bluuebunny/crossref_metadata_2025 huggingface dataset:
Serum Peptide Immunoglobulin G Autoantibody Response in Patients with Different Central Nervous System Inflammatory Demyelinating Disorders
Authors: Lee Hye Lim , Park Jin-Woo , Seok Jin Myoung , Jeon Mi Young , Kim Hojin , Lim Young-Min , Shin Ha Young , Kang Sa-Yoon , Kwon Oh-Hyun , Lee Sang-Soo , Seok Hung Youl , Min Ju-Hong , Lee Sung-Hyun , Kim Byung-Jo , Kim Byoung Joon
Published: July 2021

Previous efforts to discover new surrogate markers for the central nervous system (CNS) inflammatory demyelinating disorders have shown inconsistent results; moreover, supporting evidence is scarce. The present study investigated the IgG autoantibody responses to various viral and autoantibodies-related peptides proposed to be related to CNS inflammatory demyelinating disorders using the peptide microarray method. We customized a peptide microarray containing more than 2440 immobilized peptides representing human and viral autoantigens. Using this, we tested the sera of patients with neuromyelitis optica spectrum disorders (NMOSD seropositive, n = 6; NMOSD seronegative, n = 5), multiple sclerosis (MS, n = 5), and myelin-oligodendrocyte glycoprotein antibody-associated disease (MOGAD, n = 6), as well as healthy controls (HC, n = 5) and compared various peptide immunoglobulin G (IgG) responses between the groups. Among the statistically significant peptides based on the pairwise comparisons of IgG responses in each disease group to HC, cytomegalovirus (CMV)-related peptides were most clearly distinguishable among the study groups. In particular, the most significant differences in IgG response were observed for HC vs. MS and HC vs. seronegative NMOSD (p = 0.064). Relatively higher IgG responses to CMV-related peptides were observed in patients with MS and NMOSD based on analysis of the customized peptide microarray.
Unraveling the Wide Spectrum of Melanoma Biomarkers
Authors: Revythis Antonios , Shah Sidrah , Kutka Mikolaj , Moschetta Michele , Ozturk Mehmet Akif , Pappas-Gogos George , Ioannidou Evangelia , Sheriff Matin , Rassy Elie , Boussios Stergios
Published: July 2021

The use of biomarkers in medicine has become essential in clinical practice in order to help with diagnosis, prognostication and prediction of treatment response. Since Alexander Breslow’s original report on “melanoma and prognostic values of thickness”, providing the first biomarker for melanoma, many promising new biomarkers have followed. These include serum markers, such as lactate dehydrogenase and S100 calcium-binding protein B. However, as our understanding of the DNA mutational profile progresses, new gene targets and proteins have been identified. These include point mutations, such as mutations of the BRAF gene and tumour suppressor gene tP53. At present, only a small number of the available biomarkers are being utilised, but this may soon change as more studies are published. The aim of this article is to provide a comprehensive review of melanoma biomarkers and their utility for current and, potentially, future clinical practice.
Entropy as an Objective Function of Optimization Multimodal Transportations
Authors: Bazaluk Oleg , Kotenko Sergiy , Nitsenko Vitalii
Published: July 2021

This article considers the use of the entropy method in the optimization and forecasting of multimodal transport under conditions of risks that can be determined simultaneously by deterministic, stochastic and fuzzy quantities. This will allow to change the route of transportation in real time in an optimal way with an unacceptable increase in the risk at one of its next stages and predict the redistribution of the load of transport nodes. The aim of this study is to develop a mathematical model for the optimal choice of an alternative route, the best for one or more objective functions in real time. In addition, it is proposed to use this mathematical model to estimate the dynamic change in turnover through intermediate transport nodes, forecasting their loading over time under different conditions that also include long-term risks which are significant in magnitude. To substantiate the feasibility of the proposed mathematical model, the analysis and forecast of cargo turnover through the seaports of Ukraine are presented, taking into account and analysing the existing risks.
The Entropy Gain of Linear Systems and Some of Its Implications
Authors: Derpich Milan S. , Müller Matias , Østergaard Jan
Published: July 2021

We study the increase in per-sample differential entropy rate of random sequences and processes after being passed through a non minimum-phase (NMP) discrete-time, linear time-invariant (LTI) filter G. For LTI discrete-time filters and random processes, it has long been established by Theorem 14 in Shannon’s seminal paper that this entropy gain, G(G), equals the integral of log|G(ejω)|. In this note, we first show that Shannon’s Theorem 14 does not hold in general. Then, we prove that, when comparing the input differential entropy to that of the entire (longer) output of G, the entropy gain equals G(G). We show that the entropy gain between equal-length input and output sequences is upper bounded by G(G) and arises if and only if there exists an output additive disturbance with finite differential entropy (no matter how small) or a random initial state. Unlike what happens with linear maps, the entropy gain in this case depends on the distribution of all the signals involved. We illustrate some of the consequences of these results by presenting their implications in three different problems. Specifically: conditions for equality in an information inequality of importance in networked control problems; extending to a much broader class of sources the existing results on the rate-distortion function for non-stationary Gaussian sources, and an observation on the capacity of auto-regressive Gaussian channels with feedback.
Exergy-Based Multi-Objective Optimization of an Organic Rankine Cycle with a Zeotropic Mixture
Authors: Fergani Zineb , Morosuk Tatiana , Touil Djamel
Published: July 2021

