bluuebunny/crossref_metadata_2025 huggingface dataset:
Community Structure of Eukaryotic Phytoplankton in Wetland of Golmud River and Its Lower Reaches and Relative Environmental Factors
Authors: Dong Xiaoqi , Zhu Huan , Xiong Xiong , Liu Guoxiang
Published: April 2022

Identification of the community structure of phytoplankton is an important link in studying the structure and function of aquatic ecosystems. However, research on the community structure of phytoplankton in the Golmud area is very scarce at present. To explore the composition of phytoplankton in the Golmud area, eukaryotic phytoplankton and environmental parameters were sampled in September 2020. The composition and diversity of the eukaryotic phytoplankton community were determined by microscopic observation and Illumina high-throughput sequencing technology. The results showed that a total of 40 species of eukaryotic phytoplankton from 4 phyla were identified by microscopic observation, and 154 species of eukaryotic phytoplankton from 7 phyla were obtained by high-throughput sequencing, mainly Bacillariophyta and Chlorophyta. The dominant species were Dunaliella sp., Teleaulax sp., Parvodinium mixtum, and Lindavia radiosa. The eukaryotic phytoplankton density in summer was 0.09–12.08 × 105 cells/L, the total biomass was 0.002–0.55 mg/L, and the concentration of chlorophyll-a was 0.00–0.91 μg/L. Multiple α diversity indices showed that the diversity of water in different salinities was in the order of freshwater > brackish > saline. The β diversity results showed that the eukaryotic phytoplankton community composition was more similar in water with the same salinity. The redundancy analysis results of water with different salinities showed that environmental factors susc as salinity, total phosphorus concentration, and dissolved oxygen affected the eukaryotic phytoplankton community structure, among which salinity had the greatest influence.
Magnesium—A More Important Role in CKD–MBD than We Thought
Authors: Peride Ileana , Tiglis Mirela , Neagu Tiberiu Paul , Niculae Andrei , Checherita Ionel Alexandru
Published: April 2022

Chronic kidney disease (CKD) is associated with different complications, including chronic kidney disease–mineral and bone disorder (CKD–MBD), which represents a systemic disorder that involves the presence of different mineral or bone structure abnormalities (i.e., modification of bone turnover, strength, volume, etc.), including even vascular calcification development. Even if, over the years, different pathophysiological theories have been developed to explain the onset and progression of CKD–MBD, the influence and importance of serum magnesium level on the evolution of CKD have only recently been highlighted. So far, data are inconclusive and conflicting; therefore, further studies are necessary to validate these findings, which could be useful in developing a better, more adequate, and personalized management of CKD patients.
Comparison of Different Nutritional Assessment Tools in Detecting Malnutrition and Sarcopenia among Cirrhotic Patients
Authors: Topan Mirabela-Madalina , Sporea Ioan , Dănilă Mirela , Popescu Alina , Ghiuchici Ana-Maria , Lupușoru Raluca , Șirli Roxana
Published: April 2022

Malnutrition and sarcopenia are common complications of liver cirrhosis. This study compares the performance of different nutritional assessment techniques in detecting malnourished patients. Data from 156 patients with liver cirrhosis were collected. We assessed the nutritional status of these patients according to: Subjective Global Assessment (SGA); Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT), skinfold thickness (TSF), mid-upper arm circumference (MUAC), mid-upper arm muscle circumference (MUMC), handgrip strength (HGS), body mass index (BMI), and skeletal muscle index (SMI) evaluated by Contrast-Enhanced Computed Tomography (CT). According to EWGSOP2 criteria, combining low HGS with low SMI, the prevalence of malnutrition/sarcopenia was 60.2%. RFH-NPT, MUAC, MAMC, and HGS were excellent tests for detecting malnourished patients. Combining RFH-NPT with MUAC or MUMC increased diagnosis accuracy, AUC = 0.89, p < 0.0001. Age, Child-Pugh class C, albumin level, vitamin D deficiency, male gender, and alcoholic etiology were significantly associated with malnutrition. In conclusion, the prevalence of malnutrition among patients with cirrhosis was relatively high. Our study highlights the potential use of a simpler and inexpensive alternative that can be used as a valuable tool in daily practice, the combination between RFH-NPT and MUAC.
Assessment of Oral Human Papillomavirus Prevalence in Pediatric and Adult Patients within a Multi-Ethnic Clinic Population
Authors: Kornhaber Melissa Solomon , Florence Taylor , Davis Trexton , Kingsley Karl
Published: April 2022

