bluuebunny/crossref_metadata_2025 huggingface dataset:
Is the Large-Scale Development of Wind-PV with Hydro-Pumped Storage Economically Feasible in Greece?
Authors: Dianellou Anna , Christakopoulos Theofanis , Caralis George , Kotroni Vassiliki , Lagouvardos Konstantinos , Zervos Arthouros
Published: March 2021

The achievement of the long-term national energy targets in Greece for large-scale integration of wind and solar energy may be facilitated by the development of hydro-pumped storage projects. In light of the above, technical aspects related with the operation of the Greek power system and its ability to absorb renewable energy are analyzed in connection with the role of hydro-pumped storage and relative economic aspects. The aim of this work is to assess the potential contribution of hydro-pumped storage projects and estimate the capacity magnitude order to support large-scale wind and photovoltaic (PV) integration in Greece. For this purpose, scenarios for the Greek power system with focus on Wind and PV development, in conjunction with hydro-pumped storage capacity, are developed, and results for current situation and reference years 2030 and 2050 are presented. For the simulation, among others, high resolution mesoscale wind data for a typical year in the whole Greek territory are used for the steady state simulation of the Greek power system, in order to better estimate the power that could be generated from installed wind turbines, taking into consideration technical characteristics of a typical commercial wind turbine. Results indicate the need of gradual development of hydro-pumped storage in parallel with the large-scale integration of wind and PV capacity into the Greek power system. In addition, the feasibility of the examined scenarios is supported from the low cost of wind and PV generation. In the case of Greece, thanks to the complex morphology and hydraulic conditions of the country, hydro-pumped storage composes an efficient and low-cost storage solution.
Parameter Optimization of Hole-Slot-Type Magnetron for Controlling Resonant Frequency of Linear Accelerator 6 MeV by Reverse Engineering Technique
Authors: Yachum Nattawat , Chunjarean Somjai , Russamee Nilaped , Srisertpol Jiraphon
Published: March 2021

This paper presents the parameter optimization of a twelve-hole-slot-type magnetron based on a reverse engineering technique to improve a 6-MeV linear accelerator (LINAC) operation for fruit sterilization. The magnetron structural dimensions are measured by a coordinate measuring machine (CMM) that has tolerance on a dimension of 0.5 µm to analyze the resonant frequency with a desired operating point of the magnetron in the dominant mode. There are two methods of analysis using a proper parameter for the magnetron operation. The first method is mathematical model analysis of an equivalent resonant parallel circuit. The other is 3D-model drawing of the magnetron based on particle-in-cell (PIC) using computer simulation technology microwave studio (CST). The results are demonstrated by the position of the resonant frequency of each mode of operation, and the radius and tuner slot distance of a cavity within the structures of the magnetron cause a resonant frequency change. The suitable parameters of the voltage and magnetic field supply are desired to control a resonant frequency at 2.9982 GHz by using the Takagi–Sugeno fuzzy logic control (FLC) algorithm to control a resonant frequency at 2.9982 GHz. The results of the FLC algorithm application show that the LINAC can produce X-rays with a constant dose rate for an hour with a disturbance in the range of 38 to 42 °C temperature and 1 × 10−9 to 5 × 10−8 torr vacuum pressure.
A Disc-Type High Speed Rotary Ultrasonic Motor with Internal Contact Teeth
Authors: Qiu Jianmin , Yang Ying , Hong Xin , Vasiljev Piotr , Mazeika Dalius , Borodinas Sergejus
Published: March 2021

This paper presents a disc-type ultrasonic piezoelectric motor, which is designed for micro flying vehicles. It provides a high output rotation speed under low operating voltage, compared with common piezoelectric devices, by employing a “contact teeth” wave transmission structure. The ultrasonic motor (USM) consists of a trimorph disc stator, with triple internal contact teeth, a shaft and two hemispheric hard-wearing rotors. The operating principle of the USM is based on the superposition of the in-plane B03 vibration mode of the trimorph disc, and the first longitudinal vibration of the contact teeth. An optimization method of the stator structure parameters was proposed and validated by numerical modeling. The diameter and thickness of the stator are 20 mm and 1 mm, respectively. A prototype with the weight of 2 g was made for this experimental test. The optimal frequency of the excitation signal and the preload force are 98.5 kHz and 0.5 N, respectively. The minimum operating voltage was tested under 7.5 V and reached the speed of 225 rpm, and the maximum unloaded rotational speed of the USM reached 5172 rpm when 30 V driving voltage was applied. The maximum lifting force generated by this USM was measured as 46.1 mN, which is 2.35 times bigger than its weight.
Towards Monolithic Indium Phosphide (InP)-Based Electronic Photonic Technologies for beyond 5G Communication Systems
Authors: Mukherjee Chhandak , Deng Marina , Nodjiadjim Virginie , Riet Muriel , Mismer Colin , Guendouz Djeber , Caillaud Christophe , Bertin Hervé , Vaissiere Nicolas , Luisier Mathieu , Wen Xin , De Matos Magali , Mounaix Patrick , Maneux Cristell
Published: March 2021

