bluuebunny/crossref_metadata_2025 huggingface dataset:
Harmonization of Flow Cytometric Minimal Residual Disease Assessment in Multiple Myeloma in Centers of Polish Myeloma Consortium
Authors: Krzywdzińska Agnieszka , Puła Bartosz , Czyż Anna , Krzymieniewska Beata , Kiernicka-Parulska Jolanta , Mierzwa Anna , Szymczak Donata , Milanowska Aneta , Kiraga Aleksandra , Kwiecień Iwona , Zaleska Joanna , Jamroziak Krzysztof
Published: October 2021

Minimal residual disease (MRD) status is now considered as one of the most relevant prognostic factors in multiple myeloma (MM) while MRD negativity became an important endpoint in clinical trials. Here, we report the results of the first study evaluating the reproducibility of high-sensitivity flow cytometry MM MRD assessment in four laboratories in Poland. EuroFlow protocols for instrument setting standardization and sample preparation in MM MRD assessment were implemented in each laboratory. In the inter-laboratory reproducibility study, 12 bone marrow samples from MM patients were distributed and processed in participant laboratories. In the inter-operator concordance study, 13 raw data files from MM MRD measurements were analyzed by five independent operators. The inter-laboratory study showed high 95% overall concordance of results among laboratories. In the inter-operator study, 89% of MRD results reported were concordant, and the highest immunophenotype interpretation differences with regard to expression of CD27, CD45, CD81 were noticed. We confirmed the applicability and feasibility of the EuroFlow protocol as a highly sensitive method of MRD evaluation in MM. Results of our inter-center comparison study demonstrate that the standardization of MM MRD assessment protocols is highly desirable to improve quality and comparability of results within and between different clinical trials.
Longitudinal Assessment of Tau-Associated Pathology by 18F-THK5351 PET Imaging: A Histological, Biochemical, and Behavioral Study
Authors: Moreno-Gonzalez Ines , Edwards George A. , Hasan Omar , Gamez Nazaret , Schulz Jonathan E. , Fernandez-Valenzuela Juan Jose , Gutierrez Antonia , Soto Claudio , Schulz Paul E.
Published: October 2021

Several common and debilitating neurodegenerative disorders are characterized by the intracellular accumulation of neurofibrillary tangles (NFTs), which are composed of hyperphosphorylated tau protein. In Alzheimer’s disease (AD), NFTs are accompanied by extracellular amyloid-beta (Aβ), but primary tauopathy disorders are marked by the accumulation of tau protein alone, including forms of frontotemporal dementia (FTD), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP), among others. 18F-THK5351 has been reported to bind pathological tau as well as associated reactive astrogliosis. The goal of this study was to validate the ability of the PET tracer 18F-THK5351 to detect early changes in tau-related pathology and its relation to other pathological hallmarks. We demonstrated elevated in vivo 18F-THK5351 PET signaling over time in transgenic P301S tau mice from 8 months that had a positive correlation with histological and biochemical tau changes, as well as motor, memory, and learning impairment. This study indicates that 18F-THK5351 may help fill a critical need to develop PET imaging tracers that detect aberrant tau aggregation and related neuropathology in order to diagnose the onset of tauopathies, gain insights into their underlying pathophysiologies, and to have a reliable biomarker to follow during treatment trials.
The ERG1A K+ Channel Is More Abundant in Rectus abdominis Muscle from Cancer Patients Than that from Healthy Humans
Authors: Zampieri Sandra , Sandri Marco , Cheatwood Joseph L. , Balaraman Rajesh P. , Anderson Luke B. , Cobb Brittan A. , Latour Chase D. , Hockerman Gregory H. , Kern Helmut , Sartori Roberta , Ravara Barbara , Merigliano Stefano , Da Dalt Gianfranco , Davie Judith K. , Kohli Punit , Pond Amber L.
Published: October 2021

Background: The potassium channel encoded by the ether-a-gogo-related gene 1A (erg1a) has been detected in the atrophying skeletal muscle of mice experiencing either muscle disuse or cancer cachexia and further evidenced to contribute to muscle deterioration by enhancing ubiquitin proteolysis; however, to our knowledge, ERG1A has not been reported in human skeletal muscle. Methods and Results: Here, using immunohistochemistry, we detect ERG1A immunofluorescence in human Rectus abdominis skeletal muscle sarcolemma. Further, using single point brightness data, we report the detection of ERG1A immunofluorescence at low levels in the Rectus abdominis muscle sarcolemma of young adult humans and show that it trends toward greater levels (10.6%) in healthy aged adults. Interestingly, we detect ERG1A immunofluorescence at a statistically greater level (53.6%; p < 0.05) in the skeletal muscle of older cancer patients than in age-matched healthy adults. Importantly, using immunoblot, we reveal that lower mass ERG1A protein is 61.5% (p < 0.05) more abundant in the skeletal muscle of cachectic older adults than in healthy age-matched controls. Additionally, we report that the ERG1A protein is detected in a cultured human rhabdomyosarcoma line that may be a good in vitro model for the study of ERG1A in muscle. Conclusions: The data demonstrate that ERG1A is detected more abundantly in the atrophied skeletal muscle of cancer patients, suggesting it may be related to muscle loss in humans as it has been shown to be in mice experiencing muscle atrophy as a result of malignant tumors.
Investigation of Inter-Limb Symmetry in Knee Extensors Using Different Strength Outcome Measures
Authors: Smajla Darjan , Žitnik Jure , Šarabon Nejc
Published: October 2021

