bluuebunny/crossref_metadata_2025 huggingface dataset:
End-Tidal Carbon Dioxide Pressure Measurement after Prolonged Inspiratory Time Gives a Good Estimation of the Arterial Carbon Dioxide Pressure in Mechanically Ventilated Patients
Authors: Salomé Arthur , Stoclin Annabelle , Motamed Cyrus , Sitbon Philippe , Bourgain Jean-Louis
Published: November 2021

Background: End-tidal carbon dioxide pressure (PetCO2) is unreliable for monitoring PaCO2 in several conditions because of the unpredictable value of the PaCO2–PetCO2 gradient. We hypothesised that increasing both the end-inspiratory pause and the expiratory time would reduce this gradient in patients ventilated for COVID-19 with Acute Respiratory Distress Syndrome and in patients anaesthetised for surgery. Methods: On the occasion of an arterial blood gas sample, an extension in inspiratory pause was carried out either by recruitment manoeuvre or by extending the end-inspiratory pause to 10 s. The end-expired PCO2 was measured (expiratory time: 4 s) after this manoeuvre (PACO2) in comparison with the PetCO2 measured by the monitor. We analysed 67 Δ(a-et)CO2, Δ(a-A)CO2 pairs for 7 patients in the COVID group and for 27 patients in the anaesthesia group. Results are expressed as mean ± standard deviation. Results: Prolongation of the inspiratory pause significantly reduced PaCO2–PetCO2 gradients from 11 ± 5.7 and 5.7 ± 3.4 mm Hg (p < 0.001) to PaCO2–PACO2 gradients of −1.2 ± 3.3 (p = 0.043) and −1.9 ± 3.3 mm Hg (p < 0.003) in the COVID and anaesthesia groups, respectively. In the COVID group, PACO2 showed the lowest dispersion (−7 to +6 mm Hg) and better correlation with PaCO2 (R2 = 0.92). The PACO2 had a sensitivity of 0.81 and a specificity of 0.93 for identifying hypercapnic patients (PaCO2 > 50 mm Hg). Conclusions: Measuring end-tidal PCO2 after prolonged inspiratory time reduced the PaCO2–PetCO2 gradient to the point of obtaining values close to PaCO2. This measure identified hypercapnic patients in both intensive care and during anaesthesia.
Diagnosis, Management, and Therapy of Fetal Ovarian Cysts Detected by Prenatal Ultrasonography: A Report of 36 Cases and Literature Review
Authors: Hara Takeya , Mimura Kazuya , Endo Masayuki , Fujii Makoto , Matsuyama Tatsuya , Yagi Kazunobu , Kawanishi Yoko , Tomimatsu Takuji , Kimura Tadashi
Published: November 2021

Background: Fetal ovarian cysts are the most frequently diagnosed intra-abdominal cysts; however, the evidence for perinatal management remains controversial. Methods: We retrospectively reviewed cases of fetal ovarian cysts diagnosed by prenatal ultrasonography at our institution between January 2010 and January 2020. The following were investigated: gestational age at diagnosis, cyst size, appearance, prenatal ultrasound findings, and postnatal outcomes. Prior to 2018, expectant management was applied in all cases; after 2018, in utero aspiration (IUA) of simple cysts ≥40 mm was performed. Results: We diagnosed 29 and seven simple and complex cysts, respectively. Fourteen patients had simple cysts with a maximum diameter <40 mm, and two of them progressed to complex cysts during follow-up; however, when the diameter was limited to <35 mm, no cases showed progression to complex cyst. Fifteen of the simple cysts were ≥40 mm; three progressed to complex cysts, and two of them were confirmed to be ovarian necrosis. In four patients who underwent IUA, the ovaries could be preserved. Conclusions: IUA is a promising therapy for preserving ovaries with simple cysts ≥40 mm in diameter; however, the indications for fetal surgery and the appropriate timing of intervention require further study.
Neural Network Used for the Fusion of Predictions Obtained by the K-Nearest Neighbors Algorithm Based on Independent Data Sources
Authors: Przybyła-Kasperek Małgorzata , Marfo Kwabena Frimpong
Published: November 2021

The article concerns the problem of classification based on independent data sets—local decision tables. The aim of the paper is to propose a classification model for dispersed data using a modified k-nearest neighbors algorithm and a neural network. A neural network, more specifically a multilayer perceptron, is used to combine the prediction results obtained based on local tables. Prediction results are stored in the measurement level and generated using a modified k-nearest neighbors algorithm. The task of neural networks is to combine these results and provide a common prediction. In the article various structures of neural networks (different number of neurons in the hidden layer) are studied and the results are compared with the results generated by other fusion methods, such as the majority voting, the Borda count method, the sum rule, the method that is based on decision templates and the method that is based on theory of evidence. Based on the obtained results, it was found that the neural network always generates unambiguous decisions, which is a great advantage as most of the other fusion methods generate ties. Moreover, if only unambiguous results were considered, the use of a neural network gives much better results than other fusion methods. If we allow ambiguity, some fusion methods are slightly better, but it is the result of this fact that it is possible to generate few decisions for the test object.
Quantum Transport of Particles and Entropy
Authors: Strunk Christoph
Published: November 2021

