bluuebunny/crossref_metadata_2025 huggingface dataset:
AFM study of changes in properties of horseradish peroxidase after incubation of its solution near a pyramidal structure
Authors: Ivanov Yuri D. , Pleshakova Tatyana O. , Shumov Ivan D. , Kozlov Andrey F. , Ivanova Irina A. , Valueva Anastasia A. , Ershova Maria O. , Tatur Vadim Yu. , Stepanov Igor N. , Repnikov Victor V. , Ziborov Vadim S.
Published: May 2021

In our present paper, the influence of a pyramidal structure on physicochemical properties of a protein in buffer solution has been studied. The pyramidal structure employed herein was similar to those produced industrially for anechoic chambers. Pyramidal structures are also used as elements of biosensors. Herein, horseradish peroxidase (HRP) enzyme was used as a model protein. HRP macromolecules were adsorbed from their solution onto an atomically smooth mica substrate, and then visualized by atomic force microscopy (AFM). In parallel, the enzymatic activity of HRP was estimated by conventional spectrophotometry. Additionally, attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) has been employed in order to find out whether or not the protein secondary structure changes after the incubation of its solution either near the apex of a pyramid or in the center of its base. Using AFM, we have demonstrated that the incubation of the protein solution either in the vicinity of the pyramid’s apex or in the center of its base influences the physicochemical properties of the protein macromolecules. Namely, the incubation of the HRP solution in the vicinity of the top of the pyramidal structure has been shown to lead to an increase in the efficiency of the HRP adsorption onto mica. Moreover, after the incubation of the HRP solution either near the top of the pyramid or in the center of its base, the HRP macromolecules adsorb onto the mica surface predominantly in monomeric form. At that, the enzymatic activity of HRP does not change. The results of our present study are useful to be taken into account in the development of novel biosensor devices (including those for the diagnosis of cancer in humans), in which pyramidal structures are employed as sensor, noise suppression or construction elements.
Relationship of contact angle of spray solution on leaf surfaces with weed control
Authors: da Silva Santos Renata Thaysa , Vechia Jaqueline Franciosi Della , dos Santos Cícero Antonio Mariano , Almeida Dieimisson Paulo , da Costa Ferreira Marcelo
Published: May 2021

The weeds are important in agricultural and livestock areas because these plants can cause several damages, especially in the yield. The herbicide pulverization for weed control is the most used, but the efficiency of the control can be dependent the several factors, for example, the correct chose the herbicide and the mixture or not with adjuvant. This study aimed to evaluate the contact angle of herbicide solution droplets associated with adjuvant when deposited on the leaf surface of different weed species and their relationship with chemical control. For the contact angle experiment, the design was completely randomized, with four repetitions, while for the control experiment, a randomized block design was used, both experiments were arranged in a factorial (4 × 2 + 1) design. Factor A corresponded to four spray solutions containing the herbicide no addition of adjuvants and herbicide associated with adjuvants (vegetable oil, mineral oil, and lecithin), factor B to two herbicide dosages, and additional treatment corresponded to water. The contact angle was determined in six weed species:Crotalaria incana,Lantana camara,Ipomoea grandifolia,Asclepias curassavica,Sida obtusifolia,andRicinus communis, on the adaxial and abaxial surface of each species, and an artificial surface. For the weed control experiment was used two weed species:C. incanaandL. camara. The multivariate analysis allowed the understanding of the behavior of the contact angle of the different groups on the natural and artificial surfaces, due to the formation of factors. For all plants, except for the abaxial surface ofI. grandifoliaand the adaxial surface ofA. curassavica,the association of herbicide and adjuvants reduced contact angle on the surfaces. The chemical control resulted in an indirect relation with contact angle, where smaller contact angles of the herbicide solution resulted in a higher percentage of plant intoxication. Therefore, for this situation, it is recommended to use the herbicide aminopyralid + fluroxypir associated with lecithin.
Generative adversarial network for glioblastoma ensures morphologic variations and improves diagnostic model for isocitrate dehydrogenase mutant type
Authors: Park Ji Eun , Eun Dain , Kim Ho Sung , Lee Da Hyun , Jang Ryoung Woo , Kim Namkug
Published: May 2021

Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether GAN ensures meaningful morphologic variations is still unknown. We investigated whether GAN-based synthetic images provide sufficient morphologic variations to improve molecular-based prediction, as a rare disease of isocitrate dehydrogenase (IDH)-mutant glioblastomas. GAN was initially trained on 500 normal brains and 110 IDH-mutant high-grade astocytomas, and paired contrast-enhanced T1-weighted and FLAIR MRI data were generated. Diagnostic models were developed from real IDH-wild type (n = 80) with real IDH-mutant glioblastomas (n = 38), or with synthetic IDH-mutant glioblastomas, or augmented by adding both real and synthetic IDH-mutant glioblastomas. Turing tests showed synthetic data showed reality (classification rate of 55%). Both the real and synthetic data showed that a more frontal or insular location (odds ratio [OR] 1.34 vs. 1.52; P = 0.04) and distinct non-enhancing tumor margins (OR 2.68 vs. 3.88; P < 0.001), which become significant predictors of IDH-mutation. In an independent validation set, diagnostic accuracy was higher for the augmented model (90.9% [40/44] and 93.2% [41/44] for each reader, respectively) than for the real model (84.1% [37/44] and 86.4% [38/44] for each reader, respectively). The GAN-based synthetic images yield morphologically variable, realistic-seeming IDH-mutant glioblastomas. GAN will be useful to create a realistic training set in terms of morphologic variations and quality, thereby improving diagnostic performance in a clinical model.
Pests, diseases, and aridity have shaped the genome of Corymbia citriodora
Authors: Healey Adam L. , Shepherd Mervyn , King Graham J. , Butler Jakob B. , Freeman Jules S. , Lee David J. , Potts Brad M. , Silva-Junior Orzenil B. , Baten Abdul , Jenkins Jerry , Shu Shengqiang , Lovell John T. , Sreedasyam Avinash , Grimwood Jane , Furtado Agnelo , Grattapaglia Dario , Barry Kerrie W. , Hundley Hope , Simmons Blake A. , Schmutz Jeremy , Vaillancourt René E. , Henry Robert J.
Published: May 2021