This review paper reports the prerequisites of a monolithic integrated terahertz (THz) technology capable of meeting the network capacity requirements of beyond-5G wireless communications system (WCS). Keeping in mind that the terahertz signal generation for the beyond-5G networks relies on the technology power loss management, we propose a single computationally efficient software design tool featuring cutting-edge optical devices and high speed III–V electronics for the design of optoelectronic integrated circuits (OEICs) monolithically integrated on a single Indium-Phosphide (InP) die. Through the implementation of accurate and SPICE (Simulation Program with Integrated Circuit Emphasis)-compatible compact models of uni-traveling carrier photodiodes (UTC-PDs) and InP double heterojunction bipolar transistors (DHBTs), we demonstrated that the next generation of THz technologies for beyond-5G networks requires (i) a multi-physical understanding of their operation described through electrical, photonic and thermal equations, (ii) dedicated test structures for characterization in the frequency range higher than 110 GHz, (iii) a dedicated parameter extraction procedure, along with (iv) a circuit reliability assessment methodology. Developed on the research and development activities achieved in the past two decades, we detailed each part of the multiphysics design optimization approach while ensuring technology power loss management through a holistic procedure compatible with existing software tools and design flow for the timely and cost-effective achievement of THz OEICs.
Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites
Authors: Ziche Daniel , Riek Winfried , Russ Alexander , Hentschel Rainer , Martin Jan
Published: March 2021

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.
A Hybrid Approach Combining R*-Tree and k-d Trees to Improve Linked Open Data Query Performance
Authors: Sun Yuxiang , Zhao Tianyi , Yoon Seulgi , Lee Yongju
Published: March 2021

Semantic Web has recently gained traction with the use of Linked Open Data (LOD) on the Web. Although numerous state-of-the-art methodologies, standards, and technologies are applicable to the LOD cloud, many issues persist. Because the LOD cloud is based on graph-based resource description framework (RDF) triples and the SPARQL query language, we cannot directly adopt traditional techniques employed for database management systems or distributed computing systems. This paper addresses how the LOD cloud can be efficiently organized, retrieved, and evaluated. We propose a novel hybrid approach that combines the index and live exploration approaches for improved LOD join query performance. Using a two-step index structure combining a disk-based 3D R*-tree with the extended multidimensional histogram and flash memory-based k-d trees, we can efficiently discover interlinked data distributed across multiple resources. Because this method rapidly prunes numerous false hits, the performance of join query processing is remarkably improved. We also propose a hot-cold segment identification algorithm to identify regions of high interest. The proposed method is compared with existing popular methods on real RDF datasets. Results indicate that our method outperforms the existing methods because it can quickly obtain target results by reducing unnecessary data scanning and reduce the amount of main memory required to load filtering results.
The 2017 Mega-Fires in Central Chile: Impacts on Regional Atmospheric Composition and Meteorology Assessed from Satellite Data and Chemistry-Transport Modeling
Authors: Lapere Rémy , Mailler Sylvain , Menut Laurent
Published: March 2021

In January 2017, historic forest fires occurred in south-central Chile. Although their causes and consequences on health and ecosystems were studied, little is known about their atmospheric effects. Based on chemistry-transport modeling with WRF-CHIMERE, the impact of the 2017 Chilean mega-fires on regional atmospheric composition, and the associated meteorological feedback, are investigated. Fire emissions are found to increase pollutants surface concentration in the capital city, Santiago, by +150% (+30 µg/m3) for PM2.5 and +50% (+200 ppb) for CO on average during the event. Satellite observations show an intense plume extending over 2000 km, well reproduced by the simulations, with Aerosol Optical Depth at 550 nm as high as 4 on average during the days of fire activity, as well as dense columns of CO and O3. In addition to affecting atmospheric composition, meteorology is also modified through aerosol direct and indirect effects, with a decrease in surface radiation by up to 100 W/m2 on average, leading to reductions in surface temperatures by 1 K and mixing layer heights over land by 100 m, and a significant increase in cloud optical depth along the plume. Large deposition fluxes of pollutants over land, the Pacific ocean and the Andes cordillera are found, signaling potential damages to remote ecosystems.
The Possible Effect of Space Weather Factors on Various Physiological Systems of the Human Organism
Authors: Zenchenko Tatiana Alexandrovna , Breus Tamara Konstantinovna
Published: March 2021