Muscle performance between contra-lateral knee extensors is most often assessed using maximal test for isometric/isokinetic torque evaluation. Recently, the rate of force development scaling factor (RFD-SF) has been used to evaluate neuromuscular capacity with a range of submaximal target peak torques, which could highlight other aspects of inter-limb (a)symmetry. The aim of our study was to investigate the differences, associations, and agreement between inter-limb symmetries of knee extensors using maximal torque (Tmax) rate of torque development (RTD), slope of the RFD-SF regression line (k), and theoretical peak of RTD (TPRTD). A total of 236 young, healthy athletes participated in the cross-sectional study. All participants performed unilateral knee extension (maximal voluntary contraction protocol and RFD-SF protocol) with both legs in the isometric knee dynamometer. Inter-limb symmetries were calculated for each outcome measure. Our results showed significant differences between all symmetry values (Tmax (91.7%), RTD (85.2%), k (94.2%), TPRTD (95.9%)). Significant strong correlations were found between symmetry values calculated from k and TPRTD (r = 0.88, p < 0.001), while weak correlation was found between Tmax and RTD (r = 0.17, p < 0.01. Fair agreement regarding leg dominance was found between Tmax and RTD values. Our results suggest that inter-limb (a)symmetries are metric- and task-specific.
Design and Modeling of an Experimental ROV with Six Degrees of Freedom
Authors: Kabanov Aleksey , Kramar Vadim , Ermakov Igor
Published: October 2021

With the development of underwater technology, it is important to develop a wide range of autonomous and remotely operated underwater vehicles for various tasks. Depending on the problem that needs to be solved, vehicles will have different designs and dimensions, while the issues surrounding reduced costs and increasing the functionality of vehicles are relevant. This article discusses the development of inspection class experimental remotely operated vehicles (ROVs) for performing coastal underwater inspection operations, with a smaller number of thrusters, but having the same functional capabilities in terms of controllability (as vehicles with traditionally-shaped layouts). The proposed design provides controllability of the vehicle in six degrees of freedom, using six thrusters. In classical design vehicles, such controllability is usually achieved using eight thrusters. The proposed design of the ROV is described; the mathematical model, the results of modeling, and experimental tests of the developed ROVs are shown.
Preference Parameters for the Calculation of Thermal Conductivity by Multiparticle Collision Dynamics
Authors: Wang Ruijin , Zhang Zhen , Li Long , Zhu Zefei
Published: October 2021

Calculation of the thermal conductivity of nanofluids by molecular dynamics (MD) is very common. Regrettably, general MD can only be employed to simulate small systems due to the huge computation workload. Instead, the computation workload can be considerably reduced due to the coarse-grained fluid when multiparticle collision dynamics (MPCD) is employed. Hence, such a method can be utilized to simulate a larger system. However, the selection of relevant parameters of MPCD noticeably influences the calculation results. To this end, parameterization investigations for various bin sizes, number densities, time-steps, rotation angles and temperatures are carried out, and the influence of these parameters on the calculation of thermal conductivity are analyzed. Finally, the calculations of thermal conductivity for liquid argon, water and Cu-water nanofluid are performed, and the errors compared to the theoretical values are 3.4%, 1.5% and 1.2%, respectively. This proves that the method proposed in the present work for calculating the thermal conductivity of nanofluids is applicable.
Secret-Key Agreement by Asynchronous EEG over Authenticated Public Channels
Authors: Galis Meiran , Milosavljević Milan , Jevremović Aleksandar , Banjac Zoran , Makarov Aleksej , Radomirović Jelica
Published: October 2021

In this paper, we propose a new system for a sequential secret key agreement based on 6 performance metrics derived from asynchronously recorded EEG signals using an EMOTIV EPOC+ wireless EEG headset. Based on an extensive experiment in which 76 participants were engaged in one chosen mental task, the system was optimized and rigorously evaluated. The system was shown to reach a key agreement rate of 100%, a key extraction rate of 9%, with a leakage rate of 0.0003, and a mean block entropy per key bit of 0.9994. All generated keys passed the NIST randomness test. The system performance was almost independent of the EEG signals available to the eavesdropper who had full access to the public channel.
Feature Selection for Regression Based on Gamma Test Nested Monte Carlo Tree Search
Authors: Li Ying , Li Guohe , Guo Lingun
Published: October 2021

