bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiovascular Magnetic Resonance in Peripartum Cardiomyopathy: Comparison with Idiopathic Dilated Cardiomyopathy
Authors: Petryka-Mazurkiewicz Joanna , Kryczka Karolina , Mazurkiewicz Łukasz , Miłosz-Wieczorek Barbara , Śpiewak Mateusz , Marczak Magdalena , Henzel Jan , Grzybowski Jacek , Demkow Marcin , Dzielińska Zofia
Published: September 2021

Background: Peripartum (PPCM) and dilated (DCM) cardiomyopathies are distinct forms of cardiac disease that share certain aspects in clinical presentation. Aim: We hypothesized that different cardiac structural changes underlie PPCM and DCM, and we aimed to investigate them with cardiovascular magnetic resonance (CMR). Methods: We included 21 PPCM patients (30.5 ± 5.9 years) and 30 female DCM patients (41.5 ± 16.8 years) matched for left ventricular ejection fraction. Biventricular and biatrial volumetric and functional parameters were assessed along with ventricular and atrial strain indices based on feature-tracking techniques. The presence of late gadolinium enhancement (LGE) was also assessed. Results: In PPCM, the left ventricular (LV) stroke volume index was lower (p = 0.04), right atrial (RA) minimal and pre-systolic volumes were higher (p < 0.01 and p = 0.02, respectively), and the total RA ejection fraction was lower (p = 0.02) in comparison to DCM. Moreover, in PPCM, the LV global longitudinal strain (p = 0.03), global circumferential strain rate (p = 0.04), and global longitudinal strain rate (p < 0.01) were less impaired than in DCM. Both PPCM and DCM patients with LGE had more dilated ventricles and more impaired LV and left atrial function than in PPCM and DCM patients without LGE. Conclusions: Subtle differences appear on CMR between PPCM and DCM. Most importantly, the RA is larger and more impaired, and LV global longitudinal strain is less reduced in PPCM than in DCM. Furthermore, similarly to DCM, PPCM patients with LGE have more dilated and impaired ventricles than patients without LGE.
Intergenic SNPs in Obstructive Sleep Apnea Syndrome: Revealing Metabolic, Oxidative Stress and Immune-Related Pathways
Authors: Raptis Dimitrios G. , Vavougios George D. , Siachpazidou Dimitra I. , Pastaka Chaido , Xiromerisiou Georgia , Gourgoulianis Konstantinos I. , Malli Foteini
Published: September 2021

There is strong evidence supporting the contribution of genetic factors to obstructive sleep apnea syndrome (OSAHS) susceptibility. In the current study we analyzed both in a clinical cohort and in silico, four single nucleotide polymorphisms SNPs, rs999944, rs75108997, rs35329661 and rs116133558 that have been associated with OSAHS. In 102 patients with OSAHS and 50 healthy volunteers, genetic testing of the above polymorphisms was performed. Polymorphism rs116133558 was invariant in our study population, whereas polymorphism rs35329661 was more than 95% invariant. Polymorphism rs999944 displayed significant (>5%) variance in our study population and was used in the binary logistic regression model. In silico analyses of the mechanism by which these three SNPs may affect the pathophysiology of OSAHS revealed a transcriptomic network of 274 genes. This network was involved in multiple cancer-associated gene signatures, as well as the adipogenesis pathway. This study, uncover a regulatory network in OSAHS using transcriptional targets of intergenic SNPs, and map their contributions in the pathophysiology of the syndrome on the interplay between adipocytokine signaling and cancer-related transcriptional dysregulation.
Splitting Choice and Computational Complexity Analysis of Decision Trees
Authors: Zhao Xin , Nie Xiaokai
Published: September 2021

Some theories are explored in this research about decision trees which give theoretical support to the applications based on decision trees. The first is that there are many splitting criteria to choose in the tree growing process. The splitting bias that influences the criterion chosen due to missing values and variables with many possible values has been studied. Results show that the Gini index is superior to entropy information as it has less bias regarding influences. The second is that noise variables with more missing values have a better chance to be chosen while informative variables do not. The third is that when there are many noise variables involved in the tree building process, it influences the corresponding computational complexity. Results show that the computational complexity increase is linear to the number of noise variables. So methods that decompose more information from the original data but increase the variable dimension can also be considered in real applications.
Machine Learning-Assisted Measurement Device-Independent Quantum Key Distribution on Reference Frame Calibration
Authors: Zhang Sihao , Liu Jingyang , Zeng Guigen , Zhang Chunhui , Zhou Xingyu , Wang Qin
Published: September 2021

