bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiframe Correction Blind Deconvolution for Solar Image Restoration
Authors: Wang Shuai , Rong Huiqin , He Chunyuan , Zhong Libo , Rao Changhui
Published: June 2022

A series of short-exposure images are often used for rich, small-scale structure, high-quality, and high-resolution astronomical observations. Postprocessing of the closed-loop adaptive optics (AO) image using ground-based astronomical telescopes plays an important role in astronomical observations due to it further improving image quality after AO processing. These images show several main characteristics: random spatial variation blur kernel, unclear model after AO correction, unclear physical characteristics of observation objects, etc. Our goal is to propose a multiframe correction blind deconvolution (MFCBD) algorithm to restore AO closed-loop solar images. MFCBD introduces a denoiser and corrector to help estimate the intermediate latent image and proposes using an L

q
norm of the kernel as the sparse constraint to acquire a compact blur kernel. MFCBD also uses the half-quadratic splitting strategy to optimize the objective function, which makes the algorithm not only simple to solve, but also easy to adapt to different fidelity terms and prior terms. In tests on three data sets observed from the photosphere and chromosphere of the Sun, MFCBD not only restored clearer and more detailed images, but also converged smoothly and monotonically in terms of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) after a few iterations. Taking the speckle-reconstructed image as a reference, the clear image restored by our method performs best both in PSNR and SSIM compared with the state-of-the-art traditional methods OBD and BATUD.
On the Determination of the Evolutionary Status of Supernova Remnants from Radio Observation Data
Authors: Urošević Dejan
Published: June 2022

This paper aims to give a brief review of a new concept for the preliminary determination of the evolutionary status of supernova remnants (SNRs). Data obtained by radio observations in continuum are used. There are three different methods underlying the new concept: The first one is based on the location of the observationally obtained radio surface brightness and the corresponding diameter of an SNR in theoretically derived Σ–D tracks, the second one is based on the forms of radio spectra, and the third one is based on the magnetic field strengths that are estimated through the equipartition (eqp) calculation. Using a combination of these methods, developed over the last two decades by the Belgrade SNR Research Group, we can estimate the evolutionary status of SNRs. This concept helps radio observers to determine preliminarily the stage of the evolution of an SNR observed in the radio domain. Additionally, this concept was applied to several SNRs, observed by the Australia Telescope Compact Array, and the corresponding results are reviewed here. Moreover, some of the results are revised in this review to reflect the recently published updated Σ–D and eqp analyses.
Enhancement of holding voltage by a modified low-voltage trigger silicon-controlled rectifier structure for electrostatic discharge protection
Authors: Chen Yuankang , Zhou Yuanliang , Jiang Jie , Rao Tingke , Liao Wugang , Liu Junjie
Published: June 2022

A novel structure of low-voltage trigger silicon-controlled rectifiers (LVTSCRs) with low trigger voltage and high holding voltage is proposed for electrostatic discharge (ESD) protection. The proposed ESD protection device possesses an ESD implant and a floating structure. This improvement enhances the current discharge capability of the gate-grounded NMOS and weakens the current gain of the silicon-controlled rectifier current path. According to the simulation results, the proposed device retains a low trigger voltage characteristic of LVTSCRs and simultaneously increases the holding voltage to 5.53 V, providing an effective way to meet the ESD protection requirement of the 5 V CMOS process.
GA-MKB:A Multi-kernel Boosting Learning Method based on Normalized Kernel Target Alignment and Kernel Difference
Authors: Chen Linlin , Wang Mei , Zhang Qiang , Hou Nan
Published: June 2022

Concentrates on the problem that the traditional kernel target alignment(KTA) is not invariance under data translation in the feature space, a cosine matrix alignment method is proposed for kernel selection, which is called normalized kernel target alignment(NKTA). On the basis of normalized kernel target alignment and kernel difference, we propose a new multi-kernel boosting. Firstly, the value of NKTA is taken as the election rarget of the kernel function in each iteration of algorithm, which leads to a selective kernel fusion. Secondly, the kernel difference measure is used to construct the combination coefficient to increase the diversity of weak classifiers, and then improve the generalization performance of integrated strong classifiers. Finally, among the 6 data sets, the GA-MKB performed better than MKBoost-D1 under the accuracy of classification, and can improve the generalization performance of the integrated classifier compared with MKBoost-D2.
Intelligent Recognition of UAV Pilot Training Actions Based on Dynamic Bayesian Network
Authors: Yin Wenqiang , An Ran , Zhao Qun
Published: June 2022

The recognition of UAV pilot training actions using artificial intelligence methods can effectively improve the intelligence level of UAV pilot training ability assessment. Based on the flight characteristics of UAV systems, this paper constructs an intelligent recognition model of flight training actions based on dynamic Bayesian network. Combined with the training tasks, the model recognition effect was verified. The results show that the model can accurately recognize different flight phases and typical training actions of UAV, have the advantages of high recognition accuracy and good real-time performance, and effectively improve the training effect of pilots.
A Two-stage Speech Enhancement Method Based on Deep Learning Network
Authors: Ye Moujia , Wan Hongjie
Published: June 2022

