Miracle-dz/UniFAR-FTUs huggingface dataset:
Studying the feasibility of using microirrigation systems for vegetable production in a canal command area

Field investigations were carried out for 3 years with the aim of studying the feasibility of using microsprinkler and drip irrigation systems for vegetable production in a canal command area. These systems were compared with the existing flood irrigation method for onion production with four irrigation levels, viz. 0.60, 0.80, 1.00 and 1.20 of irrigation water to cumulative pan evaporation ratio (IW/CPE). Microsprinkler and drip irrigation systems were also compared with fertigation rate of 100 (50:25:25 NPK), 150 (75:37.5:37.5 NPK) and 200 (100: 50: 50 NPK) kg ha−1. Microirrigation systems resulted in higher onion yield and greater profitability than surface irrigation at each irrigation schedule. However, microsprinklers indicated better economics than a drip irrigation system. Microsprinkler, drip and surface irrigation system with 1.20 IW/CPE of irrigation produced maximum crop yields of 34.34, 33.10 and 22.57 t ha−1, respectively. Increased crop yield with microsprinkler and drip irrigation is the factor behind higher profitability than existing surface irrigation. Reduction in nutrient application by 25% in fertigation from the dose of flood irrigation did not reduce yield and net returns significantly. But net return was significantly higher in microsprinkler (Rs 67 334 ha−1) than drip (Rs 59 930 ha−1) fertigation. The overall results of the present study favoured microsprinkler over existing irrigation methods for onion production in a canal command area with higher profit under limited available surface water. Copyright © 2008 John Wiley & Sons, Ltd.
FA-LSTM: A Novel Toxic Gas Concentration Prediction Model in Pollutant Environment

Real-time monitoring and accurate prediction of toxic gas concentration in the future are of great significance for emergency capability assessment and rescue work. At present, the method of gas concentration prediction based on artificial intelligence still has problems of low accuracy, slow convergence speed and equal feature importance. This paper proposes a feature-aware LSTM model to predict pollutant gas concentration. First of all, we design a set of multi-component toxic gas monitoring equipment that applies in pollution environment, which can at the same time monitor CO, NO2, NH3, HCN, H2S and SO2, six common pollutants; To accurate estimate the toxic gas concentration, we combine the collected the gas data and the environmental parameters and regard them as the input features, and then we obtain toxic gas data based on the sampling policy and the environmental data as our data-set. Finally, we train a FA-LSTM gas concentration prediction model on these data-set. We test the proposed model and compared with ARIMA, ETS and BP network on the same test set. Experimental results show that the proposed model outperforms traditional concentration prediction model. Also, it is better than other state-of-the-art models in predicting accuracy.
Compost Tea: Principles and Prospects For Plant Disease Control

An increasing body of experimental evidence indicates that plant disease can be suppressed by treating plant surfaces with a variety of water-based compost preparations, referred to in the literature as watery fermented compost extracts or compost teas. The terms nonaerated compost teas (NCT) and aerated compost teas (ACT) are used in this review to refer to the common production methods that diverge in the intent to actively aerate. Very little data directly compares the efficacy of NCT and ACT for plant disease suppression. A variety of foliar plant pathogens and/or diseases have been suppressed by applications of NCT while few controlled studies have examined ACT. For some diseases the level of control would be considered inadequate for conventional agriculture; organic producers with limited control options consider partial disease control to be an important improvement. For both compost tea production methods, decisions that influence pathogen suppression include choice of compost feedstocks, compost age, water ratio, fermentation time, added nutrients, temperature and pH. Application technology choices include the dilution ratio, application equipment, timing, rates, spray adjuncts and adding specific microbial antagonists. Increased understanding of compost tea microbiology and the survival and interactions of microbes on plants surfaces should make it possible to modify compost tea production practices and application technology to optimize delivery of a microflora with multiple modes of pathogen suppression. Innovative growers and practitioners are leading the development of new compost tea production methods and uses, generating many potential research opportunities. The use of compost tea as part of an integrated plant health management strategy will require much additional whole systems research by a cohesive team of farmers and experts in composting, plant pathology, phyllosphere biology, molecular microbial ecology, fermentation science, plant physiology, plant breeding, soil science, and horticulture.
Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography.

