bluuebunny/crossref_metadata_2025 huggingface dataset:
To what extent does organic farming promote species richness and abundance in temperate climates? A review
Authors: Stein-Bachinger Karin , Gottwald Frank , Haub Almut , Schmidt Elisabeth
Published: February 2020

The loss of biodiversity in agricultural landscapes has been dramatic over the past few decades with negative trends persisting. Organic farming has received widespread recognition in the scientific and politic fields for its environmental benefits, although the proportion of land cultivated organically is still small and the extent to which organic farming contributes to the promotion of biodiversity is viewed controversially. We present a critical, quantitative review of 98 mainly peer-reviewed papers selected from 801 studies in temperate climate zones published over the period 1990–2017. We quantified differences in the species richness and abundance of selected flora and fauna groups. In total, 474 pairwise comparisons that compared organic and conventional farming systems were considered. Overall, organic farming showed higher species richness or abundance in 58% of the pairs. No differences were found for 38%, 4% indicated negative effects from organic farming. The average (median) species numbers of flora on arable land were 95% higher under organic management as well as 61% higher for seedbank and 21% higher for field margin vegetation. For field birds, the species richness was 35%, and the abundance was 24% higher in organic farming; for insects, the corresponding values are 22% and 36% and for spiders 15% and 55%. Our study underlines that organic farming can play an effective role in acting against the loss of biodiversity. Future research should focus on the combined effects of landscape structures and organic farming, the effect of large-scale organic farming, as well as on the correlation of species diversity and production parameters. To meet the systems’ representativeness, even more strict selection criteria need to be applied in further analysis.
Antihypertensive Effectiveness of Perindopril Arginine and Indapamide Single-Pill Combination According to Body Mass Index: Findings from the FORSAGE Study
Authors:   The FORSAGE Investigators, Glezer M. G.
Published: February 2020

Introduction

Overweight and obesity are increasing worldwide and are associated with an increased risk for cardiovascular disease (CVD). The aim of this study was to examine the burden of CVD risk factors among normal weight, overweight, and obese subjects with hypertension, and to evaluate the effectiveness of switching to a single-pill combination (SPC) of perindopril arginine/indapamide for blood pressure (BP) control in overweight and obese subjects treated in routine clinical practice.

Methods

FORSAGE was a 3-month, multicenter, observational, open-label study conducted in Russian patients with uncontrolled arterial hypertension under previous antihypertensive therapy. Subjects were switched to the full-dose perindopril arginine 10 mg/indapamide 2.5 mg SPC. BP was assessed at 2 weeks, 1 month, and 3 months, and serum creatinine and general health status at 3 months. The present post hoc analysis of the FORSAGE study results explored the effectiveness of perindopril arginine/indapamide SPC in patients with arterial hypertension with regard to baseline body mass index (BMI): normal (< 25 kg/m2), overweight (25 ≤ BMI < 30 kg/m2), and obese (≥ 30 kg/m2).

Results

A total of 1969 patients were recruited, but BMI data were available for 1963 patients, two-thirds of whom were women. The distribution of BMI groups was as follows: < 25 kg/m2 (16.7%), overweight (48.7%), and obese (34.7%). Overweight or obese patients had more concomitant diseases such as diabetes mellitus or history of stroke, higher BP levels, serum cholesterol and creatinine, and lower glomerular filtration rates. Switching to perindopril arginine/indapamide SPC was associated with a statistically significant reduction in BP as early as the second week of treatment. At 3 months, systolic blood pressure (SBP)/diastolic blood pressure (DBP) had decreased significantly by 39.3/18.8 mmHg in the normal BMI group, 39.8/18.8 mmHg in overweight, and 39.4/18.7 mmHg in obese groups. The magnitude of the BP reduction was independent of BMI. Achievement of target BP (< 140/90 mmHg) was good in all groups, but lower in obese subjects (70.9%) than in overweight subjects (78.1%) or those with a normal BMI (81.8%) (P < 0.0001 for both comparisons).

Conclusions

In subjects with uncontrolled BP on existing antihypertensive therapy, switching to perindopril arginine 10 mg/indapamide 2.5 mg was associated with statistically significant decreases in BP and higher rates of target BP achievement in all BMI groups, including more than 70% of overweight and obese patients.

Trial Registration

ISRCTN ID, ISRCTN14315146 (retrospectively registered 18/11/2019).
Comparison and unification of material-point and optimal transportation meshfree methods
Authors: Wobbes Elizaveta , Tielen Roel , Möller Matthias , Vuik Cornelis
Published: February 2020

Both the material-point method (MPM) and optimal transportation meshfree (OTM) method have been developed to efficiently solve partial differential equations that are based on the conservation laws from continuum mechanics. However, the methods are derived in a different fashion and have been studied independently of one another. In this paper, we provide a direct step-by-step comparison of the MPM and OTM algorithms. Based on this comparison, we derive the conditions, under which the two approaches can be related to each other, thereby bridging the gap between the MPM and OTM communities. In addition, we introduce a novel unified approach that combines the design principles from B-spline MPM and the OTM method. The proposed approach does not contain user-defined parameters and can decrease the costs of the standard OTM method. Moreover, it allows for the use of a consistent mass matrix without stability issues that are typically encountered in MPM computations.
Non-destructive imaging and spectroscopic techniques to investigate the hidden-lifestyle arthropod pests: a review
Authors: Keszthelyi Sándor , Pónya Zsolt , Csóka Ádám , Bázár György , Morschhauser Tamás , Donkó Tamás
Published: February 2020