The conventional single-channel speech enhancement algorithms require only a small amount of computation to implement, but have problems with “musical noise” and speech distortion. The learning-based enhancement method achieves a relatively good performance, but it requires a right training data set and a large computational load. This paper proposed a method to combine the two types of algorithms. This method includes two stages. In the first stage, the Berouti spectral subtraction was used to subtract part of noise from the noisy speech. In the second stage, a deep neural network was built to remove residual noise and improve the clarity of speech obtained in the first stage. The experimental results indicate that, training with the same data set, the method proposed in this paper clearly outperforms the baseline model in PESQ and FWSegSNR.
AGV Status Monitoring and Fault Diagnosis based on CNN
Authors: Wang Baiyang , Huo Dongyue , Kang Yuyun , Sun Jie
Published: June 2022

In order to solve the problem of AGV fault detection system’s complexion and low accuracy, a convolutional neural network (CNN) based on the status monitoring and fault diagnosis method for automatic guided vehicle (AGV) is proposed. Firstly, the vibration signals of the core components of AGV are converted into two-dimensional (2D) images. Secondly, 2D images are input into convolution neural network for training. Finally, the trained model is used to monitor the running status of AGV and identify faults. The results show that the proposed method can effectively monitor the status of AGV in operation.
Study of ergonomic criteria for evaluating the software user interface
Authors: Yatsenyak D V , Oleksiuk V P , Balyk N R
Published: June 2022

This article summarizes research on the development and evaluation of a set of software usability measurements. Today they are called ”ergonomic criteria”. The authors summarize the research work carried out on the development and evaluation of a set of software usability measurements. The paper contains a description of each such criterion. All of them together provide a quality user interface. The authors highlighted the significant advantages of a well-designed and well-thought-out interface. The paper also contains an analysis of each of these criteria. The authors of the article discuss ergonomic problems of software development. As a result, some characteristics of the software are identified. They reduce the ergonomics of the user interface. The paper also discusses ergonomic issues and the things developers need to get rid of to make the app enjoyable. The success of solving this problem in software development largely depends on how functional, clear and user-friendly the interface is. The authors give some examples of bad user interfaces. They are accompanied by an explanation of the problems and solutions to these shortcomings. The systems, designed with practicality in mind, are ergonomic and work exactly as users expect, allowing users to focus on their own tasks rather than the specifics of interacting with the system.
Calculation of storm fuel supply of a seagoing vessel: solving professionally-oriented tasks using cloud services
Authors: Zaytseva T V , Kravtsova L V , Bezbakh O M , Tereshchenkova O V , Voloshinov S A
Published: June 2022

The information and communicative competency today is an integral part of professional training in any sphere. Due to the fact that nowadays big amount of work is done or monitored in the remote mode the requirement is stipulated for every specialist to be able to use digital technologies professionally. For a future seafarer it means, first of all, the ability to use modern technologies as the information and data resource and also it presupposes the ability to work with software libraries, to create data bases, to perform necessary calculations by means of cloud services inclusive. This component is of extreme practical importance as it enables the satisfaction of the social mandate to prepare future seafarers for the living in the information environment. The task is quite challenging so it requires the adequate knowledge level. That is why the main objective of the course “Information technologies” together with other subjects within the curriculum for the professional training in maritime academy is to develop the reliable scientific and methodological grounds for the realization of any professionally related tasks of future merchant feet officers. Specially selected tasks acquaint cadets with information technology in terms of implementing the solution of applied professionally oriented tasks, such as navigating the course, determining the location of the vessel, calculating stocks for the trip, etc. Therefore, the obligatory elements of the tasks are: construction of mathematical (computer) models;analysis of possible solutions to the problem; of technological processes, taking into account all factors influencing the process and methods of decision-making;implementation of mathematical models of problems in spreadsheets. This article proposes a strategy for solving an applied problem using an information-modeling approach to the analysis and evaluation of the technological process, namely, the algorithm for calculating the required voyage and storm fuel reserves of a marine vessel. Both office spreadsheets and cloud services were used to implement the mathematical model for solving this problem. The use of “cloud computing” technologies in the training of seafarers is due to the fact that, firstly, while on board, the master or ship mechanic can perform some components of their work, especially joint projects, in modern services, and secondly, these technologies, supporting traditional forms of education, is a new stage in the development of education and a cost-effective, efficient and flexible way to meet the needs of students in acquiring new knowledge.
Professional competencies of future software engineers in the software design: teaching techniques
Authors: Striuk A M , Semerikov S O
Published: June 2022