This paper investigates the nested Monte Carlo tree search (NMCTS) for feature selection on regression tasks. NMCTS starts out with an empty subset and uses search results of lower nesting level simulation. Level 0 is based on random moves until the path reaches the leaf node. In order to accomplish feature selection on the regression task, the Gamma test is introduced to play the role of the reward function at the end of the simulation. The concept Vratio of the Gamma test is also combined with the original UCT-tuned1 and the design of stopping conditions in the selection and simulation phases. The proposed GNMCTS method was tested on seven numeric datasets and compared with six other feature selection methods. It shows better performance than the vanilla MCTS framework and maintains the relevant information in the original feature space. The experimental results demonstrate that GNMCTS is a robust and effective tool for feature selection. It can accomplish the task well in a reasonable computation budget.
Forecasting US Inflation in Real Time
Authors: Fulton Chad , Hubrich Kirstin
Published: October 2021

We analyze real-time forecasts of US inflation over 1999Q3–2019Q4 and subsamples, investigating whether and how forecast accuracy and robustness can be improved with additional information such as expert judgment, additional macroeconomic variables, and forecast combination. The forecasts include those from the Federal Reserve Board’s Tealbook, the Survey of Professional Forecasters, dynamic models, and combinations thereof. While simple models remain hard to beat, additional information does improve forecasts, especially after 2009. Notably, forecast combination improves forecast accuracy over simpler models and robustifies against bad forecasts; aggregating forecasts of inflation’s components can improve performance compared to forecasting the aggregate directly; and judgmental forecasts, which may incorporate larger and more timely datasets in conjunction with model-based forecasts, improve forecasts at short horizons.
A Different View on ASEAN Capital Market Integration
Authors: Robiyanto Robiyanto , Frensidy Budi , Setyawan Ignatius Roni , Huruta Andrian Dolfriandra
Published: October 2021

Capital market integration has become an interesting research topic nowadays. Many studies have tried to explain this phenomenon using various methods. Here, we used sophisticated methods to explain capital market integration. This study aims to scrutinize the Association of Southeast Asian Nations (ASEAN) capital market integration. This study hopefully can enrich the different views regarding the capital market integration and fill the gap left by previous studies. The data used were the stock price index of the monthly closing data of the capital markets in ASEAN countries during the period of January 1999 to December 2020, obtained from Bloomberg and the Indonesia Stock Exchange. Data in this study were analyzed using the wavelet method. The results indicate that there is a long-term integration in the capital markets of ASEAN countries, and the highest level of integration was in the period during and about a year after the global crisis. Using the spectrum analysis, the results show that during period from 2008 to 2010, the level of integration reached its highest level.
Empirical Analysis on Public Expenditure for Education and Economic Growth: Evidence from Indonesia
Authors: Suwandaru Agung , Alghamdi Thamer , Nurwanto Nurwanto
Published: October 2021

The purpose of this paper is to find the relationship between public expenditure in the educational sector and the economic growth in Indonesia since the government decided to spend 20% of the state budget on education. We used time series data from 1988 to 2018 and the Cobb–Douglas production function as an economic theory for measurement. In the methodology, we employed Autoregressive Distributed Lag bound tests to find the relationship between variables. The results show that public expenditure on education has an insignificant relationship in the long- and short-term estimation. However, they both have different directions, which is a positive relationship in long-term and a negative relationship in short-term estimation. Meanwhile, gross fixed capital formation shows a positive relationship, and the labour variable has a negative relationship in the short and long terms. In conclusion, the Indonesian government should manage the education system regarding the relationship between education expenditure and economic growth.
What Are the Needs of Senior Tourists? Evidence from Remote Regions of Europe
Authors: Zielińska-Szczepkowska Joanna
Published: October 2021

Tourism is one of the fastest-growing industries in Europe, with growth mostly centered in major cities and urban locations. Nevertheless, remote destinations can also offer tranquility and accessibility, as well as both unexploited and unknown development potential for active senior travelers. The purpose of this paper is to analyze, on the basis of information gathered from 1705 questionnaires, senior touristic behavior, including motivations and decision-making issues for senior travelers in 11 remote regions of nine European countries (Finland, Latvia, Poland, Slovakia, Hungary, Bulgaria, Spain, Ireland, and Greece). A mixed-methods approach was used to fulfill the research objectives. Both interviews and the survey method were applied to generate data from senior tourists. The present study will focus on the key factors explaining senior tourists’ motivations and barriers to travel. The results of surveys conducted within the TOURAGE project indicate the significant potential of remote regions in the development of senior tourism. For senior respondents, a very important reason for going on holiday is the possibility of enjoying rest and silence. Safety, nature, historical sites, quality of services, and easy transportation connections are the top five attraction factors for seniors when choosing a destination. At the same time, according to the interviews, among the important problems negatively influencing the size of the senior tourism market in remote regions are: difficulties in reaching seniors with tourist offers, a lack of promotion of local tourist products aimed at seniors, and finally a lack of financial resources for the implementation of local projects supporting the development of senior tourism.
Professional Knowledge and Self-Efficacy Expectations of Pre-Service Teachers Regarding Scientific Reasoning and Diagnostics
Authors: Hilfert-Rüppell Dagmar , Meier Monique , Horn Daniel , Höner Kerstin
Published: October 2021

