Miracle-dz/UniFAR-FTUs huggingface dataset:
RELATIONSHIP OF NITRATE AND PHOSPHATE CONCENTRATION ON PHYTOPLANKTON PRIMARY PRODUCTIVITY IN DUMAI RIVERS OF RIAU PROVINCE

This research was conducted in January 2020 in the waters of the Sembilan Dumai River which aims to determine the concentration of nitrate and phosphate on the primary productivity of phytoplankton. The research method used in this research is the survey method while the determination of the research station was done by technic purposive sampling. The results showed that the average nitrate concentration ranged from 0.0194 0.0749 mg/l and the average phosphate concentration ranged from 0.1452 0.8502 mg/l. There are 6 classes of phytoplankton found in the waters of the Sembilan Dumai River, namely Bacillariophyceae, Cocinodiscophyceae, Chroococcophyceae, Cyanophyceae, Cyanobacteria and Xanthophyceae. The results of phytoplankton abundance calculations ranged from 74.07 280.09 Ind/L. The primary productivity value of phytoplankton for gross primary productivity ranged from 62.5 104.16 mgC/m 2 /jam, respiration values ranged from 20.83 41.66 mgC/m 2 /jam and the net primary productivity value ranged from 41.67 72.91 mgC/m 2 /jam. The results of the multiple linear regression test for the relationship between nitrate and phosphate on the primary productivity of phytoplankton at each station are shown by the mathematical equation Y = 60.18 + (-233,19,35) x and Y = 60.18 + 30.44x with the coefficient of determination ( R2) = 0.140 and (R2) = 0.226 and the correlation coefficient (r) = 0.631, the mathematical equation states that the relationship between nitrate and phosphate on the primary productivity of phytoplankton is strong.
Micro‐hydro generator fed frequency adaptive sliding mode controlled air conditioning system for remote and hilly areas

This paper presents a micro-hydro generator driven frequency adaptive sliding mode (FASM) control-based improved power quality permanent magnet brushless DC motor (PMBLDCM) driven air conditioning system for remote and hilly areas. In such locations, the grid availability is poor or limited. The self-excited asynchronous generator (SEAG) is highly suitable for micro-hydro power generation. The voltage and frequency regulations of SEAG systems are very poor. Therefore, an improved power quality FASM control of a new zeta function based modiﬁed CSC (ZFM-CSC) converter scheme is developed to drive the micro-hydro power driven SEAG fed air conditioning system. The conventional air-conditioning schemes are suitable for the grid fed system, where the frequency and voltage remain constant. However, these conventional control schemes are not suitable for a standalone SEAG based micro-hydro generator driven air conditioners since the frequency and voltage of this system vary frequently at different loadings and dynamic operating conditions. This leads to an incorrect estimation of reference source current in a conventional system, which in turn affects the system stability. The sudden change of loads in a conventional air conditioning system may de-magnetize and de-stabilize the micro-hydro driven SEAG. The experimental and simulated results presented validate the robustness of this system.
Platelet and Haemostasis are the Main Targets in Severe Cases of COVID-19 Infection; a System Biology Study

Introduction: Many proteomics-based and bioinformatics-based efforts are made to detect the molecular mechanism of COVID-19 infection. Identification of the main protein targets and pathways of severe cases of COVID-19 infection is the aim of this study. Methods: Published differentially expressed proteins were screened and the significant proteins were investigated via protein-protein interaction network using Cytoscape software V. 3.7. 2 and STRING database. The studied proteins were assessed via action map analysis to determine the relationship between individual proteins using CluePedia. The related biological terms were investigated using ClueGO and the terms were clustered and discussed. Results: Among the 35 queried proteins, six of them (FGA, FGB, FGG, and FGl1 plus TLN1 and THBS1) were identified as critical proteins. A total of 38 biological terms, clustered in 4 groups, were introduced as the affected terms. “Platelet degranulation” and “hereditary factor I deficiency disease” were introduced as the main class of the terms disturbed by COVID-19 virus. Conclusion: It can be concluded that platelet damage and disturbed haemostasis could be the main targets in severe cases of coronavirus infection. It is vital to follow patients’ condition by examining the introduced critical differentially expressed proteins (DEPs).
The Mechanism Analysis on Open-Circuit Back EMF in Fractional-Slot Concentrated Winding Permanent Magnet Machines Using Air-Gap Field Modulation Theory