There are several harmful and yield decreasing arthropod pests, which live within plant tissues, causing almost unnoticeable damage, e.g.Ostrinia nubilalisHbn.,Cydia pomonellaL.,Acanthoscelides obtectusSay. Their ecological and biological features are rather known. The process leading to the damage is difficult to trace by means of conventional imaging techniques. In this review, optical techniques—X-ray, computer tomography, magnetic resonance imaging, confocal laser scanning microscopy, infrared thermography, near-infrared spectroscopy and luminescence spectroscopy—are described. Main results can contribute to the understanding of the covert pest life processes from the plant protection perspective. The use of these imaging technologies has greatly improved and facilitated the detailed investigation of injured plants. The results provided additional data on biological and ecological information as to the hidden lifestyles of covertly developing insects. Therefore, it can greatly contribute to the realisation of integrated pest management criteria in practical plant protection.
Evaluation of sticky trap colour for thrips (Thysanoptera) monitoring in pea crops (Pisum sativum L.)
Authors: Pobozniak Maria , Tokarz Krzysztof , Musynov Kazhymurat
Published: February 2020

We compared the effectiveness of three different trap colours (blue, yellow and white) to identify the optimal trap colour for the monitoring of the thripsFrankliniella intonsa,Thrips tabaci,Thrips fuscipennisandAeolothrips intermediusin the three pea cultivars, namely Polar, Izolda and Tarchalska. The number of captured thrips specimens was significantly affected by trap colour, pea cultivar and interaction between these factors. The two most attractive trap base colours for thrips were blue (peak at 450 nm) and yellow (peak at 550 nm). Irrespective of the pea cultivar, mostF. intonsawere captured on the blue and yellow traps. Blue traps were the most attractive toT. fuscipennisandT. tabaci, followed by yellow and white ones, and yellow traps were most attractive toA. intermedius. More thrips were caught on the traps located in the plots with cultivars characterised by a longer growing season Tarchalska and Izolda, which were inhabited by large numbers of thrips. There was a significant interaction effect between trap colour and pea cultivar on the number of caughtF. intonsaandT. fuscipennisin both years and forT. tabaciin 2010. Overall, among the tested trap colours, blue traps were the most effective ones for monitoring thrips in pea fields and could be used as an early detection tool. Yellow traps may be risky because they reduce population densities of the predaceousA. intermediusin pea fields, thus leading to an increase in pest numbers.
Lecture as an Event in Postdigital Education: a Dyadic Teaching Diary
Authors: Pyyhtinen Olli , Suoranta Juha
Published: February 2020

In this experimental text, we reflect in the form of a dyadic teaching diary upon a course we recently taught together on the ‘sociological imagination’. One of the main aims we set for the class was to ponder how the social scientific imagination could be enriched, and figure out ways to stress its social and political relevance. From the pedagogical point of view, we wanted to create a course which would disrupt the students’ oft-criticized routine of rote-learning, and in which they would learn to use digital platforms for the purpose of producing and sharing knowledge, meet each other, and have their social scientific thinking refreshed and perhaps even renewed. In pondering the weeks spent together with our students, we suggest that what gradually happened in our ‘postdigital classroom’ and outside of it was an Event—something surprising and unexpected that could not be controlled entirely.
Pesticides use, practice and its effect on honeybee in Ethiopia: a review
Authors: Fikadu Zekiros
Published: February 2020

Honeybees play an essential economic role in the pollination of crops. Farmers were buying, storing, and use pesticides on cultivated plants with no or little consideration of the effect on honeybees. In Ethiopia, pesticide poisoning of honeybees has increased from time to time, and beekeepers also lose their colonies due to unwise use and improper practice of pesticides. Ethiopia has developed a legal framework on pesticide registration, distribution, and use. But regulations are not strictly implemented by the farmers, and it needs enforcement. Farmers use pesticides on crops with no or little consideration of their effect on honeybees, also the use of pesticides is harmful to pollination service, behavior, communication, forage resource, poisoning, and contaminated hive products. The Effective communication between beekeepers and crop growers is important because spraying pesticides is required to minimize the impact of pesticides on honeybees. The present review should focus on the effects of pesticide use and the means of reducing its impact on honeybee colonies.
Social media use and risky behaviors in adolescents: A meta‐analysis
Authors: Vannucci Anna , Simpson Emily G. , Gagnon Sonja , Ohannessian Christine McCauley
Published: February 2020

Introduction

This systematic review and meta‐analysis examined the associations between social media use and risky behaviors during adolescence, and evaluated study characteristics (e.g., sample age, type of social media platform assessed) that may moderate these relationships.

Methods

A comprehensive search strategy identified relevant studies from PsycInfo, PubMed, Google Scholar, and Proquest Dissertations and Theses Global.

