bluuebunny/crossref_metadata_2025 huggingface dataset:
Holistic data‐driven method for optimal sizing and operation of an urban islanded microgrid
Authors: Feng Xue , Tseng King Jet
Published: April 2021

This study proposes a holistic data‐driven method for the optimal sizing and operation of a building‐level islanded microgrid with renewable energy resources in an urban setting. Firstly, various metres are integrated on an energy monitoring platform where field data are collected. A randomised learning‐based forecasting model is designed for supply/demand prediction in the microgrid. Based on the forecasting results, data‐driven uncertainty modelling is used to characterise the uncertainties associated with renewable energy supply and loads. An optimal sizing approach is then proposed to determine the optimal sizes for energy storage systems (ESSs) and distributed generators with the overall aim of minimising the investment and maintenance costs. Based on the optimal sizing and uncertainty scenarios, a two‐stage coordinated energy management method is proposed to minimise the operating cost under uncertainties. To validate the proposed method, it is compared with a benchmark method. Simulation results show that the proposed method can reduce the system cost while preserving the ESS lifetime. The developed methods are packaged onto a real‐time platform for implementation.
Research on optimal reclosing time of AC/DC hybrid system based on dynamic energy
Authors: Ma Jing , Zhou Xiaodong , Cheng Peng
Published: April 2021

A method to calculate the optimal reclosing time of AC/DC hybrid system based on dynamic energy is proposed. First, in the whole fault process starting from fault initiation to accelerated tripping of circuit breakers after reclosing, the dynamic energy function that characterizes the stability degree of system is built. On this basis, the variation rate of dynamic energy is defined as the energy accumulation speed, which quantitatively characterizes the accumulation or consumption of dynamic energy in the fault duration. And detailed expressions of energy accumulation speed when single‐phase fault and three‐phase fault occur in the system are derived respectively. Then, with the accumulated dynamic energy of system being the minimum as the objective, the optimal reclosing time is searched, and the pattern in which the trajectory of operating points passes new equilibrium point when the system is reclosed at the optimal reclosing time is revealed. Finally, hardware‐in‐the‐loop tests are conducted in RT‐LAB for simulation verification. Simulation results demonstrate that, as reclosing time varies, total accumulated dynamic energy of system has multiple minimum points. Selecting the reclosing time calculated according to the method can improve stability of system.
Inertia estimation of diesel generators based on modified loading rejection tests
Authors: Lin Chien‐Hung , Wu Chi‐Jui , Yang Jun‐Zhe , Lu Chan‐Nan
Published: April 2021

An inertia identification approach has been proposed for diesel generators by using the modified load rejection procedures. Large frequency deviation problems often occur in the Kinmen island power system where many diesel generators are used. In order to avoid erroneous evaluation of frequency deviation caused by generator tripping, one of the critical issues in system planning is to accurately estimate the maximum frequency deviation during system outage events. The main factors that influence the frequency deviation include the generator inertia (H), damping constant (D), and governor controller parameters. In order to improve the accuracy of the transient stability analysis to obtain more actual frequency deviation, it is critical to have more accurate inertia values of these diesel generators. This paper proposes a useful approach to evaluate reasonable inertia values. With the identified inertia values of diesel generators, the frequency responses of the Kinmen power system obtained from PSS/E simulation are more consistent with the field measurement results.
Imposing fair penalty to the harmonic sources based on the measurement data
Authors: Tadayon Mahdi , Hooshmand Rahmat‐Allah , Kiyoumarsi Arash , Esfahani Mehdi Torabian
Published: April 2021

Improving network power quality through harmonic reduction requires recognition of Harmonic Sources (HSs) to drive them to compensate their harmonics. This paper proposes a new method for equitable distribution of the Harmonic Compensation Cost of the network among the HSs based on the Harmonic Contribution Matrix. Each element of the Harmonic Contribution Matrix is the harmonic contribution of a specific source to the harmonic voltage of a specific bus. The output of the proposed method is a penalty curve for each HS over time. The amount of the fine estimated for each individual HS per hour is a function of not only the contribution of that HS to the harmonic voltage of different buses, but also the contribution of the Harmonic Compensation Cost from the perspective of each bus, nominal voltage of each bus, and the sensitivity of each bus to the harmonic voltage. The proposed algorithm is evaluated on the IEEE 14‐bus network and Esfahan regional electrical power network in Iran. The simulation results demonstrate the capability of the proposed method to allocate the hourly penalty curve to the HSs.
Improved information entropy weighted vague support vector machine method for transformer fault diagnosis
Authors: Zhang Hongru , Sun Jiaxiang , Hou Kaining , Li Qingquan , Liu Hongshun
Published: April 2021