The article is devoted to one of the competence components of a mobile-oriented environment for professional and practical training of future software engineers. It is shown that the introduction of higher education standard 121 “Software Engineering” for the first (bachelor) level of higher education in Ukraine has generated a number of training quality assurance problems associated primarily with the low level of detailed competencies and program learning outcomes. By solving these problems, the detailed design of the system of professional competencies for future software engineers is developed. The article deals with the approaches to developing one of the most important special professional competences of future software engineers – the ability to participate in software design, including modeling (formal description) of its structure, behavior, and processes of functioning. Based on a historical and genetic review of the software engineering training practice of future software engineers in the USA, UK, Canada, Australia, New Zealand and Singapore, recommendations for choosing forms of training organization, selection of training content, ways of students’ and teachers’ activities in software engineering, modeling and designing tools; assessment of the appropriate competence formation level are formulated. The example of organizing design training in conditions close to industrial-studio training is considered. The problems of transition from architectural to detailed design and project implementation are shown. Prospects for further development of this study are to substantiate the third (after requirements engineering and design engineering) engineering component of software engineering – the software construction.
A computer simulation of population reproduction rate on the basis of their mathematical models
Authors: Tsidylo I M , Shevchyk L O , Hrod I M , Solonetska H V , Shabaga S B
Published: June 2022

The article deals with the adoption of computer modeling as one of the leading areas of introduction of modern information technology in the modernization of content, forms and methods of teaching. In order to implement interdisciplinary integrated learning, the possibilities of interdisciplinary integration of learning content have been identified, the practice of using software environments in the process of modeling biological problems based on mathematical models has been analyzed, the possibilities of implementing algorithms of mathematical models in computer modeling have been investigated. A set of research tasks in biology as a basis for the implementation of interdisciplinary integration: nature - mathematics -computer science has been introduced into the educational process. The mathematical models of Verhulst, Arim, Leslie and the exponential law of direct proportional dependence or proportional rate of reproduction depending on the number of individuals of a population were used to design computer models of reproduction of ecological processes. They were implemented using the computer mathematics system MathCad and using programming environments Python, C#, C++. The expediency of the proposed method of interdisciplinary integration of learning content has been justified through a developmental and productive integrated approach, the use of certain collective forms of activity, the practical orientation of professional training disciplines to form algorithmic competence of students as a basis for professional competence in computer modeling of mathematical models of biological processes.
The use of augmented reality in chemistry lessons in the study of “Oxygen-containing organic compounds” using the mobile application Blippar
Authors: Karnishyna D A , Selivanova T V , Nechypurenko P P , Starova T V , Stoliarenko V G
Published: June 2022

A training kit has been created to study the topic of “Oxygen-containing organic compounds” using augmented reality. We chose the Blippar platform to work, it is quite simple and relatively free. The kit contains markers we have developed, on which, with the camera from the Blippar application, students will be able to observe thematic experiments and molecules of individual substances with the help of augmented reality. There was also a study on the effectiveness of our developments to implement augmented reality in the course of chemistry. The study results showed an increase in pupils’ motivation to study chemistry and their level of interest, facilitating the perception of the theoretical foundations of organic chemistry related to the spatial structure of molecules. Also, the use of augmented reality technologies creates the conditions for improving the level of digital and technological competencies of students, provides support for high quality teaching of chemistry in distance learning.
Using smartphone sensors for teaching mechanical oscillations
Authors: Aya Baquero Hugo
Published: June 2022

As a complement to the traditional elements of the physics laboratory, alternative strategies are sought that allow the experimentation of mechanical oscillations and improve the understanding of these phenomena by university students. Smartphones have very high quality built-in sensors, which in the particular case of the gyroscope allows to carry out oscillator experiments with excellent results. Two experiments that were implemented with the gyroscope integrated into a smartphone are shown. Appropriate setups are suggested to make these experiments.
STEM centre as a factor in the development of formal and non-formal STEM education
Authors: Balyk N R , Shmyger G P , Vasylenko Ya Ph , Oleksiuk V P
Published: June 2022

The article is devoted to the study of STEM education. It is one of the important directions of educational reform of the XXI century and can be implemented through the integration of formal and non-formal education. The authors of the paper study the ecosystem of formal and non-formal STEM education. Researchers have identified the main characteristics of this ecosystem such as the harmonious combination of formal and informal components of STEM learning, increasing the motivation of students to STEM sciences, constant updating of educational programs and professional development programs for teachers; use of non-formal education approaches; constant connection with external communities of STEM professionals; building partnerships between schools and non-formal institutions. The authors have developed the main components of the model of functioning of the educational STEM centre as an education ecosystem. In particular, they are educational research, assessment (evaluation), research projects, innovative teaching methods, programs for training, undergraduate education, teacher training, mentoring, services, communications, cooperation, infrastructure, connection, networking. To assess the extent of the impact of various forms of formal and non-formal learning activities on the results of the implementation of STEM education, an expert survey was conducted. The results of the survey are systematized, illustrated with the help of infographics, statistically significant relationships between individual parameters of the proposed model are established. To test this model in practice, an experiment was conducted. It lasted from 2016 to 2020. Researchers have confirmed the hypothesis that STEM education gives the best results due to a combination of formal and non-formal levels. Therefore, their STEM centre promotes STEM education among the general public, training and retraining of educators involved in STEM, development of STEM competencies of pupils and students.
The phenomenon of “clip thinking” in the educational and cognitive activities of students of natural and physical-mathematical educational profile
Authors: Shestopalova O P , Yu Goncharova T
Published: June 2022