Understanding and knowledge of scientific reasoning skills is a key ability of pre-service teachers. In a written survey (open response format), biology and chemistry pre-service teachers (n = 51) from two German universities claimed central decisions or actions school students have to perform in scientific reasoning in the open inquiry instruction of an experiment. The participants’ answers were assessed in a quality content analysis using a rubric system generated from a theoretical background. Instruments in a closed response format were used to measure attitudes towards the importance of diagnostics in teacher training and the domain-specific expectations of self-efficacy. The pre-service teacher lacked pedagogical (didactics) content knowledge about potential student difficulties and also exhibited a low level of content methodological (procedural) knowledge. There was no correlation between the knowledge of student difficulties and the approach to experimenting with expectations of self-efficacy for diagnosing student abilities regarding scientific reasoning. Self-efficacy expectations concerning their own abilities to successfully cope with general and experimental diagnostic activities were significantly lower than the attitude towards the importance of diagnostics in teacher training. The results are discussed with regard to practical implications as they imply that scientific reasoning should be promoted in university courses, emphasising the importance of understanding the science-specific procedures (knowing how) and epistemic constructs in scientific reasoning (knowing why).
Telework Experience of Pedagogues during the COVID-19 Pandemic: Strong Learning Seniors and Relaxed Leaders?
Authors: Raišienė Agota Giedrė , Lučinskaitė-Sadovskienė Rita , Gardziulevičienė Laura
Published: October 2021

Due to the wide application of remote teaching during the COVID-19 pandemic, the foundations of the education system have been shaken; education has entered a new era of teaching and learning on digitalized platforms. How do pedagogues evaluate their experiences when information technologies have become the main axis of carrying out their work? What impact did telework have on pedagogues as employees of an education institution or as individuals? What could be expected from older pedagogues in the shift to using digital means of teaching? These were the main questions raised in this research, the results of which are presented in this article. This research is original because the differences in experiences of telework were studied not only in terms of age and nature of work (professional/leader) but also the type of education institution. This delineation is of key importance in understanding the virtual work challenges faced by pedagogues in schools, professional education institutions, colleges, and universities.
Physical Spaces in Higher Education as Scenarios of Learning Innovation: Compositional and Formative Synergies among Architecture, Music, and Fashion
Authors: Campos Pablo , Luceño Laura , Aguirre Carlos
Published: October 2021

Learning innovation is a positive approach on the contemporary higher education international stage. This article stresses the need to devise physical spaces that are also innovative. For that purpose, using a qualitative methodology, we investigated recent trends based on the synergies between certain creative disciplines: architecture, music, and fashion. The comparison was based on compositional features and formative dimension. Using a qualitative methodological comprehensive approach, a set of case studies was analysed. The findings show the usefulness of activating these synergies as effective strategies when enriching educational processes in different ways. Six cases of excellence wherein university physical spaces reached levels of innovation were studied, representing relevant transfers among the three disciplines. The text presents examples that show the educational consequences in the establishment of those synergies, in terms of both composition (music–architecture) and the activation of heritage sites in the city as venues of learning innovation (fashion–architecture). The basic conclusions were based on the fact that the increase in teaching and spatial creativity that emanates from said synergies among the three disciplines can be potentially extrapolated to other areas of knowledge.
Effectiveness of a Program to Improve Attention towards Affective-Sexual, Bodily and Gender Diversity in University Students
Authors: Morales-Rodríguez Francisco Manuel
Published: October 2021

It is necessary for the university environment to contribute to the improvement of the attention paid to affective-sexual, bodily, and gender diversity. This research deals with how, by means of a teaching innovation program, competences for affective-sexual diversity were developed. Specifically, negative attitudes towards diversity, knowledge, and degree of empathy on these issues before and after the implementation of the program are compared. The degree of satisfaction, perceived usefulness, and fulfillment of the objectives proposed in the program were also evaluated. An ex post facto design was used. The participants in this study were 129 students belonging to Educational Sciences and Psychology, out of 2400 who benefited from the innovation program. The results showed an increase in competences related to the attention to diversity, with the improvement of attitudes and knowledge about affective-sexual diversity after the application of the program. It is concluded that this type of innovation program, with quality training, contributes to the improvement of coexistence and the prevention of gender violence in university classrooms, eliminating stereotypes and negative attitudes towards diversity.
Analysis and Recognition of Human Lower Limb Motions Based on Electromyography (EMG) Signals
Authors: Wang Junyao , Dai Yuehong , Si Xiaxi
Published: October 2021