Corymbia citriodorais a member of the predominantly Southern Hemisphere Myrtaceae family, which includes the eucalypts (Eucalyptus,CorymbiaandAngophora; ~800 species).Corymbiais grown for timber, pulp and paper, and essential oils in Australia, South Africa, Asia, and Brazil, maintaining a high-growth rate under marginal conditions due to drought, poor-quality soil, and biotic stresses. To dissect the genetic basis of these desirable traits, we sequenced and assembled the 408 Mb genome ofCorymbia citriodora, anchored into eleven chromosomes. Comparative analysis withEucalyptus grandisreveals high synteny, although the two diverged approximately 60 million years ago and have different genome sizes (408 vs 641 Mb), with few large intra-chromosomal rearrangements.C. citriodorashares an ancient whole-genome duplication event withE. grandisbut has undergone tandem gene family expansions related to terpene biosynthesis, innate pathogen resistance, and leaf wax formation, enabling their successful adaptation to biotic/abiotic stresses and arid conditions of the Australian continent.
Computationally guided in-vitro vascular growth model reveals causal link between flow oscillations and disorganized neotissue
Authors: van Haaften Eline E. , Quicken Sjeng , Huberts Wouter , Bouten Carlijn V. C. , Kurniawan Nicholas A.
Published: May 2021

Disturbed shear stress is thought to be the driving factor of neointimal hyperplasia in blood vessels and grafts, for example in hemodialysis conduits. Despite the common occurrence of neointimal hyperplasia, however, the mechanistic role of shear stress is unclear. This is especially problematic in the context of in situ scaffold-guided vascular regeneration, a process strongly driven by the scaffold mechanical environment. To address this issue, we herein introduce an integrated numerical-experimental approach to reconstruct the graft–host response and interrogate the mechanoregulation in dialysis grafts. Starting from patient data, we numerically analyze the biomechanics at the vein–graft anastomosis of a hemodialysis conduit. Using this biomechanical data, we show in an in vitro vascular growth model that oscillatory shear stress, in the presence of cyclic strain, favors neotissue development by reducing the secretion of remodeling markers by vascular cells and promoting the formation of a dense and disorganized collagen network. These findings identify scaffold-based shielding of cells from oscillatory shear stress as a potential handle to inhibit neointimal hyperplasia in grafts.
The folding propensity of α/sulfono-γ-AA peptidic foldamers with both left- and right-handedness
Authors: Teng Peng , Zheng Mengmeng , Cerrato Darrell Cole , Shi Yan , Zhou Mi , Xue Songyi , Jiang Wei , Wojtas Lukasz , Ming Li-June , Hu Yong , Cai Jianfeng
Published: May 2021

The discovery and application of new types of helical peptidic foldamers have been an attractive endeavor to enable the development of new materials, catalysts and biological molecules. To maximize their application potential through structure-based design, it is imperative to control their helical handedness based on their molecular scaffold. Herein we first demonstrate the generalizability of the solid-state right-handed helical propensity of the 413-helix of L-α/L-sulfono-γ-AA peptides that as short as 11-mer, using the high-resolution X-ray single crystallography. The atomic level folding conformation of the foldamers was also elucidated by 2D NMR and circular dichroism under various conditions. Subsequently, we show that the helical handedness of this class of foldamer is controlled by the chirality of their chiral side chains, as demonstrated by the left-handed 413-helix comprising 1:1 D-α/D-sulfono-γ-AA peptide. In addition, a heterochiral coiled-coil-like structure was also revealed for the first time, unambiguously supporting the impact of chirality on their helical handedness. Our findings enable the structure-based design of unique folding biopolymers and materials with the exclusive handedness or the racemic form of the foldamers in the future.
A highly stable multifunctional aptamer for enhancing antitumor immunity against hepatocellular carcinoma by blocking dual immune checkpoints
Authors: Du Yanlin , Zhang Da , Wang Yiru , Wu Ming , Zhang Cuilin , Zheng Youshi , Zheng Aixian , Liu Xiaolong
Published: May 2021

A highly stable multifunctional aptamer was prepared for strengthening antitumor immunity through a dual immune checkpoint blockade of CTLA-4 and PD-L1.
Controlling line defects in wrinkling: a pathway towards hierarchical wrinkling structures
Authors: Knapp André , Nebel Lisa Julia , Nitschke Mirko , Sander Oliver , Fery Andreas
Published: May 2021