Introduction: Human papillomavirus (HPV) encompasses a large family of oncogenic viruses responsible for increasing rates of both cervical and oral cancer, particularly among minority and low-income populations. Although this represents an increasingly significant public health risk, few studies have screened for oral HPV within Nevada. Based upon this information, the primary objective of this study was to provide a temporal analysis of oral HPV screening among a primarily low-income, minority patient population. Methods: This retrospective analysis was reviewed and approved by the Institutional Review Board (IRB). In brief, unstimulated saliva samples were previously obtained from clinical patient volunteers who provided informed consent and pediatric assent (if applicable). DNA was isolated and screened using spectrophotometry for quality (A260:A280 ratio > 1.70) and quantity (concentration > 100 ng). Validated qPCR primers were used to screen repository samples for high-risk HPV strains HPV16 and HPV18. Results: A total of N = 930 samples were identified for this study, which involved n = 555 samples from adults and n = 375 from pediatric patients treated between 2011 and 2019. A demographic analysis revealed nearly equal distribution between males and females with most derived from non-White (minority) patients. A qPCR screening revealed an overall increase in high-risk HPV of 3.17-fold from 5.7% in 2011 to 18.1% in 2019 and a coefficient of determination or R2 = 0.764, suggesting a strong, positive correlation between more recent sample years and HPV-positive results, which was observed among both pediatric (R2 = 0.671) and adult (R2 = 0.971) patients. In addition, although the average age among adult patients increased over time, a significant decrease was observed among pediatric patients from an average of 16.0 years to 14.81 years. Conclusions: These data suggest temporal changes and positive increases in the prevalence of oral HPV among both the pediatric and adult patient samples taken from this clinic population. These data are important as considerations are made regarding which HPV vaccination education and awareness programs are introduced and the specific populations most likely to benefit from these interventions.
Radiographic and Histomorphologic Evaluation of the Maxillary Bone after Crestal Mini Sinus Lift Using Absorbable Collagen—Retrospective Evaluation
Authors: Cosola Saverio , Di Dino Biagio , Traini Tonino , Kim Young-Sam , Park Young-Min , Marconcini Simone , Covani Ugo , Vinci Raffaele
Published: April 2022

Background: After tooth extraction, the alveolar bone loses volume in height and width over time, meaning that reconstructive procedures may be necessary to perform implant placement. In the maxilla, to increase the bone volume, a mini-invasive surgery, such as a sinus lift using the crestal approach, could be performed. Methods: A crestal approach was used in this study to perform the sinus lift, fracturing the bone and inserting collagen (Condress®). The single dental implant was placed in the healed bone after six months. Results: The newly formed bone was histologically analyzed after healing. Histomorphological analyses confirmed the quality of the new bone formation even without graft biomaterials. This is probably due to the enlargement of the space, meaning more vascularization and stabilization of the coagulum. Conclusion: Using just collagen could be sufficient to induce proper new bone formation in particular clinical situations, with a minimally invasive surgery to perform a sinus lift.
Influence of Needle Design and Irrigant Flow Rate on the Removal of Enterococcus faecalis Biofilms In Vitro
Authors: Provoost Charley , Rocca Giovanni Tommaso , Thibault Anna , Machtou Pierre , Bouilllaguet Serge
Published: April 2022

This study aimed to evaluate the influence of needle design and irrigant flow rate on the removal of Enterococcus faecalis mature biofilms during sodium hypochlorite irrigation. Forty-eight single-rooted human teeth were instrumented (ProTaper F3), autoclaved and inoculated with Enterococcus faecalis to establish a two-week-old biofilm. E. faecalis biofilms were treated with Sodium hypochlorite that was injected in the root canals using three types of needles (NaviTip, ProRinse, IrriFlex). For the IrriFlex needle, one, two, or four bars of pressure was applied to the irrigating solution to increase flow rates. Bacteria were labeled with the LIVE/DEAD BacLight Bacterial Viability kit, and viability was assessed by flow cytometry (FCM). Results were statistically analyzed using one-way ANOVA and Tukey multiple comparison intervals (α = 0.05). Bacterial viability was significantly reduced after sodium hypochlorite passive irrigation but the number of viable bacteria retrieved from root canal specimens irrigated with the Pro-Rinse needle was significantly higher compared to NaviTip and IrriFlex needles (p < 0.05). When the irrigant flow rate was increased, the viability of bacterial biofilms was significantly reduced compared to passive irrigation using the IrriFlex needle (p < 0.05). Applying higher flow rates during irrigation using the IrriFlex needle did not further reduce bacterial viability.
The Determinants of the Usage of Accounting Information Systems toward Operational Efficiency in Industrial Revolution 4.0: Evidence from an Emerging Economy
Authors: Thuan Pham Quoc , Khuong Nguyen Vinh , Anh Nguyen Duong Cam , Hanh Nguyen Thi Xuan , Thi Vo Huynh Anh , Tram Tieu Ngoc Bao , Han Chu Gia
Published: April 2022

The purpose of this study is to determine the factors affecting the application of accounting information systems (AIS) in small and medium enterprises (SMEs) in Vietnam. Drawing upon the Technology–Organization–Environment (TOE) theoretical framework, Diffusion of Innovations theory (DOI), and Resource-based theory (RBV), we proposed a research model to investigate the antecedents and influence of AIS usage in Vietnamese SMEs. This study used an online survey of individuals who work in Vietnamese SMEs for data collection. The result was assembled by applying the PLS-SEM model to test the proposed hypotheses based on 132 valid responses. First, the factors that have a significant impact on AIS usage are as follows: relative advantage; owner/manager commitment; and impact of COVID-19. Second, the research results also confirm that there is a positive relationship between AIS usage and AIS effectiveness; AIS performance has a positive impact on business performance. Research implications are to help business owners and leaders decide whether to use AIS to strengthen the company’s position and reduce the burden on departments, particularly the accounting department.
Computer Animation Education Online: A Tool to Teach Control Systems Engineering throughout the COVID-19 Pandemic
Authors: Patete Anna , Marquez Ronald
Published: April 2022