In most of the realistic measurement device-independent quantum key distribution (MDI-QKD) systems, efficient, real-time feedback controls are required to maintain system stability when facing disturbance from either external environment or imperfect internal components. Traditionally, people either use a “scanning-and-transmitting” program or insert an extra device to make a phase reference frame calibration for a stable high-visibility interference, resulting in higher system complexity and lower transmission efficiency. In this work, we build a machine learning-assisted MDI-QKD system, where a machine learning model—the long short-term memory (LSTM) network—is for the first time to apply onto the MDI-QKD system for reference frame calibrations. In this machine learning-assisted MDI-QKD system, one can predict out the phase drift between the two users in advance, and actively perform real-time phase compensations, dramatically increasing the key transmission efficiency. Furthermore, we carry out corresponding experimental demonstration over 100 km and 250 km commercial standard single-mode fibers, verifying the effectiveness of the approach.
Interactive Multiobjective Procedure for Mixed Problems and Its Application to Capacity Planning
Authors: Nowak Maciej , Trzaskalik Tadeusz , Sitarz Sebastian
Published: September 2021

A problem that appears in many decision models is that of the simultaneous occurrence of deterministic, stochastic, and fuzzy values in the set of multidimensional evaluations. Such problems will be called mixed problems. They lead to the formulation of optimization problems in ordered structures and their scalarization. The aim of the paper is to present an interactive procedure with trade-offs for mixed problems, which helps the decision-maker to make a final decision. Its basic advantage consists of simplicity: after having obtained the solution proposed, the decision-maker should determine whether it is satisfactory and if not, how it should be improved by indicating the criteria whose values should be improved, the criteria whose values cannot be made worse, and the criteria whose values can be made worse. The procedure is applied in solving capacity planning treated as a mixed dynamic programming problem.
Using Analytics to Identify When Course Materials Are Accessed Relative to Online Exams during Digital Education
Authors: Guzsvinecz Tibor , Szűcs Judit
Published: September 2021

Face-to-face education has changed to blended or distance teaching due to the COVID-19 pandemic. Since education took a digital format, it can be investigated when course materials are accessed relative to online exams: are they opened before exams or during them? Therefore, four subjects were chosen for investigation at the University of Pannonia: one theoretical, one practical, and two that are both theoretical and practical were selected. Two groups of non-repeater 2nd-semester students and two groups of non-repeater 5th-semester students attended these classes. Slides were uploaded to the university’s Moodle system, while videos were uploaded to YouTube. Their analytics were used for the investigation. The analyses were conducted in five groups of days relative to the exam day. According to the results, students studied throughout the semester for the normal exam in most cases, while they studied a day before the supplementary one. For cheating, the 2nd-semester students used significantly more slides, while 5th-semester students used significantly more videos. Even with cheating, the students in their 2nd semester received significantly worse marks by 26.06% than those who were in their 5th semester.
Is It a Cube? Common Visual Perception of Cuboid Drawings
Authors: Hoffmann Miklós , Németh László
Published: September 2021

A cube is one of the most fundamental shapes we can draw and can observe from a drawing. The two visualization methods most commonly applied in mathematics textbooks and education are the axonometric and the perspective representations. However, what we see in the drawing is really a cube or only a general cuboid (i.e., a polyhedron with different edge lengths). In this experimental study, 153 first-year ( 19–20-year-old) students, two-thirds of them being female, were asked to interactively adjust a cuboid figure until they believe what they see is really a cube. We were interested in how coherently people, who are actually students of arts studies and engineering with advanced spatial perception skills in most cases, evaluate these drawings. What we have experienced is that for most people there is a common visual understanding of seeing a cube (and not a general cuboid). Moreover, this common sense is surprisingly close to the conventions applied in axonometric drawings, and to the theoretical, geometric solution in the case of three-point perspective drawings, which is the most realistic visualization method.
Milwaukee Makes a Difference: Recognizing Gifted Students from Culturally and Linguistically Diverse Families
Authors: O’Brien Susan , Coleman Mary Ruth , Schuller Dorothy L. , López Martha A. , Díaz German
Published: September 2021

Gifted education today faces a significant challenge in reaching equity as well as excellence. This is reflected in the disproportionate underrepresentation of children from Black, Hispanic, Native, and low-income families. This pattern of underrepresentation within programs for students with gifts and talents is pervasive and pernicious and impacts gifted education programming across all 50 states in the United States of America. This article describes the efforts of Milwaukee Public Schools, a large urban school district in Wisconsin, to address the need for both equity and excellence within their gifted education programming. The U~STRARS~PLUS model formed the foundation for changing the culture of the schools from “at risk” to “at potential”. Dedicated leadership and the combination of securing external support, developing internal trust, and building capacity across the district were critical to creating a strength-based focus within the schools. While the journey is not over, the authors hope that others can learn from Milwaukee’s experiences.
Emergency Teaching–Learning Methods (ETLM) during COVID-19: Lessons Learned from Sri Lanka
Authors: Gangahagedara Ruchira , Karunarathna Muditha , Athukorala Wasantha , Subasinghe Shyamantha , Ekanayake Prabath
Published: September 2021