A combined model based on improved information entropy and vague support vector machine (IVSVM) is introduced into transformer fault diagnosis using dissolved gas analysis in oil (DGA). The improved information entropy method is used to obtain the weights of each gas and to weight the raw data, and the processed training data and the corresponding fault types are inputted into the vague support vector machine (VSVM) model to obtain classifiers. Firstly, the training data are weighted by the improved information entropy method to discretise the original data from the mixed state for subsequent classifier training. Then, the vague set divides the events into true, false and unknown factors, which can optimise the sub‐interface of SVM and improve the accuracy of the boundary point classification. Finally, fault data from the literature and actual collections are selected for training and testing. By comparing with the widely used ratio method and artificial intelligence method, it can be concluded that the method described herein can effectively improve the accuracy of fault diagnosis. The result shows that this method has better applicability when facing actual fault type classification with higher data similarity.
Learning‐free handwritten word spotting method for historical handwritten documents
Authors: Mohammed Hanadi Hassen , Subramanian Nandhini , Al‐Madeed Somaya
Published: April 2021

Word spotting on degraded and noisy historical documents can become a challenging task considering the computational time and memory usage required to scan the entire document image. This paper proposes a new effective technique for multi‐language word spotting using a two different feature extraction techniques, Histogram of Oriented Gradients (HOG) and Speeded Up Robust Features (SURF) features. First, regions of interest (ROIs) are extracted using a cross‐correlation measure, and the extracted ROIs are re‐ranked using feature extraction and matching methods. The algorithm handles two types of scenarios: Segmentation‐based and segmentation‐free. It also facilitates the search for words that occur once as well as multiple times in the image. Evaluations were conducted on the George Washington and HADARA datasets using a standard evaluation method. The proposed methodology shows improved performance over contemporary technologies currently being used in the word spotting research field.
Weight‐based colour constancy using contrast stretching
Authors: Abedini Zeinab , Jamzad Mansour
Published: April 2021

One of the main issues in colour image processing is changing objects' colour due to colour of illumination source. Colour constancy methods tend to modify overall image colour as if it was captured under natural light illumination. Without colour constancy, the colour would be an unreliable cue to object identity. Till now, many methods in colour constancy domain are presented. They are in two categories; statistical methods and learning‐based methods. This paper presents a new statistical weighted algorithm for illuminant estimation. Weights are adjusted to highlight two key factors in the image for illuminant estimation, that is contrast and brightness. The focus was on the convex part of the contrast stretching function to create the weights. Moreover, a novel partitioning mechanism in the colour domain that leads to improvement in efficiency is proposed. The proposed algorithm is evaluated on two benchmark linear image databases according to two evaluation metrics. The experimental results showed that it is competitive to the statistical state of the art methods. In addition to its low computational cost, it has the advantage of improving the efficiency of statistics‐based algorithms for dark images and images with low brightness contrast. Moreover, it is robust to camera change types.
Investigation on the partial discharge characteristics of eco‐friendly nanofluid insulation of corn oil nanofluid
Authors: M Shantha Kumar , P Kasi Viswanathan , H Shree Kumar
Published: April 2021

The suitability of corn oil nanofluid as an insulation material is studied herein by analysing the partial discharge characteristics. Experiments are conducted on nano‐silica modified corn oil at 0.01, 0.05, and 0.1 wt.% mass fractions. Electrode configurations are used to generate partial discharge (PD) sources such as corona discharge, internal discharge, and surface discharge. Partial discharge inception voltage dependency on electrode geometry is studied. Phase‐resolved partial discharge analysis (PRPD) at various test conditions is done to understand the influence of live element geometry that causes PD in real‐time operations, Weibull statistical analysis of PD parameters like scale parameter, shape parameter, skewness, and repetition rate is evaluated to understand the influence of nanofiller mass fraction in corn oil. The results illustrate that the addition of silica nanoparticles to corn oil has a significant influence on PD characteristics. The PRPD pattern analysis reveals information about the PD dependency on electrode configuration of the test condition. The addition of nanofillers in optimal concentrations without agglomeration can influence the PD characteristics to a certain degree. The test results may be inferred to suggest corn oil‐based silica nanofluids as an alternative biodegradable liquid insulation.
Analysis and robust passivity‐based control of zero‐voltage switching quasi‐resonant Cuk converter
Authors: Ayubirad Mostafa Ali , Yazdanpanah Mohammad Javad
Published: April 2021

Here, a general state‐space average model of the half‐wave zero‐voltage switching quasi‐resonant Cuk converter (HW‐ZVS‐QRCC) is derived and validated. The development of an extended Lyapunov‐function‐based robust passivity‐based control strategy for HW‐ZVS‐QRCC is carried out using the derived model. The first feature of the proposed controller is that that the resulted closed‐loop HW‐ZVS‐QRCC is globally asymptotically stabilized even if the physical constraint on the magnitude of the control signal is taken into account. Also, to deal with the uncertainties in the conventional passivity‐based control (PBC) design, an integral function of the output voltage error is incorporated in PBC structure such that zero‐voltage regulation error is assured. Lastly, it shows which variables are most suitable for feedback purposes over a wide range of controller gains. Simulation and experimental results are also provided to validate the theoretical conclusions.
Tracing spinning reserve inadequacy risk via hybrid importance sampling with an optimised partially collapsed Gibbs sampler
Authors: Wang Yue
Published: April 2021

