bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protein cages as building blocks for superstructures
Authors: Sun Ruoxuan , Lim Sierin 
Published: June 2021

AbstractProteins naturally self‐assemble to function. Protein cages result from the self‐assembly of multiple protein subunits that interact to form hollow symmetrical structures with functions that range from cargo storage to catalysis. Driven by self‐assembly, building elegant higher‐order superstructures with protein cages as building blocks has been an increasingly attractive field in recent years. It presents an engineering challenge not only at the molecular level but also at the supramolecular level. The higher‐order constructs are proposed to provide access to diverse functional materials. Focussing on design strategy as a perspective, current work on protein cage supramolecular self‐assembly are reviewed from three principles that are electrostatic, metal‐ligand coordination and inherent symmetry. The review also summarises possible applications of the superstructure architecture built using modified protein cages.
Deception electronic counter‐countermeasure applicable to multiple jammer sources in distributed multiple‐radar system
Authors: Zhao Shanshan , Liu Ziwei 
Published: June 2021

AbstractDeception jamming poses a fatal threat to the radar performance, and its jamming performance has been greatly improved through networking. However, available deception electronic counter‐countermeasure (ECCM) methods are mostly developed in the scenario of a single jamming source. Therefore, it is of great importance to develop deception ECCM methods that can counter multiple jammers. This work proposes a deception jamming discrimination method applicable to multiple jammer sources in distributed multiple‐radar system, based on the correlation coefficient between different target‐received signal vectors. The false targets generated by one jammer are highly correlated, while a radar target is uncorrelated with either other radar targets or false targets. For the estimated correlation coefficient, the Fisher z‐transformation is applied to determine the correlation between targets with the Z‐test. Since the jammer usually generates multiple false targets at once to enhance its deceptions, a target can be judged as a false target when multiple targets are highly correlated with it; otherwise a radar target is declared. More importantly, compared with existing methods, no prior information is required here. Simulation results corroborate the feasibility of the proposed discrimination method and its performance due to the influence of jamming‐to‐noise ratio. The spatial correlation of radar targets and geometry conditions are covered.
Coprime array‐adaptive beamforming via atomic‐norm‐based sparse recovery
Authors: Cheng Yun , Zhang Xinyu , Liu Tianpeng , Shi Junpeng , Liu Zhen , Hu Panhe , Li Xiang 
Published: June 2021

AbstractCoprime arrays (CPAs) have been found to be an effective configuration for adaptive beamforming (ABF). However, most ABF methods for CPAs are embedded with the spatial spectrum estimation technique, and therefore they usually deteriorate in the case of low signal‐to‐noise ratio (SNR), especially without prior information of interferences. To address this issue, a robust ABF method for CPAs via atomic‐norm‐based sparse recovery is proposed. This method begins with initialised virtual array interpolation to avoid aperture loss caused by ‘holes’, which is subsequently transformed to a matrix completion and denoising issue via a Toeplitz step. With the matrix’s Hermitian Toeplitz structure and the intrinsic sparsity of interferences, sparse recovery for the interference covariance matrix is introduced by subtracting the target signal and noise from the received signal and implemented by atomic‐norm minimisation. Concretely, this non‐convex process is decomposed into two convex steps and solved iteratively. Unlike previous methods, this method can interpolate the virtual array and estimate the steering vector of the target and the noise power simultaneously; consequently, the interference‐plus‐noise covariance matrix is reconstructed with merely some trivial entry selections without the need for the spatial spectrum. Furthermore, the optimality conditions and boundedness in this method are proven theoretically. Simulation results demonstrate the effectiveness of the proposed method and its advantages over previous methods under those non‐ideal conditions.
ELISa: A new tool for fast modelling of eclipsing binaries
Authors: Čokina Michal , Fedurco Miroslav , Parimucha Štefan 
Published: June 2021