The article presents an analysis of the phenomenon of “clip thinking” in the educational and cognitive activities of students of natural and physical-mathematical educational profile. The involvement of clip thinking in the initial stage of cognition in comparison with rational and theoretical thinking is theoretically substantiated. An empirical verification of the originality of cognitive processes of students of natural and physical-mathematical educational profile in the situation of comparing traditional linear (textual) and hypertextual way of presenting information is established. Deficiency of cognitive processes characteristic of clip thinking for results is revealed, which is characterized by characteristics of mental (theoretical) level of cognition. Therefore, the next stage of cognition should be the understanding of information through the mechanisms of comparison, generalization, categorization and re-synthesis.
A blended English for Specific Purposes course with the focus on critical thinking skills development for computer science students
Authors: Zaitseva N V , Symonenko S V , Osadchyi V V
Published: June 2022

The paper deals with the pedagogical aspects of blended learning implementation in the educational process of undergraduates majoring in computer science. Certain peculiarities of blended learning for foreign language teaching have been presented. The design principles of a blended course for one term as well as the practice of its functioning have been discussed. The blended English for Specific Purposes course for computer science students with the focus on critical thinking skills formation and development has been introduced. One specific profession-related theme studying within the blend has been described. The experience of applying authentic demonstration videos in the English language as contents of tasks for critical thinking skills enhancing has been propounded. Practical aspects of carrying out a 30 multiple-choice question test for determining the undergraduates’ critical thinking skills level have been presented.
The impact of psychological and learning training on educational motives and reflective skills of future IT specialists
Authors: Krasheninnik I V , Koniukhov S L , Osadcha K P , Chorna A V , Serdiuk I M
Published: June 2022

Nowadays, there are a lot of psychological and pedagogical research aimed to explore students’ individual characteristics and how to take them into account in educational process, as well as to develop new teaching techniques. In this study, we focus on future IT specialists’ internal motivation to continue education and training, internal motivation for professional activity as a software engineer, and reflective skills. We consider the impact of psychological and learning training on educational motivation and reflective skills of university students. We present pedagogical technique which involves motivational training, training exercises, and learning training. In particular, we give a brief description of author’s learning training on “NoSQL databases: MongoDB and ASP.NET MVC”. The results of pedagogical experiment conducted to evaluate effciency of this technique are presented. In experimental work 405 higher education students majoring in 121 Software Engineering, 122 Computer Science, 123 Computer Engineering took part. Based on statistical processing of empirical data, we made a conclusion about potency of our technique.
Machine learning-based method of calorimeter saturation correction for helium flux analysis with DAMPE experiment
Authors: Stolpovskiy M. , Wu X. , Tykhonov A. , Deliyergiyev M. , Perrina C. , Muñoz Salinas M. , Droz D. , Ruina A. , Catanzani E.
Published: June 2022

DAMPE is a space-borne experiment for the measurement of the cosmic-ray fluxes at energies up to around 100 TeV per nucleon. At energies above several tens of TeV, the electronics of DAMPE calorimeter would saturate, leaving certain bars with no energy recorded. In the present work we discuss the application of machine learning techniques for the treatment of DAMPE data, to compensate the calorimeter energy lost by saturation.
A portable neutron gamma discrimination detector based on NaIL and SiPM
Authors: Zhang Z. , Wang D. , Feng S. , Ye Z. , Zhou T. , Zheng Z. , Wang F. , Zhao C. , Wang Z. , Bai L. , Zhou R. , Yang C.
Published: June 2022

neutron-gamma detection technology is widely used in nuclear
physics, high-energy physics, radiation medicine, and other
fields. A NaIL scintillator coupled with a silicon photomultiplier
(SiPM) can form a neutron-gamma detector with excellent
discrimination, small size, and low cost. However, the performances
of a NaIL scintillator and SiPM are affected by temperature, which
leads to a shift in energy spectrum and deterioration in
neutron-gamma discrimination. Most of the current studies have used
digitizers to store data and analyze detector energy spectrum and
waveform characteristics offline to eliminate temperature
dependence. In this study, a small neutron-gamma detector was
constructed using NaIL scintillators, SiPM, and circuits developed
in the laboratory. Online calibration of the ARM processor
eliminates the temperature dependence of the detector's energy
spectrum and neutron-gamma discrimination. Automatic energy spectrum
stabilization and good neutron-gamma discrimination were achieved in
a wide temperature range. The test results show that the peak shift
of the 137Cs 662 keV full-energy peak of the detector is
reduced from 5.3% to 0.4% at 0–50°C. After the online
correction of the temperature feedback PSD parameters, the figure of
merit at 45°C is 40% higher than that before the correction,
and the detector's figure of merit at 0–50°C is maintained
above 3.4.
Bioink derived from human placenta supporting angiogenesis
Authors: Duan Yongchao , Huang Wenhui , Zhan Bo , Li Yuanyuan , Xu Xue , Li Kai , Li Xia , Liu Xin , Ding Shenglong , Wang Shuo , Guo Jia , Wang Yukai , Gu Qi
Published: June 2022