From the simulation perspective, spinning reserve risk evaluation of power system is commonly a rare‐event assessing issue, for which importance sampling is an appealing solution technique. This paper proposes a hybrid importance sampling method for tracing spinning reserve inadequacy risk of power system integrating with renewables. The proposed method is oriented towards a generic high‐dimensional integral calculus, which allows for continuous and discrete random variables mixed together for casting kinds of risk indices. To improve the robustness in high‐dimensional applications, a partially collapsed Gibbs sampler is devised to help in exploring adaptive training samples which feature typical rare outage events. Interestingly, the originators engendering extreme spinning reserve inadequacy events can be traced using the sampling information of the proposed method. The performance of the proposed method is tested in an updated RTS‐79 system vis‐à‐vis several existing methods. Spinning reserve inadequacy risk tracing is explained by uncovering a scenario frequency distribution concerning the short‐term expected energy not supplied.
Online inertia estimation for power systems with high penetration of RES using recursive parameters estimation
Authors: Makolo Peter , Zamora Ramon , Lie Tek‐Tjing
Published: April 2021

Low and time‐changing inertia values due to the high percentage of renewable energy sources (RESs) can cause stability problems in power systems due to rapid frequency instabilities. Inertia monitoring will assist operators to apply suitable actions and more proper control methods to alleviate stability issues. Therefore, this paper proposes an online method to estimate the total inertia of a network using a recursive least‐squares approach. The proposed method uses network measurements with a non‐recursive system identification approach to initially estimate the network hypothesis model. Then, the recursive method is used together with time changing measurements to recursively estimate model parameters and extract online inertia estimates of the network. During the estimation, the method does not need to store previous data after each sample step; therefore, the computation burden is significantly reduced. More importantly, the technique incorporates the use of available electromechanical oscillation modes in the system, which are linked with system parameters, to determine the network inertia estimates. The applicability of the proposed method has been validated by numerical simulations of the IEEE 39‐bus network and the aggregated New Zealand network with its actual inertia data.
Research on sub/super‐synchronous oscillation suppression method for direct‐drive wind turbine based on energy compensation
Authors: Ma Jing , Zhang Min , Phadke A. G.
Published: April 2021

A method to suppress sub/super‐synchronous oscillation of direct‐drive wind turbines based on energy compensation is proposed. First, the transient energy model of direct‐drive wind turbine is built, and the negative damping energy terms that lead the oscillation of direct‐drive wind turbine are extracted. On this basis, the expressions of voltage compensation terms corresponding to negative damping energy terms are derived by backward deduction, thus supplementary energy branches are constructed, and their impact on fundamental frequency characteristics of wind turbine is analyzed. And then, with the compensation energy of supplementary branches reaching the maximum and the increment of fundamental‐frequency voltage being the minimum as the objective, and with the frequency‐domain characteristic and fundamental‐frequency voltage characteristic of control links being satisfied as constraints, a scheme to optimize the compensation coefficients of multiple branches is established. Finally, the model of direct‐drive wind turbine is built in RT‐LAB for hardware‐in‐the‐loop tests. Simulation results verify that, the method can realize fast frequency‐dependent suppression of sub/super‐synchronous oscillation in different frequency bands concerning different grid strengths.
Polarisation variation of linear polarised Bi‐ISAR system in space targets imaging
Authors: Bu Linsheng , Wang Junling
Published: April 2021

A bistatic inverse synthetic aperture radar (Bi‐ISAR) system is used to observe space targets through different viewing angles via a bistatic radar configuration. It is seen that the receiver of a linear polarised Bi‐ISAR system with a long baseline will encounter energy variation and high‐order phase deviation in ISAR imaging due to the polarisation variation of this system. Here, the authors quantitatively analyse the energy variation caused by polarisation mismatch in a linearly polarised Bi‐ISAR system by investigating the time‐varying bistatic angle and intrinsic variable polarisation effect of targets via the combination of observation geometry and computational electromagnetic. The high‐order phase deviation in long‐term coherent processing is also presented through the same strategy. The authors conducted simulations for a bistatic system, which is configured with different baseline vectors, to analyse the impact of polarisation variation of the linear polarised Bi‐ISAR system on the energy loss and high‐order phase terms.
Multi‐carrier and multi‐polarimetric model based adaptive target detector for passive radar systems
Authors: Filippini Francesca , Colone Fabiola
Published: April 2021