Context. We present a new, fast, and easy to use tool for modelling light and radial velocity curves of close eclipsing binaries with built-in methods for solving an inverse problem.
Aims. The main goal of ELISa (Eclipsing binary Learning and Interactive System) is to provide an acceptable compromise between computational speed and precision during the fitting of light curves and radial velocities of eclipsing binaries. The package is entirely written in the Python programming language in a modular fashion, making it easy to install, modify, and run on various operating systems.
Methods. ELISa implements Roche geometry and the triangulation process to model a surface of the eclipsing binary components, where the surface parameters of each surface element are treated separately. Surface symmetries and approximations based on the similarity between surface geometries were used to reduce the runtime during light curve calculation significantly. ELISa implements the least square trust region reflective algorithm and Markov-chain Monte Carlo optimisation methods to provide the built-in capability to determine parameters of the binary system from photometric observations and radial velocities.
Results. The precision and speed of the light curve generator were evaluated using various benchmarks. We conclude that ELISa maintains an acceptable level of accuracy to analyse data from ground-based and space-based observations, and it provides a significant reduction in computational time compared to the current widely used tools for modelling eclipsing binaries.
Solar prominence diagnostics from non-LTE modelling of Mg II h&k line profiles
Authors: Peat A. W. , Labrosse N. , Schmieder B. , Barczynski K. 
Published: June 2021

Aims. We investigate a new method to for obtaining the plasma parameters of solar prominences observed in the Mg II h&k spectral lines by comparing line profiles from the IRIS satellite to a bank of profiles computed with a one-dimensional non-local thermodynamic equilibrium (non-LTE) radiative transfer code.
Methods. Using a grid of 1007 one-dimensional non-LTE radiative transfer models, some including a prominence-corona transition region (PCTR), we carry out this new method to match computed spectra to observed line profiles while accounting for line core shifts not present in the models. The prominence observations were carried out by the IRIS satellite on 19 April 2018.
Results. The prominence is very dynamic with many flows, including a large arm extending from the main body seen near the end of the observation. This flow is found to be redshifted, as is the prominence overall. The models are able to recover satisfactory matches in areas of the prominence where single line profiles are observed. We recover: mean temperatures of 6000–50 000 K; mean pressures of 0.01–0.5 dyne cm−2; column masses of 3.7 × 10−8–5 × 10−4 g cm−2; a mean electron density of 7.3 × 108–1.8 × 1011 cm−3; and an ionisation degree nHII/nHI = 0.03 − 4500. The highest values for the ionisation degree are found in areas where the line of sight crosses mostly plasma from the PCTR, correlating with high mean temperatures and correspondingly no Hα emission.
Conclusions. This new method naturally returns information on how closely the observed and computed profiles match, allowing the user to identify areas where no satisfactory match between models and observations can be obtained. The inclusion of the PCTR was found to be important when fitting models to data as regions where satisfactory fits were found were more likely to contain a model encompassing a PCTR. The line core shift can also be recovered from this new method, and it shows a good qualitative match with that of the line core shift found by the quantile method. This demonstrates the effectiveness of the approach to line core shifts in the new method.
Die Spül-Saug-Drainage zur Therapie der septischen Tenosynovialitis der Fingerbeugesehnen
Authors: Pillukat Thomas , Rahimli M. , Windolf J. , van Schoonhoven Jörg 
Published: June 2021