The world is changing, and university education must be able to adapt to it. New technologies such as artificial intelligence and robotics are requiring tools such as simulation and process control to develop products and services. Thus, control systems engineering schools are adapting to new educational frameworks tailored to deploy promising and feasible new technologies. Herein, we have relied on computer animation-based education and its implementation as an online project-based strategy to attain the objectives and goals of the control systems engineering courses at University of Los Andes, Venezuela. The ControlAnimation library developed in Mathematica program in 2002 has been used as a tool to teach control systems engineering courses since 2008 and with greater prominence since 2020, when the stay-at-home orders due to the COVID-19 pandemic were enacted. Consequently, computer animation-based education has proven its feasibility as an online tool combined with project-based learning techniques, thus allowing students to interact with an animated control system by changing the mathematical model and the design parameters of control laws in a comfortable and somewhat playful way. This enabled new capabilities to study the dynamic behaviors of primordial control systems online. In addition, it allowed students to co-identify and relate in a more intuitive way to the mathematical models and control equations with the physical behavior of the real control systems.
Investigations on Field Distribution along the Earth’s Surface of a Submerged Line Current Source Working at Extremely Low Frequency Band
Authors: Yang Ke , Wang Jinhong , Liu Shuwen , Ding Kai , Li Hao , Li Bin
Published: April 2022

A numerical analysis on field distribution along the Earth’s surface of a line current source submerged in the ground is conducted in this paper to investigate the potential of the extremely low frequency (ELF) technology in the envisioned long-distance communication techniques. The problem is modeled as a submerged horizontal electric dipole (HED) in a two-layered homogeneous half space and solved by the combined numerical methods of the Romberg-Euler method and Gauss-Laguerre method. The model is validated by experimental results with only a maximum 10% error at 9 Hz around 490 m. Meanwhile, the study shows that the ELF signals emitted by a submerged line current source can transmit at least 1 km with a current sensor sensitivity of 0.1 pT. These results indicate the possibility of applying of ELF technology to long-distance communication or the long-distance transmedia detection.
Research on Fractional-Order Global Fast Terminal Sliding Mode Control of MDF Continuous Hot-Pressing Position Servo System Based on Adaptive RBF Neural Network
Authors: Zhu Liangkuan , Chen Xinrui , Qi Xing , Zhang Jian
Published: April 2022

In this paper, a novel fractional-order global fast terminal sliding mode control (FGFTSMC) strategy based on an adaptive radial basis function (RBF) neural network is proposed to improve the performance of a medium density fiberboard (MDF) continuous hot-pressing position servo system with parameter perturbation and external load disturbance. Primarily, the mathematical model of the MDF continuous hot-pressing position servo system is constructed based on the dynamic equation of the hydraulic system. Then, a FGFTSMC is designed to speed up the convergence rate of the system, in which an adaptive law is used to estimate the upper bound of the unknown parameters to overcome the existing parameter perturbation of the system. In addition, an RBF neural network is introduced to approximate the external load disturbance of the system. The stability of MDF continuous hot-pressing position servo system based on the control scheme developed in this paper is proven using the Lyapunov theory. Finally, the simulation results show that the presented control scheme can effectively ensure the tracking accuracy of the system and enhance the robustness of the system.
Can I Sleep Safely in My Smarthome? A Novel Framework on Automating Dynamic Risk Assessment in IoT Environments
Authors: Collen Anastasija , Nijdam Niels Alexander
Published: April 2022

Fully automated homes, equipped with the latest Internet of Things (IoT) devices, aiming to drastically improve the quality of lives of those inhabiting such homes, is it not a perfect setting for cyber threats? More than that, this is a fear of many regular citizens and a trending topic for researchers to apply Cyber Threat Intelligence (CTI) for seamless cyber security. This paper focuses on the Risk Assessment (RA) methodology for smarthome environments, targeting to include all types of IoT devices. Unfortunately, existing approaches mostly focus on the manual or periodic formal RA, or individual device-specific cyber security solutions. This paper presents a Dynamic Risk Assessment Framework (DRAF), aiming to automate the identification of ongoing attacks and the evaluation of the likelihood of associated risks. Moreover, DRAF dynamically proposes mitigation strategies when full automation of the decision making is not possible. The theoretical model of DRAF was implemented and tested in smarthome testbeds deployed in several European countries. The resulting data indicate strong promises for the automation of decision making to control the tightly coupled balance between cyber security and privacy compromise in terms of the embedded services’ usability, end-users’ expectations and their level of cyber concerns.
Forensic Analysis on Internet of Things (IoT) Device Using Machine-to-Machine (M2M) Framework
Authors: Mazhar Muhammad Shoaib , Saleem Yasir , Almogren Ahmad , Arshad Jehangir , Jaffery Mujtaba Hussain , Rehman Ateeq Ur , Shafiq Muhammad , Hamam Habib
Published: April 2022