A new adaptive detection strategy for passive radar systems that fruitfully capitalizes on signals, simultaneously emitted by the same transmitter of opportunity at different carrier frequencies and collected by a set of differently polarized surveillance antennas is derived. Based on recent results that demonstrated the benefits provided by proper strategies to exploit polarimetric diversity, the authors aim at further improving the target detection performance by combining polarimetric and frequency diversity. Real data collected through an FM radio‐based passive radar prototype is used to extensively demonstrate the effectiveness of the derived strategy with respect to state‐of‐the‐art approaches. The conceived solution is proved to successfully enhance the capability to discriminate targets, thanks to an effective disturbance rejection performed at each frequency channel as well as a target echo enhancement and an increased robustness to the time‐varying characteristics of the exploited source of opportunity.
Deep learning for aircraft classification from VHF radar signatures
Authors: Fix Jérémy , Ren Chengfang , Costa Lopes Arthur , Morice Guillaume , Kobayashi Shuwa , Leterte Thierry , Hinostroza Sáenz Israel D.
Published: April 2021

Radio sources in the Very High Frequency (VHF) band can be seized as opportunity donors in a passive radar configuration such as FM radio stations and VHF omnidirectional range (VOR). A full‐wave simulation of three size classes of aeroplanes shows that their bistatic radar cross‐section (RCS) are statistically comparable, albeit perform differently in time while the plane is flying. This difference can be exploited to recognize the size of the aeroplanes with respect to these classes. Measurements confirm this possible differentiation between the aeroplanes within the same class. Encouraging initial results were obtained using convolutional or recurrent neural networks to classify aircraft classes, combining simulated bistatic RCS results and real trajectories (collected from automatic dependent surveillance‐broadcast data).
WG2AN: Synthetic wound image generation using generative adversarial network
Authors: Sarp Salih , Kuzlu Murat , Wilson Emmanuel , Guler Ozgur
Published: April 2021

In part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN) algorithms have been successfully applied to many applications, such as data augmentation, text‐to‐image translation, image‐to‐image translation, and image inpainting. Learning from data without crafting loss functions for each application provides broader applicability of the GAN algorithm. Medical image synthesis is also another field that the GAN algorithm has great potential to assist clinician training. This paper proposes a synthetic wound image generation model based on GAN architecture to increase the quality of clinical training. The proposed model is trained on chronic wound datasets with various sizes taken from real hospital environments. Hyperparameters such as epoch count and dataset size for training tasks are studied to find optimum training conditions as well. The performance of the developed model was evaluated through a mean squared error (MSE) metric to determine the similarity between generated and actual wounds. Visual inspection is performed to examine generated wound images. The results show that the proposed synthetic wound image generation (WG2AN) model has great potential to be used in medical training and performs well in producing synthetic wound images with a 1000‐image training dataset and 200 epochs of training.
Design and implementation of fast and hardware‐efficient parallel processing elements to set full and partial permutations in Beneš networks
Authors: Koloko Labson , Matsumoto Takahiro , Obara Hitoshi
Published: April 2021

A new design for parallel and distributed processing elements (PEs) is proposed to configure Beneš networks based on a novel parallel algorithm that can realise full and partial permutations in a unified manner with very little overhead time and extra hardware. The proposed design reduces the hardware complexity of PEs from to due to a distributed architecture. In the proposed design, asynchronous operation was introduced in parts to reduce the time complexity per PE stage down to O(1) within a certain N, while it takes time per PE stage in conventional algorithms. A prototype parallel was constructed and PEs were distributed in a field programmable gate array to investigate performance for the switch size of N = 4 to 32. The experimental results demonstrate that the proposed design outperforms a recent method by at least several times in terms of hardware and processing time complexities.
The GOGREEN survey: Internal dynamics of clusters of galaxies at redshift 0.9–1.4
Authors: Biviano A. , van der Burg R. F. J. , Balogh M. L. , Munari E. , Cooper M. C. , De Lucia G. , Demarco R. , Jablonka P. , Muzzin A. , Nantais J. , Old L. J. , Rudnick G. , Vulcani B. , Wilson G. , Yee H. K. C. , Zaritsky D. , Cerulo P. , Chan J. , Finoguenov A. , Gilbank D. , Lidman C. , Pintos-Castro I. , Shipley H.
Published: April 2021

Context.The study of galaxy cluster mass profiles (M(r)) provides constraints on the nature of dark matter and on physical processes affecting the mass distribution. The study of galaxy cluster velocity anisotropy profiles (β(r)) informs the orbits of galaxies in clusters, which are related to their evolution. The combination of mass profiles and velocity anisotropy profiles allows us to determine the pseudo phase-space density profiles (Q(r)); numerical simulations predict that these profiles follow a simple power law in cluster-centric distance.

Aims.We determine the mass, velocity anisotropy, and pseudo phase-space density profiles of clusters of galaxies at the highest redshifts investigated in detail to date.