We show a novel method to generate highly localized and hierarchical wrinkling structures with controllable branching features.
SERS diagnosis of liver fibrosis in the early stage based on gold nanostar liver targeting tags
Authors: Xiang Songtao , Lu Lin , Zhong Huiqing , Lu Min , Mao Hua
Published: May 2021

Liver targeting tags made up of gold nanostars and glycyrrhetinic acid were reported in this paper. Based on the tags, SERS signals and corresponding matters in the early stage of liver fibrosis were analyzed. The diagnosis strategy might be a potential approach in clinic.
Heterotypic tumor models through freeform printing into photostabilized granular microgels
Authors: Molley Thomas G. , Jalandhra Gagan K. , Nemec Stephanie R. , Tiffany Aleczandria S. , Patkunarajah Amrutha , Poole Kate , Harley Brendan A. C. , Hung Tzong-tyng , Kilian Kristopher A.
Published: May 2021

We report the freeform printing of vessel structures and tumor aggregates within a granular suspension of cells and gelatin methacrylate microgels for modelling cancer progression and metastasis.
Synthesis of palygorskite supported spherical ZnS nanocomposites with enhanced photocatalytic activity
Authors: Wang Sheng , Wang Yan , Zhuang Yu , Lian Wei , Ren Hengdong , Liu Yin , Zhang Tianshu , Kong Ling Bing
Published: May 2021

The acquired nanocomposites exhibited a significant enhancement in photoactivity for the degradation of rhodamine B under simulated sunlight irradiation.
Impact of Cu(ii) and Al(iii) on the conformational landscape of amyloidβ1-42
Authors: Roldán-Martín Lorena , Peccati Francesca , Sciortino Giuseppe , Sodupe Mariona , Maréchal Jean-Didier
Published: May 2021

Accelerated molecular dynamics simulations highlight differential behavior between metal free Aβ1-42, Cu(ii)–Aβ1-42 and Al(iii)–Aβ1-42.
Photo-initiated enhanced antibacterial therapy using a non-covalent functionalized graphene oxide nanoplatform
Authors: Mei Lin , Shi Yanmei , Miao Zhiqiang , Cao Fengyi , Hu Kai , Lin Chunlei , Li Xiumin , Li Jing , Gao Jiagui
Published: May 2021

A non-covalent functionalized graphene oxide nanoplatform can kill bacteria at very low dosages and promote rapid healing of bacteria-infected wounds.
Go with the flow: modeling unique biological flows in engineeredin vitroplatforms
Authors: Wasson Elisa M. , Dubbin Karen , Moya Monica L.
Published: May 2021

In this review we outline flow regimes experienced by vasculature, lymphatics, and the intestinal system. We highlight state-of-the-art platforms that aim to replicate physiological flows within engineered tissues and discuss gaps in the field.
Integration of segmented microflow chemistry and online HPLC/MS analysis on a microfluidic chip system enabling enantioselective analyses at the nanoliter scale
Authors: Piendl Sebastian K. , Schönfelder Thomas , Polack Matthias , Weigelt Laura , van der Zwaag Till , Teutenberg Thorsten , Beckert Erik , Belder Detlev
Published: May 2021

In this work, we introduce an approach to merge droplet microfluidics with an HPLC/MS functionality on a single chip to analyze the contents of individual droplets.
Nontoxic photoluminescent tin oxide nanoparticles for cell imaging: deep eutectic solvent mediated synthesis, tuning and mechanism
Authors: Das Laboni , Koonathan Linmariya Devassy , Kunwar Amit , Neogy Suman , Debnath Anil K. , Adhikari Soumyakanti
Published: May 2021

Deep eutectic solvents as versatile green media for the synthesis of non-toxic photoluminescent tin oxide nanoparticles with potential applications demonstrated in cell imaging and as antioxidants.
CO2 electrochemical reduction boosted by the regulated electronic properties of metalloporphyrins through tuning an atomic environment
Authors: Ye Jingjing , Rao Dewei , Yan Xiaohong
Published: May 2021

The selectivity of metalloporphyrins can be regulated via doping ions, and the reduction products are changed from HCOOH to HCHO or CH4 after ion doping, which is attributed to the regulated electronic structure of the metal center.
Palladium-catalyzed stereoselective (3 + 2) cycloaddition of vinylethylene carbonates with cyclic N-sulfonyl ketimines
Authors: Gao Xing , Zhu Dongyu , Jiang Feng , Liao Jianning , Wang Wei , Wu Yongjun , Zheng Lufei , Guo Hongchao
Published: May 2021

Palladium-catalyzed stereoselective (3 + 2) annulation of vinylethylene carbonates with cyclic N-sulfonyl ketimines affording highly functionalized oxazolidine frameworks in good to excellent yields.
Data-driven approximations to the bridge function yield improved closures for the Ornstein–Zernike equation
Authors: Goodall Rhys E. A. , Lee Alpha A.
Published: May 2021

A central challenge for soft matter is determining interaction potentials that give rise to observed condensed phase structures. Here we tackle this problem by combining the power of Deep Learning with the physics of the Ornstein–Zernike equation.
Atomically-dispersed cobalt ions on polyphenol-derived nanocarbon layers to improve charge separation, hole storage, and catalytic activity of water-oxidation photoanodes
Authors: Choi Yuri , Bae Sanghyun , Kim Byeong-Su , Ryu Jungki
Published: May 2021