The versatility of IoT devices increases the probability of continuous attacks on them. The low processing power and low memory of IoT devices have made it difficult for security analysts to keep records of various attacks performed on these devices during forensic analysis. The forensic analysis estimates how much damage has been done to the devices due to various attacks. In this paper, we have proposed an intelligent forensic analysis mechanism that automatically detects the attack performed on IoT devices using a machine-to-machine (M2M) framework. Further, the M2M framework has been developed using different forensic analysis tools and machine learning to detect the type of attacks. Additionally, the problem of an evidence acquisition (attack on IoT devices) has been resolved by introducing a third-party logging server. Forensic analysis is also performed on logs using forensic server (security onion) to determine the effect and nature of the attacks. The proposed framework incorporates different machine learning (ML) algorithms for the automatic detection of attacks. The performance of these models is measured in terms of accuracy, precision, recall, and F1 score. The results indicate that the decision tree algorithm shows the optimum performance as compared to the other algorithms. Moreover, comprehensive performance analysis and results presented validate the proposed model.
A Simple and Efficient Tree-Based Algorithm for the Distributed Trigger Counting Problem
Authors: Lee Jaeheung , Park Yongsu
Published: April 2022

The distributed trigger counting (DTC) problem is defined as raising an alarm and notifying a user when the total number of received triggers reaches a predefined value w in a distributed system of n nodes. DTC algorithms can be used for environmental surveillance with sensor networks and global snapshots. In this paper, we propose a simple and efficient algorithm for the DTC problem. The proposed algorithm is based on a tree structure of degree n and height 2. The proposed algorithm operates in three phases depending on the remaining number of triggers. We prove the correctness of the proposed algorithm: the probability of not notifying a user even though the total number of received triggers reaches w is 0. Experimental results show that the proposed algorithm has lower message complexity than the best previous algorithms: CoinRand and TreeFill. MaxRcv (the maximum number of received messages per node) of the proposed algorithm is also smaller than CoinRand and TreeFill when the number of nodes is not very large.
Safe and Efficient Take-Off of VTOL UAV Swarms
Authors: Sastre Carles , Wubben Jamie , Calafate Carlos T. , Cano Juan-Carlos , Manzoni Pietro
Published: April 2022

Currently multicopters are facing a continuous growth in terms of recreational uses, and multiple companies focused on these aircrafts to facilitate certain tasks that were nearly inaccessible to humans, or otherwise involved a great cost. In this context, the drone swarm concept allows us to broaden and incorporate new, more refined applications in which various aircraft coordinate with each other to carry out large-scale tasks. When the number of UAVs involved becomes too high, guaranteeing that the take-off procedure is efficient and yet secure becomes quite complex. Hence, in this paper we propose and validate different algorithms to optimize the take-off time of drones belonging to a swarm, with the objective that there are no collisions between them. In particular, we propose algorithms for both trajectory analysis and batch generation for take-off. Based on a large number of experiments using the ArduSim simulator we prove that the proposed algorithms provide a robust solution within a reasonable time frame when testing with different aerial formations. In addition, we will assess how different UAV position assignment strategies impact our algorithm performance in terms of take-off time and number of batches required.
Prototyping Power Electronics Systems with Zynq-Based Boards Using Matlab/Simulink—A Complete Methodology
Authors: Caseiro Luís , Caires Diogo , Mendes André
Published: April 2022

Many advanced power electronics control techniques present a steep computational load, demanding advanced controllers, such as FPGAs. However, FPGA development is a daunting and time-consuming task, inaccessible to most users. This paper proposes a complete methodology for prototyping power electronics with Xilinx Zynq-based boards using Matlab/Simulink and HDL Coder. Even though these tools are relatively well documented, and several works in the literature have used them, a methodology for developing power electronics systems with them has never been proposed. This paper aims to address that, by proposing a complete programming and design methodology for Zynq-based power electronics and discussing important drawbacks and hurdles in Simulink/HDL Coder development, as well as their possible solutions. In addition, techniques for the implementation of all required peripherals (ADCs, digital outputs, etc.), system protections, and real-time data acquisition on Zynq boards are presented. This methodology considerably reduces the development time and effort of power electronics solutions using Zynq-based boards. In addition, a demonstration Simulink model is provided with all proposed techniques and protections, for use with a readily available development board (Zedboard) and ADC modules. This should further reduce the learning curve and development effort of this type of solution, contributing to a broader access to high-performance control prototyping using Zynq-based platforms. An application example is presented to demonstrate the potential of the proposed workflow, using a Zedboard to control a multilevel UPS inverter prototype with Model Predictive Control.
An Efficient Crypto Processor Architecture for Side-Channel Resistant Binary Huff Curves on FPGA
Authors: Umer Usama , Rashid Muhammad , Alharbi Adel R. , Alhomoud Ahmed , Kumar Harish , Jafri Atif Raza
Published: April 2022