Importance Stereoelectroencephalography (SEEG) has become the criterion standard in case of inconclusive noninvasive presurgical epilepsy workup. However, up to 40% of patients are subsequently not offered surgery because the seizure-onset zone is less focal than expected or cannot be identified. Objective To predict focality of the seizure-onset zone in SEEG, the 5-point 5-SENSE score was developed and validated. Design, Setting, and Participants This was a monocentric cohort study for score development followed by multicenter validation with patient selection intervals between February 2002 to October 2018 and May 2002 to December 2019. The minimum follow-up period was 1 year. Patients with drug-resistant epilepsy undergoing SEEG at the Montreal Neurological Institute were analyzed to identify a focal seizure-onset zone. Selection criteria were 2 or more seizures in electroencephalography and availability of complete neuropsychological and neuroimaging data sets. For validation, patients from 9 epilepsy centers meeting these criteria were included. Analysis took place between May and July 2021. Main Outcomes and Measures Based on SEEG, patients were grouped as focal and nonfocal seizure-onset zone. Demographic, clinical, electroencephalography, neuroimaging, and neuropsychology data were analyzed, and a multiple logistic regression model for developing a score to predict SEEG focality was created and validated in an independent sample. Results A total of 128 patients (57 women [44.5%]; median [range] age, 31 [13-58] years) were analyzed for score development and 207 patients (97 women [46.9%]; median [range] age, 32 [16-70] years) were analyzed for validation. The score comprised the following 5 predictive variables: focal lesion on structural magnetic resonance imaging, absence of bilateral independent spikes in scalp electroencephalography, localizing neuropsychological deficit, strongly localizing semiology, and regional ictal scalp electroencephalography onset. The 5-SENSE score had an optimal mean (SD) probability cutoff for identifying a focal seizure-onset zone of 37.6 (3.5). Area under the curve, specificity, and sensitivity were 0.83, 76.3% (95% CI, 66.7-85.8), and 83.3% (95% CI, 72.30-94.1), respectively. Validation showed 76.0% (95% CI, 67.5-84.0) specificity and 52.3% (95% CI, 43.0-61.5) sensitivity. Conclusions and Relevance High specificity in score development and validation confirms that the 5-SENSE score predicts patients where SEEG is unlikely to identify a focal seizure-onset zone. It is a simple and useful tool for assisting clinicians to reduce unnecessary invasive diagnostic burden on patients and overutilization of limited health care resources.
Neurofilament markers in serum and cerebrospinal fluid of patients with amyotrophic lateral sclerosis

Abstract This study aims to determine the serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NFL) and phosphorylated neurofilament heavy chain (pNFH) in amyotrophic lateral sclerosis (ALS) patients, and to explore their feasibility as valid biomarkers for quantifying disease progression and predicting individual prognosis. 52 patients with ALS and 30 controls with noninflammatory neurological diseases were included. NFL and pNFH levels in serum and CSF were measured by enzyme‐linked immunosorbent assay. Our findings showed that serum and CSF levels of NFL and pNFH in ALS patients were significantly increased. These values were negatively correlated with disease duration (except CSF NFL with disease duration) and ALSFRS‐r score, and positively correlated with disease progression rate (DPR) and upper motor neuron (UMN) score, but did not correlate with bilateral median and ulnar nerve compound muscle action potential (cMAP) amplitudes (except a weak correlation between CSF NFL and cMAP amplitudes). The optimal cut‐off values with high sensitivity and specificity were obtained in ROC curve analysis to discriminate ALS from controls. Kaplan‐Meier survival curves illustrated that survival was significantly shorter for patients with higher neurofilament levels at diagnosis. The Cox proportional hazards regressions confirmed that NFL and pNFH were significant predictors of survival. Overall, NFL and pNFH in serum and CSF can be used as reliable biomarkers in ALS.
Auditory Interface for Teleoperation - Path Following Experimental Results