N-doped graphene quantum dots derived from natural polyphenol tannic acid can form ultrathin and stable layers on a BiVO4 photoanode together with Co2+ ions by a simple dipping method and significantly improve PEC water-oxidation performance.
Controllable synthesis of single-layer graphene over cobalt nanoparticles and insight into active sites for efficient oxygen evolution
Authors: Park Gisang , Shin Cheol-Hwan , Kang Joonhee , Lee Kug-Seung , Zhang Chunfei , Lim Byeonghwa , Kim CheolGi , Yu Jong-Sung
Published: May 2021

Single-layer graphene-coated cobalt core–shell particles (Co@SG and Co@N-SG) are successfully synthesized by using a SiO2 matrix as a radical sieve. Interestingly, the graphene shell possesses varying defects, resulting in key OER active sites.
SmartOil: Blockchain and smart contract‐based oil supply chain management
Authors: Haque Bahalul , Hasan Rifat , Zihad Oahiduzzaman Mondol
Published: May 2021

The traditional oil supply chain suffers from various shortcomings regarding crude oil extraction, processing, distribution, environmental pollution and traceability. It offers only forward flow of products with limitations in quality inspection, fraudulent information and monopolistic behavior of supply chain entities. Inclusion of counterfeiting products and opaqueness of the system urge renovation in this sector. Technological advancement can now reshape the infrastructure of the supply chain for the future. Here, a conceptual framework utilizing blockchain and smart contract to monitor the overall oil supply chain is suggested. Blockchain is a used to monitor and support the security building of a decentralized type supply chain. The Internet of Things (IoT) sensors open a broader window to track the process and attributes in real time. A methodology to support reverse traceability for each participant of the supply chain is constructed. Implementation of smart contracts is also shown with detailed analysis. The challenges of implementing such a system are further described and our framework's adaptability in the real world is validated. The paper concludes with future research scope to mitigate the restrictions of data management and maintenance with advanced
working prototypes and agile systems achieving greater traceability and transparency.
Linking ice and gas in the λ Orionis Barnard 35A cloud
Authors: Perotti G. , Jørgensen J. K. , Fraser H. J. , Suutarinen A. N. , Kristensen L. E. , Rocha W. R. M. , Bjerkeli P. , Pontoppidan K. M.
Published: May 2021

Context. Dust grains play an important role in the synthesis of molecules in the interstellar medium, from the simplest species, such as H2, to complex organic molecules. How some of these solid-state molecules are converted into gas-phase species is still a matter of debate.

Aims. Our aim is to directly compare ice and gas abundances of methanol (CH3OH) and carbon monoxide (CO) obtained from near-infrared (2.5−5 μm) and millimetre (1.3 mm) observations and to investigate the relationship between ice, dust, and gas in low-mass protostellar envelopes.

Methods. We present Submillimeter Array (SMA) and Atacama Pathfinder EXperiment (APEX) observations of gas-phase CH3OH (JK = 5K−4K), 13CO, and C18O (J = 2−1) towards the multiple protostellar system IRAS 05417+0907, which is located in the B35A cloud, λ Orionis region. We use archival IRAM 30 m data and AKARI H2O, CO, and CH3OH ice observations towards the same target to compare ice and gas abundances and directly calculate CH3OH and CO gas-to-ice ratios.

Results. The CO isotopologue emissions are extended, whereas the CH3OH emission is compact and traces the giant molecular outflow emanating from IRAS 05417+0907. A discrepancy between sub-millimetre dust emission and H2O ice column density is found for B35A−4 and B35A−5, similar to what has previously been reported. B35A−2 and B35A−3 are located where the sub-millimetre dust emission peaks and show H2O column densities lower than that of B35A−4.

Conclusions. The difference between the sub-millimetre continuum emission and the infrared H2O ice observations suggests that the distributions of dust and H2O ice differ around the young stellar objects in this dense cloud. The reason for this may be that the four sources are located in different environments resolved by the interferometric observations: B35A−2, B35A−3, and, in particular, B35A−5 are situated in a shocked region that is plausibly affected by sputtering and heating, which in turn impacts the sub-millimetre dust emission pattern, while B35A−4 is situated in a more quiescent part of the cloud. Gas and ice maps are essential for connecting small-scale variations in the ice composition with the large-scale astrophysical phenomena probed by gas observations.
X-ray emission from magnetized neutron star atmospheres at low mass-accretion rates
Authors: Sokolova-Lapa E. , Gornostaev M. , Wilms J. , Ballhausen R. , Falkner S. , Postnov K. , Thalhammer P. , Fürst F. , García J. A. , Shakura N. , Becker P. A. , Wolff M. T. , Pottschmidt K. , Härer L. , Malacaria C.
Published: May 2021