Methods.We exploited the combination of the GOGREEN and GCLASS spectroscopic data-sets for 14 clusters with massM200 ≥ 1014 M⊙at redshifts 0.9 ≤ z ≤ 1.4. We constructed anensemblecluster by stacking 581 spectroscopically identified cluster members with stellar massM⋆ ≥ 109.5 M⊙. We used the MAMPOSSt method to constrain severalM(r) andβ(r) models, and we then inverted the Jeans equation to determine theensembleclusterβ(r) in a non-parametric way. Finally, we combined the results of theM(r) andβ(r) analysis to determineQ(r) for theensemblecluster.

Results.The concentrationc200of theensemblecluster mass profile is in excellent agreement with predictions from Λ cold dark matter (ΛCDM) cosmological numerical simulations, and with previous determinations for clusters of similar mass and at similar redshifts, obtained from gravitational lensing and X-ray data. We see no significant difference between the total mass density and either the galaxy number density distributions or the stellar mass distribution. Star-forming galaxies are spatially significantly less concentrated than quiescent galaxies. The orbits of cluster galaxies are isotropic near the center and more radial outside. Star-forming galaxies and galaxies of low stellar mass tend to move on more radially elongated orbits than quiescent galaxies and galaxies of high stellar mass. The profileQ(r), determined using either the total mass or the number density profile, is very close to the power-law behavior predicted by numerical simulations.

Conclusions.The internal dynamics of clusters at the highest redshift probed in detail to date are very similar to those of lower-redshift clusters, and in excellent agreement with predictions of numerical simulations. The clusters in our sample have already reached a high degree of dynamical relaxation.
Lung MRI in Children: The Road Less Travelled
Authors: Sodhi Kushaljit Singh
Published: April 2021

Magnetic resonance imaging (MRI) of the lungs is one of the most underutilized imaging modality when it comes to imaging of thoracic diseases in children. This is largely due to less-than-optimal image quality and multiple technical challenges involved with MRI of the lungs. Advances in MRI technology along with increased awareness about optimization of MR protocol have led to it being viewed as a feasible option for evaluation of various chest diseases in children. This short review article takes the reader to the road less travelled to explore newer horizons for applications of this rapidly evolving magnetic resonance technique in the field of thoracic diseases in children.
Senna alata (candle bush).
Authors: Vélez-Gavilán Jeanine
Published: April 2021

A datasheet on Senna alata covering, as an economically important tree, its taxonomy, importance, silviculture, distribution, biology and ecology, uses, products and pests.
Annona cherimola (cherimoya).
Authors: Datiles Marianne Jennifer , Acevedo-Rodríguez Pedro
Published: April 2021

A datasheet on Annona cherimola covering, as an economically important tree, its taxonomy, importance, silviculture, distribution, biology and ecology, uses, products and pests.
Research on the stress relaxation behaviour of Cu–0.23Cr–0.08Ag alloy
Authors: Li Peng Fei , Zou Min Qiang , Song Cheng Yin , Qi Liang , Guan Ren Guo
Published: April 2021

The stress relaxation behaviour of Cu–0.23Cr–0.08Ag alloy was studied at different deformations (10%, 20%, 30%). The high percentage of low ΣCSL (Coincidence Site Lattice) grain boundary could improve the stress relaxation resistance of the alloy. There are two main factors affecting the stress relaxation resistance: one is the pinning effect of Cr to movable dislocations; the other is the obstacle of twins to the movement of movable dislocations.
How soccer scouts identify talented players
Authors: Bergkamp Tom L. G. , Frencken Wouter G. P. , Niessen A. Susan M. , Meijer Rob R. , den Hartigh Ruud. J. R.
Published: April 2021

Scouts of soccer clubs are often the first to identify talented players. However, there is a lack of research on how these scouts assess and predict overall soccer performance. Therefore, we conducted a large‐scaled study to examine the process of talent identification among 125 soccer scouts. Through an online self‐report questionnaire, scouts were asked about (1) the players’ age at which they can predict players’ soccer performance, (2) the attributes they consider relevant, and (3) the extent to which they predict performance in a structured manner. The most important results are as follows. First, scouts who observed 12‐year‐old and younger players perceived they could predict at older ages (13.6 years old, on average) whether a player has the potential to become a professional soccer player. This suggests that scouts are aware of the idea that early indicators of later performance are often lacking, yet do advise on selection of players at younger ages. Second, when identifying talented players, scouts considered more easily observable attributes, such as technical attributes. However, scouts described these often in a broad sense rather than in terms of specific predictors of future performance. Finally, scouts reported that they assess attributes of players in a structured manner. Yet, they ultimately based their prediction (i.e. final score) on an intuitive integration of different performance attributes, which is a suboptimal strategy according to existing literature. Taken together, these outcomes provide specific clues to improve the reliability and validity of the scouting process.

Highlights

Based on a large sample of soccer scouts, we examine three issues that are important in the process of identifying talented soccer players: The age at which good performance predictions can be made, which attributes are relevant predictors, and how performance predictions are formed.

Scouts who observe players in young age cohorts believe that the age at which they can predict performance is older than the players they typically scout, suggesting that they are aware that early indicators of performance are often lacking.