Abstract For teloperated unmanned vehicles, mishaps tend to occur during the periods of high workload, in situations where the operator must perform complex and stressful tasks. However, with many tasks performed simultaneously with flying, the relevant information is typically dispersed on a number of screens overloading the operator's visual channel. In order to address these unique human-factors problems associated with unmanned vehicles we suggest the use of an auditory display as a mean to reduce visual workload, to enhance situation awareness, and mitigate the visual and cognitive demands of contemporary marine teleoperations. Experiments were performed on the remotely operated surface marine platform (PlaDyPos) developed at the Laboratory for Underwater Systems and Technologies, Faculty of Electrical Engineering and Computing, University of Zagreb. The results show that the concept, guidance-by-sound is feasible in the real environment. The results are in line with previously obtained results from the real-time simulator showing that tracking quality can be further improved introducing supernormal auditory cues in order to provide better-than-normal operator's auditory resolution in the frontal region. We conclude that the use of hearing in the form of the auditory display emerges as an important advantage. Since practice has a major effect on performance, there is definitely more room for improvement in using interfaces we are not trained for.
On nonlinear Rudin-Carleson type theorem

Abstract. In this paper we study nonlinear interpolation problems for interpolation and peak-interpolation sets of function algebras. The subject goes back to the classical Rudin-Carleson interpolation theorem. In particular, we prove the following nonlinear version of this theorem: Let D̄ ⊂ C be the closed unit disk, T ⊂ D̄ the unit circle, S ⊂ T a closed subset of Lebesgue measure zero and M a connected complex manifold. Then for every continuous M -valued map f on S there exists a continuous M -valued map g on D̄ holomorphic on its interior such that g|S = f . We also consider similar interpolation problems for continuous maps f : S → M̄ , where M̄ is a complex manifold with boundary ∂M and interior M . Assuming that f(S) ∩ ∂M 6= ∅ we are looking for holomorphic extensions g of f such that g(D̄ \ S) ⊂ M .
Novel 1-D microstrip PBG cells

Novel one-dimensional (1-D) microstrip photonic bandgap (PBG) cells are proposed. They are sections of microstrip line with special perforation patterns etched on the line itself. As examples, two types of PBG cell are investigated. Simulation and experiments show that the cell exhibits remarkable slow-wave and band-stop effects. An equivalent L-C circuit is used to model the PBG cell. Several cells connected in series form an excellent band-stop filter.
Full-Length Transcriptome Sequencing of the Scleractinian Coral Montipora foliosa Reveals the Gene Expression Profile of Coral–Zooxanthellae Holobiont

Simple Summary Coral bleaching (the disintegration of coral–zooxanthellae symbionts) is one of the important factors leading to coral death. However, we still lack an understanding of the mechanism of coral–zooxanthellae symbiosis. One of the reasons is the lack of reliable transcriptome sequence data. In this paper, through PacBio Sequel II sequencing technology polished with the Illumina RNA-seq platform, the Montipora foliosa transcriptome was obtained. The function and isoform of symbiosis-related genes were analyzed. This study provides a valuable resource for the study of coral symbiosis. Abstract Coral–zooxanthellae holobionts are one of the most productive ecosystems in the ocean. With global warming and ocean acidification, coral ecosystems are facing unprecedented challenges. To save the coral ecosystems, we need to understand the symbiosis of coral–zooxanthellae. Although some Scleractinia (stony corals) transcriptomes have been sequenced, the reliable full-length transcriptome is still lacking due to the short-read length of second-generation sequencing and the uncertainty of the assembly results. Herein, PacBio Sequel II sequencing technology polished with the Illumina RNA-seq platform was used to obtain relatively complete scleractinian coral M. foliosa transcriptome data and to quantify M. foliosa gene expression. A total of 38,365 consensus sequences and 20,751 unique genes were identified. Seven databases were used for the gene function annotation, and 19,972 genes were annotated in at least one database. We found 131 zooxanthellae transcripts and 18,829 M. foliosa transcripts. A total of 6328 lncRNAs, 847 M. foliosa transcription factors (TFs), and 2 zooxanthellae TF were identified. In zooxanthellae we found pathways related to symbiosis, such as photosynthesis and nitrogen metabolism. Pathways related to symbiosis in M. foliosa include oxidative phosphorylation and nitrogen metabolism, etc. We summarized the isoforms and expression level of the symbiont recognition genes. Among the membrane proteins, we found three pathways of glycan biosynthesis, which may be involved in the organic matter storage and monosaccharide stabilization in M. foliosa. Our results provide better material for studying coral symbiosis.
Compensatory consumption during the COVID-19 pandemic: exploring the critical role of nostalgia in sport consumer behaviour