This article investigates the production mechanism of the open-circuit back-electromotive force (back EMF) in fractional-slot concentrated winding permanent magnet (FSCW-PM) machines based on the air-gap field modulation (AFM) theory. The relationship between spatial PM field harmonics and temporal back EMF harmonics is discovered by using a general model, which is suitable for both stator-PM and rotor-PM machines. The analysis results reveal that the FSCW-PM machines produce their open-circuit back EMF on the basis of AFM, which means that each back EMF harmonic is induced not only by a specific single spatial field harmonic but also by several different spatial field harmonics. Furthermore, a general winding factor calculation formula for FSCW-PM machines is derived together with the general calculation formula of all back EMF harmonics. Finally, the analysis is verified numerically by the finite element method and experimentally.
The Ecological Niche of SARS-CoV-2-like Viruses in Bats, as Inferred from Phylogeographic Analyses of Rhinolophus Species

To date, viruses closely related to SARS-CoV-2 have been reported in four bat species: Rhinolophus acuminatus, Rhinolophus affinis, Rhinolophus malayanus, and Rhinolophus shameli. Here, we analysed 343 sequences of the mitochondrial cytochrome c oxidase subunit 1 gene (CO1) from georeferenced bats of the four Rhinolophus species identified as reservoirs of SARS-CoV-2-like viruses. Haplotype networks were constructed in order to investigate patterns of genetic diversity among bat populations of Southeast Asia. No strong geographic structure was found for the four Rhinolophus species, suggesting high dispersal capacity. The ecological niche of SARS-CoV-2 like viruses was predicted using the four localities of bat SARS-CoV-2-like viruses and the localities where bats showed identical or very similar CO1 haplotypes than virus-positive bats. The ecological niche of SARS-CoV-like viruses was deduced from the localities where bat SARS-CoV-like viruses were previously detected. The results show that the ecological niche of SARS-CoV2-like viruses includes several regions of mainland Southeast Asia whereas that of SARS-CoV-like viruses is mainly restricted to China. In agreement with these results, human populations in Laos, Vietnam, Cambodia, and Thailand appear to be much less affected by the Covid-19 pandemic than other countries of Southeast Asia. In the climatic transitional zone between the two ecological niches (southern Yunnan, northern Laos, northern Vietnam, and possibly Hainan and Taiwan), genomic recombination between highly divergent viruses is more likely to occur. Since recombinant viruses can threaten the benefit of vaccination campaigns, these regions should be under surveillance.
Identification of Vocs Responsible of Odour During Field Retting of Hemp Stems

Incorporation of natural fibres into polymers to manufacture biocomposites is a way of limiting the environmental impact of these materials. However, the fibres quality is essential to fulfil their assigned role as reinforcement in biocomposites. The extraction of fibres from hemp stems requires a retting step. Retting is a bioprocess applied to plant stems to easily separate fibres from the central woody part. Nowadays, this process is carried out directly on the field in an empirically way due to its dependence on environmental conditions which could cause problems of the inconsistency of the hemp fibres quality.During few weeks of retting, odours are generated by the degradation of plant material by microorganisms. The modification of these odours can be correlated with the progress of the retting degree of hemp stems. This change in odour is obviously combined with a change in the type and quantity of VOCs emitted. Identifying odours and VOCs emitted when the retting is optimal can lead to make sensors able to survey the progress of this biological process. Then, if this process is well controlled, much higher quality with more uniform fibres could be produced.This article will focus on the identification of the odour emitted when the optimal retting of the stems is reached as well as the identification of the VOCs analysed at this stage.
Faster deep neural network image processing by using vectorized posit operations on a RISC-V processor