Technical performance attributes are considered as most important performance predictors by scouts, but these are often described in a broad ‐ rather than specific ‐ sense.

Scouts indicate that they predict performance in a structured manner, but form their overall performance prediction on an intuitive integration of different performance attributes, which can be a suboptimal approach.
The effect of fatiguing lower‐body exercise on punch forces in highly‐trained boxers
Authors: Dunn Emily C. , Humberstone Clare E. , Franchini Emerson , Iredale Fiona K. , Blazevich Anthony J.
Published: April 2021

This study aimed to examine the effect of intense intermittent lower‐body and trunk exercise (rowing) on punching performance in 28 highly‐trained male amateur boxers. Straight‐ and bent‐arm punch performances were assessed with a custom‐built punch integrator using a 3‐min maximal‐effort punch test, completed in both non‐fatigued (ROWpre) and fatigued (ROWpost) states. A within‐subject repeated measures design was implemented; subjects completed ROWpre, then 9 × 1‐min bouts of rowing (1‐min rest intervals), followed by ROWpost. Peak punch force and force‐time variables, including impulse and rate of force development (RFD; calculated to five time points), were assessed. Differences between ROWpre and ROWpost for each punch type (jab, cross, lead‐ and rear‐hand hook) were tested with a linear mixed model, and effect sizes (Cohen's d) were calculated. Results showed significant (p < 0.05) reductions in punch force in ROWpost compared to ROWpre for all punch types as well as significant delays in the time to reach specific force levels, and relative percentages of peak force (RFD) in all punches except the jab. It is likely that fatigue of the lower body and trunk muscles impaired ground reaction force, and thus punch force, production. This effect was larger in punches that involved a greater degree of trunk rotation, crosses and hooks, than in the jab which relies predominantly on arm extension. These findings reveal the negative effect of fatigue on punch force production, and provide evidence that lower‐body and trunk force are important for generating punch force.

Highlights

The ability of the lower body to generate force affects the magnitude of punch force produced in trained boxers.

A bout of intense rowing exercise significantly reduces punch force, and rate of force development. This should be carefully considered when programming and scheduling boxing specific training sessions and strength and conditioning sessions.

While non‐specific fatigue affected the punch performance of boxers, the authors call for further research to examine the effects of fatigue sustained during a boxing bout in comparison to non‐boxing muscular fatigue and a non‐exercise control.
Macroautophagy in lymphatic endothelial cells inhibits T cell–mediated autoimmunity
Authors: Harlé Guillaume , Kowalski Camille , Dubrot Juan , Brighouse Dale , Clavel Gaëlle , Pick Robert , Bessis Natacha , Niven Jennifer , Scheiermann Christoph , Gannagé Monique , Hugues Stéphanie
Published: April 2021

Lymphatic endothelial cells (LECs) present peripheral tissue antigens to induce T cell tolerance. In addition, LECs are the main source of sphingosine-1-phosphate (S1P), promoting naive T cell survival and effector T cell exit from lymph nodes (LNs). Autophagy is a physiological process essential for cellular homeostasis. We investigated whether autophagy in LECs modulates T cell activation in experimental arthritis. Whereas genetic abrogation of autophagy in LECs does not alter immune homeostasis, it induces alterations of the regulatory T cell (T reg cell) population in LNs from arthritic mice, which might be linked to MHCII-mediated antigen presentation by LECs. Furthermore, inflammation-induced autophagy in LECs promotes the degradation of Sphingosine kinase 1 (SphK1), resulting in decreased S1P production. Consequently, in arthritic mice lacking autophagy in LECs, pathogenic Th17 cell migration toward LEC-derived S1P gradients and egress from LNs are enhanced, as well as infiltration of inflamed joints, resulting in exacerbated arthritis. Our results highlight the autophagy pathway as an important regulator of LEC immunomodulatory functions in inflammatory conditions.
Intelligent Chatbot Adapted from Question and Answer System Using RNN-LSTM Model
Authors: Anki P , Bustamam A , Al-Ash H S , Sarwinda D
Published: April 2021

In modern times, the chatbot is implemented to store data collected through a question and answer system, which can be applied in the Python program. The data to be used in this program is the Cornell Movie Dialog Corpus which is a dataset containing a corpus which contains a large collection of metadata-rich fictional conversations extracted from film scripts. The application of chatbot in the Python program can use various models, the one specifically used in this program is the LSTM. The output results from the chatbot program with the application of the LSTM model are in the form of accuracy, as well as a data set that matches the information that the user enters in the chatbot dialog box input. The choice of models that can be applied is based on data that can affect program performance, with the aim of the program which can determine the high or low level of accuracy that will be generated from the results obtained through a program, which can be a major factor in determining the selected model. Based on the application of the LSTM model into the chatbot, it can be concluded that with all program test results consisting of a variety of different parameter pairs, it is stated that Parameter Pair 1 (size_layer 512, num_layers 2, embedded_size 256, learning_rate 0.001, batch_size 32, epoch 20) from File 3 is the LSTM Chatbot with the avg accuracy value of 0.994869 which uses the LSTM model is the best parameter pair.
Photovoltaic-Based Intelligent Search and Rescue Trolley
Authors: Zhang J , Zhao M Z , Zhou W D , Tian Y , Zhu Y J , Zhang W Y
Published: April 2021