Recent observations of X-ray pulsars at low luminosities allow, for the first time, the comparison of theoretical models of the emission from highly magnetized neutron star atmospheres at low mass-accretion rates (Ṁ ≲ 1015 g s−1) with the broadband X-ray data. The purpose of this paper is to investigate spectral formation in the neutron star atmosphere at low Ṁ and to conduct a parameter study of the physical properties of the emitting region. We obtain the structure of the static atmosphere, assuming that Coulomb collisions are the dominant deceleration process. The upper part of the atmosphere is strongly heated by the braking plasma, reaching temperatures of 30–40 keV, while its denser isothermal interior is much cooler (∼2 keV). We numerically solve the polarized radiative transfer in the atmosphere with magnetic Compton scattering, free–free processes, and nonthermal cyclotron emission due to possible collisional excitations of electrons. The strongly polarized emitted spectrum has a double-hump shape that is observed in low-luminosity X-ray pulsars. A low-energy “thermal” component is dominated by extraordinary photons that can leave the atmosphere from deeper layers because of their long mean free path at soft energies. We find that a high-energy component is formed because of resonant Comptonization in the heated nonisothermal part of the atmosphere even in the absence of collisional excitations. However, these latter, if present, affect the ratio of the two components. A strong cyclotron line originates from the optically thin, uppermost zone. A fit of the model to NuSTAR and Swift/XRT observations of GX 304−1 provides an accurate description of the data with reasonable parameters. The model can thus reproduce the characteristic double-hump spectrum observed in low-luminosity X-ray pulsars and provides insights into spectral formation.
Machine learning techniques in studies of the interior structure of rocky exoplanets
Authors: Zhao Yong , Ni Dongdong
Published: May 2021

Context. Earth-sized exoplanets have been discovered and characterized thanks to new developments in observational techniques, particularly those planets that may have a rocky composition that is comparable to terrestrial planets of the Solar System. Characterizing the interiors of rocky exoplanets is one of the main objectives in investigations of their habitability. Theoretical mass-radius relations are often used as a tool to constrain the internal structure of rocky exoplanets. But one mass-radius curve only represents a single interior structure and a great deal of computation time is required to obtain all possible interior structures that comply with the given mass and radius of a planet.

Aims. We apply a machine-learning approach based on mixture density networks (MDNs) to investigate the interiors of rocky exoplanets. We aim to provide a well-trained MDN model to quickly and efficiently predict the interior structure of rocky exoplanets.

Methods. We presented a training data set of rocky exoplanets with masses between 0.1 and 10 Earth masses based on three-layer interior models by assuming Earth-like compositions. This data set was then used to train the MDN model to predict the layer thicknesses and core properties of rocky exoplanets, where planetary mass, radius, and water content are inputs to the MDN. The performance of the trained MDN model was investigated in order to discern its predictive ability.

Results. The MDN model is found to show good performance in predicting the layer thicknesses and core properties of rocky exoplanets through a comparison with the real solutions obtained by solving the interior models. We also applied the MDN model to the Earth and the super-Earth exoplanet LHS 1140b. The MDN predictions are in good agreement with the interior model solutions within the uncertainties of planetary mass and radius. More importantly, the MDN model takes a much shorter computational time compared to the cost of the interior model calculations, offering a convenient and powerful tool for quickly obtaining information on planetary interiors.
Spatial Load Prediction Considering Spatiotemporal Distribution of Electric Vehicle Charging Load
Authors: Gao Xiang , Wei Lingyan , Wang Bing , Chen Guiru , Wu Xiaoyue
Published: May 2021

In view of the influence of large-scale electric vehicle access to the distribution network on spatial load prediction, this paper proposes a spatial load prediction method for urban distribution network considering the spatial and temporal distribution of electric vehicle charging load. Firstly, electric vehicles are classified according to charging mode and travel characteristics of various types of vehicles. Secondly, the probability distribution function is fitted to the travel rules of electric vehicles according to the travel survey and statistical data of residents. Then, the model of electric vehicle travel chain is constructed, and the charging load in different regions and different times is calculated by Monte Carlo method. Finally, based on the actual data of a certain area, the predicted spatial load values of different functional communities in one day are obtained, which can provide reference for future urban distribution network planning.
Research on Improving Transient Stability of Power System with Distributed BESS and its Coordinated Control Method
Authors: Su Can , Zhou Hao , Yan Peng , Meng Liang , Cheng Ziwei
Published: May 2021

The feasibility of battery energy storage system (BESS) in ameliorating power system transient stability has been proved. However, the required BESS capacity is large, which leads to high price. Meanwhile, the improving effect is significantly affected by fault location and BESS location. To address the problem, a distributed configuration of BESS, with a coordinated control method, is proposed in this paper. Firstly, an independent double-closed loop decoupling controller is designed for each BESS, so that the BESS unit can realize decentralized control according to its local correlation information. Secondly, particle swarm optimization is applied to optimize the control parameters of the distributed controllers to achieve coordinated control. Simulation results show that the distributed BESS controllers optimized by particle swarm optimization can better coordinate with each other, and the transient stability of the system is significantly improved.
Technical requirements and economic benefit evaluation of interaction between vessel charging and battery swapping stations and power Grid
Authors: Jia Jun Guo , Xing Jian Xu , Song Jin Hai , Xiao Chao Yun , Jia Jun , Liu Hai Feng , Zheng Song Song
Published: May 2021

Electric vessels have developed rapidly with the advancement of transportation electrification in recent years. The power battery capacity of large vessels usually reaches several MWhs, in which case battery change technology is more applicable. A vessel charging and battery swapping station has the dual attributes of power utilization and energy storage and can realize Vessel to Grid through charging and discharging facilities. Aiming at the scenarios of interaction between vessel charging and battery swapping stations and the power grid, this paper studied technical requirements of several participants, established an input-output analysis model and analyzed multiple influencing factors. The results show that revenues cannot be increased effectively with the increase of the number of spare batteries alone; the interactive service can achieve a balance of payments when the battery cost is higher than 1.4 ¥/ Wh, and; benefits may not be gained when the battery life is less than 5 years.
Research and application of bypass replacement logic and risk control of stability control device
Authors: Gang Wang , Ke Xu
Published: May 2021