Sri Lanka’s education system was suddenly shifted from classroom-based free education to online-based distance learning as an emergency teaching and learning method (ETLM) in response to the COVID-19 pandemic lockdown. This study examines how various stakeholders used online-based distant learning as an ETLM, and highlights the lessons learned from such a transition in Sri Lanka through a case study of the Kandy education zone (KEZ), in response to the country’s COVID-19 pandemic lockdown. We obtained the data through a questionnaire survey from 19 schools in KEZ, selecting the teachers, students, and parents as a survey sample. The findings revealed that nearly 64.7% of teachers used social media for the teaching–learning process (TLP), 27.9% used standard online teaching platforms, and only 7.4% used traditional teaching methods during the pandemic lockdown. Additionally, 36.5% of teachers and 41.2% of students favored the WhatsApp mobile application for the TLP, while others preferred other applications. However, during the COVID-19 lockdown, most of the less privileged schools in the peripheral areas of the KEZ adopted traditional teaching methods (TTM). The extent of the gap in ETLM adaptation and the driving factors that led to observable discrepancies between privileged and non-privileged schools, even in the urban settings of the KEZ, are also discussed in this study. These findings are significant in terms of educational policy making and management. Overall, this research contributes to understanding the ETLM adaptation of the KEZ by proposing policy directions that policymakers and other higher education authorities in the country should consider in an emergency.
Students’ Self-Organization of the Learning Environment during a Blended Knowledge Creation Course
Authors: Ritella Giuseppe , Loperfido Fedela Feldia
Published: September 2021

Learner-centered blended learning approaches, such as Knowledge Creation, emphasize the self-organizing characteristic of thought and action, and value the students’ autonomy and self-regulation during the engagement in collaborative learning tasks. In blended contexts, the students need to organize their learning paths within a complex environment, including multiple online and offline learning spaces. This process of self-organization during courses based on the Knowledge Creation approach is currently an overlooked topic of research. The present case study is aimed at addressing this research gap by providing an in-depth understanding of the collaborative self-organization of a group of five undergraduate students participating in an interdisciplinary media design course. The course was designed according to the Knowledge Creation approach and was carried out before the start of the COVID-19 pandemic. The dialogical theory of the chronotope and the theory of cultural models constitute the main theoretical tools for the research. We used qualitative methods inspired by ethnography, including participant observation, in addition to the collection and analysis of audio-visual records, stimulated recall interviews, and learning diaries completed by the students. The findings show that the group self-organization changed across different phases of the collaborative task and involved the development of specific practices of self-organization. Cultural models associated with the task contributed to determine the students’ choices related to self-organization.
Anonymous Sealed-Bid Auction on Ethereum
Authors: Sharma Gaurav , Verstraeten Denis , Saraswat Vishal , Dricot Jean-Michel , Markowitch Olivier
Published: September 2021

In a competitive market, online auction systems enable optimal trading of digital products and services. Bidders can participate in existing blockchain-based auctions while protecting the confidentiality of their bids in a decentralized, transparent, secure, and auditable manner. However, in a competitive market, parties would prefer not to disclose their interests to competitors, and to remain anonymous during auctions. In this paper, we firstly analyze the specific requirements for blockchain-based anonymous fair auctions. We present a formal model tailored to study auction systems that facilitate anonymity, as well as a generic protocol for achieving bid confidentiality and bidder anonymity using existing cryptographic primitives such as designated verifier ring signature. We demonstrate that it is secure using the security model we presented. Towards the end, we demonstrate through extensive simulation results on Ethereum blockchain that the proposed protocol is practical and has minimal associated overhead. Furthermore, we discuss the complexity and vulnerabilities that a blockchain environment might introduce during implementation.
Practices of Motivators in Adopting Agile Software Development at Large Scale Development Team from Management Perspective
Authors: Khan Rashid Ali , Abrar Muhammad Faisal , Baseer Samad , Majeed Muhammad Faran , Usman Muhammad , Ur Rahman Shams , Cho You-Ze
Published: September 2021

Agile software development methodologies have become the most popular software development methods in the last few years. These methodologies facilitate rapid development. The low cost and prioritized user satisfaction make these methodologies more attractive. These methodologies were also intended for small scale developmental teams. Therefore, challenges were encountered when these methodologies were used in large-scale development teams. This study was based on the identification of factors which were discovered in our previous study. Some of the factors included “leadership strong commitment and team autonomy”, “cooperative organizational culture”, and “team competency—agile development expertise”. A total of 147 practices were identified in this study via a systematic literature review. These practices will help practitioners and project managers to adopt agile software methodologies and encourage them to the enhance them.
A Survey on Energy Harvesting Wireless Networks: Channel Capacity, Scheduling, and Transmission Power Optimization
Authors: Sarkar Nurul I. , Singh Dev Pal , Ahmed Monjur
Published: September 2021

This paper presents a survey on energy harvesting (EH) wireless communication networks focusing on channel capacity, transmission schemes, and power optimization. While many network researchers focus on energy management policies addressing the intermittency and randomness of the EH processes, but the channel capacity, and transmission power optimization have not been fully explored yet. In this paper, we provide a review and analysis of channel capacity, offline and online transmission schemes, and power optimization from an information theory perspective. By reviewing and analyzing wireless networking literature, we found that EH is a technologically feasible and economically viable paradigm for cost-effectiveness in the design and deployment of next-generation wireless networks. Finally, we identify open research problems and future research directions in the emerging field of EH wireless networks. We expect this study to stimulate more research endeavors to build energy-efficient scalable next-generation wireless network systems.
Transmission Network Expansion Planning Considering Wind Power and Load Uncertainties Based on Multi-Agent DDQN
Authors: Wang Yuhong , Zhou Xu , Shi Yunxiang , Zheng Zongsheng , Zeng Qi , Chen Lei , Xiang Bo , Huang Rui
Published: September 2021