Real-time processing of images and videos is becoming considerably crucial in modern applications of machine learning (ML) and deep neural networks. Having a faster and compressed floating point arithmetic can significantly increase the performance of such applications optimizing memory occupation and transfer of information. In this field, the novel posit number system is very promising. In this paper we exploit posit numbers to evaluate the performance of several machine learning algorithms in real-time image and video processing applications. Future steps will involve further hardware accelerations for native posit operations.
Sensitivity and stability of pretrained CNN filters

Convolutional Neural Network (CNN) is a powerful and successful deep learning technique for a variety of computer vision and image analysis applications. Interpreting and explaining the decisions of CNNs is one of the most challengeable tasks despite its significant success in various image analysis tasks. Topological Data Analysis (TDA) is an approach that exploits algebraic invariants from topology to analyse high dimensional and noisy datasets as well as growing challenges of big data applications. Persistent homology (PH) is an algebraic topology method for measuring topological features of shapes and/or functions at different distance or similarity resolutions. This work is an attempt to investigate the algebraic properties of pretrained CNN convolutional layer filters based on random Gaussian/Uniform distribution. We shall investigate the stability and sensitivity of the condition number of CNN filters during and post the model training with focus on class discriminability of the PH features of the convolved images. We shall demonstrate a strong link between the condition number of the CNN filters and their discriminating power of the PH representation. In particular, we shall establish that if small perturbation added to the original images then feature maps with well-conditioned filters will produce similar topological features to the original image. Our investigation and findings are based on training CNN’s with Digits, MNIST and CIFAR-10 datasets. Our ultimate interest in applying the results of these findings in designing appropriate CNN models for classifications of ultrasound tumor scan images. Preliminary results for these applications are encouraging.
1.5-kV and 2.2-m (Omega ) -cm (^{2}) Vertical GaN Transistors on Bulk-GaN Substrates

In this letter, vertical GaN transistors fabricated on bulk GaN substrates are discussed. A threshold voltage of 0.5 V and saturation current >2.3 A are demonstrated. The measured devices show breakdown voltages of 1.5 kV and specific ON-resistance of 2.2 mΩ-cm 2 , which translates to a figure-of-merit of V BR 2 /R ON ~1 × 10 9 V 2 Ω -1 · cm -2 .
AUTOMATED CLASSIFICATION OF SOLITARY PULMONARY NODULES USING CONVOLUTIONAL NEURAL NETWORK BASED ON TRANSFER LEARNING STRATEGY

This study aimed to propose an effective malignant solitary pulmonary nodule classification method based on improved Faster R-CNN and transfer learning strategy. In practice, the existing solitary pulmonary nodule classification methods divide the lung cancer images into two categories only: normal and cancerous. This study proposed the deep convolution neural network to classify the computed tomography (CT) images of lung cancer into four categories: lung adenocarcinoma, lung squamous cell carcinoma, metastatic lung cancer, and normal types of lung cancer. Some high-resolution lung CT images have unnecessary characters such as a large number of high-density continuity features, small-size lung nodule targets, CT image background complexity, and so forth. In this study, the CT image sub-block preprocessing strategy was used to extract nodule features for enhancement and alleviate the aforementioned problems. The experimental results showed that the proposed system was effective in resolving issues such as high false-positive rate and long classification time cost based on the original Faster R-CNN detection method. Meanwhile, the transfer learning strategy was used to improve the classification efficiency so as to avoid the overfitting problem caused by a few labeled samples of lung cancer datasets. The classification results were integrated using the majority vote algorithm. The classification results of the lung CT imaging showed that the proposed method had an average detection accuracy of 89.7% and reduced the rate of misdiagnosis to meet the clinical needs.
Uncertain citizenship