In order to prevent the power failure of the whole line caused by the maintenance of line switch, bypass switch is set in 220kV Main Wiring of some power plants. When the bypass replaces a line, there are three states in turn: line, bypass and line parallel operation, bypass operation. The bypass replacement logic of stability control device needs to correctly distinguish and switch these three states. This paper deeply studies the variation law of bypass, line analog and switching value in the whole bypass replacement process, puts forward the correct switching judgment method of line outage, trip and overload criteria, as well as the operation risk and prevention and control measures of bypass platen in the bypass replacement process, and then takes a power plant stability control device as an example to verify the results, which shows that the bypass replacement logic proposed in this paper is feasible. Risk prevention and control measures can ensure the correctness of logical discrimination of stability control devices in the process of bypass replacement, and can be extended to other power plant stability control devices.
Nontechnical Loss Detection using Neural Architecture Search and Outlier Detection
Authors: Fei Ke , Li Qi , Cui Can , chen Xue , Xu Xinxin , Xue Benshan , Cai Weifeng
Published: May 2021

Electricity supply is essential to economy growth and improvement of people’s life. For a long time, illegal electricity theft not only affects the supply of power, but also causes significant economic loss. Traditional techniques for detecting electricity theft are inefficient and time-consuming. Data-based detecting algorithms become a new solution. This article analyses the features of electricity consumption, current, voltage and opening records under various electricity theft modes and proposes a new simulation method for electricity theft users. Based on the simulation dataset, a feature extraction method based on neural architecture search (NAS) is proposed. The advantage of this feature extraction model is demonstrated in the comparison experiments with other feature extraction model. Finally, the effectiveness and accuracy of the electricity theft detection method based on NAS model and outlier detection are verified through an industrial case study.
Influence Analysis of Current Limiting Reactor on Pole-to-Pole Short Circuit Fault in DC Distribution System
Authors: Wang Zhenyu , Wang Shouxiang , Liu Qi , Zhang Chunyu , Zhao Qianyu , Mu Hao
Published: May 2021

With the development of power electronic technology, flexible DC distribution system has gradually become a research hotspot. Pole-to-pole short circuit fault is the most serious fault type in DC distribution system. When pole-to-pole short circuit fault occurs in DC side, it will produce a large fault current, which will cause serious harm to DC distribution system. Therefore, it is urgent to install current limiting reactor to limit fault over-current. Aiming at the DC distribution system based on half bridge MMC, this paper analyses the fault mechanism and fault characteristics of pole-to-pole short circuit fault, studies the current limiting effect of the installation position and capacity of current limiting reactor on fault current, and carries out simulation verification in PSCAD / EMTDC platform. The analysis and simulation results show that installing a current limiting reactor at the outlet of the DC side can reduce the peak value of capacitor discharge current, and installing a current limiting reactor at the outlet of the AC side can reduce the overall amplitude of fault current.
A Multi-Functional De-Icing Equipment Using Modular Parallel PWM Current Source Converters
Authors: Hu Yang , Zhang Heng , Chen Jing , Zhang Huan , Liu Xinmeng , Li Jiachen , Chen Hanyu , Hu Haiyang
Published: May 2021

For transmission line de-icing, a five level specific harmonic elimination (5l-she) modulation method for high-power parallel current source is proposed, which realizes the current balance of DC bridge arm and the suppression of common mode voltage, and ensures the power quality of grid connected current at low switching frequency. In addition the reactive power of the low voltage load can be compensated at the same time. Firstly, the switching states are classified according to the different mode lengths of PWM current, and the common mode voltage corresponding to each switching state is calculated. Secondly, the current sharing control strategy is established based on the analysis of the influence of redundant switching state on the current sharing of DC bridge arm. Then, the 5l-she waveform is constructed based on the switching state with lower common mode voltage, and the redundant switching states is optimized according to the current sharing strategy. Finally, the effectiveness of the proposed method is verified by simulation.
Optimal configuration of energy storage system in multi-station fusion mode
Authors: Du Zhendong , Jin Guosheng , Fang Yu , Yu Chenyin , Hu Yupeng , Guo Chuangxin , Wang Chutong
Published: May 2021

Multi-station fusion mode (MSF) generally includes energy storage system, data center and electric vehicle charging station. It can improve the utilization rate of land and power distribution resources of urban substations. This paper studies configuration of ESS in the MSF model, aiming at reducing total cost. Firstly, an AC-DC system of MSF model is established. Then, aiming at economy, the optimal configuration model of ESS is established. Finally, the effectiveness of the model is verified by a practical example, and the MATLAB toolbox YALMIP with the CPLEX solver is used to conduct the ESS planning.
The Long-Term Optimization Model of Pumped-Hydro Power Storage System Based on Approximate Dynamic Programming
Authors: Liang Zhencheng , Li Ling , Li Yiming , Zhang Pan , Luo Cuiyun
Published: May 2021