Results

The final sample included 27 independent cross‐sectional studies with a total of 67,407 adolescents (Mage = 15.5, range: 12.6–18.0 years; 51.7% girls; 57.2% White). Results from random effects models indicated that there were positive, small‐to‐medium correlations between social media use and engagement in risky behaviors generally (r = 0.21, 95% CI = 0.16‐0.25), substance use (r = 0.19, 95% CI = 0.12‐0.26), and risky sexual behaviors (r = 0.21, 95% CI = 0.15‐0.28). There were an insufficient number of independent samples available to conduct a random effect models for violence‐related behaviors (k = 3). Moderator analyses suggested that studies assessing solely early social media platforms (e.g., Facebook/MySpace only) in relation to substance use had smaller effect sizes than substance use studies assessing a broader range of contemporary social media platforms. In addition, younger samples had larger effect sizes for studies focused on social media use and risky sexual behaviors.

Conclusions

The positive links identified between social media and risky behaviors during adolescence in this meta‐analysis suggest that developmental theories of risk taking would benefit from incorporating the social media context. Longitudinal studies are needed to clarify directionality and make more specific practice and policy recommendations so that social media is a safe place in which adolescents can thrive.
CitGVD: a comprehensive database of citrus genomic variations
Authors: Li Qiang , Qi Jingjing , Qin Xiujuan , Dou Wanfu , Lei Tiangang , Hu Anhua , Jia Ruirui , Jiang Guojin , Zou Xiuping , Long Qin , Xu Lanzhen , Peng Aihong , Yao Lixiao , Chen Shanchun , He Yongrui
Published: February 2020

Citrus is one of the most important commercial fruit crops worldwide. With the vast genomic data currently available for citrus fruit, genetic relationships, and molecular markers can be assessed for the development of molecular breeding and genomic selection strategies. In this study, to permit the ease of access to these data, a web-based database, the citrus genomic variation database (CitGVD, http://citgvd.cric.cn/home) was developed as the first citrus-specific comprehensive database dedicated to genome-wide variations including single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs). The current version (V1.0.0) of CitGVD is an open-access resource centered on 1,493,258,964 high-quality genomic variations and 84 phenotypes of 346 organisms curated from in-house projects and public resources. CitGVD integrates closely related information on genomic variation annotations, related gene annotations, and details regarding the organisms, incorporating a variety of built-in tools for data accession and analysis. As an example, CitGWAS can be used for genome-wide association studies (GWASs) with SNPs and phenotypic data, while CitEVOL can be used for genetic structure analysis. These features make CitGVD a comprehensive web portal and bioinformatics platform for citrus-related studies. It also provides a model for analyzing genome-wide variations for a wide range of crop varieties.
Hydrogen sulfide inhibits ethylene-induced petiole abscission in tomato (Solanum lycopersicum L.)
Authors: Liu Danmei , Li Jianing , Li Zhuowen , Pei Yanxi
Published: February 2020

Abscission is a dynamic physiological process that is ubiquitous in plants and can also be an essential agronomic trait in crops, thus attracting attention from plant growers and breeders. In general, the process of plant organ abscission can be divided into four steps, among which the step to obtain the competence to respond to abscission signals (step 2) is the most complex; however, the molecular mechanism underlying this process remains unclear. In this study, we found that hydrogen sulfide (H2S) inhibited the abscission of the tomato petiole in a dose-dependent manner, and the abscission of the petiole was accelerated when an H2S scavenger was applied. Further enzymatic activity and gene expression analyses showed that H2S suppressed the activity of enzymes capable of modifying the cell wall by inhibiting the usual upregulation of the transcription of the corresponding genes during the abscission process but not by affecting the activities of these enzymes by direct posttranslational modification. H2S treatment upregulated the expression levels of SlIAA3 and SlIAA4 but downregulated the transcription of ILR-L3 and ILR-L4 in the earlier stages of the abscission process, indicating that H2S probably functioned in the second step of the abscission process by preventing the abscission zone cells from obtaining the competence to respond to abscission signals by modulating the content of the bioactive-free auxin in these cells. Moreover, similar H2S inhibitory effects were also demonstrated in the process of floral organ abscission and anther dehiscence in other plant species, suggesting a ubiquitous role for H2S in cell separation processes.
MdMYB8 is associated with flavonol biosynthesis via the activation of the MdFLS promoter in the fruits of Malus crabapple
Authors: Li Hua , Li Yu , Yu Jiaxuan , Wu Ting , Zhang Jie , Tian Ji , Yao Yuncong
Published: February 2020