Zusammenfassung
Hintergrund/Ziel Die septische Tenosynovialitis der Beugesehnenscheiden erfordert eine dringliche Behandlung, um Sehnennekrosen und den Verlust von Fingern zu verhindern. Gegenstand des vorliegenden Artikels ist die Behandlung durch Revision und postoperativ kontinuierliche Spülung über eine geschlossene Spül-Saug-Drainage.
Patienten und Methoden Vom 1.1.2007 bis zum 31.12.2016 wurden 54 Patienten mit septischer Tenosynovialitis einer Beugesehnenscheide mit einer Spül-Saug-Drainage behandelt. Zusätzlich zur Auswertung der Krankenakten (betroffener Finger, betroffene Hand, Dauer des stationären Aufenthaltes, notwendige Revisionsoperationen) konnten 33 Patienten (19 Männer und 14 Frauen) mit einem Durchschnittsalter von 51 (8–85) Jahren nach durchschnittlich 21 (4–38) Monaten nachuntersucht werden. Dabei wurden die Beweglichkeit des betroffenen Fingers/Daumens (Abstand der Fingerkuppe zur distalen Hohlhandbeugefurche beim Faustschluss, resp. der Kapandji-Index), die Grobkraft/Spitzgriffkraft prozentual zur unverletzten Gegenseite, die Schmerzen mittels numerischer Ratingskala (NRS) und der DASH-Score erfasst. Das Gesamtergebnis wurde mittels des Bewertungsschemas von Buck-Gramcko für Beugesehnenrekonstruktionen beurteilt.
Ergebnisse Der Krankenhausaufenthalt dauerte im Durchschnitt 9 (3–26) Tage. Elfmal war eine Revision erforderlich, 3-mal davon eine Neuanlage der Spül-Saug-Drainage, 2-mal eine Strahlresektion und einmal eine Amputation in Höhe des Mittelgelenkes. Die nachuntersuchten Patienten wiesen im Mittel eine Grobkraft von 84 (23–163) % der nicht betroffenen Gegenseite auf. Der Ruheschmerz betrug durchschnittlich 0,2 (0–4), der Belastungsschmerz 1,2 (0–8) auf der NRS, der DASH-Score 16,8 (0–58) Punkte. Nach dem Bewertungssystem für Beugesehnenfunktionen war ein Ergebnis unbefriedigend, eines befriedigend, 5 gut und 26 sehr gut.
Schlussfolgerungen Die kontinuierliche Spülung über eine Spül-Saug-Drainage bei der septischen Tenosynovialitis der Beugesehnenscheiden ist ein erfolgreiches Verfahren mit niedriger Amputationsrate. Die funktionellen Ergebnisse sind überwiegend gut und sehr gut.
Gelenkinfektionen an Hand und Handgelenk
Authors: Lamou Hayat Jolie , Kim Simon , Kuchenbuch Christian , Thelen Simon , Eisenschenk Andreas , Hakimi Mohssen 
Published: June 2021

ZusammenfassungDiese Arbeit gibt einen Überblick über Epidemiologie, Ätiologie, Klinik, Diagnostik und Therapie von Infektionen an Hand und Handgelenk.
Electrical conductivity measurement of λ DNA molecules by conductive atomic force microscopy
Authors: Wang Ying , Xie Ying , Gao Mingyan , Zhang Wenxiao , Liu Lanjiao , Qu Yingmin , Wang Jiajia , Hu Cuihua , Song Zhengxun , Wang Zuobin 
Published: June 2021

Abstract
Conductive atomic force microscopy (C-AFM) is a powerful tool used in the microelectronics analysis by applying a certain bias voltage between the conducting probe and the sample and obtaining the electrical information of sample. In this work, the surface morphological information and current images of the lambda DNA (λ DNA) molecules with different distributions were obtained by C-AFM. The 1 and 10 ng μl−1 DNA solutions were dripped onto mica sheets for making randomly distributed DNA and DNA network samples, and another 1 ng μl−1 DNA sample was placed in a DC electric field with a voltage of 2 V before being dried for stretching the DNA sample. The results show that the current flowing through DNA networks was significantly higher than the stretched and random distribution of DNA in the experiment. The I–V curve of DNA networks was obtained by changing the bias voltage of C-AFM from −9 to 9 V. The currents flowing through stretched DNA at different pH values were studied. When the pH was 7, the current was the smallest, and the current was gradually increased as the solution became acidic or alkaline.
A comparative review of some physicochemical properties of biodiesels synthesized from different generations of vegetative oils
Authors: Binhweel Fozy , Bahadi Murad , Pyar Hassan , Alsaedi Alyaa , Hossain Sohrab , Ahmad Mardiana Idayu 
Published: June 2021

Abstract
Physicochemical properties of different biodiesel generations synthesized from 11 vegetative oils have been reviewed in purpose of comparing the values of biodiesel physicochemical properties and determination the required feedstock for preferable biodiesel. According to the review, two main factors are affecting the physicochemical properties of yielded biodiesel; the first factor is the raw material of vegetative oil that leads to inherent properties like the energy content, cloud, pour, flash points, kinematic viscosity, cetane and iodine numbers. The other factor is synthesis method and handling procedures of biodiesel production which results in properties such as alcohol and glycerin content, suspended solids, and acid value. This review focuses on 9 important physicochemical properties; Density at 15 °C, kinematic viscosity at 40 °C, cloud, pour, and flash points, heating value, acid value, Cetane number, and iodine number. The standards of ASTM D6751, EN 14214, IS 15607, and MS 2008:2008 are provided to check matching with the physiochemical properties of reviewed biodiesels.
Rainfall forecasting in arid regions using an ensemble of artificial neural networks
Authors: Elshaboury N , Elshourbagy M , Al-Sakkaf A , Abdelkader E M 
Published: June 2021