A unified view on macroscopic thermodynamics and quantum transport is presented. Thermodynamic processes with an exchange of energy between two systems necessarily involve the flow of other balancable quantities. These flows are first analyzed using a simple drift-diffusion model, which includes the thermoelectric effects, and connects the various transport coefficients to certain thermodynamic susceptibilities and a diffusion coefficient. In the second part of the paper, the connection between macroscopic thermodynamics and quantum statistics is discussed. It is proposed to employ not particles, but elementary Fermi- or Bose-systems as the elementary building blocks of ideal quantum gases. In this way, the transport not only of particles but also of entropy can be derived in a concise way, and is illustrated both for ballistic quantum wires, and for diffusive conductors. In particular, the quantum interference of entropy flow is in close correspondence to that of electric current.
A Lightweight YOLOv4-Based Forestry Pest Detection Method Using Coordinate Attention and Feature Fusion
Authors: Zha Mingfeng , Qian Wenbin , Yi Wenlong , Hua Jing
Published: November 2021

Traditional pest detection methods are challenging to use in complex forestry environments due to their low accuracy and speed. To address this issue, this paper proposes the YOLOv4_MF model. The YOLOv4_MF model utilizes MobileNetv2 as the feature extraction block and replaces the traditional convolution with depth-wise separated convolution to reduce the model parameters. In addition, the coordinate attention mechanism was embedded in MobileNetv2 to enhance feature information. A symmetric structure consisting of a three-layer spatial pyramid pool is presented, and an improved feature fusion structure was designed to fuse the target information. For the loss function, focal loss was used instead of cross-entropy loss to enhance the network’s learning of small targets. The experimental results showed that the YOLOv4_MF model has 4.24% higher mAP, 4.37% higher precision, and 6.68% higher recall than the YOLOv4 model. The size of the proposed model was reduced to 1/6 of that of YOLOv4. Moreover, the proposed algorithm achieved 38.62% mAP with respect to some state-of-the-art algorithms on the COCO dataset.
A Quaternary Code Correcting a Burst of at Most Two Deletion or Insertion Errors in DNA Storage
Authors: Khuat Thi-Huong , Kim Sunghwan
Published: November 2021

Due to the properties of DNA data storage, the errors that occur in DNA strands make error correction an important and challenging task. In this paper, a new code design of quaternary code suitable for DNA storage is proposed to correct at most two consecutive deletion or insertion errors. The decoding algorithms of the proposed codes are also presented when one and two deletion or insertion errors occur, and it is proved that the proposed code can correct at most two consecutive errors. Moreover, the lower and upper bounds on the cardinality of the proposed quaternary codes are also evaluated, then the redundancy of the proposed code is provided as roughly 2log48n.
Energy-Efficient Trajectory Optimization for UAV-Based Hybrid FSO/RF Communications with Buffer Constraints
Authors: Lu Rong-Rong , Ma Yang , Lin Sheng-Hong , Zhang Bingyuan , Wang Qinglin , Wang Jin-Yuan
Published: November 2021

This paper focuses on an unmanned aerial vehicle (UAV) assisted hybrid free-space optical (FSO)/radio frequency (RF) communication system. Considering the rate imbalance between the FSO and RF links, a buffer is employed at the UAV. Initially, theoretical models of energy consumption and throughput are obtained for the hybrid system. Based on these models, the theoretical expression of the energy efficiency is derived. Then, a nonconvex trajectory optimization problem is formulated by maximizing the energy efficiency of the hybrid system under the buffer constraint, velocity constraint, acceleration constraint, start–end position constraint, and start–end velocity constraint. By using the sequential convex optimization and first-order Taylor approximation, the nonconvex problem is transformed into a convex one. An iterative algorithm is proposed to solve the problem. Numerical results verify the efficiency of the proposed algorithm and also show the effects of buffer size on a UAV’s trajectory.
Shapley-Based Estimation of Company Value—Concept, Algorithms and Parameters
Authors: Mercik Jacek , Gładysz Barbara , Stach Izabella , Staudacher Jochen
Published: November 2021

The aim of the article is to propose a new method of valuation of a company, considering its ownership relations with other companies. For this purpose, the concept of the Shapley value from cooperative game theory is used as the basis for assessing such dependent companies. The paper presents proposals for Shapley value calculation algorithms for our model. We expand our model by discussing personal relations in addition to ownership relations and point out how intuitionistic fuzzy sets may be helpful in this context. As a result, we propose two new expanded models. In the first probabilistic model, we apply Pearson’s correlation coefficient, in the second, we use a correlation coefficient between intuitionistic fuzzy sets to determine the personal relationships. Finally, we present and interpret results for a real-world economic network with 17 companies.
Half-Elliptical Resonator Lowpass Filter with a Wide Stopband for Low Band 5G Communication Systems
Authors: Azadi Rasoul , Roshani Saeed , Nosratpour Arez , Lalbakhsh Ali , Mozaffari Mohammad Hazhir
Published: November 2021