Flavonols are polyphenolic compounds that play important roles in plant stress resistance and development. They are also valuable components of the human diet. TheMaluscrabapple cultivar ‘Flame’ provides an excellent model for studying flavonol biosynthesis due to the high flavonol content of its fruit peel. To obtain a more detailed understanding of the flavonol regulatory network involved in fruit development, the transcriptomes of the fruit of theMaluscv. ‘Flame’ from five continuous developmental stages were analyzed using RNA sequencing. A flavonol-related gene module was identified through weighted gene coexpression network analysis (WGCNA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that phytohormones are involved in regulating flavonol biosynthesis during fruit development. A putative transcription factor,MdMYB8, was selected for further study through hub gene correlation network analysis and yeast one-hybrid assays. Stable overexpression or RNAi knockdown ofMdMYB8in transgenic ‘Orin’ apple calli resulted in a higher or lower flavonol content, respectively, suggesting thatMdMYB8is a regulator of flavonol biosynthesis. This transcriptome analysis provides valuable data for future studies of flavonol synthesis and regulation.
A chromosome-scale genome assembly of Isatis indigotica, an important medicinal plant used in traditional Chinese medicine
Authors: Kang Minghui , Wu Haolin , Yang Qiao , Huang Li , Hu Quanjun , Ma Tao , Li Zaiyun , Liu Jianquan
Published: February 2020

Isatis indigotica (2n = 14) is an important medicinal plant in China. Its dried leaves and roots (called Isatidis Folium and Isatidis Radix, respectively) are broadly used in traditional Chinese medicine for curing diseases caused by bacteria and viruses such as influenza and viral pneumonia. Various classes of compounds isolated from this species have been identified as effective ingredients. Previous studies based on transcriptomes revealed only a few candidate genes for the biosynthesis of these active compounds in this medicinal plant. Here, we report a high-quality chromosome-scale genome assembly of I. indigotica with a total size of 293.88 Mb and scaffold N50 = 36.16 Mb using single-molecule real-time long reads and high-throughput chromosome conformation capture techniques. We annotated 30,323 high-confidence protein-coding genes. Based on homolog searching and functional annotations, we identified many candidate genes involved in the biosynthesis of main active components such as indoles, terpenoids, and phenylpropanoids. In addition, we found that some key enzyme-coding gene families related to the biosynthesis of these components were expanded due to tandem duplications, which likely drove the production of these major active compounds and explained why I. indigotica has excellent antibacterial and antiviral activities. Our results highlighted the importance of genome sequencing in identifying candidate genes for metabolite synthesis in medicinal plants.
A CIN-like TCP transcription factor (LsTCP4) having retrotransposon insertion associates with a shift from Salinas type to Empire type in crisphead lettuce (Lactuca sativa L.)
Authors: Seki Kousuke , Komatsu Kenji , Tanaka Keisuke , Hiraga Masahiro , Kajiya-Kanegae Hiromi , Matsumura Hideo , Uno Yuichi
Published: February 2020

To improve several agronomic traits in crisphead lettuce (Lactuca sativaL.) under high-temperature growth conditions, we investigated the correlation among those traits in multiple cultivars and performed genetic mapping of their causal genes. In a field cultivation test of Empire type (serrated leaf) and Salinas type (wavy leaf) cultivars, Empire type cultivars showed increased tipburn susceptibility and late bolting compared with Salinas type cultivars. We attempted genetic mapping of leaf shape and bolting time by ddRAD-seq using the F2population derived from a cross between ‘VI185’ (Empire type) and ‘ShinanoGreen’ (Salinas type). These analyses suggested that both traits are controlled by a single locus in LG5. Genotyping of 51 commercial lettuce cultivars with a tightly linked marker (LG5_v8_252.743Mbp) at this locus showed an association between its genotype and the serrated leaf phenotype. By further fine mapping and transcriptome analysis, a gene encoding putative CIN-like TCP transcription factor was determined to be a candidate gene at this locus and was designated asLsTCP4. An insertion of retrotransposable element was found in the allele of ‘VI185’, and its transcript level in the leaves was lower than that in ‘ShinanoGreen’. Because shapes of leaf epidermal cells in ‘VI185’ were similar to those in the TCP family mutant ofArabidopsis thaliana, the leaf shape phenotype was likely caused by reduced expression ofLsTCP4. Furthermore, because it is known that the TCP family protein also controls flowering time via interaction with FT inA. thaliana, it was highly possible thatLsTCP4gave pleiotropic effects on both leaf shape and bolting time in lettuce.
Proteome and transcriptome profile analysis reveals regulatory and stress-responsive networks in the russet fruit skin of sand pear
Authors: Wang Yuezhi , Dai Meisong , Cai Danying , Shi Zebin
Published: February 2020

The epidermal tissues of the cuticular membrane (CM) and periderm membrane (PM) confer first-line protection from environmental stresses in terrestrial plants. Although PM protection is essentially ubiquitous in plants, the protective mechanism, the function of many transcription factors and enzymes, and the genetic control of metabolic signaling pathways are poorly understood. Different microphenotypes and cellular components in russet (PM-covered) and green (CM-covered) fruit skins of pear were revealed by scanning and transmission electron microscopy. The two types of fruit skins showed distinct phytohormone accumulation, and different transcriptomic and proteomic profiles. The enriched pathways were detected by differentially expressed genes and proteins from the two omics analyses. A detailed analysis of the suberin biosynthesis pathways identified the regulatory signaling network, highlighting the general mechanisms required for periderm formation in russet fruit skin. The regulation of aquaporins at the protein level should play an important role in the specialized functions of russet fruit skin and PM-covered plant tissues.
Multielemental determination in sugarcane products from the southern region of Brazil by microwave induced plasma optical emission spectrometry after acid decomposition with a reflux system
Authors: Sampaio Maicon Renato Ferreira , Lisboa Meibel Teixeira , Timm Janaína Garcia , Schwingel Ribeiro Anderson , Antunes Vieira Mariana , Otero Deborah Murowaniecki , Zambiazi Rui Carlos
Published: February 2020