Background: This paper focuses on the characteristics of lower limb EMG signals for common movements. Methods: We obtained length data for lower limb muscles during gait motion using software named OpenSim; statistical product and service solutions (SPSS) were utilized to study the correlation between each muscle, based on gait data. Low-correlation muscles in different regions were selected; inertial measurement unit (IMU) and EMG sensors were used to measure the lower limb angles and EMG signals when on seven kinds of slope, in five kinds of gait (walking on flat ground, uphill, downhill, up-step and down-step) and four kinds of movement (squat, lunge, raised leg and standing up). Results: After data denoising and feature extraction, we designed a double hidden-layer BP neural network to recognize the above motions according to EMG signals. Results show that EMG signals of selected muscles have a certain periodicity in the process of movement that can be used to identify lower limb movements. Conclusions: It can be seen, after the recognition of different proportions of training and testing sets that the average recognition rate of the BP neural network is 86.49% for seven gradients, 93.76% for five kinds of gait and 86.07% for four kinds of movements.
Iterative Learning Sliding Mode Control for UAV Trajectory Tracking
Authors: Nguyen Lanh Van , Phung Manh Duong , Ha Quang Phuc
Published: October 2021

This paper presents a novel iterative learning sliding mode controller (ILSMC) that can be applied to the trajectory tracking of quadrotor unmanned aerial vehicles (UAVs) subject to model uncertainties and external disturbances. Here, the proposed ILSMC is integrated in the outer loop of a controlled system. The control development, conducted in the discrete-time domain, does not require a priori information of the disturbance bound as with conventional SMC techniques. It only involves an equivalent control term for the desired dynamics in the closed loop and an iterative learning term to drive the system state toward the sliding surface to maintain robust performance. By learning from previous iterations, the ILSMC can yield very accurate tracking performance when a sliding mode is induced without control chattering. The design is then applied to the attitude control of a 3DR Solo UAV with a built-in PID controller. The simulation results and experimental validation with real-time data demonstrate the advantages of the proposed control scheme over existing techniques.
Online Multiple Object Tracking Using a Novel Discriminative Module for Autonomous Driving
Authors: Chen Jia , Wang Fan , Li Chunjiang , Zhang Yingjie , Ai Yibo , Zhang Weidong
Published: October 2021

Multi object tracking (MOT) is a key research technology in the environment sensing system of automatic driving, which is very important to driving safety. Online multi object tracking needs to accurately extend the trajectory of multiple objects without using future frame information, so it will face greater challenges. Most of the existing online MOT methods are anchor-based detectors, which have many misdetections and missed detection problems, and have a poor effect on the trajectory extension of adjacent object objects when they are occluded and overlapped. In this paper, we propose a discrimination learning online tracker that can effectively solve the occlusion problem based on an anchor-free detector. This method uses the different weight characteristics of the object when the occlusion occurs and realizes the extension of the competition trajectory through the discrimination module to prevent the ID-switch problem. In the experimental part, we compared the algorithm with other trackers on two public benchmark datasets, MOT16 and MOT17, and proved that our algorithm has achieved state-of-the-art performance, and conducted a qualitative analysis on the convincing autonomous driving dataset KITTI.
Demand Forecasting of Online Car-Hailing with Combining LSTM + Attention Approaches
Authors: Ye Xiaofei , Ye Qiming , Yan Xingchen , Wang Tao , Chen Jun , Li Song
Published: October 2021

The accurate prediction of online car-hailing demand plays an increasingly important role in real-time scheduling and dynamic pricing. Most studies have found that the demand of online car-hailing is highly correlated with both temporal and spatial distributions of journeys. However, the importance of temporal and spatial sequences is not distinguished in the context of seeking to improve prediction, when in actual fact different time series and space sequences have different impacts on the distribution of demand and supply for online car-hailing. In order to accurately predict the short-term demand of online car-hailing in different regions of a city, a combined attention-based LSTM (LSTM + Attention) model for forecasting was constructed by extracting temporal features, spatial features, and weather features. Significantly, an attention mechanism is used to distinguish the time series and space sequences of order data. The order data in Haikou city was collected as the training and testing datasets. Compared with other forecasting models (GBDT, BPNN, RNN, and single LSTM), the results show that the short-term demand forecasting model LSTM + Attention outperforms other models. The results verify that the proposed model can support advanced scheduling and dynamic pricing for online car-hailing.
Short-Term Electricity Price Forecasting Based on BP Neural Network Optimized by SAPSO
Authors: Yi Min , Xie Wei , Mo Li
Published: October 2021

In the electricity market environment, the market clearing price has strong volatility, periodicity and randomness, which makes it more difficult to select the input features of artificial neural network forecasting. Although the traditional back propagation (BP) neural network has been applied early in electricity price forecasting, it has the problem of low forecasting accuracy. For this reason, this paper uses the maximum information coefficient and Pearson correlation analysis to determine the main factors affecting electricity price fluctuation as the input factors of the forecasting model. The improved particle swarm optimization algorithm, called simulated annealing particle swarm optimization (SAPSO), is used to optimize the BP neural network to establish the SAPSO-BP short-term electricity price forecasting model and the actual sample data are used to simulate and calculate. The results show that the SAPSO-BP price forecasting model has a high degree of fit and the average relative error and mean square error of the forecasting model are lower than those of the BP network model and PSO-BP model, as well as better than the PSO-BP model in terms of convergence speed and accuracy, which provides an effective method for improving the accuracy of short-term electricity price forecasting.
Experimental Fitting of Redesign Electrified Turbocompressor of a Novel Mild Hybrid Power Train for a City Car
Authors: Capata Roberto
Published: October 2021