This article presents an efficient crypto processor architecture for point multiplication acceleration of side-channel secured Binary Huff Curves (BHC) on FPGA (field-programmable gate array) over GF(2233). We have implemented six finite field polynomial multiplication architectures, i.e., (1) schoolbook, (2) hybrid Karatsuba, (3) 2-way-karatsuba, (4) 3-way-toom-cook, (5) 4-way-toom-cook and (6) digit-parallel-least-significant. For performance evaluation, each implemented polynomial multiplier is integrated with the proposed BHC architecture. Verilog HDL is used for the implementation of all the polynomial multipliers. Moreover, the Xilinx ISE design suite tool is employed as an underlying simulation platform. The implementation results are presented on Xilinx Virtex-6 FPGA devices. The achieved results show that the integration of a hybrid Karatsuba multiplier with the proposed BHC architecture results in lower hardware resources. Similarly, the use of a least-significant-digit-parallel multiplier in the proposed design results in high-speed (in terms of both clock frequency and latency). Consequently, the proposed BHC architecture, integrated with a least-significant-digit-parallel multiplier, is 1.42 times faster and utilizes 1.80 times lower FPGA slices when compared to the most recent BHC accelerator architectures.
Efficient FPGA Implementation of an ANN-Based Demapper Using Cross-Layer Analysis
Authors: Ney Jonas , Hammoud Bilal , Dörner Sebastian , Herrmann Matthias , Clausius Jannis , ten Brink Stephan , Wehn Norbert
Published: April 2022

In the field of communication, autoencoder (AE) refers to a system that replaces parts of the traditional transmitter and receiver with artificial neural networks (ANNs). To meet the system performance requirements, it is necessary for the AE to adapt to the changing wireless-channel conditions at runtime. Thus, online fine-tuning in the form of ANN-retraining is of great importance. Many algorithms on the ANN layer are developed to improve the AE’s performance at the communication layer. Yet, the link of the system performance and the ANN topology to the hardware layer is not fully explored. In this paper, we analyze the relations between the design layers and present a hardware implementation of an AE-based demapper that enables fine-tuning to adapt to varying channel conditions. As a platform, we selected field-programmable gate arrays (FPGAs) which provide high flexibility and allow to satisfy the low-power and low-latency requirements of embedded communication systems. Furthermore, our cross-layer approach leverages the flexibility of FPGAs to dynamically adapt the degree of parallelism (DOP) to satisfy the system-level requirements and to ensure environmental adaptation. Our solution achieves 2000× higher throughput than a high-performance graphics processor unit (GPU), draws 5× less power than an embedded central processing unit (CPU) and is 5800× more energy efficient compared to an embedded GPU for small batch size. To the best of our knowledge, such a cross-layer design approach combined with FPGA implementation is unprecedented.
A Generalized Predictive Controller for a Wind Turbine Providing Frequency Support for a Microgrid
Authors: Prieto Cerón Carlos E. , Normandia Lourenço Luís F. , Solís-Chaves Juan S. , Sguarezi Filho Alfeu J.
Published: April 2022

The power system is moving away from the centralized generation paradigm. One of the current trends is the microgrid concept, where loads, small generators and renewable energy resources (RERs) that are in close proximity are controlled as one entity. Microgrids also allow for an increase in power availability as they can continue to supply electric power to loads even in the absence of a connection to the main grid. During the transition to islanded operation, microgrids may be subject to frequency disturbances caused by the power imbalance between load and generation. When microgrids contain high shares of renewable energy, the challenge is significantly higher due to the control strategies that aim to maximize power production, which are typically applied to RERs and render them insensitive to grid changes. Therefore, new control strategies need to be developed to enable the participation of RERs in the support of the frequency response. This work proposes a predictive control strategy that is based on a generalized predictive controller (GPC) being applied to the grid side converter of a doubly fed induction generator (DFIG) wind turbine to enable frequency support capabilities. The control objective was to track a time varying power reference signal that was generated according to the deviation from the nominal frequency, thereby enabling the energy storage device to inject power into the microgrid without a communication system. The GPC is a controller belonging to the family of model predictive controllers (MPCs), the main principles of which are the use of a system model to predict future states and the choice of an optimal input to ensure that the reference values are followed. To validate the proposed control strategy, a microgrid was simulated in MATLAB Simscape Electrical. The frequency response using the proposed GPC strategy was compared to another MPC-based strategy, known as finite control set, and a scenario in which the DFIG was not equipped with frequency support capabilities. The results show that the proposed strategy was able to improve the frequency response of the microgrid, reduce frequency oscillations and increase the value of the frequency nadir.
MATRYCS—A Big Data Architecture for Advanced Services in the Building Domain
Authors: Pau Marco , Kapsalis Panagiotis , Pan Zhiyu , Korbakis George , Pellegrino Dario , Monti Antonello
Published: April 2022