Bioprinting is an emerging approach for constructing sophisticated tissue analogues with detailed architectures such as vascular networks, which requires bioink to fulfill the highly printable property and provide a cell-friendly microenvironment mimicking a native extracellular matrix (ECM). Here, we developed a human placental ECM-derived bioink (hp-bioink) meeting the requirements of 3D printing for printability and bioactivity. We first decellularized the human placenta, followed by enzymatic digestion, dialysis, lyophilization, and re-solubilization to convert the extracts into hp-bioink. Then, we demonstrated that 3%–5% of hp-bioink can be printed with self-standing and 1%–2% of hp-bioink can be embedded and printed within suspended hydrogels. Moreover, hp-bioink supports human umbilical vein endothelial cell assembly in vitro and angiogenesis in mice in vivo. Our research enriches the bank of human-derived bioinks, and provides a new opportunity to further accelerate bioprinting research and application.
Ternary logic design in topological quantum computing
Authors: Ilyas Muhammad , Cui Shawn , Perkowski Marek
Published: June 2022

A quantum computer can perform exponentially faster than its classical counterpart. It works on the principle of superposition. But due to the decoherence effect, the superposition of a quantum state gets destroyed by the interaction with the environment. It is a real challenge to completely isolate a quantum system to make it free of decoherence. This problem can be circumvented by the use of topological quantum phases of matter. These phases have quasiparticles excitations called anyons. The anyons are charge-flux composites and show exotic fractional statistics. When the order of exchange matters, then the anyons are called non-abelian anyons. Majorana fermions in topological superconductors and quasiparticles in some quantum Hall states are non-abelian anyons. Such topological phases of matter have a ground state degeneracy. The fusion of two or more non-abelian anyons can result in a superposition of several anyons. The topological quantum gates are implemented by braiding and fusion of the non-abelian anyons. The fault-tolerance is achieved through the topological degrees of freedom of anyons. Such degrees of freedom are non-local, hence inaccessible to the local perturbations. In this paper, the Hilbert space for a topological qubit is discussed. The Ising and Fibonacci anyonic models for binary gates are briefly given. Ternary logic gates are more compact than their binary counterparts and naturally arise in a type of anyonic model called the metaplectic anyons. The mathematical model, for the fusion and braiding matrices of metaplectic anyons, is the quantum deformation of the recoupling theory. We proposed that the existing quantum ternary arithmetic gates can be realized by braiding and topological charge measurement of the metaplectic anyons.
RETRACTED: AI-driven techniques for controlling the metal melting production: a review, processes, enabling technologies, solutions, and research challenges
Authors: Chadha Utkarsh , Selvaraj Senthil Kumaran , Raj Aditya , Mahanth T , Praveen Vignesh S T , Lakshmi Pasham Janani , Samhitha K , Reddy Nagireddy Bharath , Adefris Addisalem
Published: June 2022

Artificial Intelligence has left no stone unturned, and mechanical engineering is one of its biggest consumers. Such technological advancements in metal melting can help in process simplification, hazard reduction, human involvement reduction & lesser process time. Implementing the AI models in the melting technology will ultimately help various industries, i.e., Foundry, Architecture, Jewelry Industry, etc. This review extensively sheds light on Artificial Intelligence models implemented in metal melting processes or the metal melting aspect, alongside explaining additive manufacturing as a competitor to the current melting processes and its advances in metal melting and AI implementations.
Explaining the dosimetric impact of contouring errors in head and neck radiotherapy
Authors: González Patrick J , Simões Rita , Kiers Karen , Janssen Tomas M
Published: June 2022