Abstract
Water rainfall prediction is one of the most difficult tasks in hydrology because rainfall events are extremely random. This research presents a comparative analysis of different models that predict rainfall in an arid region. The forecasting models comprise the feed-forward, general regression, recurrent, cascade, and Elman neural networks. The performance of the aforementioned models is assessed using three evaluation metrics, namely the correlation coefficient, coefficient of efficiency, and Willmott’s index of agreement. Furthermore, the statistical significance of the neural network models is evaluated using the Wilcoxon-Mann-Whitney test. Finally, the correspondence of the neural network model results compared to the observations is examined using the Taylor diagram. The findings reveal that the general neural network exhibits the best performance compared to other models using the tropical rainfall measuring mission dataset at Suez city in Egypt. The Egyptian water municipality is intended to benefit from the proposed model in monthly rainfall forecasting in this arid region. The precise modeling of rainfall is vital for managing water resources such as food production, water allocation, and drought management.
Study of Multichannel QCM Prospects in VOC Detection
Authors: Bhattacharjee Soumik , Ralib Aliza Aini , Vyakaranam Aparna , Svpk Satya Devu , Shameem SSS , Sulo Rafida , Zainuddin Ahmad Anwar 
Published: June 2021

Abstract
Quartz Crystal Microbalance (QCM) is a mass detection sensor capable of measuring mass sensitivity at nanogram levels when based on a thickness shear mode piezoelectric crystal set at high frequencies. These sensors detect with high accuracy while benefiting from simple geometry, low costs, and ease of fabrication. Researchers prefer piezoelectric crystal sensors to the recent methods of gas chromatography/mass chromatography (GC/MC), high pressure liquid chromatography and nuclear magnetic resonance (NMR), which are time-consuming and not cost-effective. Unlike conventional QCM sensors that are limited to a single-electrode structure—which minimizes their scope of detection—the Multichannel QCM (MQCM) incorporates multiple sensors fabricated on a single crystal wafer. Each sensor is selectively coated with a sensing material that promotes the adsorption of target vapours. One of the widely used application of QCM sensors is in Volatile Organic Compounds (VOC) detection. This paper imparts a critical overview of recent publications on the application of MQCMs with various sensing materials.
Application of Intuitionistic Fuzzy Soft Set to Topology
Authors: Ultami E Y , Haripamyu  , Ekariani S , Jenizon  
Published: June 2021

Abstract
A new topology on a set can be generated by a basis. In this paper, we construct an intuitionistic fuzzy soft basis for an intuitionistic fuzzy soft topology. Furthermore, we define the intuitionistic fuzzy soft topology generated by basis and establish some important theorem. Also, some concepts of intuitionistic fuzzy soft basis and subbasis are introduced here.
Study of Neutronic Performance of Sodium-Cooled Fast Reactor Design for Various Output Power Using Radial Fuel Shuffling Strategy
Authors: Ali Shafii Mohammad , Yolanda Putri Elsa , Handayani Feriska , Fitriyani Dian , Su’ud Zaki 
Published: June 2021

Abstract
Study of neutronic performance analysis of Sodium-Cooled Fast Reactor (SFR) design based on the variations of output power using radial fuel suffling strategy has been performed. SFR is a type of the generation IV reactor that is widely researched for application on a commercial scale. The reactor design uses natural uranium as a fuel and Sodium as a coolant. The research has been carried out by using the SRAC code and JENDL-3.2 as a library with two dimensional R- Z suffling strategy of cylinder core for variations of power output 300, 350, 400, 450 and 500 MWTh. The neutronic parameters such as a multiplication factor (k-eff and k-inf) and burn-up analysis are observed. The SFR core is separated into 10 regions having the same volume fraction in the radial direction. At beginning of burn-up process, the reactor core is only filled with natural uranium fuel called fresh fuel and prepared for the one cycle of 10 years of burn-up time. The burn-up result in the first region is shifted into the second region, the burn-up result in the second region is shifted into the third region, and so on until burn-up result into the tenth region. The burn-up result in the tenth region is removed from the reactor core, then the first region can be filled with fresh natural uranium fuel and so on up to 10 times fuel cycles of reactor operation. The neutron calculation results indicate that the multiplication factors (k-eff and k-inf) in a critical condition are occurred on the 300 MWTh of output power. Overall, the output power of 300 MWTh has requirements and a greater chance of being operated for SFR designed.
Study of the influence of different activator agents on the dimensions, mass, volume, and density of activated carbon monoliths for large-scale practical applications
Authors: Taer Erman , Ratna Dewi Mega , Apriwandi  , Taslim Rika , Agustino  , Sinta Mustika Widya 
Published: June 2021