In this paper, the performance of an organic Rankine cycle with a zeotropic mixture as a working fluid was evaluated using exergy-based methods: exergy, exergoeconomic, and exergoenvironmental analyses. The effect of system operation parameters and mixtures on the organic Rankine cycle’s performance was evaluated as well. The considered performances were the following: exergy efficiency, specific cost, and specific environmental effect of the net power generation. A multi-objective optimization approach was applied for parametric optimization. The approach was based on the particle swarm algorithm to find a set of Pareto optimal solutions. One final optimal solution was selected using a decision-making method. The optimization results indicated that the zeotropic mixture of cyclohexane/toluene had a higher thermodynamic and economic performance, while the benzene/toluene zeotropic mixture had the highest environmental performance. Finally, a comparative analysis of zeotropic mixtures and pure fluids was conducted. The organic Rankine cycle with the mixtures as working fluids showed significant improvement in energetic, economic, and environmental performances.
Photonic Reservoir Computer with Output Expansion for Unsupervized Parameter Drift Compensation
Authors: Pauwels Jaël , Van der Sande Guy , Verschaffelt Guy , Massar Serge
Published: July 2021

We present a method to improve the performance of a reservoir computer by keeping the reservoir fixed and increasing the number of output neurons. The additional neurons are nonlinear functions, typically chosen randomly, of the reservoir neurons. We demonstrate the interest of this expanded output layer on an experimental opto-electronic system subject to slow parameter drift which results in loss of performance. We can partially recover the lost performance by using the output layer expansion. The proposed scheme allows for a trade-off between performance gains and system complexity.
Agency Contracts under Maximum-Entropy
Authors: Gutiérrez Oscar , Salas-Fumás Vicente
Published: July 2021

This article proposes the application of the maximum-entropy principle (MEP) to agency contracting (where a principal hires an agent to make decisions on their behalf) in situations where the principal and agent only have partial knowledge on the probability distribution of the output conditioned on the agent’s actions. The paper characterizes the second-best agency contract from a maximum entropy distribution (MED) obtained from applying the MEP to the agency situation consistently with the information available. We show that, with the minimum shared information about the output distribution for the agency relationship to take place, the second-best compensation contract is (a monotone transformation of) an increasing affine function of output. With additional information on the output distribution, the second-best optimal contracts can be more complex. The second-best contracts obtained theoretically from the MEP cover many compensation schemes observed in real agency relationships.
Local Analysis of Heterogeneous Intracellular Transport: Slow and Fast Moving Endosomes
Authors: Korabel Nickolay , Han Daniel , Taloni Alessandro , Pagnini Gianni , Fedotov Sergei , Allan Viki , Waigh Thomas Andrew
Published: July 2021

Trajectories of endosomes inside living eukaryotic cells are highly heterogeneous in space and time and diffuse anomalously due to a combination of viscoelasticity, caging, aggregation and active transport. Some of the trajectories display switching between persistent and anti-persistent motion, while others jiggle around in one position for the whole measurement time. By splitting the ensemble of endosome trajectories into slow moving subdiffusive and fast moving superdiffusive endosomes, we analyzed them separately. The mean squared displacements and velocity auto-correlation functions confirm the effectiveness of the splitting methods. Applying the local analysis, we show that both ensembles are characterized by a spectrum of local anomalous exponents and local generalized diffusion coefficients. Slow and fast endosomes have exponential distributions of local anomalous exponents and power law distributions of generalized diffusion coefficients. This suggests that heterogeneous fractional Brownian motion is an appropriate model for both fast and slow moving endosomes. This article is part of a Special Issue entitled: “Recent Advances In Single-Particle Tracking: Experiment and Analysis” edited by Janusz Szwabiński and Aleksander Weron.
How to Measure a Two-Sided Market
Authors: Zheng Wen , Yao Xiaoming
Published: July 2021

Applying the theories of complex network and entropy measurement to the market, the two-sided market structure is analyzed in constructing the O2O platform transaction on the entropy measurement of the nodes and links. Market structure entropy (MSE) is initially introduced to measure the consistency degree of the individuals and the groups in the O2O market, according to the interaction in the profits, the time/space, and the information relationship. Considering that the market structure entropies are changing upward or downward, MSE is used to judge the consistency degree between the individuals and the groups. Respectively, considering the scale, the cost and the value dimensions, MSE is expanded to explain the market quality entropy, the market time-effect entropy, and the market capacity entropy.MSE provides a methodology in studying the O2O platform transaction and gives the quantitative index in the evaluation of the O2O market state.
Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
Authors: Choo Yeon-Moon , Kim Ji-Min , An Ik-Tae
Published: July 2021