This paper presents a multi-agent Double Deep Q Network (DDQN) based on deep reinforcement learning for solving the transmission network expansion planning (TNEP) of a high-penetration renewable energy source (RES) system considering uncertainty. First, a K-means algorithm that enhances the extraction quality of variable wind and load power uncertain characteristics is proposed. Its clustering objective function considers the cumulation and change rate of operation data. Then, based on the typical scenarios, we build a bi-level TNEP model that includes comprehensive cost, electrical betweenness, wind curtailment and load shedding to evaluate the stability and economy of the network. Finally, we propose a multi-agent DDQN that predicts the construction value of each line through interaction with the TNEP model, and then optimizes the line construction sequence. This training mechanism is more traceable and interpretable than the heuristic-based methods. Simultaneously, the experience reuse characteristic of multi-agent DDQN can be implemented in multi-scenario TNEP tasks without repeated training. Simulation results obtained in the modified IEEE 24-bus system and New England 39-bus system verify the effectiveness of the proposed method.
Development of a Low-Cost Data Acquisition System for Very Short-Term Photovoltaic Power Forecasting
Authors: Bassous Guilherme Fonseca , Calili Rodrigo Flora , Barbosa Carlos Hall
Published: September 2021

The rising adoption of renewable energy sources means we must turn our eyes to limitations in traditional energy systems. Intermittency, if left unaddressed, may lead to several power-quality and energy-efficiency issues. The objective of this work is to develop a working tool to support photovoltaic energy forecast models for real-time operation applications. The current paradigm of intra-hour solar-power forecasting is to use image-based approaches to predict the state of cloud composition for short time horizons. Since the objective of intra-minute forecasting is to address high-frequency intermittency, data must provide information on and surrounding these events. For that purpose, acquisition by exception was chosen as the guiding principle. The system performs power measurements at 1 Hz frequency, and whenever it detects variations over a certain threshold, it saves the data 10 s before and 4 s after the detection point. A multilayer perceptron neural network was used to determine its relevance to the forecasting problem. With a thorough selection of attributes and network structures, the results show very low error with R2 greater than 0.93 for both input variables tested with a time horizon of 60 s. In conclusion, the data provided by the acquisition system yielded relevant information for forecasts up to 60 s ahead.
Research on Machining Workshop Batch Scheduling Incorporating the Completion Time and Non-Processing Energy Consumption Considering Product Structure
Authors: Li Nailiang , Feng Caihong
Published: September 2021

Energy-saving scheduling is a well-known issue in the manufacturing system. The flexibility of the workshop increases the difficulty of scheduling. In the workshop schedule, considering the collaborative optimization of multi-level structure product production and energy consumption has certain practical significance. The process sequence of parts and components should be consistent with the assembly sequence. Additionally, the non-production energy consumption (NPEC) (such as the energy consumption of workpiece handling, equipment standby, and workpiece conversion) generated by the auxiliary machining operations, which make up the majority of the total energy consumption, should not be ignored. A sub-batch priority is set according to the upper and lower coupling relationship in the product structure. A bi-objective batch scheduling model that minimizes the total energy consumption and the total completion time is developed, and the multi-objective gray wolf optimizer (MOGWO) is employed as the solution to obtain the optimal schedule scheme. A case study is performed to demonstrate the potential possibilities concerning NPEC in regard to reducing the total energy consumption and to show the effectiveness of the algorithm. Compared with the traditional optimization model, the joint optimization of NPEC and PEC can reduce the energy consumption of standby and handling by 9.95% and 22.28%, respectively.
Thermodynamic Analysis of a Hybrid System Coupled Cooling, Heating and Liquid Dehumidification Powered by Geothermal Energy
Authors: Xu Aixiang , Xu Mengjin , Xie Nan , Xiong Yawen , Huang Junze , Cai Yingjie , Liu Zhiqiang , Yang Sheng
Published: September 2021