For the search and rescue work after the earthquake or the exploration of unknown areas, a photovoltaic-based intelligent search and rescue device was designed. A hardware platform for a car automatic driving system controlled by an STM32 single-chip microcomputer based on an ARM core is constructed, which consists of a photovoltaic auxiliary power generation module, a power supply module, a main controller module, obstacle detection, a motor drive module, a speed detection module, and a video transmission module. And constructed a software platform based on ARM core STM32F103 single-chip microcomputer controlled automatic control system. Finally, through the joint debugging of the hardware and software parts of the photovoltaic intelligent search and rescue equipment, the stability and feasibility of the system were verified, and the functions of photovoltaic-assisted power generation, manual control, autonomous obstacle avoidance, and video transmission of the car were realized.
Study of Salt Effect on Semi-Continuous Anaerobic Digestion of Food Waste with Modified First-Order Model
Authors: Li X F , Hu T N , Huang J J , Liu Y Y , Peng D P , Wu Z , Huang T
Published: April 2021

In semi-continuous anaerobic digestion, organic material feed sometimes may not be consumed completely in one day and it may considerably help to increase biogas production of next day. Such occurrence is called ’biogas accumulation phenomenon’, which cannot reflect the real biogas production from next day’s feed. In this test, first-order model was modified to solve this problem. Compared with first-order model, k values of modified first-order model had smaller relative standard deviation for each week with better fitting degree. Modified first-order model was then verified using food waste with different theoretical biogas production. Therefore, it can be concluded that the modified model can remove biogas accumulation phenomenon effectively. However, this model didn’t perform well in methane production fitting. The modified first-order model was utilized to study the variation trend of biogas production from anaerobic digestion of food waste with increasing salt concentration in the reactor. Results showed that when salt concentration in reactor increased from 0.69 to 2.12 g.-L−1, biogas production experienced increasing first and then deceasing. 0.98 to 1.27g-L.−1salt concentration was more appropriate for biogas production (653-718L.-kg−1 VS) and when salt concentration increased to 1.36-1.61 g.-L−1, inhibition phenomenon began. Biogas production (363-420L.-kg−1 VS) was further suppressed with 1.68-2.12 g.-L−1salt concentration. At this time, the ratio of volatile organic acids to the total inorganic carbon (VOA/TIC) increased to 0.24-0.58, showing anaerobic digestion process was unstable.
Research and Design of Heat Transfer Coefficient Measuring Instrument for Vacuum Glass
Authors: Zhang X Y , Ning D , Huang J Y , Zhu G L , Chen Y X
Published: April 2021

In order to solve the problem of building energy loss and actively respond to the implementation of the national energy conservation and emission reduction policy, this system, according to the international standard of vacuum glass JC/T1079-2008, combined with the development status and production demand of the measuring instrument, developed a set of instruments that can meet the design requirements to quickly and accurately measure the heat transfer coefficient of vacuum glass. At the same time, the constant pressure measurement conditions are put forward and implemented on the basis of the system. The circuit, software and mechanical structure of the system are studied and designed. Through the above design, the design and test of the vacuum glass heat transfer coefficient measuring instrument are completed. The experimental data show that the measurement error is 0.34% under the condition of adopting effective control strategy, which is about 16 times lower than the measurement error of low-end control method, which is 5.6%. The conclusion shows that the instrument can be used to measure the target more accurately, which is of economic and practical significance.
Historical Aspects of Development of Metall Structures and Application Thereof in Buildings and Facilities
Authors: Gabitov A I , Udalova E A , Salov A S , Yamilova V V
Published: April 2021

Brief history of development of metal structures and application thereof in various buildings and facilities starting from the 12th century and up to now is presented herein. “The metal structures” notion includes structural form, manufacturing technology and ways of installation. Evolution step in making metal structures is defined both by public needs therein and level and capabilities of technical facilities: development of metal industry, engineering technology, metalworking, construction machinery and science. Proceeding from this, five periods in metal structures evolution may be singled out. Development of industry and construction is shown to result in vast variety of metal structures to be applied nowadays in different buildings and constructions especially in significant spans, heights and loads. Therewith wide scientific R&D in engineering design with application of modern high-power PCs and CAD complexes, in particular, enable to efficiently upgrade and vary the structural form of facilities with less materials and resources expenses. In-depth and comprehensive analysis of centuries-old evolution of metals application in construction and implementation of investigation results in teaching high-skilled builders and architects of today will enable to efficiently provide staffing for successful solving of state challenges of hi-tech and social development of the Russian Federation.
Qualitative and Quantitative Composition of Gas Emissions of Energy-Technological Equipments
Authors: Sazonov E V , Drapalyuk N A , Burak E E , Vorob’eva Y A
Published: April 2021