In this paper, a lowpass filter is designed using half elliptical resonators with a wide stopband. New formulas are presented to achieve a circuit model for the half elliptical resonators used in this work. Additionally, the transfer function and transmission zero equations are used to adjust the frequency of the transmission zeros of the filter. The cut-off frequency of the lowpass filter is 1.26 GHz with a sufficiently large stopband, extending from 1.48 GHz to 20 GHz. The proposed filter’s figure of merit is 62,520, demonstrating its outperformance compared to the state of the art. The filter is implemented on a RT-5880 substrate with a constant dielectric of 2.2, thickness of 31 mil and loss tangent of 0.0009. The LPF was fabricated and tested, showing good agreement between the simulated and measured results.
Hybrid Machine Learning Approaches and a Systematic Model Selection Process for Predicting Soot Emissions in Compression Ignition Engines
Authors: Shahpouri Saeid , Norouzi Armin , Hayduk Christopher , Rezaei Reza , Shahbakhti Mahdi , Koch Charles Robert
Published: November 2021

The standards for emissions from diesel engines are becoming more stringent and accurate emission modeling is crucial in order to control the engine to meet these standards. Soot emissions are formed through a complex process and are challenging to model. A comprehensive analysis of diesel engine soot emissions modeling for control applications is presented in this paper. Physical, black-box, and gray-box models are developed for soot emissions prediction. Additionally, different feature sets based on the least absolute shrinkage and selection operator (LASSO) feature selection method and physical knowledge are examined to develop computationally efficient soot models with good precision. The physical model is a virtual engine modeled in GT-Power software that is parameterized using a portion of experimental data. Different machine learning methods, including Regression Tree (RT), Ensemble of Regression Trees (ERT), Support Vector Machines (SVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Bayesian Neural Network (BNN) are used to develop the black-box models. The gray-box models include a combination of the physical and black-box models. A total of five feature sets and eight different machine learning methods are tested. An analysis of the accuracy, training time and test time of the models is performed using the K-means clustering algorithm. It provides a systematic way for categorizing the feature sets and methods based on their performance and selecting the best method for a specific application. According to the analysis, the black-box model consisting of GPR and feature selection by LASSO shows the best performance with test R2 of 0.96. The best gray-box model consists of SVM-based method with physical insight feature set along with LASSO for feature selection with test R2 of 0.97.
R&D Spending in the Energy Sector and Achieving the Goal of Climate Neutrality
Authors: Guzowska Małgorzata K. , Kryk Barbara , Michalak Dorota , Szyja Paulina
Published: November 2021

Research and development (R&D) spending in the energy sector, which is aimed at exploring ways to reduce greenhouse gas emissions, among other things, plays a vital role in achieving the goal of climate neutrality. The purpose of this paper is to assess the environmental performance of R&D spending in the energy sector of selected EU member states from 2011–2017/2019, and to compare the results. Taxonomic research with the zero unitarization method was used, which enabled a synthetic assessment of EU countries according to the environmental performance of the total spending in the energy sector and an analysis of the changes in performance for six categories of spending in this area. The assessment of changes in the environmental performance of individual categories of R&D spending over time using the applied method was an added value compared with the assessment methods previously used in this area. The study found that there were significant differences in the level of environmental efficiency of R&D expenditures in the energy sector between countries, changes in environmental efficiency in most of the countries studied were not satisfactory, the most environmentally efficient expenditures were on renewable energy, other power and storage, hydro and fuel cell technologies, and the least on fossil fuels and nuclear energy. The results reflected both the member states’ progress towards climate neutrality and the discussion on the environmental performance of the means and directions of actions aimed at this.
Analysis and Revision of Torque Formula for Hydro-viscous Clutch
Authors: Liao Xiangping , Yang Shuai , Hu Dong , Gong Guofang
Published: November 2021

Hydro-viscous clutch is a speed-regulating device for heavy fans and water pumps. It has important engineering significance in the fields of soft-start for rotating machinery. More and more attention has been paid to its torque and control characteristics. This paper is focused on the torque formula for hydro-viscous clutch (HVC), assuming that multi-friction plates distribute ununiformly with different oil film thickness. A mathematical model of friction plates was constructed, then the distribution formula of the oil film thickness was obtained. A new expression was presented using a modified factor. Parameters such as pressure, viscous torque, and oil film thickness were obtained. The results show that each clearance of friction plates is not the same and the distribution of oil film thickness is influenced by pressing force, groove depth, angular ratio of groove/non-groove, and static friction force. To verify the proposed expression, relevant experiments were carried out on an HVC with multi-friction plates, and the experimental results indicate that the new expression is more accurate compared to the original one.
Overview of Thermal Hydraulic Optimization and Verification for the EU-DEMO HCPB BOP ICD Variant
Authors: Hering Wolfgang , Bubelis Evaldas , Perez-Martin Sara , Bologa Maria-Victoria
Published: November 2021