The utilization of geothermal energy is favorable for the improvement of energy efficiency. A hybrid system consisting of a seasonal heating and cooling cycle, an absorption refrigeration cycle and a liquid dehumidification cycle is proposed to meet dehumidification, space cooling and space heating demands. Geothermal energy is utilized effectively in a cascade approach. Six performance indicators, including humidity efficiency, enthalpy efficiency, moisture removal rate, coefficient of performance, cooling capacity, and heating capacity, are developed to analyze the proposed system. The effect of key design parameters in terms of desiccant concentration, air humidity, air temperature, refrigeration temperature and segment temperature on the performance indicators are investigated. The simulation results indicated that the increase of the desiccant concentration makes the enthalpy efficiency, the coefficient of performance, the moisture removal rate and the cooling capacity increase and makes the humidity efficiency decrease. With the increase of air humidity, the humidity efficiency and moisture removal rate for the segment temperatures from 100 to 130 °C are approximately invariant. The decreasing rates of the humidity efficiency and the moisture removal rate with the segment temperature of 140 °C increases respectively. Six indicators, except the cooling capacity and heating capacity, decrease with an increase of air temperature. The heating capacity decreases by 49.88% with the reinjection temperature increasing from 70 to 80 °C. This work proposed a potential system to utilize geothermal for the dehumidification, space cooling and space heating effectively.
Estimation of the Influence of Compressed Hydrogen on the Mechanical Properties of Pipeline Steels
Authors: Bolobov Victor I. , Latipov Il’nur U. , Popov Gregory G. , Buslaev George V. , Martynenko Yana V.
Published: September 2021

Consideration of the possibility of transporting compressed hydrogen through existing gas pipelines leads to the need to study the regularities of the effect of hydrogen on the mechanical properties of steels in relation to the conditions of their operation in pipelines (operating pressure range, stress state of the pipe metal, etc.). This article provides an overview of the types of influence of hydrogen on the mechanical properties of steels, including those used for the manufacture of pipelines. The effect of elastic and plastic deformations on the intensity of hydrogen saturation of steels and changes in their strength and plastic deformations is analyzed. An assessment of the potential losses of transported hydrogen through the pipeline wall as a result of diffusion has been made. The main issues that need to be solved for the development of a scientifically grounded conclusion on the possibility of using existing gas pipelines for the transportation of compressed hydrogen are outlined.
A Meta-Modeling Power Consumption Forecasting Approach Combining Client Similarity and Causality
Authors: Kontogiannis Dimitrios , Bargiotas Dimitrios , Daskalopulu Aspassia , Tsoukalas Lefteri H.
Published: September 2021

Power forecasting models offer valuable insights on the electricity consumption patterns of clients, enabling the development of advanced strategies and applications aimed at energy saving, increased energy efficiency, and smart energy pricing. The data collection process for client consumption models is not always ideal and the resulting datasets often lead to compromises in the implementation of forecasting models, as well as suboptimal performance, due to several challenges. Therefore, combinations of elements that highlight relationships between clients need to be investigated in order to achieve more accurate consumption predictions. In this study, we exploited the combined effects of client similarity and causality, and developed a power consumption forecasting model that utilizes ensembles of long short-term memory (LSTM) networks. Our novel approach enables the derivation of different representations of the predicted consumption based on feature sets influenced by similarity and causality metrics. The resulting representations were used to train a meta-model, based on a multi-layer perceptron (MLP), in order to combine the results of the LSTM ensembles optimally. This combinatorial approach achieved better overall performance and yielded lower mean absolute percentage error when compared to the standalone LSTM ensembles that do not include similarity and causality. Additional experiments indicated that the combination of similarity and causality resulted in more performant models when compared to implementations utilizing only one element on the same model structure.
Optimization of a Mixed Refrigerant Based H2 Liquefaction Pre-Cooling Process and Estimate of Liquefaction Performance with Varying Ambient Temperature
Authors: Jackson Steven , Brodal Eivind
Published: September 2021

Hydrogen used as an energy carrier can provide an important route to the decarbonization of energy supplies, but realizing this opportunity will require both significantly increased production and transportation capacity. One route to increased transportation capacity is the shipping of liquid hydrogen, but this requires an energy-intensive liquefaction step. Recent study work has shown that the energy required in this process can be reduced through the implementation of new and improved process designs, but since all low-temperature processes are affected by the available heat-sink temperature, local ambient conditions will also have an impact. The objective of this work is to identify how the energy consumption associated with hydrogen liquefaction varies with heat-sink temperature through the optimization of design parameters for a next-generation mixed refrigerant based hydrogen liquefaction process. The results show that energy consumption increases by around 20% across the cooling temperature range 5 to 50 °C. Considering just the range 20 to 30 °C, there is a 5% increase, illustrating the significant impact ambient temperature can have on energy consumption. The implications of this work are that the modelling of different liquified hydrogen based energy supply chains should take the impact of ambient temperature into account.
Living in the “Age of Humans”. Envisioning CAD Architecture for the Challenges of the Anthropocene—Energy, Environment, and Well-Being
Authors: Januszkiewicz Krystyna , Paszkowska-Kaczmarek Natalia , Duguma Fekadu Aduna , Kowalski Karol G.
Published: September 2021