Objective. Auto-contouring of organs at risk (OAR) is becoming more common in radiotherapy. An important issue in clinical decision making is judging the quality of the auto-contours. While recent studies considered contour quality by looking at geometric errors only, this does not capture the dosimetric impact of the errors. In this work, we studied the relationship between geometrical errors, the local dose and the dosimetric impact of the geometrical errors. Approach. For 94 head and neck patients, unmodified atlas-based auto-contours and clinically used delineations of the parotid glands and brainstem were retrieved. VMAT plans were automatically optimized on the auto-contours and evaluated on both contours. We defined the dosimetric impact on evaluation (DIE) as the difference in the dosimetric parameter of interest between the two contours. We developed three linear regression models to predict the DIE using: (1) global geometric metrics, (2) global dosimetric metrics, (3) combined local geometric and dosimetric metrics. For model (3), we next determined the minimal amount of editing information required to produce a reliable prediction. Performance was assessed by the root mean squared error (RMSE) of the predicted DIE using 5-fold cross-validation. Main results. In model (3), the median RMSE of the left parotid was 0.4 Gy using 5% of the largest editing vectors. For the right parotid and brainstem the results were 0.5 Gy using 10% and 0.4 Gy using 1% respectively. The median RMS of the DIE was 0.6 Gy, 0.7 Gy and 0.9 Gy for the left parotid, the right parotid and the brainstem, respectively. Model (3), combining local dosimetric and geometric quantities, outperformed the models that used only geometric or dosimetric information. Significance. We showed that the largest local errors plus the local dose suffice to accurately predict the dosimetric impact, opening the door to automated dosimetric QA of auto-contours.
A camera array based reconstruction method for limited observation windows projection in three-dimensional flame chemiluminescence tomography
Authors: Rong Shaohua , Song Yang , Wu Chunxia , Yuan Qun , Gao Zhishan , Guo Zhenyan
Published: June 2022

Three-dimensional(3D) flame chemiluminescence tomography (FCT) is realized in multi-direction and multi-angle using traditional iterative algorithms. However, 3D-FCT is often challenged by insufficient sampling data because of the limited observation windows provided in practical for flame measurement. To obtain flame multiple projections in limited observation windows, we develop a camera array arrangement in FCT. In addition, a residual network with a new loss function combing physical model of flame is proposed to achieve higher reconstruction accuracy, faster reconstruction speed and efficient image feature in residual network for 3D FCT measurement. Furthermore, the determination of the weight coefficient in the loss function is performed by numerical simulation experiments. The flame reconstruction results show that the proposed residual network method including the new loss function has more reliable structural similarity and noise immunity compared with the ART algorithm and the CNN algorithm. This work provides a faster and more accurate method for combustion diagnosis under limited observation windows with insufficient projections.
Electromechanical switching voltage converters with application to cold start for thermoelectric generators
Authors: Kozalakis Konstantinos , Siskos Stylianos
Published: June 2022

This work proposes a novel technique for the control of modern inductor-based switching voltage converters (SVC) (e.g., boost, or buck converter), which is inspired by an old self-oscillating mechanical converter topology. According to the proposed technique, a relay component replaces both the inductor and the semiconductor switch of the SVC. The magnetic coupling between the switch and the inductor eliminates the need for a separate oscillating control circuit, which is usually required for the operation of an SVC, leading to a very simple converter topology. The electromechanical SVC (EMSVC) is self-oscillating, operating automatically whenever sufficient power is applied at its input. In this work a boost converter EMSVC design, as well as a buck converter EMSVC design are presented. Additionally, a boost converter EMSVC implementation, optimized towards thermoelectric cold start applications, is presented with experimental results. The converter can operate with an input of only 25 mV and 6.5 mA, and if combined with a thermoelectric harvester, it can be used for heat energy harvesting from temperature difference as low as 1 °C.
Minkowski dimension for measures
Authors: Falconer Kenneth , Fraser Jonathan , Käenmäki Antti
Published: June 2022

The purpose of this article is to introduce and motivate the notion of Minkowski (or box) dimension for measures. The definition is simple and fills a gap in the existing literature on the dimension theory of measures. As the terminology suggests, we show that it can be used to characterise the Minkowski dimension of a compact metric space. We also study its relationship with other concepts in dimension theory.
On starlikeness of regular Coulomb wave functions
Authors: Baricz Árpád , Kumar Pranav , Singh Sanjeev
Published: June 2022

In this paper, we study some geometric properties of a class of analytic functions which is defined from the

J
J

-fraction expansion of the ratio

z

f
′

(
z
)

/

f
(
z
)

{zf’(z)}/{f(z)}

. We find the disk domain which is mapped into a starlike domain by these functions. Moreover, we study similar results for two different normalized forms of regular Coulomb wave functions and a normalized Bessel function of the first kind by using continued fractions expansions.
3. Microbiota and microbiome in humans
Authors: Amyes Sebastian G. B.
Published: June 2022

‘Microbiota and microbiome in humans’ examines the microbiota and microbiome in humans. Humans could not have evolved to their current sophistication without the help of bacteria, both for their ability to obtain energy in their cells through mitochondria and also more directly in their ability to maximize the nutrients obtained from food and their primary defence against serious infection. Microbiome exist on the skin, in the vagina, the mouth, and the gut. Many infections result from the disruption of the microbiome, or dysbiosis. Probiotics and faecal transplants play a role in achieving a more balanced microbiota.
2. Viscosity
Authors: Lauga Eric
Published: June 2022