When progressing from the International Thermonuclear Experimental Reactor (ITER) to the Demonstration Fusion Reactor (DEMO), a system for transferring plasma heat exhaust to a power conversion system is necessary for the so-called Balance of Plant (BOP). During the preconceptual phase of the EU-DEMO project, different BOP concepts were investigated in order to identify the main requirements and feasible architectures to achieve that goal in the most efficient way. This paper comprises the investigations performed during the DEMO preconceptual design phase (p-CDP) and compares the different variants. The main aspect was focused on the helium-cooled pebble bed (HCPB) breeding blanket (BB) concept. After all assessments were performed, the indirect coupled design (ICD) was chosen as the reference configuration for the DEMO HCPB BOP for further development and optimization. The ICD provides decoupling using a molten salt storage loop, which accumulates thermal power during plasma pulses that are released during dwell periods. The work is supported by simulations using design codes EBSILON and MATLAB/SIMULINK, providing the basis for the next design phase.
Moisture Risk Analysis for Three Construction Variants of a Wooden Inverted Flat Roof
Authors: Sadłowska-Sałęga Agnieszka , Wąs Krzysztof
Published: November 2021

The paper presents an analysis of the hygrothermal performance of an inverted flat roof with a CLT (cross-laminated timber) structure in a building that meets the requirements of Passive House Standard (PHS) with regards to the potential risk of moisture. The calculations were made in the WUFI®Plus and WUFI®Bio software. The following variants were taken into account: three structure configurations, three different external climates and different scenarios of microclimate control and air change rate. The results of the calculations show that, especially in cooler climates, there is an actual moisture risk in the structure despite the excellent thermal insulation. The structure of the inverted flat roof, due to the use of a tight membrane on the outer side, allows for the partition to discharge the excess moisture only to the inside of the building. Ensuring the comfort of users may require periodic humidification of internal air, which translates directly into an increase in moisture content of the structure. The performed analysis clearly showed that there are no universal solutions. It is important to point out that for the proper performance of inverted wooden roofs, it is crucial to analyse moisture, not only thermal and energy parameters.
Will Aggregator Reduce Renewable Power Surpluses? A System Dynamics Approach for the Latvia Case Study
Authors: Pakere Ieva , Gravelsins Armands , Bohvalovs Girts , Rozentale Liga , Blumberga Dagnija
Published: November 2021

Power demand-side management has been identified as one of the possible elements towards a more flexible power system in case of increased capacities of variable renewable energy sources—solar and wind energy. The market coordinators or aggregators are introduced to adjust the electricity consumption by following the market situation. However, the role of aggregators is mainly analysed from the economic perspective, and the demand side management is performed to maximise the utilisation of low price power during off-peak hours. However, this research focuses on analysing the introduction of aggregators as a future player to increase the total share of renewable power and decrease the surplus solar and wind electricity occurrence. An in-depth system dynamics model has been developed to analyse the hourly power production and power consumption rates at the national level for the Latvia case study. The results show that introducing aggregators and load shifting based on standard peak shaving can increase the share of surplus power and does not benefit from increased utilisation of solar and wind power. On the contrary, demand-side management based on available RES power can decrease the surplus power by 5%.
Evaluation of Home Energy Efficiency Improvements in a Hot Desert Climate in Northwestern Mexico: The Energy Saving vs. Money Saving Conflict
Authors: Valenzuela Edgar , Campbell Hector , Montero Gisela , Coronado Marcos A. , Lambert-Arista Alejandro A. , Perez-Tello Carlos , Ramos-Sanchez Víctor H.
Published: November 2021

Reducing household energy consumption is one of the most important strategies used to decrease fossil fuel consumption and greenhouse gases emissions, and to encourage renewable energy utilization. Most energy conservation strategies in the domestic sector are aimed at preferential loans, i.e., purchasing renewable electricity or to improve the efficiency of home appliances, such as air conditioning and lighting. However, despite the relative economic successes of these technologies, they have not had expected impacts in regard to energy consumption. In this work, the authors analyzed the consumption patterns of two equivalent households—one was adapted with improved thermal insulation and a 1.2 kW photovoltaic system to reduce consumption from the electrical grid. The results show that dwellings where no improvements were made registered lower electric energy consumption, due the fact that users were aware that no strategy had been implemented, and its consumption; hence, electricity payments depended solely on one’s attention over the electronic device operations. On the other hand, energy conservation strategies in households promotes confident and relaxed attitudes toward the use of energy, leading to lower energy billings, but a higher gross energy consumption.
Enabling Optimal Energy Management with Minimal IoT Requirements: A Legacy A/C Case Study
Authors: Michailidis Panagiotis , Pelitaris Paschalis , Korkas Christos , Michailidis Iakovos , Baldi Simone , Kosmatopoulos Elias
Published: November 2021