The Anthropocene thesis poses new challenges to human activity on the planet. These challenges also apply to the built environment. Climate change will increase existing threats, and create new ones, for both human and natural systems. Above all, the built environment is expected to provide structural stability, access to water necessary for life, and safe production of clean energy. This research-by-design was focused on designing an adaptive built environment for Anthropocene societies and the maintenance of their well-being, and on envisioning and conceptualizing new architectural solutions based on multidisciplinary knowledge and CAD parametric design methods and tools. The conceptual designs are the result of these studies. These visions show how wind loads can be reduced, water can be stored, diverse energy sources can be integrated into one work of architecture, and thermal comfort can be provided to support local communities and the life of the environment in the belief that the coexistence of species on the planet will happen. They also illustrate how humanity will be able to use the Earth and its atmosphere as an energy producer and conductor and create a global, wireless, non-commercial energy network, accessible to all.
Frequency Coordinated Control Strategy for an HVDC Sending-End System with Wind Power Integration Based on Fuzzy Logic Control
Authors: Wang Yuhong , Zhu Jie , Zeng Qi , Zheng Zongsheng , Yu Guangyuan , Yin Aihui
Published: September 2021

Under the background of high wind power permeability, the frequency regulation capability of high voltage direct current (HVDC) sending-end system tends to deteriorate. For this reason, this paper regards the wind farm (WF) and HVDC as a combined frequency regulation system, and a fuzzy-based coordinated control strategy is proposed for the cooperation of HVDC and WF to participate in frequency regulation. First of all, at a system level, in order to realize the dynamic cooperation of the WF and the HVDC to participate in frequency regulation, two fuzzy logic controllers (FLCs) are designed to determine the total power support of the combined system and the participation coefficient of the WF in the frequency regulation according to the frequency characteristics of the sending-end system and the operation state of the WF, respectively. Secondly, at the WF level, considering the rotating kinetic energy and capacity of the wind turbines (WTs), a power allocation strategy is proposed to maximize the utilization of the frequency regulation capacity of the grid-connected WTs in WF. Finally, based on the fast power regulation of HVDC, an active secondary frequency drop (SFD) suppression strategy is proposed to avoid the possible SFD caused by the rotor speed recovery of WTs. The simulation results show that the proposed strategy can make full use of the frequency regulation ability of the WF and HVDC, and can effectively improve the frequency characteristics of the HVDC sending-end system.
Design of Machine Learning Prediction System Based on the Internet of Things Framework for Monitoring Fine PM Concentrations
Authors: Wang Shun-Yuan , Lin Wen-Bin , Shu Yu-Chieh
Published: September 2021

In this study, a mobile air pollution sensing unit based on the Internet of Things framework was designed for monitoring the concentration of fine particulate matter in three urban areas. This unit was developed using the NodeMCU-32S microcontroller, PMS5003-G5 (particulate matter sensing module), and Ublox NEO-6M V2 (GPS positioning module). The sensing unit transmits data of the particulate matter concentration and coordinates of a polluted location to the backend server through 3G and 4G telecommunication networks for data collection. This system will complement the government’s PM2.5 data acquisition system. Mobile monitoring stations meet the air pollution monitoring needs of some areas that require special observation. For example, an AIoT development system will be installed. At intersections with intensive traffic, it can be used as a reference for government transportation departments or environmental inspection departments for environmental quality monitoring or evacuation of traffic flow. Furthermore, the particulate matter distributions in three areas, namely Xinzhuang, Sanchong, and Luzhou Districts, which are all in New Taipei City of Taiwan, were estimated using machine learning models, the data of stationary monitoring stations, and the measurements of the mobile sensing system proposed in this study. Four types of learning models were trained, namely the decision tree, random forest, multilayer perceptron, and radial basis function neural network, and their prediction results were evaluated. The root mean square error was used as the performance indicator, and the learning results indicate that the random forest model outperforms the other models for both the training and testing sets. To examine the generalizability of the learning models, the models were verified in relation to data measured on three days: 15 February, 28 February, and 1 March 2019. A comparison between the model predicted and the measured data indicates that the random forest model provides the most stable and accurate prediction values and could clearly present the distribution of highly polluted areas. The results of these models are visualized in the form of maps by using a web application. The maps allow users to understand the distribution of polluted areas intuitively.
New and Emerging Insect Pest and Disease Threats to Forest Plantations in Vietnam
Authors: Thu Pham Quang , Quang Dao Ngoc , Chi Nguyen Minh , Hung Tran Xuan , Binh Le Van , Dell Bernard
Published: September 2021

The planted forest area in Vietnam increased from 3.0 to 4.4 million hectares in the period 2010–2020, but the loss of productivity from pests and diseases continues to be a problem. During this period, frequent and systematic plantation forest health surveys were conducted on 12 native and 4 exotic genera of trees as well as bamboo across eight forest geographic regions of Vietnam. Damage caused by insects and pathogens was quantified in the field and laboratory in Hanoi. The threats of greatest concern were from folivores (Antheraea frithi, Arthroschista hilaralis, Atteva fabriciella, Hieroglyphus tonkinensis, Lycaria westermanni,Krananda semihyalina, and Moduza procris), wood borers (Batocera lineolata, Euwallacea fornicatus, Tapinolachnus lacordairei, Xyleborus perforans, and Xystrocera festiva), sap-sucking insects (Aulacaspis tubercularis and Helopeltis theivora) and pathogens (Ceratocystis manginecans, Fusarium solani, and Phytophthora acaciivora). The number of new and emerging pests and pathogens increased over time from 2 in 2011 to 17 in 2020, as the damage became more widespread. To manage these pests and diseases, it is necessary to further invest in the selection and breeding of resistant genotypes, improve nursery hygiene and silvicultural operations, and adopt integrated pest management schemes. Consideration should be given to developing forest health monitoring protocols for forest reserves and other special-purpose forests.
Phase Dislocations in Hollow Core Waveguides
Authors: Pryamikov Andrey
Published: September 2021