ABSTRACT During the COVID-19 pandemic, sport consumers have been deprived of many of their usual fitness activities due to social distancing measures. Individuals accordingly vary in perceptions, emotions, and behaviours regarding the COVID-19 situation. Thus, this study examined the interrelationships among the perception of COVID-19, boredom, nostalgia, and compensatory behaviours of sport consumers. Data were collected from 608 sport consumers in the United States and analysed using partial least squares structural equation modelling. Results showed that the perception of COVID-19 positively affected boredom and nostalgia. Boredom produced positive effects on nostalgia, browsing, and impulse buying behaviour with regard to fitness products. Nostalgia was positively associated with browsing, which was positively related to impulse buying behaviour. The present study revealed sport consumers’ compensatory responses to the distinctive emotions elicited by the perception of COVID-19.
The Fourier reconstruction of a head section

The Fourier reconstruction may be viewed simply in the spatial domain as the sum of each line integral times a weighting function of the distance from the line to the point of reconstruction. A modified weighting function simultaneously achieves accuracy, simplicity, low computation time, as well as low sensitivity to noise. Using a simulated phantom, the authors compare the Fourier algorithm and a search algorithm. The search algorithm required 12 iterations to obtain a reconstruction of accuracy and resolution comparable to that of the Fourier reconstruction, and was more sensitive to noise. To speed the search algorithm by using fewer interactions leaves decreased resolution in the region just inside the skull which could mask a subdural hematoma.
PHANTOM ECHOES 2: A Five-Eyes SDA Experiment on GEO Proximity Operations

On 12 April 2021, Mission Extension Vehicle-2 (MEV-2) conducted rendezvous and docking with INTELSAT 1002 as part of a commercial life-extension mission in Geostationary Earth Orbit (GEO). The defence science and technology (S&T) agencies of the Five-Eyes (FVEY) nations – the United Kingdom, United States, Australia, Canada and New Zealand – exploited this opportunity to successfully pursue a coordinated Space Domain Awareness (SDA) experiment, observing and scrutinising the dynamics and behaviours of the two satellites to improve allied capabilities for protection of allied spacecraft in GEO. This experiment, known as “PHANTOM ECHOES 2” (PE2), followed-on from an initial campaign undertaken in 2020 on the MEV-1 mission [1] and forms Phase II of a series of collaborative SDA activities conducted by the FVEY SDA S&T community on GEO proximity operations. These activities have been performed under The Technical Cooperation Program (TTCP), as part of a wider research initiative named “PHANTOM ECHOES”. In this paper, an overview of activity conducted within Phase II of the PHANTOM ECHOES experiment is presented; describing application of a FVEY SDA S&T sensor and processing architecture in observing the activities of MEV-2 from launch through to successful docking with INTELSAT 10-02. The paper first introduces the wider PHANTOM ECHOES initiative and the motivations for collection of real-world data on surrogate targets in Deep Space, before proceeding to provide an outline summary of specific observation campaigns conducted on orbital transfer and proximity docking phases of the MEV-2 mission. Preliminary data and results from these campaigns are then provided, highlighting where the FVEY SDA S&T community is exploring the challenges associated with flight safety of allied spacecraft in Geostationary Earth Orbit (GEO) and is identifying potential solutions. Copyright © 2021 Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS) – www.amostech. com
CAPTIVATING STEREOTYPES: NATIVE AMERICANS IN CAPTIVITY LITERATURE OF COLONIAL AMERICA