The existing literature on energy saving focuses on large-scale buildings, wherein the energy-saving potential is substantially larger than smaller-scale buildings. However, the research intensity is significantly less for small-scale deployments and their capacities to regulate energy use individually, directly and without depreciating users’ comfort and needs. The current research effort focused on energy saving and user satisfaction, concerning a low-cost—yet technically sophisticated—methodology for controlling conventional residential HVAC units through cheap yet reliable actuation and sensing and auxiliary IoT equipment. The basic ingredients of the proposed experimental methodology involve a conventional A/C unit, an Arduino microcontroller, typical wireless IoT sensors and actuators, a configured graphical environment and a sophisticated, model-free, optimization-and-control algorithm (PCAO) that portrays the ground basis for achieving improved performance results in comparison with conventional methods. The main goal of this study was to produce a system that would adequately and expeditiously achieve energy savings by utilizing minimal hardware/equipment (affordability). The system was designed to be easily expandable in terms of new units or thermal equipment (expandability) and also to be autonomous, requiring zero user interventions at the experimental site (automation). The real-life measurements were collected over two different seasonal periods of the year (winter, summer) and concerned a conventional apartment in the city of Xanthi, Northern Greece, where summers and winters exhibit quite diverse climate characteristics. The final results revealed the increased efficiency of PCAO’s optimization in comparison with a conventional rule-based control strategy (RBC), as concerns energy savings and user satisfaction.
Equivalent Modeling of Microgrids Based on Optimized Broad Learning System
Authors: Wang Lin , Xue Anke
Published: November 2021

The DC microgrid is an important structure of microgrids. Aiming at the problem of the grid-connected DC microgrid modeling, a grid-connected DC microgrid equivalent modeling method based on the optimized Broad Learning System (BLS) is proposed. Taking the electrical parameter data of the grid-connected DC microgrid access point as the training data set of BLS, the equivalent model of the grid-connected equivalent model is constructed. In order to further improve the accuracy and generalization performance of the model, the shark smell optimization (SSO) algorithm is used to optimize the input weights and thresholds of the BLS. Furthermore, the shark smell optimization-Broad Learning System (SSO-BLS) algorithm is proposed. SSO-BLS is compared with RBF, BLS, BFO-ELM, and other algorithms. The results show that the grid-connected DC microgrid model based on SSO-BLS has good accuracy and generalization characteristics.
Consumer Attitudes to the Smart Home Technologies and the Internet of Things (IoT)
Authors: Korneeva Elena , Olinder Nina , Strielkowski Wadim
Published: November 2021

This paper focuses on the consumer preferences for the so-called “smart homes” (also known as “smart houses”) which represent a novel addition and a product of the on-going digitalization and the deployment of the Internet of Things (IoT). The major scientific contribution of our study is the empirical model build on the data from the online questionnaire conducted with randomly selected respondents (N = 523) from four European Union (EU) countries and Russia. Even though our results are subject to limitations (no Southern of Northern European countries are included in the scope of this research, which might have yielded different results due to the differences in wealth of citizens and climate in comparison to the Central and Eastern European countries or Germany), they demonstrate that the users included in our sample generally feel inclined to the smart homes technologies and perceive them as a plausible means for improving the safety and security of their lives. On the other hand, some respondents from our sample expressed their concerns over the cybersecurity and technology dependence issues associated with smart homes. It is also apparent that younger respondents (aged 16–35) featured in our research are more worried about their personal data being monitored and analyzed (with a pending threat of leakages). All these results are original and constitute an important scientific value-added to the field of research in smart home technologies and their acceptance by the general public. We demonstrate that the further enhancement of smart homes, and the increase of their popularity and affordability among the customers both in the Central and Eastern European countries and beyond, might depend on the development of the smart grids which these smart homes are an integral part of. The reliability of the smart systems constitutes the key element for achieving the satisfaction of the smart homes residents, and hence needs to be achieved and secured in an effective way. This would ensure the right mix and balance of energy security and efficiency for all customers involved in this process.
Estimation of Real-World Fuel Consumption Rate of Light-Duty Vehicles Based on the Records Reported by Vehicle Owners
Authors: Zeng Isabella Yunfei , Tan Shiqi , Xiong Jianliang , Ding Xuesong , Li Yawen , Wu Tian
Published: November 2021

Private vehicle travel is the most basic mode of transportation, so that an effective way to control the real-world fuel consumption rate of light-duty vehicles plays a vital role in promoting sustainable economic growth as well as achieving a green low-carbon society. Therefore, the factors impacting individual carbon emissions must be elucidated. This study builds five different models to estimate the real-world fuel consumption rate of light-duty vehicles in China. The results reveal that the light gradient boosting machine (LightGBM) model performs better than the linear regression, naïve Bayes regression, neural network regression, and decision tree regression models, with a mean absolute error of 0.911 L/100 km, a mean absolute percentage error of 10.4%, a mean square error of 1.536, and an R-squared (R2) value of 0.642. This study also assesses a large pool of potential factors affecting real-world fuel consumption, from which the three most important factors are extracted, namely, reference fuel-consumption-rate value, engine power, and light-duty vehicle brand. Furthermore, a comparative analysis reveals that the vehicle factors with the greatest impact are the vehicle brand, engine power, and engine displacement. The average air pressure, average temperature, and sunshine time are the three most important climate factors.
ARIMA Models in Electrical Load Forecasting and Their Robustness to Noise
Authors: Chodakowska Ewa , Nazarko Joanicjusz , Nazarko Łukasz
Published: November 2021