The concentrations of Ba, Ca, Cu, Fe, K, Na, Mg and Mn in different sugars, molasses and brown sugar candy were determined by MIP OES after acid decomposition.
Ultra-small Bi2S3 nanodot-doped reversible Fe(ii/iii)-based hollow mesoporous Prussian blue nanocubes for amplified tumor oxidative stress-augmented photo-/radiotherapy
Authors: Ren Chuchu , Cheng Yu , Li Wen , Liu Ping , Yang Lifang , Lu Qianglan , Xu Min , Tan Fengping , Li Jiao , Li Nan
Published: February 2020

Oxidative stress imbalance could be induced by the reversible redox property of Fe(ii/iii), thereby causing DNA damage and increasing the cell membrane permeability to realize enhanced photo-/radiotherapy.
Establishing structure-sensitivity of ceria reducibility: real-time observations of surface-hydrogen interactions
Authors: Duchoň Tomáš , Hackl Johanna , Mueller David N. , Kullgren Jolla , Du Dou , Senanayake Sanjaya D. , Mouls Caroline , Gottlob Daniel M. , Khan Muhammad I. , Cramm Stefan , Veltruská Kateřina , Matolín Vladimír , Nemšák Slavomír , Schneider Claus M.
Published: February 2020

Unraveling the thermodynamic origin of the structure–reducibility of cerium oxide (100) and (111) surface planes.
Enhancement of Ni–(Y2O3)0.08(ZrO2)0.92 fuel electrode performance by infiltration of Ce0.8Gd0.2O2−δ nanoparticles
Authors: Park Beom-Kyeong , Scipioni Roberto , Cox Dalton , Barnett Scott A.
Published: February 2020

GDC nanoparticles reduce the reaction resistance associated with three-phase boundaries and improve oxygen transport in the Ni–YSZ electrode, as measured by electrochemical impedance spectroscopy under actual solid oxide cell operating conditions.
Reactive oxygen species (ROS)-responsive ferrocene-polymer-based nanoparticles for controlled release of drugs
Authors: Na Yoonhee , Lee Jin Sil , Woo Jiseob , Ahn Sukyung , Lee Eunhye , Il Choi Won , Sung Daekyung
Published: February 2020

Ferrocene-containing nanoparticles show reversible redox activity that could trigger drug release mediated by reactive oxygen species (ROS).
Highly sensitive, selective and stable NO2 gas sensors with a ppb-level detection limit on 2D-platinum diselenide films
Authors: Su Teng-Yu , Chen Yu-Ze , Wang Yi-Chung , Tang Shin-Yi , Shih Yu-Chuan , Cheng Faliang , Wang Zhiming M. , Lin Heh-Nan , Chueh Yu-Lun
Published: February 2020

High quality PtSe2 can be fabricated under 600 °C and has excellent NO2 sensitivity, which can reach sub ppb level.
Cooperative object segmentation and recognition via restricted Boltzmann machine
Authors: Huang Wei , Yu Huimin
Published: February 2020

The authors present a model where object segmentation and recognition are connected with a bottom‐up inference and a top‐down generation pathway so that the two models can communicate and cooperate with each other. They are integrated into an energy function and optimised at the same time. To achieve the cooperation, objects are modelled in two aspects: shape and appearance, so that the recognition result could feedback to the segmentation process. Restricted Boltzmann machine is employed to learn the shapes of the objects with corresponding labels and perform object recognition based on the object shapes. Another pathway involved with the appearance knowledge of the objects is also established so that both the shape and appearance information will guide and constrain the evolution of the segmentation developing towards the region of interest, which will further facilitate the performances of both tasks. Experiments demonstrate the effectiveness of the proposed model.
Improved dynamic frequency‐scaling approach for energy‐saving‐based radial basis function neural network
Authors: Li Deguang , Zhang Ruiling , Jia Shijie , Liu Dong , Jin Yanling , Li Junke
Published: February 2020

As dynamic voltage and frequency scaling (DVFS) does not consider predicting system behaviour in the future stage, to improve efficiency of DVFS in fine‐grained, the authors propose a central processing unit (CPU) utilisation prediction model based on radial basis function neural network. Their model first collects five typical system characteristics related to CPU utilisation during system running, then they use radial basis neural network to fit the non‐linear relationship between these system characteristics and CPU utilisation in the next period. According to the predicted CPU utilisation, specific frequency scaling is performed to change frequency in real time. Finally, they evaluate their model with classical DVFS by means of different task sets. Experimental results show that their model could predict CPU utilisation in more fine‐grained compared with other models, and changes frequency‐scaling effect of traditional DVFS.
Data‐driven approach to iterative learning control via convex optimisation
Authors: Nicoletti Achille , Martino Michele , Aguglia Davide
Published: February 2020