This paper discusses the basic concepts of phase dislocations and vortex formation in the electric fields of fundamental air core mode of hollow core waveguides with specific types of rotational symmetry of the core-cladding boundary. Analysis of the behavior of the electric field phase in the transmission bands shows that the mechanism of light localization in the hollow core waveguides with discrete rotational symmetry of the core-cladding boundary cannot be completely described by the ARROW model. For an accurate description of the phase behavior, it is necessary to account for phase jumps of the magnitude of π when passing through the phase dislocations.
SARS-CoV-2 Pandemic and Food Safety Oversight: Implications in Canada and Coping Strategies
Authors: Charlebois Sylvain , Music Janet
Published: September 2021

The SARS-CoV-2 pandemic has created enormous societal disruptions in the Western world, including Canada, with serious implications for food safety. Since the start of the pandemic, many scholars have investigated the issue of food safety through different lenses. In this review, two research thrusts were identified, the epidemiology of the virus and food safety oversight. Both were challenged by the pandemic in Canada and elsewhere. In this paper, we first present how Canada experienced the pandemic. We then present how epidemiology and food safety oversight were affected by the virus and how the spread exposed gaps in Canada’s food safety system. We explain how Canada was not adequately prepared to face the food safety challenges posed by SARS-CoV-2. The review ends with an explanation on how risk perceptions will be altered by the pandemic in Canada and how food safety systems will adjust to better anticipate systemic risks in the future.
Kinetic Study of Subcritical Water Extraction of Scopoletin, Alizarin, and Rutin from Morinda citrifolia
Authors: Jamaludin Roslina , Kim Dong-Shin , Salleh Liza Md , Lim Sang-Bin
Published: September 2021

Noni fruits (Morinda citrifolia) are a source of phenolic bioactive compounds (scopoletin, alizarin, and rutin), which have antioxidant, antimicrobial, anticancer, and anti-inflammatory activities. In this study, subcritical water was applied to determine the extraction yields and kinetics of phenolic compounds from noni fruits. The scopoletin and alizarin yields increased with the increase in temperature from 100 to 140 °C, while that of rutin increased up to 120 °C and then decreased at 140 °C. The yields of all the compounds rapidly increased from 1 to 2 mL/min and then slightly up to 3 mL/min of water flow rate. The extraction kinetics were assessed using two mathematical models. The two-site kinetic desorption model had a better fit for all experimental conditions throughout the extraction cycle and best described the extraction kinetics of phenolic compounds from noni fruits. The diffusion coefficients of scopoletin and alizarin at 140 °C and 3 mL/min were 3.7- and 16.2-fold higher than those at 100 °C and 1 mL/min, respectively. The activation energies of alizarin were 2.9- to 8.5-fold higher than those of scopoletin at various flow rates. Thus, subcritical water could be an excellent solvent with higher extraction yields and shorter extraction times using an environmentally friendly solvent.
Natural Gums to Improve the Physicochemical Stability of Cake Creams
Authors: López-Balladares Oscar , Espinoza-Montero Patricio J. , Acosta-Sandoval Ramiro
Published: September 2021

The physicochemical properties of pastry and confectionery products greatly influence the aesthetic design of a cake topping, since they can be susceptible to physicochemical changes in a very short time, so maintaining a good appearance and texture of the topping becomes a challenge. Generally, cake creams deteriorate over time. The evaluation of the physicochemical properties of natural gums (arabic gum, tara gum, carrageenan, and pectin) is proposed in this work as a way to improve the physicochemical stability of butter-based cake creams (coverage creams) to maintain the initial appearance of the cream and to lengthen the separation time of their phases. For this purpose, some parameters related to the physicochemical stability of the cream, such as viscosity, density, bubble size, syneresis, volume and rheological behavior were measured. The result of the ANOVA and Tukey’s tests displayed significant differences for the measured parameters, which shows that natural gums substantially improve the stability of butter cream. The best natural gum found was the tara gum (TG) which improved viscosity 5.6 times with respect to that of the cream without gums (η¯ without gums = 15.49 Pa·s, η¯ with TG = 87.09 Pa·s), while the bubble size remained small, 1.6 times smaller compared to that of the cream without gum (BS¯) without gums = 57 μm, (BS¯) with TG = 35 μm), and the volume loss decreased two times when compared to that of the cream without gums ((ΔV¯) without gums = 1.57 cm3, (ΔV¯) with TG = 0.80 cm3). The cream with TG showed better rheology compared to that of the cream without gums (the cream without gums exhibited a plastic and thixotropic behavior, with permanent elastic deformation, while cream with TG exhibited thixotropic behavior without permanent elastic deformation). Finally, it was found that the cream with TG acquired a higher thixotropic index (TI) compared to that of the cream without gums (TI max. without gums = 17.40 y 71.78 q.u., TI max. with TG = 74.67 and 1559.90 q.u., at 4 °C and 25 °C, respectively) which demonstrates the effective contribution of cream with TG in 66.67% of the measured parameters.
Moroccan Strawberry Tree (Arbutus unedo L.) Fruits: Nutritional Value and Mineral Composition
Authors: Ait lhaj Zakaria , Bchitou Rahma , Gaboun Fatima , Abdelwahd Rabha , Benabdelouahab Tarik , Kabbour Mohammed Rachid , Pare Paul , Diria Ghizlane , Bakhy Khadija
Published: September 2021