The paper addresses the problem of insufficient knowledge on the impact of noise on the auto-regressive integrated moving average (ARIMA) model identification. The work offers a simulation-based solution to the analysis of the tolerance to noise of ARIMA models in electrical load forecasting. In the study, an idealized ARIMA model obtained from real load data of the Polish power system was disturbed by noise of different levels. The model was then re-identified, its parameters were estimated, and new forecasts were calculated. The experiment allowed us to evaluate the robustness of ARIMA models to noise in their ability to predict electrical load time series. It could be concluded that the reaction of the ARIMA model to random disturbances of the modeled time series was relatively weak. The limiting noise level at which the forecasting ability of the model collapsed was determined. The results highlight the key role of the data preprocessing stage in data mining and learning. They contribute to more accurate decision making in an uncertain environment, help to shape energy policy, and have implications for the sustainability and reliability of power systems.
Towards Sustainable Heat Supply with Decentralized Multi-Energy Systems by Integration of Subsurface Seasonal Heat Storage
Authors: van der Roest Els , Beernink Stijn , Hartog Niels , van der Hoek Jan Peter , Bloemendal Martin
Published: November 2021

In the energy transition, multi-energy systems are crucial to reduce the temporal, spatial and functional mismatch between sustainable energy supply and demand. Technologies as power-to-heat (PtH) allow flexible and effective utilisation of available surplus green electricity when integrated with seasonal heat storage options. However, insights and methods for integration of PtH and seasonal heat storage in multi-energy systems are lacking. Therefore, in this study, we developed methods for improved integration and control of a high temperature aquifer thermal energy storage (HT-ATES) system within a decentralized multi-energy system. To this end, we expanded and integrated a multi-energy system model with a numerical hydro-thermal model to dynamically simulate the functioning of several HT-ATES system designs for a case study of a neighbourhood of 2000 houses. Results show that the integration of HT-ATES with PtH allows 100% provision of the yearly heat demand, with a maximum 25% smaller heat pump than without HT-ATES. Success of the system is partly caused by the developed mode of operation whereby the heat pump lowers the threshold temperature of the HT-ATES, as this increases HT-ATES performance and decreases the overall costs of heat production. Overall, this study shows that the integration of HT-ATES in a multi-energy system is suitable to match annual heat demand and supply, and to increase local sustainable energy use.
The Impact of the COVID-19 Pandemic on Consumers’ Preferences for Wood Furniture: An Accounting Perspective
Authors: Chen Jianxiong , Yang Chung-Cheng
Published: November 2021

The COVID-19 pandemic has had a major impact on forest product markets and the forest product industry, and has also seriously affected the sales of forest products. This research aimed to analyze people’s preference for wood furniture and make policy recommendations. We examined the impact of the pandemic on consumers’ preferences for wood furniture from the perspective of accounting. Taking the accounting data of wood furniture enterprises as the research object, through the translog revenue function, and using the relationship between revenue and consumption in economics, we found that the COVID-19 pandemic has reduced consumers’ preferences for wood furniture, but the decline in preference is smaller for wood furniture produced by extra-large furniture manufacturers. This study contributes to the literature and in view of our research results and the severity of the COVID-19 pandemic, we provide policy suggestions for the related governmental agencies and wood furniture manufacturers, in this special environment, that can reduce the negative impact of a pandemic on the wood furniture industry.
Experimental Investigation and Modelling of the Layered Concrete with Different Concentration of Short Fibers in the Layers
Authors: Lusis Vitalijs , Kononova Olga , Macanovskis Arturs , Stonys Rimvydas , Lasenko Inga , Krasnikovs Andrejs
Published: November 2021

The use of steel fiber reinforced concrete (SFRC) in structures with high physical-mechanical characteristics allows engineers to reduce the weight and costs of the structures, to simplify the technology of their production, to reduce or completely eliminate the manual labor needed for reinforcement, at the same time increasing reliability and durability. Commonly accepted technology is exploiting randomly distributed in the concrete volume fibers with random each fiber orientation. In structural members subjected to bending, major loads are bearing fibers located close to outer member surfaces. The majority of fibers are slightly loaded. The aim of the present research is to create an SFRC construction with non-homogeneously distributed fibers. We prepared layered SFRC prismatic specimens. Each layer had different amount of short fibers. Specimens were tested by four point bending till the rupture. Material fracture process was modelled based on the single fiber pull-out test results. Modelling results were compared with the experimental curves for beams. Predictions generated by the model were validated by 4PBT of 100 × 100 × 400 mm prisms. Investigation had shown higher load-bearing capacity of layered concrete plates comparing with plate having homogeneously distributed the same amount of fibers. This mechanism is strongly dependent on fiber concentration. A high amount of fibers is leading to new failure mechanisms—pull-out of FRC blocks and decrease of load-bearing capacity. Fracture surface analysis was realized for broken prisms with the goal to analyze fracture process and to improve accuracy of the elaborated model. The general conclusion with regard to modelling results is that the agreement with experimental data is good, numeric modelling results successfully align with the experimental data. Modelling has indicated the existence of additional failure processes besides simple fiber pull-out, which could be expected when fiber concentration exceeds the critical value.
Acrylamide in Baby Foods: A Probabilistic Exposure Assessment
Authors: Esposito Francesco , Nolasco Agata , Caracciolo Francesco , Velotto Salvatore , Montuori Paolo , Romano Raffaele , Stasi Tommaso , Cirillo Teresa
Published: November 2021