Since the 1960s, many rivers have been destroyed as a consequence of the process of rapid urbanization. As accurate figures are important to repair rivers, there have been many research reports on methods to obtain the exact river slope and elevation. Until now, many research efforts have analyzed the river using measured river topographic factors, but when the flow velocity changes rapidly, such as during a flood, surveying is not easy; and due to cost, frequent measurements are difficult. Previous research has focused on the cross section of the river, so the information on the river longitudinal profile is insufficient. In this research, using informational entropy theory, equations are presented that can calculate the average river slope, river slope, and river longitudinal elevation for a river basin in real time. The applicability was analyzed through a comparison with the measured data of river characteristic factors obtained from the river plan. The parameters were calculated using informational entropy theory and nonlinear regression analysis using actual data, and then the longitudinal elevation entropy equation for each river and the average river slope were calculated. As a result of analyzing the applicability of the equations presented in this study by R2 and Root Mean Square Error, all R2 values were over 0.80, while RMSE values were analyzed to be between 0.54 and 2.79. Valid results can be obtained by calculating river characteristic factors.
Children’s Right to Belong?—The Psychosocial Impact of Pedagogy and Peer Interaction on Minority Ethnic Children’s Negotiation of Academic and Social Identities in School
Authors: McGillicuddy Deirdre , Machowska-Kosciak Malgosia
Published: July 2021

Migration across the OECD this decade is reflected in increasingly diverse societies. Although migration into Ireland remains relatively low, increasing pupil diversity is evident in the physical, pedagogical, curricular, and socio-relational aspects of schooling. While the intensity of such changes are evident in teacher pedagogy, children’s social worlds, and classroom/school dynamics, most notable is the lack of policy development to support school practices. Drawing on two in-depth case studies, this paper aims to foreground minority ethnic children/young people’s voice(s) as they negotiate the complexity of identity (re)formation and belonging in school. It explores whether mis/recognition impacts teacher pedagogical practices through ability grouping, and minority ethnic children’s navigation of social spaces within/between the classroom. Using a children’s rights lens, this paper interrogates whether minority ethnic children’s right to education preparing them “for responsible life in a free society, in the spirit of understanding, peace (and) tolerance” (Article 29 (1), UNCRC, 1989) is being realised. Findings indicate the need to foreground minority ethnic children’s voices and rights to ensure how they “do”/”feel” learning is in their best interests and affords them equal opportunities in their school lives.
Digital Competence Analysis of University Students Using Latent Classes
Authors: Burgos-Videla Carmen Gloria , Castillo Rojas Wilson Andrés , López Meneses Eloy , Martínez Javiera
Published: July 2021

The objective of this study is to characterize Latent Classes emerging from the analysis of the level of digital competences, use and consumption of applications and/or services through the Internet. For this purpose, the results of the survey Basic Digital Competences (Competencias Básicas Digitales-COBADI®) applied to university students, with more than 60 categorical variables, were considered. A total of 4762 undergraduate and graduate students from five Spanish universities participated in this survey: Complutense University of Madrid (UCM), Pablo de Olavide University (UPO), Almeria University (UAL), National University of Distance Education (UNED) and Rey Juan Carlos University (URJC). The application of the questionnaire was done through the Internet, from the Institute for Research in Social Sciences and Education of University of Atacama—Chile. The methodology used is mixed, because the questions of the questionnaire provide qualitative information that can be interpreted and elaborated from the results. It is also quantitative because basic statistical techniques are used for the exploratory analysis of the data, and later Latent Class Analysis (LCA), to complement the description of the data set and the variables considered in the study, thus allowing us to group the classes of variables that do not appear explicitly in the set of observed variables, but which nevertheless affect them. The results of the study show that regardless of the gender and age range of the participants, there are four clearly differentiated groups or classes in the use and consumption of ICTs in different ways for their activities, both personal and academic, which allows for identifying different developments of digital competences. This study allows establishing a baseline in order to be able to elaborate later, in the development of the digital competences currently needed, which should be developed by university students.
Method for Dynamic Service Orchestration in Fog Computing
Authors: Morkevicius Nerijus , Venčkauskas Algimantas , Šatkauskas Nerijus , Toldinas Jevgenijus
Published: July 2021

Fog computing is meant to deal with the problems which cloud computing cannot solve alone. As the fog is closer to a user, it can improve some very important QoS characteristics, such as a latency and availability. One of the challenges in the fog architecture is heterogeneous constrained devices and the dynamic nature of the end devices, which requires a dynamic service orchestration to provide an efficient service placement inside the fog nodes. An optimization method is needed to ensure the required level of QoS while requiring minimal resources from fog and end devices, thus ensuring the longest lifecycle of the whole IoT system. A two-stage multi-objective optimization method to find the best placement of services among available fog nodes is presented in this paper. A Pareto set of non-dominated possible service distributions is found using the integer multi-objective particle swarm optimization method. Then, the analytical hierarchy process is used to choose the best service distribution according to the application-specific judgment matrix. An illustrative scenario with experimental results is presented to demonstrate characteristics of the proposed method.
RG Hyperparameter Optimization Approach for Improved Indirect Prediction of Blood Glucose Levels by Boosting Ensemble Learning
Authors: Wang Yufei , Zhang Haiyang , An Yongli , Ji Zhanlin , Ganchev Ivan
Published: July 2021