Uncertainty is central to the governance of citizenship, but in ways that erase, even deny, this uncertainty. This book investigates uncertain citizenship from the unique vantage point of 'citizenisation': twenty-first-century integration and naturalisation measures that make and unmake citizens and migrants, while indefinitely holding many applicants for citizenship in what Fortier calls the 'waiting room of citizenship'. Fortier's distinctive theory of citizenisation foregrounds how the full achievement of citizenship is a promise that is always deferred: if migrants and citizens are continuously citizenised, so too are they migratised. Citizenisation and migratisation are intimately linked within the structures of racial governmentality that enables the citizenship of racially minoritised citizens to be questioned and that casts them as perpetual migrants. Drawing on multi-sited fieldwork with migrants applying for citizenship or settlement and with intermediaries of the state tasked with implementing citizenisation measures and policies, Fortier brings life to the waiting room of citizenship, giving rich empirical backing to her original theoretical claims. Scrutinising life in the waiting room enables Fortier to analyse how citizenship takes place, takes time and takes hold in ways that conform, exceed, and confound frames of reference laid out in both citizenisation policies and taken-for-granted understandings of 'the citizen' and 'the migrant'. Uncertain Citizenship's nuanced account of the social and institutional function of citizenisation and migratisation offers its readers a grasp of the array of racial inequalities that citizenisation produces and reproduces, while providing theoretical and empirical tools to address these inequalities.
Measuring free ellagic acid: influence of extraction conditions on recovery by studying solubility and UV-Visible spectra

Recent investigations into plant tissues have indicated that the free form of the natural polyphe-nolic antioxidant, ellagic acid (EA), is much more plentiful than first envisaged; consequently a re-assessment of solvent systems for the extraction of this water-insoluble form is needed. As EA solubility and its UV-Vis spectrum, commonly used for detection and quantification, are both governed by pH, an understanding of this dependence is vital if accurate EA measurements are to be achieved. After evaluating the pH effects on the solubility and UV-Vis spectra of commercial EA, an extraction protocol was devised that promoted similar pH conditions for both standard solutions and plant tissue extracts. The extraction so devised followed by HPLC with photodiode-array detection (DAD) provided a simple, sensitive and validated methodology that determined free EA in a variety of plant extracts. The use of 100 % methanol or a triethanolamine-based mixture as the standard dissolving solvents were the best choices, while these higher pH-generating solvents were more efficient in extracting EA from the plants tested with the final choice allied to the plants’ natural acidity. Two of the native Australian plants anise myrtle (Syzygium anisatum) and Kakadu plum (Terminalia ferdinandiana) exhibited high concentrations of free EA. Furthermore, the dual approach to measuring EA UV-Vis spectra made possible an assessment of the effect of acidified eluent on EA spectra when the DAD was employed.
Sialic acid catabolism and transport gene clusters are lineage specific 4 in Vibrio vulnificus 5 6

Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA 10 11 12 13 14 15 Corresponding author 16 E. Fidelma Boyd – fboyd@udel.edu 17 Department of Biological Sciences, 341 Wolf Hall, University of Delaware 18 Newark, DE 19716 19 Phone: (302) 831-1088. Fax: (302) 831-2281 20 21 Copyright © 2012, American Society for Microbiology. All Rights Reserved. Appl. Environ. Microbiol. doi:10.1128/AEM.07395-11 AEM Accepts, published online ahead of print on 17 February 2012
Atomically precise graphene nanoribbons: interplay of structural and electronic properties

Graphene nanoribbons hold great promise for future applications in nanoelectronic devices, as they may combine the excellent electronic properties of graphene with the opening of an electronic band gap – not present in graphene but required for transistor applications. With a two-step on-surface synthesis process, graphene nanoribbons can be fabricated with atomic precision, allowing precise control over width and edge structure. Meanwhile, a decade of research has resulted in a plethora of graphene nanoribbons having various structural and electronic properties. This article reviews not only the on-surface synthesis of atomically precise graphene nanoribbons but also how their electronic properties are ultimately linked to their structure. Current knowledge and considerations with respect to precursor design, which eventually determines the final (electronic) structure, are summarized. Special attention is dedicated to the electronic properties of graphene nanoribbons, also in dependence on their width and edge structure. It is exactly this possibility of precisely changing their properties by fine-tuning the precursor design – offering tunability over a wide range – which has generated this vast research interest, also in view of future applications. Thus, selected device prototypes are presented as well.
HMW DNA extraction from diverse plants species for PacBio and Nanopore sequencing v1