Acrylamide (also known as 2-propenamide) (AA) is a toxicant that develops in food during high-temperature cooking, and its occurrence is common in biscuits and baked snacks. AA is known for its in vivo neurotoxic and carcinogenic effects, and it is considered a potential carcinogen for humans. Infants may be exposed to AA as early as during weaning through baked food such as biscuits. This study set out to ascertain the concentration of AA in food products intended for infants to assess the dietary exposure to this food contaminant. AA levels were determined through GC/MS and bromination, and dietary exposure was evaluated by a probabilistic method based on Monte Carlo simulation. The results showed that the probability of a carcinogenic exposure is 94%, 92%, and 87%, respectively, for 6-, 12-, and 18-months infants, suggesting the need to delay the introduction of baked products in the diet of weaned infants. It should be noted, however, that these conclusions were drawn considering the biscuits as the primary source of exposure.
Non-Thermal Technologies as Tools to Increase the Content of Health-Promoting Compounds in Whole Fruits and Vegetables While Retaining Quality Attributes
Authors: Jacobo-Velázquez Daniel A. , Benavides Jorge
Published: November 2021

Fruits and vegetables contain health-promoting compounds. However, their natural concentration in the plant tissues is low and in most cases is not sufficient to exert the expected pharmacological effects. The application of wounding stress as a tool to increase the content of bioactive compounds in fruits and vegetables has been well characterized. Nevertheless, its industrial application presents different drawbacks. For instance, during the washing and sanitizing steps post-wounding, the primary wound signal (extracellular adenosine triphosphate) that elicits the stress-induced biosynthesis of secondary metabolites is partially removed from the tissue. Furthermore, detrimental reactions that affect the quality attributes of fresh produce are also activated by wounding. Therefore, there is a need to search for technologies that emulate the wound response in whole fruits and vegetables while retaining quality attributes. Herein, the application of non-thermal technologies (NTTs) such as high hydrostatic pressure, ultrasound, and pulsed electric fields are presented as tools for increasing the content of health-promoting compounds in whole fruits and vegetables by inducing a wound-like response. The industrial implementation and economic feasibility of using NTTs as abiotic elicitors is also discussed. Whole fruits and vegetables with enhanced levels of bioactive compounds obtained by NTT treatments could be commercialized as functional foods.
New Vegetable Brassica Foods: A Promising Source of Bioactive Compounds
Authors: Soengas Pilar , Velasco Pablo , Fernández Juan Carlos , Cartea María Elena
Published: November 2021

Brassica rapa is grown in northwestern Spain to obtain turnip greens. The tops of the same plants (flower stems with buds) are cut and sell as turnip tops, increasing the value of the crop. This practice could be extended to other brassicas. The objectives of this work are to study the phytochemical potential of tops of coles (Brassica oleracea) and leaf rape (Brassica napus) compared to turnip tops and to compare tops of different coles (cabbage, kale, tronchuda cabbage), which differ in their morphology and use. We evaluated the content of glucosinolates and phenolic compounds and the antioxidant capacity in leaves and tops of the three species. We found that tops had higher amount of glucosinolates than leaves. Phenolic content and antioxidant capacity followed the opposite trend. Therefore, consumption of leaves and tops are complementary, since both type of organs are enriched with different types of compound. Local varieties of kale, curly kale, cabbage and curly leave cabbage are interesting because of their GSLs and phenolic content and antioxidant capacity in both leaves and tops. From the human health perspective, tops of coles and leaf rape are interesting as new crops to include in the diet.
Chemometric Profiling and Bioactivity of Verbena (Aloysia citrodora) Methanolic Extract from Four Localities in Tunisia
Authors: Tammar Sonia , Salem Nidhal , Aidi Wannes Wissem , Limam Hajer , Bourgou Soumaya , Fares Nedia , Dakhlaoui Sarra , Hammami Majdi , Khammassi Saber , Re Giovanni Del , Hessini Kamel , Msaada Kamel
Published: November 2021

This research aimed to study the chemical composition of Aloysia citrodora methanolic extract and its biological activities as an antioxidant, and its antibacterial, antifungal and anti-inflammatory activities based on four bioclimatic collection stages. The contents of total phenols, total flavonoids and total tannins were determined. Nine phenolic compounds were identified by LC-DAD–ESI-MS/MS. The major compound was acteoside, a phenylpropanoid which represented about 80% of the methanolic fraction in the various regions. The antioxidant activities of different locations were measured by different analytical assays, such as DPPH, ABTS and iron reducing power. The results showed that phenolic compounds and antioxidant activities varied with climatic and environmental factors. Moreover, there was a significant dependency between regions and biological activities. The use of a principal component analysis showed that there was a close relationship among phenylpropanoids, phenolic compounds and the studied biological activities.
High–Pressure Processing vs. Thermal Treatment: Effect on the Stability of Polyphenols in Strawberry and Apple Products
Authors: Salazar-Orbea Gabriela Lorena , García-Villalba Rocío , Tomás-Barberán Francisco A. , Sánchez-Siles Luis Manuel
Published: November 2021