The building sector is undergoing a deep transformation to contribute to meeting the climate neutrality goals set by policymakers worldwide. This process entails the transition towards smart energy-aware buildings that have lower consumptions and better efficiency performance. Digitalization is a key part of this process. A huge amount of data is currently generated by sensors, smart meters and a multitude of other devices and data sources, and this trend is expected to exponentially increase in the near future. Exploiting these data for different use cases spanning multiple application scenarios is of utmost importance to capture their full value and build smart and innovative building services. In this context, this paper presents a high-level architecture for big data management in the building domain which aims to foster data sharing, interoperability and the seamless integration of advanced services based on data-driven techniques. This work focuses on the functional description of the architecture, underlining the requirements and specifications to be addressed as well as the design principles to be followed. Moreover, a concrete example of the instantiation of such an architecture, based on open source software technologies, is presented and discussed.
Proxy Re-Encryption-Based Traceability and Sharing Mechanism of the Power Material Data in Blockchain Environment
Authors: Song Jien , Yang Yang , Mei Jie , Zhou Gaofeng , Qiu Weiqiang , Wang Yixing , Xu Lu , Liu Yanran , Jiang Jinyu , Chu Zhenyue , Tan Weitao , Lin Zhenzhi
Published: April 2022

The need to accelerate the innovation and application of the supply chain has been suggested by the State Council of China. To solve the problem of data isolation caused by privacy protection in the power material supply chain, a data traceability and sharing mechanism based on blockchain is designed in this paper. Firstly, the existing problems of the power material supply chain are introduced, and the applicability of blockchain in the power material supply chain in view of these problems is analyzed. Secondly, blockchain-based power material supply deployment and application structures are proposed. Then, considering the problem of data isolation in the material inspection and distribution links between suppliers and the material company, a data traceability mechanism based on blockchain is designed to provide evidence for the data authenticity and a proxy re-encryption method is used to ensure security and privacy in data sharing. Finally, the effectiveness of the proposed data traceability and sharing mechanism is verified using the Hyperledger Fabric platform for power material case studies. The simulation results show that the combination of proxy re-encryption and blockchain technology in the power material supply chain can confirm the validity of the historical data and keep the private data of the material company confidential, so as to realize the traceability and sharing of the power material supply data.
Simulation and Modeling of Ported Shroud Effects on Radial Compressor Stage Stability Limits
Authors: Cravero Carlo , Leutcha Philippe , Marsano Davide
Published: April 2022

The design features of a centrifugal compressor must guarantee high performance and a wide operating range. The ported shroud was developed specifically to extend the operating limit. It is a passive flow control device based on a cavity for flow recirculation to avoid blade passage blocking in near surge conditions. A CFD simulation campaign using a simplified model identified the differences in the performance of the centrifugal compressor with ported shroud, compared to the baseline case. The use of a stability criterion to determine the limit mass flow rate, developed in a previous study by the authors, highlighted and quantified the extension of the surge margin in the case with ported shroud for different rotational speeds. An increase in the surge margin of 11% was detected at design speed, but with a lower trend at higher speeds. An in-depth flow analysis showed the main physical mechanisms in the compressor that occur for different operating conditions: at near surge conditions the cavity recirculates the low momentum flow located in the inducer region; it re-energizes the mainstream decreasing the circumferential velocity component; an improvement of up to 7% of the pressure ratio was obtained. Instead, at best efficiency conditions the flow recirculation worsens the performance by reducing the flow incidence at the rotor leading edge. Finally, using unsteady simulations with a complete 3D model and with the application of the stability criterion it was possible to confirm that the ported shroud can effectively extend the operating range.
Energy-Efficiency Passive Strategies for Mediterranean Climate: An Overview
Authors: Matos Ana Mafalda , Delgado João M. P. Q. , Guimarães Ana Sofia
Published: April 2022

Among all the activities in a society, construction has a key role in environmental, social, and economic pillars. Construction is also responsible for a considerable amount of waste production, energy consumption, pollutant gas emissions, and consumption of nonrenewable natural resources. Regarding energy consumption, a high demand for building operational energy has been observed in the last decades due to the more demanding requirements of the users with a continuous search for better thermal comfort in their homes, namely in developed countries. In Portugal, for instance, more than 20% of the electricity consumed is related to residential buildings, which is based on CO2 emissions and other pollutants that negatively affect the environment. Much of this consumed energy is a result of the HVAC systems installed inside buildings to provide users with thermal comfort. One exciting opportunity to mitigate buildings’ operational energy consumption while contributing to thermal user comfort is the use of passive solutions. Even though several passive options are available and constantly under research, their use is still considered limited. This paper overviews and highlights the potential of energy-efficiency passive strategies, namely for Mediterranean-climate countries, where passive solar technologies can be set as a viable solution, as this climate is mainly known for its solar availability (solar hours and solar irradiance). A comprehensive overview of innovative and traditional housing passive solutions currently available is presented and discusses the main advantages, disadvantages, and concerns contributing to the optimal use of climatic conditions and natural resources in those regions.
Decarbonizing Natural Gas: A Review of Catalytic Decomposition and Carbon Formation Mechanisms
Authors: Tong Sirui , Miao Bin , Zhang Lan , Chan Siew Hwa
Published: April 2022