Based on the hypothesis that pumped storage power station is available for multi-day optimization and adjustment, the paper has proposed a long-term operation optimization model of pumped-hydro power storage (PHPS) system based on approximate dynamic programming (ADP). In this multistage decision model, across the stages, value function approximation (VFA) of the reservoir energy storage was used to keep the overall optimization characteristics; during the stages, generated energy & generating periods, and electricity consumption for pumping & pumping periods are used as decision variables to conduct daily optimization operation. The paper got the approximate optimal solution through iteration solution decision variable and value function so as to avoid “curse of dimensionality” in conventional multistage decision model. According to the experiment, the ADP-based model can accurately describe the long-term operation modes of pumped storage power station, and its calculation methods are more appropriate for this kind of large-scale optimized decision problem than conventional mathematic planning methods.
Research on the designation of business model and bi-level optimization scheduling strategy of a VPP in energy market
Authors: Zhang Ming , Guo Mingxing , Bai Bingqing , Guan Shufeng , Lyu Ran , Wang Su , Xu Gaoxiu
Published: May 2021

With the rapid development of distributed energy resource, a more powerful market operation and energy management system is in great demand for a more precise scheduling strategy. And owing to the advantages in communication and control, virtual power plant (VPP) can provide solutions to these problems. In this paper, the business orientation and service plan are discussed first. Then the mathematical model of the settled market is established to figure out the scheduling strategy of participating in energy market. And a bi-level optimization model is built, with the upper level of maximizing the profits of VPP and lower level of clearing process of energy market. Finally, the scheduling scheme under typical scenarios is discussed in the example, and the ability of the VPP to adapt to the price change is analyzed. It can be seen that the VPP can adjust its own load and processing in the face of price fluctuation to achieve the maximum benefit.
Joint Optimization for Visual Data Transmission in the Resource Constraint 5G IoT
Authors: Xu Jingce , Zhang Xinsheng , Lu Jianfei
Published: May 2021

With the integration of 5G and Internet of Things (IoT), the application of large-scale IoT devices networking is increasingly extensive, such as building management, property maintenance, autonomous vehicles, healthcare, and shopping to tourism. In these scenes, the volume of data transmission is quite large, especially visual data (image, video, et al). However, due to the limited resource of IoT devices, such as battery, power, bandwidth, visual data transmission is complex to optimize, single objective optimization is difficult to insure the optimal latency, throughput and power at the same time. In this paper, we propose a method to jointly optimize the resource allocation of visual data transmission in resource constraint 5G IoT. Instead of single objective optimization, we combine the bandwidth, power consumption and latency into a hybrid model, then propose a low-complexity algorithm to solve this multiple objective optimization problem. The simulation results demonstrate that the proposed method increases the comprehensive utility of visual data transmission in the resource constraint 5G-IoT by 35%-48% compared with existing approaches.
Optimal Configuration of Photovoltaic-wind-storage Microgrid for Agricultural Irrigation in Mountainous Areas
Authors: Zhang Yangyang , Li Bin , Deng Youxiong , Lian Chunjie , Wang Jingde
Published: May 2021

Water and electricity supply for irrigation is difficult in remote mountainous areas. This paper explores agricultural irrigation systems’ integration mechanism, pumped storage power plants, and renewable power sources in mountainous areas to solve this problem. It establishes a microgrid power supply system with multiple complementary energy sources according to local conditions. By analyzing the load of agricultural irrigation in mountainous areas, the irrigation water consumption and electricity consumption are obtained. The capacity of pumped storage power stations, wind power, and photovoltaic power generation in the microgrid can be configured accordingly. They use the renewable power supply active power fluctuation rate index as a constraint and use the spectrum analysis method to calibrate the capacity configuration results. Finally, the scenic storage microgrid model is constructed and solved to minimize the microgrid’s grid connection cost. The algorithm shows that the proposed capacity allocation method can meet the irrigation load demand and realize the microgrid’s coordinated operation.
Optimal scheduling of regional integrated energy system considering multiple uncertainties
Authors: Guan Shufeng , Wang Lingling , Jiang Chuanwen
Published: May 2021

Integrated energy system (IES) is an effective way to realize the efficient utilization of energy. Under the deregulated electricity market, IES operator gains profits by providing customers with energy service, including electricity, heat or cooling energy. With the deepening of market reform, higher penetration rate of renewable energy, economic risks embed in the IES. Based on this, an optimal scheduling model of regional IES considering uncertainties is proposed, aiming at maximizing the profits. Scenario analysis method has been adopted to model the uncertainties: Markov-Chain-Monte-Carlo (MCMC) sampling method, which has a better performance in fitting the probability distribution, is utilized to generate scenarios; K-means clustering method is applied to narrow down the sampling sets. By replacing the parameters in the deterministic model with the sampling sets, a series of optimal results can be achieved. The case study shows that the cooling storage tank can improve the economic benefits about 4.97% by converting electricity to cooling energy at lower price period and releasing energy at peak hours. Besides, through the proposed optimization model, operators can have a straight understanding of the venture brought by the uncertainties and a more reliable scheduling result is formed for reference.
Multi-energy load forecasting model based on bi-directional gated recurrent unit multi-task neural network
Authors: Zheng Zhijie , Feng Liang , Wang Xuan , Liu Rui , Wang Xian , Sun Yi
Published: May 2021