Polyphenols are important bioactive compounds that are affected by processing. The consumer’s demand for minimally processed products contributes to the increase in non-thermal technologies such as high-pressure processing (HPP) in the food industry. This review is aimed at critically discussing the positive and negative effects of thermal treatment (TT) and HPP on the stability of different polyphenol families in agro-food products obtained from strawberry and apple, two of the most used fruits in food processing. Our findings show that the phenolic content was affected by processing, fruit type, polyphenol family, and storage conditions (time and temperature) of the final product. To increase shelf life, manufacturers aiming to preserve the natural content of polyphenols need to find the sweet spot between polyphenol stability and product shelf-life since the residual enzyme activity from HPP can affect polyphenols negatively.
A Review of Microbial Decontamination of Cereals by Non-Thermal Plasma
Authors: Scholtz Vladimír , Jirešová Jana , Šerá Božena , Julák Jaroslav
Published: November 2021

Cereals, an important food for humans and animals, may carry microbial contamination undesirable to the consumer or to the next generation of plants. Currently, non-thermal plasma (NTP) is often considered a new and safe microbicidal agent without or with very low adverse side effects. NTP is a partially or fully ionized gas at room temperature, typically generated by various electric discharges and rich in reactive particles. This review summarizes the effects of NTP on various types of cereals and products. NTP has undisputed beneficial effects with high potential for future practical use in decontamination and disinfection.
Mechanical Disintegration and Particle Size Sieving of Chondrus crispus (Irish Moss) Gametophytes and Their Effect on Carrageenan and Phycoerythrin Extraction
Authors: Bahari Adiguna , Moelants Katlijn , Kloeck Marie , Wallecan Joel , Mangiante Gino , Mazoyer Jacques , Hendrickx Marc , Grauwet Tara
Published: November 2021

To better understand the migration properties of hybrid carrageenan from the seaweed tissue during carrageenan extraction, the effect of increasing the seaweed surface area by the mechanical disintegration of gametophyte Chondrus crispus chips was studied under various temperature and time extraction conditions. Dried Chondrus crispus seaweed chips were milled by a rotor beater mill and classified into eight different size fractions by sieving with varying mesh sizes from 50 to 2000 μm. During extraction at 22 °C, the red color of the filtrate increased significantly with the decreasing particle size of the fraction, correlating with the increasing phycoerythrin concentration (from 0.26 mg PE/g dry seaweed in the >2000 μm size fraction to 2.30 mg PE/g dry seaweed in the <50 μm size fraction). On the other hand, under the same extraction conditions, only a small increase in carrageenan precipitate was obtained with the decreasing size fractions (from no recovery in the >2000 μm size fraction to 2.1 ± 0.1 g/kg filtrate in the <50 μm size fraction). This yield was significantly lower than the ones from extractions at 45 °C (5.4 ± 0.1 g/kg) or at 90 °C (9.9 ± 2.1 g/kg) for the same particle size and time conditions. It could be concluded that hybrid carrageenan extraction is not surface area dependent, while phycoerythrin is. Therefore, it seems that phycoerythrin and carrageenan extraction follow different mechanisms. This creates potential for the selective extraction of each of those two compounds.
Using Microalgae as a Sustainable Feed Resource to Enhance Quality and Nutritional Value of Pork and Poultry Meat
Authors: Martins Cátia F. , Ribeiro David M. , Costa Mónica , Coelho Diogo , Alfaia Cristina M. , Lordelo Madalena , Almeida André M. , Freire João P. B. , Prates José A. M.
Published: November 2021

Cereal grains and soybean meal are the main feedstuffs used in swine and poultry feeding, two of the most consumed meats and of key relevance to food security worldwide. Such crops are grown mostly in North and South America and transported over large distances creating sustainability concerns and, furthermore, are in direct competition with human nutrition. Alternatives to these ingredients are, thus, a pressing need to ensure the sustainability of swine and poultry production. Microalgae seem to be a viable alternative due to their interesting nutritional composition. The use of different microalgae in monogastric feeding has been addressed by different researchers over the last decade, particularly their use as a supplement, whilst their use as a feed ingredient has been comparatively less studied. In addition, the high production costs of microalgae are a barrier and prevent higher dietary inclusion. Studies on the effect of microalgae on meat quality refer mostly to fatty acid composition, using these either as a functional ingredient or as a feedstuff. Within such a context and in line with such a rationale, in this review we address the current research on the topic of the use of microalgae in poultry and swine nutrition, particularly aspects concerning pork and poultry meat quality and nutritional traits.