In the context of energy conservation and the reduction of CO2 emissions, inconsistencies between the inevitable emission of CO2 in traditional hydrogen production methods and eco-friendly targets have become more apparent over time. The catalytic decomposition of methane (CDM) is a novel technology capable of producing hydrogen without releasing CO2. Since hydrogen produced via CDM is neither blue nor green, the term “turquoise” is selected to describe this technology. Notably, the by-products of methane cracking are simply carbon deposits with different structures, which can offset the cost of hydrogen production cost should they be harvested. However, the encapsulation of catalysts by such carbon deposits reduces the contact area between said catalysts and methane throughout the CDM process, thereby rendering the continuous production of hydrogen impossible. This paper mainly covers the CDM reaction mechanisms of the three common metal-based catalysts (Ni, Co, Fe) from experimental and modelling approaches. The by-products of carbon modality and the key parameters that affect the carbon formation mechanisms are also discussed.
Validation of a Large-Eddy Simulation Approach for Prediction of the Ground Roughness Influence on Wind Turbine Wakes
Authors: Stein Victor , Kaltenbach Hans-Jakob
Published: April 2022

The ability of high-fidelity computational fluid mechanics simulation to quantitatively predict the influence of ground roughness on the evolution of the wake of a three-bladed horizontal axis wind turbine model is tested by comparison with wind tunnel measurements. The approach consists of the implicit approximate deconvolution large-eddy simulation formulation of Hickel et al., (2006), that is, for the first time, combined with a wall-stress model for flow over rough surfaces and with the actuator line approach (ALM) for modeling of the rotor. A recycling technique is used for the generation of turbulent inflow that matches shear exponents α=0.16 (medium roughness) and α=0.32 (high roughness) and turbulence level of the reference experiments at hub height. Satisfactory agreement of the spectral content in simulation and experiment is achieved for a grid resolution of 27 cells per rotor radius. Except for minor differences due to neglecting nacelle and tower in the simulation the LES reproduces the shapes of mean flow and Reynolds stress profiles in the wake. The deviations between measurement and simulation are more prominent in a vertical cut plane through the rotor center than in a horizontal cut plane. Simulation and experiment deviate with respect to the roughness influence on the development of the wake width; however, the relative change of the maximum wake deficit and of the vertical wake center position due to changes in ground roughness is reproduced very well.
Exploring Greek Citizens’ Circular Thinking on Food Waste Recycling in a Circular Economy—A Survey-Based Investigation
Authors: Papamonioudis Konstantinos , Zabaniotou Anastasia
Published: April 2022

Food waste is one of the biggest global challenges. Thinking and acting for closed-loop cycles for energy and resources recovery is pivotal for meeting the Sustainable Development Goal 12.3 (SDG 12.3) by 2030. In this paper, the multifaceted problem of food waste and Greece’s national policy of circular economy is briefly given. Greece produces the highest annual per capita food waste output (142 kg) in Europe, indicating that the problem is rather large for the country. The solution to the problem inextricably linked to the implementation of the food waste hierarchy, was investigated through a survey integrating the possibility of energy recovery. The tailored questionnaire sent via e-mails and social media with the goal of identifying a snapshot of Greek citizens’ conceptions and practices regarding the management of their household food waste, and their familiarity with circular economy concepts. Results have shown that most respondents are aware of the problem’s existence, however, without considering it as important, according to 1565 responses gathered and analyzed using the IBM SPSS Statistics 27.0 program. Greek individuals are eager to recycle their food waste without expecting anything in return, but the majority seek recommendations on how to do it.
Improvement and Validation of the System Analysis Model and Code for Heat-Pipe-Cooled Microreactor
Authors: Ge Li , Li Huaqi , Tian Xiaoyan , Ouyang Zeyu , Kang Xiaoya , Li Da , Shan Jianqiang , Jiang Xinbiao
Published: April 2022

Heat-pipe-cooled microreactors (HPMR) use a passive high-temperature alkali metal heat pipe to directly transfer the heat of solid core to the hot end of the intermediate heat exchanger or thermoelectric conversion device, thus avoiding a single point failure. To analyze and evaluate the transient safety characteristics of an HPMR system under accident conditions, such as heat pipe failure in the core or a loss of system heat sink and other accidents, a previously developed model for transient analysis of a heat-pipe-cooled space nuclear reactor power system (HPSR) was improved and validated in this study. The models improved mainly comprise: (1) An entire 2-D solid-core heat transfer model is established to analyze the accident conditions of core heat pipe failure and system heat sink loss. In this model, radial and axial Fourier heat conduction equations are used to divide the core into r-θ direction control volumes. The physical parameters of the material in the control volume are calculated according to the volume-weighted average. (2) By coupling the heat transfer limit model and the two-dimensional thermal resistance network model, the transient model of a heat pipe for HPMR system analysis is improved. (3) Conversion system models are established to simulate the system characteristics of the advanced HPMR concept, such as thermoelectric conversion, Stirling conversion, and the open Brayton conversion analysis model. Based on the improved models, the HPMR system analysis program TAPIRSD was developed, which was verified by experimental data of the separated conversion components and the ground nuclear test device KRUSTY. The maximum deviation of the power output predicted by the energy conversion model is less than 8%. The accident conditions of the KRUSTY tests, such as load change, core heat pipe failure, and heat sink loss accident, were studied by using TAPIRSD. The results show that the simulation results of the TAPIRSD code agree well with the experimental data of the KRUSTY prototype reactor. The maximum error between the TAPIRSD code prediction and the measured value of the core temperature under accident conditions is less than 10 K, and the maximum deviation is less than 2%. The results show that the developed code can predict the transient response process of the HPMR system well. At the same time, the accuracy and reliability of the improved model are proved. The TAPIRSD is suitable for system transient analysis of different types of HPMRs and provides an optional tool for the system safety characteristics analysis of HPMR.
Comparative Thermodynamic Analysis of the Performance of an Organic Rankine Cycle Using Different Working Fluids
Authors: Méndez-Cruz Ladislao Eduardo , Gutiérrez-Limón Miguel Ángel , Lugo-Méndez Helen , Lugo-Leyte Raúl , Lopez-Arenas Teresa , Sales-Cruz Mauricio
Published: April 2022

