filter time of 2–3 min perform best in that they remove most of the non-turbulent motions while at the same time capturing most of the turbulence. For the studied sites and conditions, a time-varying filter time does not outperform a well chosen constant filter time because of relatively small variations in the filter time predicted by the correlation with mean flow parameters.
EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies
Authors: Koenig Thomas , Diezig Sarah , Kalburgi Sahana Nagabhushan , Antonova Elena , Artoni Fiorenzo , Brechet Lucie , Britz Juliane , Croce Pierpaolo , Custo Anna , Damborská Alena , Deolindo Camila , Heinrichs Markus , Kleinert Tobias , Liang Zhen , Murphy Michael M , Nash Kyle , Nehaniv Chrystopher , Schiller Bastian , Smailovic Una , Tarailis Povilas , Tomescu Miralena , Toplutaş Eren , Vellante Federica , Zanesco Anthony , Zappasodi Filippo , Zou Qihong , Michel Christoph M 
Published: July 2023

AbstractOver the last decade, EEG resting-state microstate analysis has evolved from a niche existence to a widely used and well-accepted methodology. The rapidly increasing body of empirical findings started to yield overarching patterns of associations of biological and psychological states and traits with specific microstate classes. However, currently, this cross-referencing among apparently similar microstate classes of different studies is typically done by “eyeballing” of printed template maps by the individual authors, lacking a systematic procedure. To improve the reliability and validity of future findings, we present a tool to systematically collect the actual data of template maps from as many published studies as possible and present them in their entirety as a matrix of spatial similarity. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps from ongoing or published studies. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps in the literature. The analysis of 40 included sets of template maps indicated that: (i) there is a high degree of similarity of template maps across studies, (ii) similar template maps were associated with converging empirical findings, and (iii) representative meta-microstates can be extracted from the individual studies. We hope that this tool will be useful in coming to a more comprehensive, objective, and overarching representation of microstate findings.
Surface soil moisture estimate from Sentinel-1 and Sentinel-2 data in agricultural fields in areas of high vulnerability to climate variations: the Marche region (Italy) case study
Authors: Brunelli Benedetta , De Giglio Michaela , Magnani Elisa , Dubbini Marco 
Published: July 2023

AbstractSurface soil moisture is a key hydrologic state variable that greatly influences the global environment and human society. Its significant decrease in the Mediterranean region, registered since the 1950s, and expected to continue in the next century, threatens soil health and crops. Microwave remote sensing techniques are becoming a key tool for the implementation of climate-smart agriculture, as a means for surface soil moisture retrieval that exploits the correlation between liquid water and the dielectric properties of soil. In this study, a workflow in Google Earth Engine was developed to estimate surface soil moisture in the agricultural fields of the Marche region (Italy) through Synthetic Aperture Radar data. Firstly, agricultural areas were extracted with both Sentinel-2 optical and Sentinel-1 radar satellites, investigating the use of Dual-Polarimetric Entropy-Alpha decomposition's bands to improve the accuracy of radar data classification. The results show that Entropy and Alpha bands improve the kappa index obtained from the radar data only by 4% (K = 0.818), exceeding optical accuracy in urban and water areas. However, they still did not allow to reach the overall optical accuracy (K = 0.927). The best classification results are reached with the total dataset (K = 0.949). Subsequently, Water Cloud and Tu Wien models were implemented on the crop areas using calibration parameters derived from literature, to test if an acceptable accuracy is reached without in situ observation. While the first model’s accuracy was inadequate (RMSD = 12.3), the extraction of surface soil moisture using Tu Wien change detection method was found to have acceptable accuracy (RMSD = 9.4).
Building rehabilitation, sustainable development, and rural settlements: a contribution to the state of the art
Authors: Mouraz Catarina P. , Ferreira Tiago Miguel , Silva J. Mendes 
Published: July 2023

AbstractThe quality of life in rural housing settlements is at the heart of territorial cohesion concerns across Europe and the United Nations’ sustainable development goals. However, the gap between urban and rural developments remains substantial, stressing the need to adopt integrated approaches for rural territories. These approaches should include heritage preservation strategies as a priority. Vernacular constructions integrate rural built heritage and comprise a sustainable response of communities in territories, stressing the pertinence of its rehabilitation. The aim of this paper is to raise awareness of this issue through a scoping review since it lacks general frameworks that may contribute towards perceiving rural territories and their constructions as catalysts of territorial cohesion and sustainable development. As a main goal, we provide insights on sustainable development and its importance in the global and European contexts, as well as the role of building rehabilitation towards its three dimensions—environmental, social, and economic. Additionally, the impact of rural settlements on territorial cohesion and global sustainability is stressed, and vernacular construction is highlighted as a component of rural heritage.
The future of protein feed: a case study of sustainable substitutes in the German livestock industry
Authors: Soisontes Sakson , Freund Florian , Laquai Verena 
Published: August 2023

AbstractThe use of imported soybean/soybean meal is criticized in the context of the sustainability discussion in Germany. Imported soybean is often associated with deforestation and genetic modification, which is largely viewed critically by consumers. This study aims to forecast changes in future demand for imported soybean/soybean meal and its possible substitutes in the German livestock industry. The two-round Delphi method was used in the study by sending questionnaires to 28 experts from four groups: food retailers, livestock associations, animal nutrition manufacturers and research institutes. Our main result is that the total use of soybeans in German livestock farming will decrease from almost 4 million tons of soybean equivalents in 2018/19 to approximately 3.4 million tons by 2030/31. In contrast, the share of non-GM soybean is forecast to increase from 26 to 53%. Factors that influence the increased use of non-GM protein feeds most are “specifications from downstream processors” and “demand from the feed industry.” Experts forecast that about 36% of imported soybean/soybean meal (from non-EU countries) for German livestock farming could be replaced by protein feed produced in the EU. Rapeseed was considered to have a particularly high potential for production in the EU, followed by soybean and sunflower. Experts considered the factors: “requirements by the food retailers,” “reasonable price,” “political regulation” and “better profitability for the producer” as the most influential for extended use of regional protein feeds.
Lefebvrian analysis of livestock keeping in Fingo Village, Makhanda (Grahamstown), South Africa
Authors: Memela Sinenhlanhla 
Published: July 2023

AbstractPublic nuisance caused by livestock has resulted in many local governments having a designated area to keep them, called commonages. In Makhanda, livestock owners often do not effectively utilize commonages; they let animals wander in the streets and keep them in the backyards, which is against municipal regulations. This study uses Lefebvre's production of the space-spatial triad, which provides a holistic understanding of why bylaws are circumvented in Fingo Village. The focus is on the dialectic process in the spatial triad between representational space and representations of space to understand spatial patterns. Purposive sampling methods were used to select ten household plots in Fingo Village. Primary data was collected using semi-structured interviews. The study's findings reveal that bylaws are circumvented because there are spatial contradictions between the conceived land use designations of the Makana Municipality and the lived experiences of the users/inhabitants. Three issues were noted: conceived ideas were not inline with cultural beliefs about livestock keeping in backyard kraal; commonage geographic location was not ideal as it's not visible to residential areas so users can see them while grazing, which increased chances of livestock theft; and Makana Municipality not effectively enforcing regulations and administering commonages.