Abstract
By single step pyrolysis and different chemical activation (KOH and ZnCl2) with different concentrations of 0.3 M, 0.5 M, 0.7 M, and 0.9 M, activated carbon monolith based on jengkol Pithecellobium jiringa shell wastes is obtained. The Samples are prepared in monolith form. The pyrolysis process begins with carbonization from room temperature to 600ºC in the N2 gas environment and followed by physical activation in the CO2 gas environment at a high temperature of 850 ºC for 2.5 hours. Monolith carbon is observed in the change of dimensions, mass, thickness, volume, and density. That it was observed that the pyrolysis process which includes carbonization and activation effectively reduces all the dimensions, mass and density parameters of carbon monoliths. Furthermore, the concentration of chemical activators dramatically exhibits excellent effects with increasing concentrations of activator agents, indicating that the porosity and highly micro-, and mesopores structure of activated carbon monoliths. This study is a model and reference for producing high-porous activated carbon from biomass waste for different practical applications.
Optimization of Nitrate and Nitrite Anions Adsorption on Modified Silica using Batch Method
Authors: Arianti Yuliana , Oktavia Budhi 
Published: June 2021

Abstract
Ammonia inorganic compounds are compounds that are often found because it is soluble in ground water which causes health hazards that are carcinogenic, mutagenic, tetratogenic and cause metamoglobinemia. Ammonia compounds that have negative effects on humans are nitrate and nitrite anions. Disposal of liquid waste and the use of fertilizers cause nitrates and nitrites to dissolve so that it has a negative impact on groundwater. One of the efforts to overcome nitrate and nitrite in waste is by adsorping with adsorbent., where the adsorbent used is DMA modified silica. Characterization by adsorption of nitrites and nitrates from aqueous solution at various pH, concentrartions, and contact times. The result showed that silica modification with DMA increased the adsorption capacity of nitrates and nitrtites. The Langmuir isotherm yields a regression coefficient R2 = for 0.9809 for nitrate and 0.9469 for nitrite. Nitrate adsorption capacity of 0.1669 mg g-1 with an initial nitrate concentration of 60 ppm at pH 8 with stirring for 120 minutes while the maximum adsorption capacity of nitrite was 0.1669 mg g-1 with an initial nitrite concentration of 40 ppm at pH 6 with stirring for 120 minutes.
Antimicrobial activity of endophytic fungi from Andalas (Morus macroura Miq.) plant
Authors: Handayani D , Putri D H , Oktaviani M , Rahwani  
Published: June 2021

Abstract
Many of recent study were conducted to find and investigate new antimicrobial substance to overcome the bacterial resistance problem. We can explore antimicrobial substance from medicine plant including Andalas (Morus macroura Miq.), but this plant is an endangered species. So, we can use endophytic fungi from this plant since they were known have the ability to produce similar antimicrobial compound. The aim of this study is to find some endophytic fungi from Andalas plant that have the ability to inhibit pathogen growth. Part (roots and leaves) of Andalas plant sample are from Andaleh village, Tanah Datar district, West Sumatera. Part of plant surface sterilization was using NaOCl 0.5%. Isolation of endophytic fungi from Andaleh plant was using PDA containing Chloramphenichol 500mg/l. Antimicrobial activity assay was conducted by agar dilution method. This study using 3 microbial agent i.e. Escherichia coli, Staphylococcus aureus and Candida albicans. We found 19 pure isolates of endophytic fungi from roots sample meanwhile 9 pure isolates from leaves. Most of those endophytic fungi (24 of 28 isolates) have the ability to inhibit E.coli and S. aureus growth, but none of them have the same ability to inhibit C. albicans. The highest average inhibition zone against E. coli was 47.1 mm and 51.7 mm against S. aureus. Meanwhile the lowest average inhibition zone against E.coli and S. aureus was 13.6 mm. Based on this study, we can conclude that endophytic fungi from Andalas plant are potential source to develop antimicrobial agent.