The purpose of this paper is to (re)consider representations of Native Americans in captivity narratives from the perspective of cultural studies. It is generally agreed among scholars that some of the early captivity narratives shaped the perceptions of Native Americans and contributed to the formation of stereotypes which later significantly affected the fates of these peoples. As “stereotyping involves a reduction of images and ideas to a simple and manageable form” and “the function of stereotypes is to perpetuate an artificial sense of difference between ‘self’ and ‘other’” (Loomba, 2000: 59–60), one important goal of this paper would be to evaluate the significance of these representations of Native Americans for the broader context of American studies, thus hopefully, shedding more light on the issues of (American) identity and power relations within the (American) society.
The use of damage functionals in earthquake engineering: A comparison between different methods

The behaviour of the EPP-SDOF model under seismic actions is analysed herein by different ‘damage functionals’ to define collapse under cyclic loading. In particular, the damage functionals based on the concept of maximum ductility and dissipated plastic energy are first compared. Afterwards the methods of Banon and Veneziano, Park and Ang and the linear cumulative law of plastic fatigue are reviewed and extensively analysed. Comparisons in the case of simple cyclic histories and in terms of acceleration collapse spectra are carried out with reference to significant earthquake records. In particular, it is shown in which cases the damage functionals of Banon and Veneziano, Park and Ang and the linear cumulative law of plastic fatigue, completely defined by the value of a single parameter, degenerate in the limit methods of ductility or dissipated energy and in which cases they provide similar results.
CONSEQUENTIAL FACTORS OF BIG DATA’S ANALYTICS CAPABILITY FOR DIGITAL TRANSFORMATION

The article aims to discover, by identifying the main models of its use descriptive, diagnostic, predictive and prescriptive the consequent factors of Big Data’s Analytics Capability in companies that seek Digital Transformation. The research had a quantitative approach, using a survey of data from companies located in the state of São Paulo Brazil. Structural Equation Modeling was used to validate the model. As a result, all hypotheses with direct and indirect relationships were accepted. Satisfaction was the construct that had the most explanatory power in the model. This study revealed that the transformation digital that occurred in companies is not limited to the area of technologies and systems, but also in the way professionals are being inserted in this context. It is necessary to invest more in analytical tools, as well as people trained in analysis of these models, in addition to a change of mindset, which will dictate the bias of the company’s strategic decision making. It will also be necessary to invest in professional training, so that those involved can better handle Big Data tools to increase their influence in the organizational decision-making process. FATORES CONSEQUENTES DA CAPACIDADE ANALÍTICA DE BIG DATA PARA TRANSFORMAÇÃO DIGITAL Resumo O artigo tem como objetivo investigar por meio da identificação dos principais modelos de sua utilização – descritiva, diagnóstica, preditivos e prescritivos – os fatores consequentes da Capacidade Analítica de Big Data em empresas que buscam a Transformação Digital. A pesquisa teve abordagem quantitativa, por meio de levantamento de dados junto a empresas localizadas no estado de São Paulo – Brasil. A Modelagem de Equações Estruturais foi usada para validar o modelo. Como resultado, todas as hipóteses com relações diretas e indiretas foram aceitas. Satisfação foi o construto que teve maior poder explicativo no modelo. Este estudo revelou que a transformação digital ocorrida nas empresas não se limita à área de tecnologia e sistemas, mas também na forma como os profissionais estão sendo inseridos nesse contexto. É necessário investir mais em ferramentas analíticas, bem como em pessoas treinadas na análise desses modelos, além de uma mudança de mentalidade, que ditará o viés da tomada de decisão estratégica da empresa. Também será necessário investir na capacitação profissional, para que os envolvidos manejem melhor as ferramentas de Big Data para aumentar sua influência no processo de tomada de decisão organizacional. Big Data’s Analytics Capability Congresso Transformação Digital 2020 2