A new data‐driven iterative learning control methodology is presented which uses the frequency response data of a system in order to avoid the problem of unmodelled dynamics associated with low‐order parametric models. A convex optimisation problem is formulated to design the learning filters such that the convergence criterion is minimised. Since the frequency response data of the system is used in obtaining these filters, robustness is ensured by eliminating the uncertainty in the modelling process. The effectiveness of the method is illustrated by considering a case study where the proposed design scheme is applied to a power converter control system for a specific accelerator requirement at CERN.
Frequency domain identification using adaptive Fourier decomposition method with polynomials
Authors: Mi Wen , Zheng Wei Xing
Published: February 2020

The adaptive Fourier decomposition method is an approximation technique of generalised Fourier series, it leads to fast approximations by selecting basis functions in a maximal selection criterion. In recent research studies, it has been efficiently applied in the identification of linear time‐invariant systems and a new algorithm is named two‐step (T‐S) algorithm. In this work, some further modification is made for the T‐S algorithm. The improvement is made at the first step, where polynomials are used instead of cauchy integral formula. By doing this, the algorithm becomes simpler and easier to realise. The approximation errors are analysed. Owing to the analysed results, this new T‐S algorithm is only to get poles for the finite rational orthogonal basis functions but not the approximation to the systems, the coefficients are estimated by using least‐squares methods. The effectiveness is examined through numerical examples that show it takes much less running times and can get comparable approximating results. Besides, the case that errors are included in the frequencies is also studied, the obtained results imply that minor errors in the frequencies would not affect the estimation.
Safety‐constrained robust adaptive control for a class of MIMO non‐linear systems
Authors: Sachan Kapil , Padhi Radhakant
Published: February 2020

This study proposes two new safety‐constrained robust indirect adaptive control schemes for a class of multi‐input multi‐output non‐linear systems subject to unstructured additive model uncertainties and external disturbances. The controllers are designed using a novel error transformation and a new asymptotically stable closed‐loop non‐linear error dynamics. The model uncertainties of the actual system are approximated by constructing a neural network‐based auxiliary observer dynamics. The weights of the neural network are updated using a robust Lyapunov stable weight update rule. Using the estimation information of model uncertainties, two different asymptotically and finite‐time exponentially stable tracking controllers are designed to minimise the error between auxiliary observer states and reference signals. It is proven that the closed‐loop states of the actual system will remain bounded by the imposed state constraints and the steady‐state tracking error of the system will converge asymptotically (or exponentially in finite time) to a user‐defined domain. The beauty of the proposed control designs lies in the fact that they are easy to design and implement, and provide design freedom to impose constraints on an individual component of the system states. The effectiveness of the proposed techniques is shown by controlling a two‐link robot manipulator in a constrained environment.
Event‐triggered communication for passivity and synchronisation of multi‐weighted coupled neural networks with and without parameter uncertainties
Authors: Wang Yihao , Huang Yanli , Yang Erfu
Published: February 2020

A multi‐weighted coupled neural networks (MWCNNs) model with event‐triggered communication is studied here. On the one hand, the passivity of the presented network model is studied by utilising Lyapunov stability theory and some inequality techniques, and a synchronisation criterion based on the obtained output‐strict passivity condition of MWCNNs with event‐triggered communication is derived. On the other hand, some robust passivity and robust synchronisation criteria based on output‐strict passivity of the proposed network with uncertain parameters are presented. At last, two numerical examples are provided to testify the effectiveness of the output‐strict passivity and robust synchronisation results.
Predictive deviation filter for deadbeat control
Authors: Wang Zitan , Chai Jianyun , Sun Xudong , Lu Haifeng
Published: February 2020

Deadbeat control calculates excitation by a differential equation model that takes measurements of state variables as initial values and instructions as terminal values. Ideally, this excitation can force state variables to track instructions in the succeeding control interval. However, in a practical system, noises in measured signals can mislead the control system and degrade its performance with increased ripples and harmonics. Therefore, some filters are often used in measurements, but their inherent delay can lead to inaccurate initial values and cause severe overshoots in dynamic cases. In this study, a new type filtering algorithm called predictive deviation filter is proposed for deadbeat control, which filters only the predicted deviation obtained by removing the expected values from measured ones, and then the real values of state variables are recovered. With this method, the influence of the filter delay can be limited only on the deviation which is a small part of the signal, significantly improving the accuracy of the initial values. Furthermore, a comprehensive frequency‐domain analysis of the predictive deviation filter is provided. Finally, the new filtering algorithm is applied to drive control of permanent magnet synchronous motor. The simulation and experimental results verify the effectiveness and performance of this approach.
Research on eddy current losses algorithm in solid rotor of high speed squirrel cage induction motor
Authors: Chou Weixiang , Liang Yanping , Gao Lianlian , Wang Dongmei
Published: February 2020