The strawberry tree (Arbutus unedo L.), grown throughout the Mediterranean, produces edible fruit; as it is easily bruised, the sweet, reddish fruit is used mostly to prepare jams, marmalades and alcoholic beverages. As the genus is paraphyletic, phytochemical analysis can assist in defining the fruit composition with the species Arbutus unedo L. (A. unedo). Here we report on the carbohydrate, total sugar, protein, fat, fiber, ash, and mineral content of wild fruit, harvested from 45 specimens from five locations. The dominant nutrients were carbohydrates (78.2–84.8 g/100 g), total sugars (52.1–67.2 g/100 g) and dietary fiber (11.0–20.1 g/100 g). Other important nutrients supplied by A. unedo fruit include P, K, and Fe. The fruit was observed to contain health-promoting components providing 42 and 36%, of recommended daily allowance (RDA) for fiber and zinc, respectively, as well as iron and manganese, at levels exceeding minimum RDA. The free-sugar profile revealed high glucose followed by fructose content with minor amounts of sucrose (14, 11, and 6 g/100 g, respectively). Significant differences both between regions and within individuals were observed for several traits. The richness of fruit nutrients in A. unedo confers nutritional value and as such, a promising alternative fruit source.
Potential Probiotic Enterococcus faecium OV3-6 and Its Bioactive Peptide as Alternative Bio-Preservation
Authors: Choeisoongnern Thiwanya , Sirilun Sasithorn , Waditee-Sirisattha Rungaroon , Pintha Komsak , Peerajan Sartjin , Chaiyasut Chaiyavat
Published: September 2021

Probiotic Enterococcus faecium OV3-6 and its secreted active peptide were characterized and investigated. The strain survived in simulated gastric and small intestinal conditions at 88.16% and 94.33%, respectively. The safety assessment revealed that the strain was shown α-hemolysis and susceptible to most clinically relevant antibiotics, but intermediate sensitivity to erythromycin and kanamycin was found. It does not harbor any virulence genes except for the efaAfm gene. Both of its living cells and the cell-free supernatants (CFS) of the strain significantly reduced the adhesion of E. coli and S. Typhi on Caco-2 cells. The strain can regulate the secretion of pro and inflammatory cytokines, IL-6 and IL-12 and induce the secretion of anti-inflammatory IL-10 of the Caco-2 cell. The strain can prevent the growth of Gram-positive strains belonging to the genera Bacillus, Carnobacterium, Listeria, and Staphylococcus. It also presented the entP gene that involves the production of bacteriocin named enterocin P. The antimicrobial peptide was matched 40% with 50S ribosomal proteins L29 (7.325 kDa), as revealed by LC-MS/MS. This active peptide exhibits heat stability, is stable over a wide pH range of 2−10, and maintains its activity at −20 and 4 °C for 12 weeks of storage. Altogether, E. faecium OV3-6 thus has potential for consideration as a probiotic and bio-preservative for applied use as a fermented food starter culture and in functional food or feed industries.
Traceability of Sustainability and Safety in Fishery Supply Chain Management Systems Using Radio Frequency Identification Technology
Authors: Rahman Labonnah Farzana , Alam Lubna , Marufuzzaman Mohammad , Sumaila Ussif Rashid
Published: September 2021

At present, sustainability and emerging technology are the main issues in any supply chain management (SCM) sector. At the same time, the ongoing pandemic is increasing consumers’ concerns about food safety, processing, and distribution, which should meet sustainability requirements. Thus, supervision and monitoring of product quality with symmetric information traceability are important in fresh food and fishery SCM. Food safety and traceability systems based on blockchain, Internet of Things (IoT), wireless sensor networks (WSN), and radio frequency identification (RFID) provide reliability from production to consumption. This review focuses on RFID-based traceability systems in fisheries’ SCM, which have been employed globally to ensure fish quality and security, and summarizes their advantages in real-time applications. The results of this study will help future researchers to improve consumers’ trust in fisheries SCM. Thus, this review aims to provide guidelines and solutions for enhancing the reliability of RFID-based traceability in food SCM systems so to ensure the integrity and transparency of product information.