The complex coupling, coordination and complementarity of different energy in the integrated energy system puts forward higher requirements for the technology of multi-energy load forecasting. To this end, this paper proposes a novel multi-energy load forecasting model based on bi-directional gated recurrent unit (BiGRU) multi-task neural network. Firstly, through the correlation analysis, an effective multi-energy load input data set is constructed. Secondly, the input data set is utilized to train the BiGRU and master the evolution laws of multi-energy loads. Then, multi-task learning (MTL) is used to share the information learned by BiGRU from perspectives of different load forecasting tasks, so as to fully dig the coupling relations among various energy loads. Finally, different types of load forecasting results can be obtained. Simulation results show that BiGRU can simultaneously consider the known data of the past and the future, and it can learn more characteristic information effectively. At the same time, the proposed model utilizes MTL to carry out parallel learning and information sharing for forecasting tasks of various energy loads, which can dig the complex coupling relations among different types of loads more deeply, thus improving the forecasting accuracy of multi-energy loads.
Research on Distributed Power Planning Based on Supply Equipment Capacity Limitation
Authors: Liu Qiulin , Xie Xiaofan , Wang Lei
Published: May 2021

Due to the rapid economic development in recent years, the original transformers and other power supply equipment is difficult to meet the demand of the rapid growth of electricity consumption. In order to reduce the cost of power supply, adding photovoltaic/wind power/energy storage system is an effective means to meet the demand of users to achieve regional balance without the overall reform of the system. In this paper, with reference to Ganzhou region under different growth rate of electricity a internal power supply area, considering the three-phase imbalance and photovoltaic (pv) power supply under different weather factors efficiency under different conditions, building composed of piconets and time division at micro network life period earnings are applied to solve the highest net present value as the goal on the premise of micro power grid planning for the next step, meet the increasing social demand of power supply area, improve power supply reliability, provide strong theoretical support. Finally, based on the power supply load of a certain region in Ganzhou, the method is calculated and proved to be effective.
Suchtspezifische Schulungsbedarfe von Jobcenterfachkräften in der Beratung und Vermittlung von Menschen mit einer Suchterkrankung
Authors: Kuhn Ulrike , Herrlein Jannah
Published: May 2021

Ziel der Studie Der suchtspezifische Qualifikationsstand von Jobcenterfachkräften hat einen Einfluss auf die berufliche Integration von Arbeitslosengeld II-Beziehenden mit Suchtproblemen. In der vorliegenden Studie wurde der suchtspezifische Weiterbildungsbedarf von Jobcenterfachkräften in 4 Grundsicherungsstellen in Nordrhein-Westfalen (NRW) ermittelt, um auf der Grundlage dieser Bedarfsanalyse ein passgenaues Weiterbildungskonzept zum Thema Sucht für Beschäftigte in den Jobcentern zu entwickeln.

Methode Um die Weiterbildungsbedarfe sowie geeignete Rahmenbedingungen zu identifizieren, wurde eine standardisierte Onlinebefragung in 4 Jobcentern in Nordrhein-Westfalen (im Rechtskreis des Sozialgesetzbuchs II (SGB II)) durchgeführt. Diese orientierte sich inhaltlich an der bundesweiten Erhebung zu den Rahmenbedingungen für suchtkranke Leistungsbeziehende und enthielt neben Items zu Schulungs- und Beratungsbedarfen auch Fragen zu bisher besuchten suchtspezifischen Weiterbildungen sowie geeigneten Rahmenbedingungen für eine bedarfsorientierte Umsetzung einer Schulung zum Thema Sucht.

Ergebnisse Insgesamt nahmen an der Befragung 511 Jobcenterfachkräfte teil. Es konnte eine Netto-Rücklaufquote von 64,1% erzielt werden. 76% der Befragten geben einen suchtbezogenen Schulungsbedarf an, wobei insgesamt 29,4% der Stichprobe hierzu bereits geschult worden sind. Die größten Bedarfe werden bereichsübergreifend im Erkennen von Suchtproblemen (55,1%) und im Ansprechen auf Suchtverdacht (52,1%) gesehen. Je nach Fachkräftegruppe zeigen sich unterschiedliche Schwerpunktsetzungen in den Bedarfen: Integrationsfachkräfte geben neben den genannten Aspekten einen hohen Bedarf in der Bedeutung der Sucht für die Arbeitsfähigkeit (54,3%) und im Überblick über suchtspezifische Behandlungsangebote (51,4%) an, Leistungssachbearbeiterinnen und -bearbeiter in Deeskalationsstrategien (49,8%). Eine Präsenzschulung wird von 85,8% gegenüber Online- oder Blended-Learning-Angeboten bevorzugt. Diese soll eher von einer externen Bildungsleitung (90,1%) als von internen Mitarbeitenden (9,9%) durchgeführt werden.

Schlussfolgerung Der Bedarf an suchtspezifischen Schulungen ist trotz verschiedener Bemühungen und Initiativen der letzten Jahre weiterhin hoch. Die wichtigsten Schulungsbedarfe beziehen sich eher auf konkrete Integrationsangebote und praktische Unterstützungsmöglichkeiten der Betroffenen als auf Informationen zu Sucht oder Methoden und Vorgehensweisen im Beratungsprozess. Auch Leistungssachbearbeiterinnen und -bearbeiter sollten in Schulungen einbezogen werden. In diesem Bereich sind jedoch stärker Beratungsstrategien relevant.