This paper proposes an RG hyperparameter optimization approach, based on a sequential use of random search (R) and grid search (G), for improving the blood glucose level prediction of boosting ensemble learning models. An indirect prediction of blood glucose levels in patients is performed, based on historical medical data collected by means of physical examination methods, using 40 human body’s health indicators. The conducted experiments with real clinical data proved that the proposed RG double optimization approach helps improve the prediction performance of four state-of-the-art boosting ensemble learning models enriched by it, achieving 1.47% to 24.40% MSE improvement and 0.75% to 11.54% RMSE improvement.
Securing IoT Devices: A Robust and Efficient Deep Learning with a Mixed Batch Adversarial Generation Process for CAPTCHA Security Verification
Authors: Dankwa Stephen , Yang Lu
Published: July 2021

The Internet of Things environment (e.g., smart phones, smart televisions, and smart watches) ensures that the end user experience is easy, by connecting lives on web services via the internet. Integrating Internet of Things devices poses ethical risks related to data security, privacy, reliability and management, data mining, and knowledge exchange. An adversarial machine learning attack is a good practice to adopt, to strengthen the security of text-based CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), to withstand against malicious attacks from computer hackers, to protect Internet of Things devices and the end user’s privacy. The goal of this current study is to perform security vulnerability verification on adversarial text-based CAPTCHA, based on attacker–defender scenarios. Therefore, this study proposed computation-efficient deep learning with a mixed batch adversarial generation process model, which attempted to break the transferability attack, and mitigate the problem of catastrophic forgetting in the context of adversarial attack defense. After performing K-fold cross-validation, experimental results showed that the proposed defense model achieved mean accuracies in the range of 82–84% among three gradient-based adversarial attack datasets.
The Bright and Dark Sides of Energy Efficiency Obligation Scheme: The Case of Latvia
Authors: Blumberga Andra , Āzis Reinis , Reinbergs Dāvis , Pakere Ieva , Blumberga Dagnija
Published: July 2021

Evidence collected by researchers over several decades suggests that the successful implementation of the Energy Efficiency Obligation Scheme (EEOS) may deliver significant, cost-effective energy savings over many years. However, before starting EEOS in Latvia, predictions by energy efficiency policy researchers envisaged that it is at high risk of savings shortfalls. This study aims to carry out an ex-post policy evaluation of EEOS in Latvia and assess its ability to deliver significant savings in the first phase of the new EEOS. This paper questions whether the new EEOS can reach savings goals without prior experience with voluntary agreement schemes and emulation of successful EEOS from other countries. The second goal of the research is to create a web-based optimization tool as an Interactive Learning Environment to help policymakers and EEOS-obliged parties to create goal-oriented strategies. The study has found that, contrary to expectations, Latvia has reached and even overfulfilled EEOS saving goals. Estimated cumulative savings obtained during the starting phase (329.2 GWh) are 68% higher than the cumulative savings planned by the policymakers for 2020 (234 GWh). This success is related to the enforcement of a stick-type approach in the policy. However, the study also revealed the dark side of EEOS implementation by discussing different types of energy efficiency measures applied by EEOS and the role of implementing and monitoring institutions. The ex-ante evaluation projected that 50% of the EEOS savings would be derived from information and education measures and 50% through contributions to the Energy Efficiency Fund or by implementing the most cost-effective energy efficiency measures. The ex-post evaluation shows that around 95% of savings are achieved through information measures and the rest by introducing energy efficiency measures on the consumer side. EEOS parties do not contribute to the Fund because the cost of information measures (on average 4 EUR/MWh) is significantly lower than the contribution to the Fund (70 EUR/MWh).
Advanced Manufacturing in Civil Engineering
Authors: Guimarães Ana S. , Delgado João M. P. Q. , Lucas Sandra S.
Published: July 2021

The main goal of this work is the analysis of potential energy and green benefits of 3D printing on building construction. Current literature reports a considerable number of benefits for 3D printing, namely, reduction of material use, lower operational costs and time-saving. The authors also mention design freedom, higher efficiency, productivity and quality. This work presents the latest developments in 3D printing in civil engineering, namely, a review of the last 3D printing projects and the limitations of construction 3D printing with a focus on large-scale applications, technology costs, mix development and optimisation and thermal behaviour.
Modeling of Persistence, Non-Acceptance and Sufficiency in Long-Term Energy Scenarios for Germany
Authors: Kost Christoph , Brandes Julian , Senkpiel Charlotte , Sterchele Philip , Wrede Daniel , Henning Hans-Martin
Published: July 2021