Power-generating plants are devices for producing heat, electrical and mechanical energy. They are widely used as internal combustion engines for ground and air vehicles. A significant drawback of internal combustion engines is their exhaust gases - the main environmental pollutants. The article identifies benchmarks (CO, NOx, CmHn, SOx) and secondary chemical compounds in the exhausts of internal combustion engines, their percentage and degree of toxicity are given. The influence of the highway on the surrounding territory and processes that reduce the migration of pollutants into the airspace are considered. Recommendations are given on reducing the number of parameters for analyzing the state of the environment and the possible penetration of pollutants into the human body.
Analysis of Efficiency of Toll Road Network Development
Authors: Karpushko M O , Bartolomei I L , Karpushko E N , Zhidelev A V , Bryzgalov V I
Published: April 2021

The article analyzes the experience of Russian cities that provide toll roads charging. Based on the analysis, rates for toll roads were proposed depending on the category of vehicles, corresponding to the volume and quality of services provided to the user of the toll road. Based on the data obtained and the methodology for calculating the rate for vehicles on toll roads, the calculation of the amount of savings received by users when driving a toll road, compared with an alternative free route, was made. The calculation included determining the cost of operating a vehicle when driving through a toll road facility by reducing the consumption of fuel and lubricants, tire wear, repair costs, and other items of operating costs. The advantage for users of toll roads was determined by saving time for delivery of goods and passengers, increasing comfort and traffic safety. Additional attraction of funds through placement of gas stations and advertising is considered. The payback period of the toll road has been determined. The conclusion is made about the need for further research on the problems of development of the network of toll roads.
On the Question of Reducing Technogenic Risks of Accidents in the Technical Systems of Buildings and Structures
Authors: Glukhanov A S , Biryuzova E A
Published: April 2021

The necessity of making changes to the functionality of a structured system for monitoring and managing engineering systems of buildings and structures is justified. An approach to modernizing the algorithmic support of a structured system for monitoring and managing engineering systems of buildings and structures is proposed in order to identify failures that lead to emergency situations at an early stage of their occurrence. The main features of the structure and application of technical systems of objects of various purposes, essential for the analysis of their technical condition, are determined. The necessity of developing and implementing a system for managing the technical condition of the studied systems is justified. A model for monitoring the operability of engineering systems of buildings and structures has been developed. The use of parametric statistics methods as a basis for the development of performance monitoring algorithms is justified. Regression equations are constructed as algebraic polynomials of various degrees, which are also the simplest combinations of elementary functions. Regression dependences of the monitored parameters of the diagnosed engineering systems on input influences are determined. Lists of these parameters are defined. The dependence of the reliability of determining the technical condition of engineering systems on the value of the confidence interval of the measured parameters was determined by numerical experiment. An algorithm for determining regression dependencies and a block diagram of the proposed algorithmic support are presented.
Updating the Matrix Approach to Creating a Parametric Balance of Technological Process
Authors: Shakhov V A , Piskaryova T I , Ivanova A P , Mezhueva L V
Published: April 2021

Currently, the feed industry uses a large number of different types of feed mixers. The preparation of feed mixtures with different ingredients, with frequently changing compositions, must comply with such condition as uniformity. Basically, any prepared multicomponent mass should be distributed uniformly throughout the volume of each recipe element.

The mixtures homogeneity can be achieved by using various equipment, which, unfortunately, is not always efficient and cost-effective. The selection of a technological line from equipment that provides a low-cost production cycle is a very time-consuming task, since the use of an experimental base of changing types of mixing machines implies unforeseen economic expenditures.

Often when starting a certain production cycle of dry or wet mixtures, a preliminary forecast of the process effectiveness which can be achieved by creating a mathematical model of mixing is needed. All kinds of technological units designs, their geometric components classification, physico-mechanical and rheological indicators, operating-kinematic characteristics of the process can be used in the mathematical model.

Having studied the mixing process we came to the conclusion that a high degree of mixing uniformity can be obtained with the same geometric particle sizes. But such a phenomenon is quite rare. Thus, an ideal mixture can be obtained by forcibly selecting process parameters.

The effectiveness of this process can be based on a matrix approach. The process matrix will contain the dominant most significant indicators which have interconnections in the intermatrix space that create a certain parametric balance.

It is advisable to divide the mathematical interpretation of the homogeneous feed mixtures creating process into several stages:

- the first stage includes loading into the software model of the characteristics displaying the specific features of the process in question;

- the second stage includes empirical patterns description;

- the third stage creates an opportunity for searching for optimal tasks solutions.

When studying the graphical dependences of the influence of process parameters on the output of quality energy indicators, the optimal solutions region is determined, each point of which allows to effectively carry out the mixing process in a screw-blade mixer.