Today, the study of thermal systems that take advantage of residual thermal sources in the power generation sector is of great importance to mitigate environmental impact and promote sustainable alternatives in this sector. Among these alternatives, the organic Rankine cycle (ORC) is of great relevance since it allows taking advantage of residual energy sources at low temperatures. This work presents a methodology to evaluate the feasibility of using a refrigerant as a working fluid in an organic Rankine cycle based on an exergetic viability index. As a case study, R134a, R600a, R245fa, and R123 refrigerants were considered. A residual thermal source was used that came from the Hybrid Cycle Plant of the Valley of Mexico. Thermodynamic analysis was performed to determine generated power, thermal efficiency, refrigerant mass flow, pinch point temperature difference, specific steam consumption, unused thermal exergy flow, exergy efficiency, and total heat transfer requirement. The weighted average of the differences between these indicators, the global warming index, and the ozone depletion potential relative to the most favorable indicator corresponded to the definition of the exergetic viability index of the refrigerant. The results indicate that the ORC operating at condensing temperatures of 25, 35, and 45 °C with R245fa shows the highest rate of exergetic viability despite not generating the greatest amount of power and being one of the refrigerants with the highest total heat transfer requirement. Finally, at condensing temperatures above 45 °C, it is observed that R600a is exergetically the most viable refrigerant used in the ORC.
Waste Mandarin Peel as an Eco-Friendly Water-Based Drilling Fluid Additive
Authors: Medved Igor , Gaurina-Međimurec Nediljka , Novak Mavar Karolina , Mijić Petar
Published: April 2022

Drilling fluid represents the most important fluid that must fulfill numerous important assignments during drilling operations. Many commercially available additives for water-based drilling fluid fall into the category of non-degradable and environmentally hazardous materials. Significant development in this area can be made by using biodegradable materials as additives in drilling fluids. The objective of this study was to determine whether mandarin peel powder particle size affects the properties of the drilling fluid. In this paper, mandarin peel was used in the form of a dry powder divided into particle sizes smaller than 0.1 mm, and between 0.1 mm and 0.16 mm. Mandarin peel powder was added to a water-based drilling fluid in four different concentrations (0.5, 1, 1.5, and 2% by volume of water). By increasing the mandarin peel powder concentration, the API filtration reduced up to 42%, PPT filtration significantly decreased up to 61.54%, while the rheological parameters generally increased but remained within acceptable limits. It is determined that the optimal concentration of mandarin peel powder is up to 1.5% by volume of water.
A Novel Method for the Estimation of Higher Heating Value of Municipal Solid Wastes
Authors: Dong Weiguo , Chen Zhiwen , Chen Jiacong , Ting Zhao Jia , Zhang Rui , Ji Guozhao , Zhao Ming
Published: April 2022

The measurement of the higher heating value (HHV) of municipal solid wastes (MSWs) plays a key role in the disposal process, especially via thermochemical approaches. An optimized multi-variate grey model (OBGM (1, N)) is introduced to forecast the MSWs’ HHV to high accuracy with sparse data. A total of 15 cities and MSW from the respective city were considered to develop and verify the multi-variant models. Results show that the most accurate model was POBGM (1, 5) of which the least error measured 5.41% MAPE (mean absolute percentage error). Ash, being a major component in MSW, is the most important factor affecting HHV, followed by volatiles, fixed carbon and water contents. Most data can be included by using the prediction interval (PI) method with 95% confidence intervals. In addition, the estimations indicated that the MAPE from estimating the HHV for various MSW samples, collected from various cities, were in the range of 3.06–34.50%, depending on the MSW sample.
Machine Learning Based Prediction for the Response of Gas Discharge Tube to Damped Sinusoid Signal
Authors: Wang Jinjin , Cui Zhitong , Chen Zhiqiang , Dong Yayun , Nie Xin
Published: April 2022

In order to predict the circuit response of a Gas Discharge Tube (GDT) to an electromagnetic pulse, a “black box” model for a GDT based on a machine learning method is proposed and validated in this paper.Firstly, the machine learning model of the Elman neural network is established by taking advantage of the existing measurement data to dampen the sinusoid signal, and then the established model is adopted to predict the response waveform of an unknown injection current grade and frequency.Without considering the complex physical parameters and dynamic behavior of GDTs, the Elman neural network modeling method is simpler than the existing physical or Pspice model.Validation experiments show a good agreement between the predicted and the measured waveforms.