Long-term transition pathways to a low-carbon energy system are analysed by applying the energy system model REMod. All in all, the paper contributes to the current research through an innovative scenario approach, using assumptions for societal trends and quantitative results for scenarios, analysing the paths towards climate neutrality and defossilization in 2050. In the case study of Germany, these trends and drivers influence the results and the technology composition in each consumption sector (buildings, transport, and industry). Across all scenarios, it can be observed that the electrification of all sectors is important for the defossilization of the energy system, as the direct use of electricity from renewable energy is more efficient than the consumption of carbon-neutral synthetic energy carriers. However, different consumer behavior (e.g., non-acceptance or resistance against specific technologies) influences not only the efficient use of (green) electricity, it also changes the optimal pathways of the transition to paths with greater efforts. One potential societal trend—sufficiency—could be an important cornerstone for reaching the targets, as the required expansion and exchange of technologies are lower and thus facilitate the transition.
Modelling Yawed Wind Turbine Wakes: Extension of a Gaussian-Based Wake Model
Authors: Wei De-Zhi , Wang Ni-Na , Wan De-Cheng
Published: July 2021

Yaw-based wake steering control is a potential way to improve wind plant overall performance. For its engineering application, it is crucial to accurately predict the turbine wakes under various yawed conditions within a short time. In this work, a two-dimensional analytical model is proposed for far wake modeling under yawed conditions by taking the self-similarity assumption for the streamwise velocity deficit and skewness angle at hub height. The proposed model can be applied to predict the wake center trajectory, streamwise velocity, and transverse velocity in the far-wake region downstream of a yawed turbine. For validation purposes, predictions by the newly proposed model are compared to wind tunnel measurements and large-eddy simulation data. The results show that the proposed model has significantly high accuracy and outperforms other common wake models. More importantly, the equations of the new proposed model are simple, the wake growth rate is the only parameter to be specified, which makes the model easy to be used in practice.
Dynamic Cost-Optimal Assessment of Complementary Diurnal Electricity Storage Capacity in High PV Penetration Grid
Authors: Dumlao Samuel , Ishihara Keiichi
Published: July 2021

Solar Photovoltaics (PV) is seen as one of the renewable energy technologies that could help reduce the world’s dependence on fossil fuels. However, since it is dependent on the sun, it can only generate electricity in the daytime, and this restriction is exacerbated in electricity grids with high PV penetration, where solar energy must be curtailed due to the mismatch between supply and demand. This study conducts a techno-economic analysis to present the cost-optimal storage growth trajectory that could support the dynamic integration of solar PV within a planning horizon. A methodology for cost-optimal assessment that incorporates hourly simulation, Monte Carlo random sampling, and a proposed financial assessment is presented. This approach was tested in Japan’s southernmost region since it is continuously increasing its solar capacity and is at the precipice of high PV curtailment scenario. The results show the existence of a cost-optimal storage capacity growth trajectory that balances the cost penalty from curtailment and the additional investment cost from storage. This optimal trajectory reduces the impact of curtailment on the energy generation cost to manageable levels and utilizes more solar energy potential that further reduces CO2 emissions. The results also show that the solar capacity growth rate and storage cost significantly impact the optimal trajectory. The incorporation of the Monte Carlo method significantly reduced the computational requirement of the analysis enabling the exploration of several growth trajectories, and the proposed financial assessment enabled the time-bound optimization of these trajectories. The approach could be used to calculate the optimal growth trajectories in other nations or regions, provided that historical hourly temperature, irradiance, and demand data are available.
Influence of Valorization of Sewage Sludge on Energy Consumption in the Drying Process
Authors: Siedlecka Ewa , Siedlecki Jarosław
Published: July 2021

Valorization of digested sewage sludge generated in a medium-sized sewage treatment plant and the effect of valorization on energy consumption during sludge drying used for energy recovery are presented. Anaerobic digestion of sewage sludge reduces dry matter content compared to raw sludge. This lowers its calorific value leading to the lower interest of consumers in using it as fuel. The aim of the study was to valorize digested sewage sludge prior to drying with high-energy waste with low moisture content. The procedure led to the reduction in moisture content by about 50% in the substrate supplied for solidification and drying. The calorific value of digested sewage sludge increased by 50–80%, and the energy consumption of the drying process decreased by about 50%. Physical and chemical properties of sewage sludge and moisture content of substrates and mixtures after valorization were determined. The heat of combustion of valorized sewage sludge mixtures, their elemental composition, and ash content is investigated. Their calorific value in the analytical and working states of 10% H2O was calculated. The highest calorific value was obtained for the mixture of sewage sludge valorized with waste plastics or combined with wood dust, averaging 23 MJ/kg. A mathematical approximation of sewage sludge valorization is presented.
Assessing the Risk in Urban Public Transport for Epidemiologic Factors
Authors: Budzynski Marcin , Luczkiewicz Aneta , Szmaglinski Jacek
Published: July 2021