Aiming at the shortcomings of the analytical algorithm and numerical algorithm for calculating the eddy current losses in the solid rotor of high speed squirrel cage induction motor, this study proposes a semi‐analytical algorithm. Based on the magnetic field of the rotor surface and Maxwell's equations, the analytical formula of this algorithm is derived. According to the law of energy conservation, the losses in rotor and rotor bars are calculated, respectively, so that the eddy current losses in the solid rotor are calculated indirectly. Taking a high speed squirrel cage induction motor as an example, the eddy current losses in the solid rotor are calculated by the semi‐analytical method. The calculation result is verified by the two‐dimensional transient finite‐element method, and the calculation result meets the basic requirements of engineering practice.
Peak current compensation for reducing the negative impact of LEE on SRLM
Authors: Nie Rui , Chen Hao , Liu Jinfu , Zhao Wenmin , Zhao Shuyan , Tian Jiacheng , Wang Xing , Huo Yingjie
Published: February 2020

The longitudinal end effect (LEE) has a negative influence on the performance of the flat‐type switched‐reluctance linear machines (SRLMs). For example, it can give rise to the imbalance of peak currents of different phases and the aggravation of the force ripple. This study proposes a modified current estimation model and an adaptive adjustment method (AAM) of turn‐on position to compensate for the LEE of SRLMs. The modified current estimation model considers not only the self‐inductance characteristics but also the mutual inductance characteristics. Some simulation results demonstrate that this modified estimation model has better estimation accuracy than a previous one. Then, the AAM of turn‐on position is proposed based on this modified current estimation model. It can balance the peak currents of different phases so that the negative impact of the LEE is greatly reduced. This new control method is easy to implement and requires little test, and its effectiveness in compensating for the peak currents and reducing force ripple is experimentally verified.
Reconfiguration and reinforcement allocation as applied to hourly medium‐term load forecasting of distribution feeders
Authors: Paredes Gonzalo , Vargas Luis , Maldonado Sebastián
Published: February 2020

In this study, a methodology to develop hourly demand scenarios in a medium‐term horizon for primary distribution substations is presented and applied to a case study. The main contribution of this study is that it addresses successfully the effect of saturation of distribution feeders in the medium term due to sustained growth in demand. In addition, the method is able to simulate the future necessary reconfiguration and reinforcements in the distribution feeders. A detailed comparative study of five well‐known forecasting techniques, to estimate future demand, is conducted. The methodology is tested with hourly power records, measured from 2008 to 2013, in 169 feeders of the distribution company of Santiago, Chile. When the performance of the forecasting techniques is compared, results of one‐year‐ahead forecasting, with hourly resolution, show that multilayer perceptron neural networks outperformed the other techniques, having a MAPE lower than 9% for more than 96% of the feeders. A final evaluation for 13 feeders, using the forecasted and registered demand from 2014 to 2017, shows that the MAPE remains in a low range (9–13%), improving the method currently used by the industry. The overall results indicate that reconfiguration and reinforcement allocation are key elements for medium‐term hourly demand forecasting in distribution feeders.
Quantitative assessment of capabilities of colour models for pen ink discrimination in handwritten documents
Authors: Dansena Prabhat , Pal Rajarshi , Bag Soumen
Published: February 2020

The addition of new words in handwritten documents such as bank cheques, bills, and notes is considered as common crime. Such immoral activities on handwritten documents have a bad effect on the victim in terms of mental and financial loss. For facilitating an impartial judicial process, it is important to differentiate between the used pen inks. Earlier, image processing and pattern recognition‐based techniques for pen ink differentiation gained attention among researchers due to their non‐destructive nature. Existing techniques use various colour models to represent the colour of pen inks. Thus, it is crucial to assess the capabilities of various colour models for differentiating pen inks in handwritten documents. In this paper, we propose a histogram distance based quantitative assessment technique for suitable colour model identification for differentiating pen inks. Seven blue and seven black pen ink samples are acquired on 112 cheque leaves. The k‐means binarisation is used to identify pen ink pixels. colour model has been identified as the best colour model for this task. The statistical features of the ink colours in the identified colour model representation are extracted and a multi‐layer perceptron (MLP) classifier validates the capability of the identified colour model for pen ink discrimination.
Automatic grading of brain tumours using LSTM neural networks on magnetic resonance spectroscopy signals
Authors: Dandil Emre , Biçer Ali
Published: February 2020

Brain tumours have increased rapidly in recent years as in other tumour types. Therefore, early and accurate diagnosis of brain tumour is vital for treatment. Magnetic resonance imaging (MRI) and histopathological assessments are the most common methods used in the detection of brain tumours. The research studies on non‐invasive imaging methods such as MRI and magnetic resonance spectroscopy (MRS) have become widespread in recent years for brain tumour detection. In this study, a computer‐assisted method is proposed for automatic grading of brain tumours on MRS signals. The classification of brain tumours with different grades is performed using long short term memory (LSTM) neural networks. In addition, additional features from MRS signals based on spectral entropy and instantaneous frequency are extracted. As a result of the experimental studies on the international MRS database (INTERPRET), it is seen that grading is achieved using the proposed method with average accuracy of 98.20%, sensitivity of 100%, and specificity of 97.53% performance results in three test studies carried out for the classification of brain tumour. Furthermore, in the grading of brain tumours using the proposed method, the average area under of the receiver operating characteristic curve is measured with high performance of 0.9936.
Gain prediction and compensation for subarray antenna with assembling errors based on improved XGBoost and transfer learning
Authors: Guo Fang , Liu Zhenyu , Hu Weifei , Tan Jianrong
Published: February 2020