As part of a project for the realization of a hybrid vehicle with an innovative power train system, the proposal presented is to disconnect the turbocharger group and study the different behavior of the compressor and turbine, so decoupled. In an actual turbocharger, when the power of the turbine exceeds that required by the compressor, the wastegate valve opens. In this way, a part of the flue gases does not evolve into a turbine and limits the power generated. In the solution proposed here (the paper considers only “compressor side”) all the flow rate of the flue gases is processed by the turbine. In this way, for each rpms of the IC engine, the turbine generates more power than that required by the compressor. This makes it possible to use this surplus of power for the auxiliaries and/or to recharge the battery pack of the considered hybrid vehicle. An additional advantage is, thanks to this surplus generated, that the battery pack can be smaller and can be recharged while driving. Therefore, the entire system operates as a “Range Extended”. As mentioned above, this work is focused on the direct compressor—innovative electric motor coupling will be sized and realized, and a subsequent series of experimental tests will confirm the feasibility of this phase of the project.
Numerical Simulation Based on the Canister Test for Shale Gas Content Calculation
Authors: Kang Shujuan , Lu Le , Tian Hui , Yang Yunfeng , Jiang Chengyang , Ma Qisheng
Published: October 2021

The accurate determination of the gas in place in shale reservoirs is a basic but challenging issue for shale gas evaluation. Conventional canister gas desorption tests on retrieved core samples and subsequent data analyses (via linear or polynomial regression)—originally developed for coalbed methane, where gases are mainly stored in the adsorbed phase—is unadvisable for shale gas, which is stored as an appreciable amount of free gas in shale reservoirs. In the present study, a mathematical model that simultaneously takes into account gas expansion, adsorption/desorption, and the gas flow in shale is proposed to simulate gas release from a core sample retrieved from the Lower Silurian Longmaxi Formation of the Fuling shale gas field, Sichuan Basin. The results indicate that, compared with the value of 2.11 m3/t rock estimated with the traditional United States Bureau of Mines (USBM) method, the total gas in place within the studied Longmaxi Shale estimated with our mathematical model under reservoir pressure conditions is up to 5.88 m3/t rock, which is more consistent with the result from the new volumetric approach based on Ambrose et al. According to our mathematical model, the content of free gas is 4.11 m3/t rock at true “time zero”, which accounts for 69.9% of the total gas. On the other hand, the lost gas portion is determined to be up to 4.88 m3/t rock (~85% of the total gas). These results suggest that the majority of the free shale gas is actually trapped within the pore space of the shale formation.
Hybrid Wind and Solar Photovoltaic Generation with Energy Storage Systems: A Systematic Literature Review and Contributions to Technical and Economic Regulations
Authors: de Doile Gabriel Nasser Doyle , Rotella Junior Paulo , Rocha Luiz Célio Souza , Bolis Ivan , Janda Karel , Coelho Junior Luiz Moreira
Published: October 2021

The operation of electrical systems is becoming more difficult due to the intermittent and seasonal characteristics of wind and solar energy. Such operational challenges can be minimized by the incorporation of energy storage systems, which play an important role in improving the stability and reliability of the grid. The economic viability of hybrid power plants with energy storage systems can be improved if regulations enable the remuneration of the various ancillary services that they can provide. Thus, the aim of this study is to provide a literature review regarding the economic feasibility of hybrid wind and solar photovoltaic generation with energy storage systems and its legal and regulatory aspects. Observing the global tendency, new studies should address the technical and economic feasibility of hybrid wind and solar photovoltaic generation in conjunction with, at least, one kind of energy storage system. In addition, it is very important to take into account the regulatory barriers and propose solutions to remove them. It was observed that although regulatory aspects can influence the economic feasibility of hybrid projects, little is known about this relationship among regulatory frameworks. The findings presented in this article are important not only for Brazil, but also for other countries that do not have regulations in force to support the use of energy storage systems in hybrid systems.
Prediction of Refracturing Timing of Horizontal Wells in Tight Oil Reservoirs Based on an Integrated Learning Algorithm
Authors: Zhang Xianmin , Ren Jiawei , Feng Qihong , Wang Xianjun , Wang Wei
Published: October 2021