Pandemics have presented new challenges for public transport organisers and operators. New diseases (e.g., influenza H1N1, severe acute respiratory syndrome—SARS, as well as, more recently, SARS-CoV-2) increase the need for new protection measures to prevent epidemic outbreaks in public transport infrastructure. The authors’ goal is to present a set of actions in the area of public transport that are adjusted to different levels of epidemic development. The goal goes back to the following question: how can the highest possible level of passenger safety be ensured and the losses suffered by urban public transport companies kept as low as possible? The sets of pro-active measures for selected epidemic scenarios presented in the article may offer support to local authorities and public transport operators. In the next steps, it is important to develop and implement tools for public transport management to ensure safety and tackle epidemic hazards.
The Application of Silica-Based Aerogel Board on the Fire Resistance and Thermal Insulation Performance Enhancement of Existing External Wall System Retrofit
Authors: Liu Kuang-Sheng , Zheng Xiao-Feng , Hsieh Chia-Hsing , Lee Shin-Ku
Published: July 2021

Due to the need of good thermal performance, external wall insulation (EWI) is usually made of materials that are not fire resistant and sometimes flammable. That restricts its application to a particular circumstance such as limited building height. Hence, a material with good thermal insulation and fire resistance performance would allow EWI to be more widely applied. This paper introduces a novel material: a silica-based aerogel porous board, which differs itself from mainstream products available in the market because of its outstanding properties, such as low density, high surface area, low thermal conductivity and superhydrophobicity. Herein, its thermal insulation and fire-resistant performance were tested and compared with commercial products. The cone calorimeter analysis results indicated that the aerogel porous board could improve the fire resistance performance. Moreover, the evaluation of thermal insulation performance suggested that the application of an aerogel porous board on the external stone wall of existing buildings can decrease the U-value by 60%. Through the detailed insight into the case-study, it is quite clear that the carbon impact of building stock could be greatly reduced by means of a coherent set of building envelope retrofitting actions based on this innovative heat insulation material, without compromising the fire safety.
Determinants of Investments in Energy Sector in Poland
Authors: Lisowski Robert , Woźniak Maciej , Jastrzębski Paweł , Karafolas Simeon , Matejun Marek
Published: July 2021

There is much research about the determinants of investments, but there is a shortage of similar studies for Poland. Therefore, the overall goal of the paper is to analyze the determinants of investments made by enterprises from the energy sector as well as their delays in Poland in the years 2000–2019. In this period, a strong growth of investments in energy was observed in the country. In connection to this, the authors set four hypotheses and verified them with the following statistical methods: canonical analysis, linear and causality correlation, autocorrelation and cointegration tests. The paper found that there is a relationship between public consumption and investment spending of small enterprises in Poland. That means that only some macroeconomic parameters are connected with investments. Moreover, the changes in the value of past investments has a negative influence in current investments.
Invert Drilling Fluids with High Internal Phase Content
Authors: Błaż Sławomir , Zima Grzegorz , Jasiński Bartłomiej , Kremieniewski Marcin
Published: July 2021

One of the most important tasks when drilling a borehole is to select the appropriate type of drilling fluid and adjust its properties to the borehole’s conditions. This ensures the safe and effective exploitation of the borehole. Many types of drilling fluids are used to drill holes for crude oil and natural gas. Most often, mainly due to cost and environmental constraints, water-based muds are used. On the other hand, invert drilling fluids are used for drilling holes in difficult geological conditions. The ratio of the oil phase to the water phase in invert drilling fluids the most common ratio being from 70/30 to 90/10. One of the disadvantages of invert drilling fluids is their cost (due to the oil content) and environmental problems related to waste and the management of oily cuttings. This article presents tests of invert drilling fluids with Oil-Water Ratio (OWR) 50/50 to 20/80 which can be used for drilling HPHT wells. The invert drilling fluids properties were examined and their resistance to temperature and pressure was assessed. Their effect on the permeability of reservoir rocks was also determined. The developed invert drilling fluids are characterized by high electrical stability ES above 300 V, and stable rheological parameters and low filtration. Due to the reduced content of the oil, the developed drilling fluid system is more economical and has limited toxicity.
Optimal Cloud Orchestration Model of Containerized Task Scheduling Strategy Using Integer Linear Programming: Case Studies of IoTcloudServe@TEIN Project
Authors: Swatthong Nawat , Aswakul Chaodit
Published: July 2021

As a playground for cloud computing and IoT networking environment, IoTcloudServe@TEIN has been established in the Trans-Eurasia Information Network (TEIN). In the IoTcloudServe@TEIN platform, a cloud orchestration for conducting the flow of IoT task demands is imperative for effectively improving performance. In this paper, we propose the model of optimal containerized task scheduling in cloud orchestration that maximizes the average payoff from completing tasks within the whole cloud system with different levels of cloud hierarchies. Based on integer linear programming, the model can take into account demand requirement and resource availability in terms of storage, computation, network, and splittable task granularity. To show the insights obtainable from the proposed model, the edge-core cluster of IoTcloudServe@TEIN and its peer-to-peer federated cloud scenario with OF@TEIN+ are numerically experimented and herein reported. To evaluate the model’s performance, payoff level and task completion time are considered by comparing with a well-known round-robin scheduling algorithm. The proposed ILP model can be a guideline for the cloud orchestration in IoTcloudserve@TEIN because of the lower task completion time and the higher payoff level especially upon the large demand growth, which is the major operation range of concerns in practice. Moreover, the proposed model illustrates mathematically the significance of implementing cloud architecture with refined splittable task granularity via the light-weighted container technology that has been used as the basis for IoTcloudServe@TEIN clustering design.
Numerical Simulations with RELAP5-3D and RELAP5/mod3.3 of the Second Experimental Campaign on In-Box LOCA Transients for HCLL TBS
Authors: Venturini Alessandro , Utili Marco , Forgione Nicola
Published: July 2021