Large array antennas are often assembled with several subarrays, and assembling errors containing position and orientation are the key factors determining the final radiation pattern. As an important feature of radiation patterns, the antenna gain significantly influences the design of the antenna. However, little research has been conducted on the accurate prediction and detailed compensation of gain with assembling errors. In this work, the authors propose an accurate gain prediction model using an improved extreme gradient boosting (XGBoost) algorithm and the transfer learning method. Knowledge from both the simulation data and experience is converted to weights to help train the improved XGBoost model. Experimental data are then used to modify the model for complex factors, such as mutual coupling and element type. Compensation methods are proposed to provide directions to limit the degradation of the gain within a range by controlling the assembling errors. Experiments are conducted on a platform with a 3 × 3 subarray antenna. The results indicate that the proposed gain prediction model is more accurate than the model developed using artificial neural network, support vector regression, and existing XGBoost algorithms. The steps of gain compensation are also reduced with the proposed compensation methods.
Study and analysis of a DC–DC soft‐switched buck converter
Authors: Alavi Peyman , Babaei Ebrahim , Mohseni Parham , Marzang Vafa
Published: February 2020

In this study, a soft‐switched buck converter is proposed and analysed. In this structure, by adding an auxiliary inductor and two auxiliary capacitors, zero‐voltage switching condition for switch's turn on and near to soft‐switching condition for switch's turn off are provided. Furthermore, the power diode turns off under zero‐current switching condition. As a result, switching losses and reverse recovery losses have been eliminated, and the proposed converter can provide high efficiencies. To prove the mentioned advantages, a 200 W laboratory prototype of the proposed converter is built and its results are investigated completely. On the basis of these results, the proposed converter can provide 96.1% experimental efficiency at 200 W output power, which proves the 96.78% theoretical efficiency. Also, in comparison results, it is shown that this converter not only provides higher efficiency in comparison with other structures, but also it has less components and simpler structure than other related buck converters.
Internet of things augmented a novel PSO‐employed modified zeta converter‐based photovoltaic maximum power tracking system: hardware realisation
Authors: Priyadarshi Neeraj , Padmanaban Sanjeevikumar , Holm‐Nielsen Jens Bo , Bhaskar Mahajan Sagar , Azam Farooque
Published: February 2020

In this study, a particle swarm optimisation (PSO) augmented internet of things (IOT)‐based maximum power point tracking (MPPT) algorithm for solar photovoltaic (PV) system has been proposed. A modified DC–DC ZETA converter is used as an interface between solar PV and DC load. The duty cycle of the converter is continuously modulated for harvesting maximum power using PSO‐IOT algorithm employing Arduino and Bluetooth system. IOT‐based control system provides monitoring and compiling of PV reference voltage for MPPT controller of the PV system. Further, the experimental results validate the improved performance of the proposed algorithm. A performance comparison is provided in order to prove the merit of proposed MPPT algorithm over existing techniques such as perturb and observe, PSO, ant colony optimisation, artificial bee colony.
Constraining the cosmic ray spectrum in the vicinity of the supernova remnant W28: from sub-GeV to multi-TeV energies
Authors: Phan V. H. M. , Gabici S. , Morlino G. , Terrier R. , Vink J. , Krause J. , Menu M.
Published: February 2020

Context. Supernova remnants interacting with molecular clouds are ideal laboratories to study the acceleration of particles at shock waves and their transport and interactions in the surrounding interstellar medium.

Aims. Here, we focus on the supernova remnant W28, which over the years has been observed in all energy domains from radio waves to very-high-energy gamma rays. The bright gamma-ray emission detected from molecular clouds located in its vicinity revealed the presence of accelerated GeV and TeV particles in the region. An enhanced ionization rate has also been measured by means of millimeter observations, but such observations alone cannot tell us whether the enhancement is due to low-energy (MeV) cosmic rays (either protons or electrons) or the X-ray photons emitted by the shocked gas. The goal of this study is to determine the origin of the enhanced ionization rate and to infer from multiwavelength observations the spectrum of cosmic rays accelerated at the supernova remnant shock in an unprecedented range spanning from MeV to multi-TeV particle energies.

Methods. We developed a model to describe the transport of X-ray photons into the molecular cloud, and we fitted the radio, millimeter, and gamma-ray data to derive the spectrum of the radiating particles.

Results. The contribution from X-ray photons to the enhanced ionization rate is negligible, and therefore the ionization must be due to cosmic rays. Even though we cannot exclude a contribution to the ionization rate coming from cosmic-ray electrons, we show that a scenario where cosmic-ray protons explain both the gamma-ray flux and the enhanced ionization rate provides the most natural fit to multiwavelength data. This strongly suggests that the intensity of CR protons is enhanced in the region for particle energies in a very broad range covering almost six orders of magnitude: from ≲100 MeV up to several tens of TeV.