‘Viscosity’ begins by examining how fluid motion is quantified using the flow velocity. Since fluids can move in three independent directions of space, the velocity is a three-dimensional vector, with each component measuring the velocity in a particular direction. Because the velocity can take different values at different locations in space, it is called a field. Flow kinematics is about the various ways in which fluids can move. There are three fundamental flow modes: translation, rotation, and extension. Extension is the only flow component that is the true deformation. Invoking the concept of conservation of mass, we have the issue of incompressibility of the flow. The forces arising inside a fluid are at the heart of fluid dynamics. There is a difference between volume forces (e.g. gravity) and surface forces. An important surface force acting tangentially along surfaces is called a shear stress. Using Isaac Newton’s famous shear-flow experimental setup, where a fluid is located between two rigid surfaces that slide past each other. The shear stress acting on a surface is proportional to the shear rate in the fluid and to a material property called the viscosity. Fluids with a high viscosity experience larger shear stresses.
4. Living together
Authors: Leather Simon
Published: June 2022

‘Living together’ talks about the most basic form of insect association that is exemplified by the aggregations that some insect species show during some parts of their lifecycle. Many ladybirds for example, aggregate in sheltered spots over the winter. These are not truly social as they are often a mixture of different species that have come together because of a response to a change in behaviour, brought about by positive touch stimulus. It is worth also considering other insect aggregations, where feeding in groups emphasizes their unpalatability by magnifying their warning colouration. Any coordination in loose associations is individual and solitary, but appears to form social aggregation.
5. Aquatic insects
Authors: Leather Simon
Published: June 2022

‘Aquatic insects’ explores the adaptations and lifestyles of insects that spend some or all of their life in or on water. Every inland waterbody, whether a river, stream seepage, or lake, supports a biological community. Insects can also be found in puddles and some, such as the pitcher plant mosquito are especially adapted to exploit the water-filled stomachs of carnivorous plants. It is worth looking at invertebrates which provide the highest number of individuals and species and the highest levels of biomass and production. In general, the insects dominate freshwater aquatic systems, where only nematodes can approach them in terms of species numbers, biomass, and productivity.
6. Mimicry, crypsis, and blatant advertising
Authors: Leather Simon
Published: June 2022

‘Mimicry, crypsis, and blatant advertising’ discusses insects as food for many animals, including other insects. Their main routes to avoiding being eaten are to hide, by camouflaging themselves so that they merge into the background or pretending to be something dangerous or poisonous, or to run or fly away. There are a number of insects that mimic inanimate objects, while others take on the appearance of a dangerous animal. It is worth considering the mimicry of dangerous beasts which has arisen from the practice adopted by a number of insect species that advertise their lethality by warning colours. Caterpillars that sequester toxins from their host plants advertise this with stripes.
Figbird: a probabilistic method for filling gaps in genome assemblies
Authors: Tarafder Sumit , Islam Mazharul , Shatabda Swakkhar , Rahman Atif
Published: June 2022

Motivation

Advances in sequencing technologies have led to the sequencing of genomes of a multitude of organisms. However, draft genomes of many of these organisms contain a large number of gaps due to the repeats in genomes, low sequencing coverage and limitations in sequencing technologies. Although there exists several tools for filling gaps, many of these do not utilize all information relevant to gap filling.

Results

Here, we present a probabilistic method for filling gaps in draft genome assemblies using second-generation reads based on a generative model for sequencing that takes into account information on insert sizes and sequencing errors. Our method is based on the expectation-maximization algorithm unlike the graph-based methods adopted in the literature. Experiments on real biological datasets show that this novel approach can fill up large portions of gaps with small number of errors and misassemblies compared to other state-of-the-art gap-filling tools.

Availability and implementation

The method is implemented using C++ in a software named ‘Filling Gaps by Iterative Read Distribution (Figbird)’, which is available at https://github.com/SumitTarafder/Figbird.

Supplementary information

Supplementary data are available at Bioinformatics online.
Altered brain rhythms and behaviour in the accelerated ovarian failure mouse model of human menopause
Authors: Vrontou Sophia , Bédécarrats Alexis , Wei Xiaofei , Ayodeji Morikeoluwa , Brassai Attila , Molnár László , Mody Istvan
Published: June 2022

To date, potential mechanisms of menopause-related memory and cognitive deficits have not been elucidated. Therefore, we studied brain oscillations, their phase–amplitude coupling, sleep and vigilance state patterns, running wheel use and other behavioural measures in a translationally valid mouse model of menopause, the 4-vinylcyclohexene-diepoxide-induced accelerated ovarian failure. After accelerated ovarian failure, female mice show significant alterations in brain rhythms, including changes in the frequencies of θ (5–12 Hz) and γ (30–120 Hz) oscillations, a reversed phase–amplitude coupling, altered coupling of hippocampal sharp-wave ripples to medial prefrontal cortical sleep spindles and reduced δ oscillation (0.5–4 Hz) synchrony between the two regions during non-rapid eye movement sleep. In addition, we report on significant circadian variations in the frequencies of θ and γ oscillations, and massive synchronous δ oscillations during wheel running. Our results reveal novel and specific network alterations and feasible signs for diminished brain connectivity in the accelerated ovarian failure mouse model of menopause. Taken together, our results may have identified changes possibly responsible for some of the memory and cognitive deficits previously described in this model. Corresponding future studies in menopausal women could shed light on fundamental mechanisms underlying the neurological and psychiatric comorbidities present during this important transitional phase in women’s lives.
Diagnosis of coexistent neurodegenerative dementias in multiple sclerosis
Authors: Londoño Diana P , Arumaithurai Kogulavadanan , Constantopoulos Eleni , Basso Michael R , Reichard R Ross , Flanagan Eoin P , Keegan B Mark
Published: June 2022