In-box LOCA was identified as one of the worst accidental scenarios for the HCLL TBS (Helium Cooled Lithium-Lead Test Blanket System). Aiming to experimentally analyze the consequences of this transient, ENEA designed and built THALLIUM (Test HAmmer in Lead LIthiUM), a facility that reproduces the LiPb loop of the HCLL TBS. Two experimental campaigns were carried out by simulating the rupture of a stiffening plate and the related helium injection in the LiPb loop. The obtained experimental data were used to check the capabilities of RELAP5 system code to reproduce the pressure wave propagation that follows this accident. The first simulations were made with RELAP5-3D using LBE (Lead–Bismuth Eutectic) as a system fluid, as the thermophysical properties of LiPb are tabulated only up to a maximum value of 40 bar in this version of the code. Then, LiPb properties were implemented in RELAP5/mod3.3, after selecting the proper correlations from a literature review. This work summarizes the numerical simulations of the second experimental campaign, which was simulated with both versions of the code. The simulations highlight that the code is able to accurately reproduce the experimental results and that RELAP5-3D is slightly more precise than RELAP5/mod3.3 in predicting the pressure trends.
Heat Transfer Analysis in Supercritical Hydrogen of Decoupled Poisoned Hydrogen Moderator with Non-Uniform Heat Source of Chinese Spallation Neutron Source
Authors: Tong Jianfei , Zhu Lingbo , Lu Yiping , Liang Tianjiao , Lu Youlian , Wang Songlin , Yu Chaoju , Dong Shikui , Tan Heping
Published: July 2021

The flow field distribution and thermal properties of supercritical hydrogen are crucial factors affecting the quality of neutrons output from spallation neutron source, which may contribute to the optimization design of the moderator. Several sensitivity studies on affecting heat transfer characteristics of liquid hydrogen inside a moderator were executed, and a choice was made to use a computational fluid dynamics method for numerical simulation. The sensitivity degree of factors affecting the heat transfer characteristics of liquid hydrogen are in sequence of inlet mass flow, beam power and operating pressure. Especially when the beam power is 500 kW (the temperature range of liquid hydrogen is about 20~30 K); where the effect of mass flow rate is remarkable, the cooling effect is best in the range of 60~90 g/s × 394 mm2. Meanwhile, the maximum temperature of liquid hydrogen is close to the bottom recirculation zone due to the influence of the flow field and the heat deposition distribution of the poisoned plate. The effect of variable pressure on the temperature of liquid hydrogen is not significant, whereas the sudden rise of wall temperature is observed near the large specific heat region of 15 bar.
A Robust Vector Current Controller with Negative-Sequence Current Capability for Grid-Connected Inverters
Authors: Karimi Houshang , Haddadi Aboutaleb , Karimi-Ghartemani Masoud , Sadabadi Mahdieh
Published: July 2021

This paper presents a vector current controller (in the synchronous reference, or the dq, frame) with negative-sequence current injection capability for three-phase grid-connected converters. This capability is desired for the operation of the converter during unbalanced conditions and also for a certain type of islanding detection. The proposed controller first determines the double-frequency current references and then uses a sixth-order two-input two-output proportional-integral-resonance (PIR) structure, which is optimally designed. Compared with the existing similar approaches, the proposed controller has a simpler structure and more robust performance, e.g., against system parameter uncertainties and weak grid conditions. The proposed controller is developed for converters with both the L-type and LCL-type filters. For the LCL-type converter, a suboptimal partial state feedback control is also proposed to achieve robust stability and active damping of resonance poles without requiring additional sensors. Detailed experimental results are presented to illustrate the properties and performances of the proposed controller.
Niche Characterization of Shrub Functional Groups along an Atlantic-Mediterranean Gradient
Authors: Olthoff Adriana E. , Martínez-Ruiz Carolina , Alday Josu G.
Published: July 2021