Refracturing technology can effectively improve the EUR of horizontal wells in tight reservoirs, and the determination of refracturing time is the key to ensuring the effects of refracturing measures. In view of different types of tight oil reservoirs in the Songliao Basin, a library of 1896 sets of learning samples, with 11 geological and engineering parameters and corresponding refracturing times as characteristic variables, was constructed by combining numerical simulation with field statistics. After a performance comparison and analysis of an artificial neural network, support vector machine and XGBoost algorithm, the support vector machine and XGBoost algorithm were chosen as the base model and fused by the stacking method of integrated learning. Then, a prediction method of refracturing timing of tight oil horizontal wells was established on the basis of an ensemble learning algorithm. Through the prediction and analysis of the refracturing timing corresponding to 257 groups of test data, the prediction results were in good agreement with the real value, and the correlation coefficient R2 was 0.945. The established prediction method can quickly and accurately predict the refracturing time, and effectively guide refracturing practices in the tight oil test area of the Songliao basin.
Two-Phase Flow Effects on Seismic Wave Anelasticity in Anisotropic Poroelastic Media
Authors: Santos Juan , Carcione José , Ba Jing
Published: October 2021

We study the wave anelasticity (attenuation and velocity dispersion) of a periodic set of three flat porous layers saturated by two immiscible fluids. The fluids are very dissimilar in properties, namely gas, oil, and water, and, at most, three layers are required to study the problem from a general point of view. The sequence behaves as viscoelastic and transversely isotropic (VTI) at wavelengths much longer than the spatial period. Wave propagation causes fluid flow and slow P modes, inducing anelasticity. The fluids are characterized by capillary forces and relative permeabilities, which allow for the existence of two slow modes and the presence of dissipation, respectively. The methodology to study the physics is based on a finite-element uspcaling approach to compute the complex and frequency-dependent stiffnesses of the effective VTI medium. The results of the experiments indicate that there is higher dissipation and anisotropy compared to the widely used model based on an effective fluid that ignores the effects of surface tension (capillarity) and viscous flow interference between the two fluid phases.
Effect of Hard Coal Combustion in Water Steam Environment on Chemical Composition of Exhaust Gases
Authors: Ciupek Bartosz , Gołoś Karol , Jankowski Radosław , Nadolny Zbigniew
Published: October 2021

This academic paper revolves around the results of research on the change in emission parameters of the used heating boiler following the introduction of the overheated water stream, which had an impact on different emission parameters. The research results provide an insight into the hard coal combustion process, which had a significant impact on the change in the chemical composition of exhaust gases: it contributed to the lower mass concentration of the emitted dust and black carbon (PM) as well as nitric oxides (NOx) while, at the same time, playing a significant role in increasing the mass concentration of the emitted carbon oxide (CO). Two types of devices were used for the purposes of conducting the research at hand: a boiler with an automatic fuel feeding system with one combustion chamber and a boiler with a combustion chamber and an afterburning chamber fitted over it. Apart from the measurements of mass concentration of the emitted harmful substances, the research also focused on measurements of temperature inside the combustion and afterburning chambers, as well as the temperature of exhaust gases and their oxygen content. As part of the research, water steam was introduced to the combustion and afterburning chambers at the flow rate of 0.71 kg/h and 3.60 kg/h for boilers operating at a minimum power of 30% and a nominal power of 100%. An original steam generator with an overheated water steam production range from 0.71 kg/h to 3.60 kg/h was used to create and feed the water steam. The efficiency of the combustion process was calculated using the obtained results for each operating configuration of a given boiler.
Characteristics of Water Contaminants from Underground Coal Gasification (UCG) Process—Effect of Coal Properties and Gasification Pressure
Authors: Pankiewicz-Sperka Magdalena , Kapusta Krzysztof , Basa Wioleta , Stolecka Katarzyna
Published: October 2021

One of the most important issues during UCG process is wastewater production and treatment. Condensed gasification wastewater is contaminated by many hazardous compounds. The composition of the generated UCG-derived wastewater may vary depending on the type of gasified coal and conditions of the gasification process. The main purpose of this study was a qualitative and quantitative characterization of the UCG wastewater produced during four different UCG experiments. Experiments were conducted using semi-anthracite and bituminous coal samples at two distinct pressures, i.e., 20 and 40 bar. The conducted studies revealed significant relationships between the physicochemical composition of the wastewater and the coal properties as well as the gasification pressure. The strongest impact is noticeable in the case of organic pollutants, especially phenols, BTEX and PAH’s. The most abundant group of pollutants were phenols. Conducted studies showed significantly higher concentration levels for bituminous coal: 29.25–49.5 mg/L whereas for semi-anthracite effluents these concentrations were in much lower range 2.1–29.7 mg/L. The opposite situation occurs for BTEX, higher concentrations were in wastewater from semi-anthracite gasification: 5483.1–1496.7 µg/L, while in samples from bituminous coal gasification average BTEX concentrations were: 2514.3–1354.4 µg/L. A similar relationship occurs for the PAH’s concentrations. The higher values were in case of wastewater from semi-anthracite coal experiments and were in range 362–1658 µg/L while from bituminous coal gasification PAH’s values are in lower ranges 407–1090 µg/L. The studies conducted have shown that concentrations of phenols, BTEX and PAH’s decrease with increasing pressure. Pearson’s correlation analysis was performed to enhance the interpretation of the obtained experimental data and showed a very strong relationship between three parameters: phenols, volatile phenols and CODcr.
Analysis of Interrelationships between Markets of Fuels in the Visegrad Group Countries from 2016 to 2020
Authors: Górska Anna , Krawiec Monika
Published: October 2021