Among people with multiple sclerosis, cognitive impairment occurs commonly and is a potent predictor of disability. Some multiple sclerosis patients present with severe cognitive impairment, and distinguishing multiple sclerosis-related cognitive impairment from co-existent progressive neurodegenerative diseases such as Alzheimer disease poses a diagnostic challenge. The use of biomarkers such as PET and CSF proteins may facilitate this distinction. The study was a retrospective, descriptive study on convenience samples of separate cohorts, one of cognitively impaired multiple sclerosis patients evaluated on autopsy to demonstrate coincidence of both multiple sclerosis and neurodegenerative cognitive diseases. The second cohort were cognitively impaired multiple sclerosis patients evaluated by biomarker to investigate possible additional neurodegenerative cognitive disorders contributing to the cognitive impairment. We investigated selected biomarkers among 31 severely impaired patients (biomarker cohort) and 12 severely impaired patients assessed at autopsy and selected 24 (23 biomarker cohort, 1 autopsy cohort) had comprehensive neurocognitive testing. Biomarker cohort investigations included 18F-Fluorodeoxyglucose PET and/or CSF amyloid Aβ1-42, phospho-tau and total tau levels. The autopsy cohort was evaluated with comprehensive neuropathological assessment for aetiology of cognitive impairment. The cohorts shared similar sex, age at multiple sclerosis onset and multiple sclerosis clinical course. The autopsy-cohort patients were older at diagnosis (69.5 versus 57 years, P = 0.006), had longer disease duration [median (range) 20 years (3–59) versus 9 (1–32), P = 0.001] and had more impaired bedside mental status scores at last follow-up [Kokmen median (range) 23 (1–38) versus 31 (9–34) P = 0.01]. Autopsy-cohort patients confirmed, or excluded, coexistent neurogenerative disease by neuropathology gold standard. Most biomarker-cohort patients had informative results evaluating coexistent neurogenerative disease. Biomarkers may be useful in indicating a coexistent neurodegenerative disease earlier, and in life, in patients with multiple sclerosis and significant cognitive impairment.
Anti-glutathione S-transferase omega 1-1 (GSTO1-1) antibodies are increased during acute and chronic inflammation in humans
Authors: Piaggi Simona , Lorenzini Evelina , Pratesi Federico , Migliorini Paola , Pompella Alfonso , Bruschi Fabrizio , Corti Alessandro
Published: June 2022

Glutathione S-transferase omega-1 (GSTO1-1) is a cytosolic enzyme involved in the modulation of critical inflammatory pathways as well as in cancer progression. Auto-antibodies against GSTO1-1 were detected in the serum of patients with esophageal squamous cell carcinoma and were proposed as potential biomarkers in the early detection of the disease. Our findings show that anti-GSTO1-1 antibodies can be found in a variety of inflammatory diseases, including autoimmune rheumatoid arthritis, infectious SARS-CoV-2, and trichinellosis. Our findings strongly suggest that anti-GSTO1-1 antibodies may be a marker of tissue damage/inflammation rather than a specific tumor-associated biomarker.
Beta-Lactam Antibiotic Therapeutic Drug Monitoring in Critically Ill Patients: A Systematic Review and Meta-Analysis
Authors: Pai Mangalore Rekha , Ashok Aadith , Lee Sue J , Romero Lorena , Peel Trisha N , Udy Andrew A , Peleg Anton Y
Published: June 2022

Therapeutic drug monitoring (TDM) of beta-lactam antibiotics is recommended to address the variability in exposure observed in critical illness. However, the impact of TDM-guided dosing on clinical outcomes remains unknown. We conducted a systematic review and meta-analysis on TDM-guided dosing and clinical outcomes (all-cause mortality, clinical cure, microbiological cure, treatment failure, hospital and intensive care unit length of stay, target attainment, antibiotic-related adverse events, and emergence of resistance) in critically ill patients with suspected or proven sepsis. Eleven studies (n = 1463 participants) were included. TDM-guided dosing was associated with improved clinical cure (relative risk, 1.17; 95% confidence interval [CI], 1.04 to 1.31), microbiological cure (RR, 1.14; 95% CI, 1.03 to 1.27), treatment failure (RR, 0.79; 95% CI, .66 to .94), and target attainment (RR, 1.85; 95% CI, 1.08 to 3.16). No associations with mortality and length of stay were found. TDM-guided dosing improved clinical and microbiological cure and treatment response. Larger, prospective, randomized trials are required to better assess the utility of beta-lactam TDM in critically ill patients.