The identification of the factors controlling the understory species distribution and abundance is essential to understand the ecology and dynamics of natural forests and their management response. We assess the relationships between environmental gradients and shrub functional groups distribution patterns and niche characteristics in a transitional area between the Eurosiberian and Mediterranean biogeographic regions in Northern Spain. Here, 772 plots from the 3rd Spanish National Forest Inventory were used. Shrub functional groups respond to the same complex environmental gradients as trees, i.e., the north-south climatic gradient and a slope gradient. Unimodal response curves of shrub functional groups and families dominate along both gradients, providing evidence of successful functional turnover. Similar to tree species, the niche location of functionally related shrubs is close. Functional groups occupying environments with sharp contrast or transitional environments have the broadest niches, whereas those specialized functional groups occupying localized habitats showed the narrowest niches. The knowledge of shrub species distributions and niche characteristics along complex environmental gradients will improve our ability to discuss potential conservation management goals or threats due to land-use changes and future climate change.
Education 4.0: Teaching the Basics of KNN, LDA and Simple Perceptron Algorithms for Binary Classification Problems
Authors: Lopez-Bernal Diego , Balderas David , Ponce Pedro , Molina Arturo
Published: July 2021

One of the main focuses of Education 4.0 is to provide students with knowledge on disruptive technologies, such as Machine Learning (ML), as well as the skills to implement this knowledge to solve real-life problems. Therefore, both students and professors require teaching and learning tools that facilitate the introduction to such topics. Consequently, this study looks forward to contributing to the development of those tools by introducing the basic theory behind three machine learning classifying algorithms: K-Nearest-Neighbor (KNN), Linear Discriminant Analysis (LDA), and Simple Perceptron; as well as discussing the diverse advantages and disadvantages of each method. Moreover, it is proposed to analyze how these methods work on different conditions through their implementation over a test bench. Thus, in addition to the description of each algorithm, we discuss their application to solving three different binary classification problems using three different datasets, as well as comparing their performances in these specific case studies. The findings of this study can be used by teachers to provide students the basic knowledge of KNN, LDA, and perceptron algorithms, and, at the same time, it can be used as a guide to learn how to apply them to solve real-life problems that are not limited to the presented datasets.
Optimization of Ultrasound-Assisted Extraction of Bioactive Compounds from Pelvetia canaliculata to Sunflower Oil
Authors: Sousa Gabriela , Trifunovska Marija , Antunes Madalena , Miranda Isabel , Moldão Margarida , Alves Vítor , Vidrih Rajko , Lopes Paula Allen , Aparicio Luis , Neves Marta , Tecelão Carla , Ferreira-Dias Suzana
Published: July 2021

In this study, Pelvetia canaliculata L. macroalga, collected from the Atlantic Portuguese coast, was used as a source of bioactive compounds, mostly antioxidants, to incorporate them in sunflower oil with the aim of increasing its biological value and oxidative stability. The lyophilized alga was added to the oil, and ultrasound-assisted extraction (UAE) was performed. Algae concentration and UAE time varied following a central composite rotatable design (CCRD) to optimize extraction conditions. The following parameters were analyzed in the oils: oxidation products, acidity, color, chlorophyll pigments, carotenoids, flavonoids, total phenolic content, antioxidant activity by DPPH (2,2-diphenyl-1-picrylhydrazyl) and FRAP (ferric reducing antioxidant power) assays, and sensory analysis. Extraction conditions did not affect the acidity and the amount of oxidation products in the oil. Chlorophylls and carotenoid contents increased with algae concentration, while flavonoid extraction did not depend on algae content or UAE time. Total phenolics in the oil were highly related only to FRAP antioxidant activity. Storage experiments of supplemented oil (12.5% algae; 20 min UAE) were carried out under accelerated oxidation conditions at 60 °C/12 days. Antioxidant activity (FRAP) of supplemented oil was 6-fold higher than the value of non-supplemented oil. Final samples retained 40% of their initial antioxidant activity. The presence of algae extracts contributed to the increased oxidative stability of sunflower oil.
Safety Evaluation and Whole Genome Sequencing of Aspergillus japonicas PJ01 Reveal Its Potential to Degrade Citrus Segments in Juice Processing
Authors: Qian Yujiao , Gao Zhipeng , Wang Jieyi , Wang Chen , Li Gaoyang , Fu Fuhua , Guo Jiajing , Shan Yang
Published: July 2021

Aspergillus japonicas PJ01 (A. japonicas PJ01) is a strain isolated from the rotten branches. In previ-ous studies, it was shown that it can produce complex enzymes to degrade polysaccharide com-ponents. In this study, we evaluated the safety of its crude enzyme solution. Acute oral toxicity, subchronic toxicity, micronucleus and sperm malformation tests all validated the high biologi-cal safety for the crude enzymes. Secondly, we carried out the citrus segment degradation ex-periment of crude enzyme solution. Compared with the control group, the crude enzyme solu-tion of A. japonicas PJ01 can completely degrade the segments in 50 min, which provides the basis for enzymatic peeling during juice processing. The whole genome sequencing showed that the genome of A. japonicus PJ01 has a GC content of 51.37% with a size of 36204647 bp, and encoded 10070 genes. GO, COG, KEGG and CAZy databases were used in gene annotation analyses. Pathway enrichment showed many genes related to carbohydrate metabolism, rich in genes re-lated to pectinase, xylanase and carboxylcellulase. Therefore, the complex enzyme produced by A. japonicus PJ01 can be used in gizzard juice processing to achieve efficient enzymatic decapsu-lation.