Modified from the protocol of Baptiste Mayjonade, Jérome Gouzy, Cécile Donnadieu, Nicolas Pouilly, William Marande, Caroline Callot, Nicolas Langlade and Stéphane Munos, High molecular weight gDNA extraction, Bio Techniques, Vol. 61, No. 4, October 2016, pp. 203-205. BioTechniques 61:203-205 (October 2016) doi 10.2144/000114460 https://www.future-science.com/doi/10.2144/000114460 The original protocol failed to extract High Molecular Weight genomic DNA from orchids samples (poor yield and low purity). Therefore modifications (mainly/mostly BME addition during the lysis step and a Phenol:Chloroform purification step) were made to create a new version of this protocol. This new version allowed to successfully extract DNA from orchid samples. This DNA was then sequenced on a Nanopore PromethION platform and good results in term of total yield and read length were obtained. This protocol was also successfully applied to a wide range of plant species (See attached document/excel sheet). ACKNOWLEDGEMENT Sequencing of the Arabidopsis thaliana samples listed in the attached reports was performed in collaboration with the GeT core facility, Toulouse, France (http://get.genotoul.fr), and was supported by France Génomique National infrastructure, funded as part of “Investissement d’avenir” program managed by Agence Nationale pour la Recherche (contract ANR-10-INBS-09). We particularly want to thank Lisa Gil and Céline Lopez-Roques for the sequencing part and Roxane Boyer for the data processing. Sampling and DNA Extraction for the Ophrys sphegodes samples were financially supported by the University of Zürich Research Priority Programme URPP "Evolution in Action" (PMS/AR). Sequencing was performed by Daniel Frei in the Department of Molecular Diagnostics, Genomics and Bioinformatics, Agroscope Wädenswil, Switzerland. We are thankful to Jürg E. Frey, Agroscope, for financial support. We are grateful to Philipp M. Schlüter and Ueli Grossniklaus for support and helpful discussion. Sequencing of Lolium multiflorium was performed in Agroscope by Daniel Frei. We thank Daniel, Jürg E. Frei, Dario Copetti and Bruno Studer, Department of Environmental Systems Science, ETH Zürich, for sharing the sequencing results. Sequencing of Brassica incana was performed at FGCZ Zürich. We are thankful to Léa Frachon, Department of Systematic and Evolutionary Botany, UZH Zürich, to share the data. DNA extraction of Gorteria diffusa was performed by Roman T. Kellenberger, Department of Plant Sciences, University of Cambridge. We wish to thank him for sharing his sequencing results.
The effect of backside elements on the light emission of a plastic optical fiber assembly

With the recent increase in leisure time and wellbeing trends, the number of individuals who enjoy nighttime leisure activities has rapidly increased. Thus, the demand for luminous night safety clothing ensuring safety and that is also fashionable is increasing. Although higher visibility is important, studies on the influence of the backside elements of optical fiber materials on light emission are limited. The main components of the plastic optical fiber assembly in this study are the plastic optical fiber and backside elements, consisting of retroreflective material, and the backside sheet. The effects of the four types of retroreflective material, which are low, medium, high, and ultra-high luminance types, and the color of the backside sheet, white or black, on the luminance of the plastic optical fiber assembly are evaluated in bright, dusky, and dark environments. The results are analyzed using the statistical analysis software, SPSS 20.0. In the dusky environment, the plastic optical fiber assembly with prism material (80.78 ± 2.17) exhibits the highest luminance. However, there was no difference between the plastic optical fiber assembly with high- (38.52 ± 1.27) and medium-retroreflective material (36.76 ± 0.68). In the dark environment, the plastic optical fiber assembly with the prism material shows the highest luminance (66.83 ± 0.24), and there is no difference between the plastic optical fiber assembly with the low- (24.43 ± 0.42), medium- (24.63 ± 0.36), and high-retroreflective material (25.12 ± 0.42). Also, the luminance of the plastic optical fiber assembly with the white backside sheet is higher than that with the black backside sheet for all retroreflective material in dusky and dark environments. In summary, the optimal constitution of a plastic optical fiber assembly’s backside element is the retroreflective material of a prism type with the white backside color.