A fuel market is an important sector of the economy and fuel prices influence the prices of numerous products and services. This paper focuses on the analysis of the interrelationships between markets of fuels in the Visegrad Group (V4) countries. The research is based on weekly prices of Pb95 gasoline and diesel in the Czech Republic, Hungary, Poland, and Slovakia observed from January 2016 through December 2020. After performing the preliminary statistical analysis, the long-term relationships between the prices of fuels are investigated through application of the cointegrated regression Durbin–Watson (CRDW) test. Next, Granger causality is tested to answer the question of whether changes in prices of fuels in separate V4 countries Granger-cause changes in prices of fuels in other V4 countries. The cointegration research uses logarithmic prices, whereas causality investigation is based on their first differences. The results reveal long-term relationships between the prices of Pb95 gasoline in the Czech Republic and prices in other V4 countries as well as Granger causality flowing from diesel price changes in Poland to diesel price changes in other V4 countries and bilateral causation between changes in the prices of Pb95 gasoline in Poland, Hungary and Slovakia.
Integrated Uncertainty/Disturbance Suppression Based on Improved Adaptive Sliding Mode Controller for PMSM Drives
Authors: Huang Mingfei , Deng Yongting , Li Hongwen , Shao Meng , Liu Jing
Published: October 2021

Permanent magnet synchronous motors (PMSMs) have attracted great attention in the field of electric drive system. However, the disturbances caused by parameter mismatching, model uncertainty, external load and torque ripple seriously weaken the control accuracy. The traditional adaptive sliding mode control (ASMC) methodology can address slow-varying uncertainties/disturbances whose frequencies are located at the bandwidth of the filter used to design the adaptive law well; however, it has been barely discussed with respect to the periodic situation. In this paper, we extend the ASMC arrangement to periodic case to suppress the torque ripple by using a series-structure resonant controller. Firstly, a typical SMC is designed to force the tracking error of speed to converge to zero and obtain a certain capacity to disturbance. Then, the improved adaptive law is incorporated to estimate the lumped disturbance and torque ripple. The improved adaptive law is enhanced by embedding the resonant controller, which can obtain a better estimating result for torque ripple with repetitive feature. Finally, simulation and experimental results with PI, SMC and proposed methods are compared to verify the effectiveness of the developed controller.
Denoising of Heavily Contaminated Partial Discharge Signals in High-Voltage Cables Using Maximal Overlap Discrete Wavelet Transform
Authors: Shams Mohammed A. , Anis Hussein I. , El-Shahat Mohammed
Published: October 2021

Online detection of partial discharges (PD) is imperative for condition monitoring of high voltage equipment as well as power cables. However, heavily contaminated sites often burden the signals with various types of noise that can be challenging to remove (denoise). This paper proposes an algorithm based on the maximal overlap discrete wavelet transform (MODWT) to denoise PD signals originating from defects in power cables contaminated with various levels of noises. The three most common noise types, namely, Gaussian white noise (GWN), discrete spectral interference (DSI), and stochastic pulse shaped interference (SPI) are considered. The algorithm is applied to an experimentally acquired void-produced partial discharge in a power cable. The MODWT-based algorithm achieved a good improvement in the signal-to-noise ratio (SNR) and in the normalized correlation coefficient (NCC) for the three types of noises. The MODWT-based algorithm performance was also compared to that of the empirical Bayesian wavelet transform (EBWT) algorithm, in which the former showed superior results in denoising SPI and DSI, as well as comparable results in denoising GWN. Finally, the algorithm performance was tested on a PD signal contaminated with the three type of noises simultaneously in which the results were also superior.
Combustion of Fuel Surrogates: An Application to Gas Turbine Engines
Authors: Al Qubeissi Mansour , Al-Esawi Nawar , Soyhan Hakan Serhad
Published: October 2021

The previously developed approaches for fuel droplet heating and evaporation processes, mainly using the Discrete Multi Component Model (DMCM), are investigated for the aerodynamic combustion simulation. The models have been recently improved and generalised for a broad range of bio-fossil fuel blends so that the application areas are broadened with an increased accuracy. The main distinctive features of these models are that they consider the impacts of species’ thermal conductivities and diffusivities within the droplets in order to account for the temperature gradient, transient diffusion of species and recirculation. A formulation of fuel surrogates is made using the recently introduced model, referred to as “Complex Fuel Surrogate Model (CFSM)”, and analysing their heating, evaporation and combustion characteristics. The CFSM is aimed to reduce the full composition of fuel to a much smaller number of components based on their mass fractions, and to formulate fuel surrogates. Such an approach has provided a proof of concept with the implementation of the developed model into a commercial CFD code ANSYS Fluent. A case study is made for the CFD modelling of a gas turbine engine using a kerosene fuel surrogate, which is the first of its kind. The surrogate is proposed using the CFSM, with the aim to reduce the computational time and improve the simulation accuracy of the CFD model.