A systematic review of heliobiological studies of the last 25 years devoted to the study of the potential influence of space weather factors on human health and well-being was carried out. We proposed three criteria (coordinates), according to which the work on solar–biospheric relations was systematized: the time scale of data sampling (years, days, hours, minutes); the level of organization of the biological system under study (population, group, individual, body system); and the degree of system response (norm, adaptation, failure of adaptation (illness), disaster (death)). This systematic review demonstrates that three parameters mentioned above are closely related in the existing heliobiological studies: the larger the selected time scale, the higher the level of estimated biological system organization and the stronger the potential response degree is. The long-term studies are devoted to the possible influence of solar activity on population disasters, i.e., significant increases in morbidity and mortality. On a daily scale, a probable effect of geomagnetic storms and other space weather events on short-term local outbreaks of morbidity is shown as well as on cases of deterioration in people functional state. On an intraday scale, in the regular functioning mode, the heart and brain rhythms of healthy people turn to be synchronized with geomagnetic field variations in some frequency ranges, which apparently is the necessary organism’s existence element. The applicability of different space weather indices at different data sampling rates, the need to take into account the contribution of meteorological factors, and the prospects for an individual approach in heliobiology are discussed. The modern important results of experiments on modeling the action of magnetic storms in laboratory conditions and the substantiation of possible theoreical mechanisms are described. These results provide an experimental and theoretical basis for studies of possible connections of space weather and human health.
C-Peptide as a Therapy for Type 1 Diabetes Mellitus
Authors: Washburn Rachel L. , Mueller Karl , Kaur Gurvinder , Moreno Tanir , Moustaid-Moussa Naima , Ramalingam Latha , Dufour Jannette M.
Published: March 2021

Diabetes mellitus (DM) is a complex metabolic disease affecting one-third of the United States population. It is characterized by hyperglycemia, where the hormone insulin is either not produced sufficiently or where there is a resistance to insulin. Patients with Type 1 DM (T1DM), in which the insulin-producing beta cells are destroyed by autoimmune mechanisms, have a significantly increased risk of developing life-threatening cardiovascular complications, even when exogenous insulin is administered. In fact, due to various factors such as limited blood glucose measurements and timing of insulin administration, only 37% of T1DM adults achieve normoglycemia. Furthermore, T1DM patients do not produce C-peptide, a cleavage product from insulin processing. C-peptide has potential therapeutic effects in vitro and in vivo on many complications of T1DM, such as peripheral neuropathy, atherosclerosis, and inflammation. Thus, delivery of C-peptide in conjunction with insulin through a pump, pancreatic islet transplantation, or genetically engineered Sertoli cells (an immune privileged cell type) may ameliorate many of the cardiovascular and vascular complications afflicting T1DM patients.
Automatic Detection of a Student’s Affective States for Intelligent Teaching Systems
Authors: Myers Mark H.
Published: March 2021

AutoTutor is an automated computer tutor that simulates human tutors and holds conversations with students in natural language. Using data collected from AutoTutor, the following determinations were sought: Can we automatically classify affect states from intelligent teaching systems to aid in the detection of a learner’s emotional state? Using frequency patterns of AutoTutor feedback and assigned user emotion in a series of pairs, can the next pair of feedback/emotion series be predicted? Through a priori data mining approaches, we found dominant frequent item sets that predict the next set of responses. Thirty-four participants provided 200 turns between the student and the AutoTutor. Two series of attributes and emotions were concatenated into one row to create a record of previous and next set of emotions. Feature extraction techniques, such as multilayer-perceptron and naive Bayes, were performed on the dataset to perform classification for affective state labeling. The emotions ‘Flow’ and ‘Frustration’ had the highest classification of all the other emotions when measured against other emotions and their respective attributes. The most common frequent item sets were ‘Flow’ and ‘Confusion’.
Citizens and Positive Energy Districts: Are Espoo and Leipzig Ready for PEDs?
Authors: Fatima Zarrin , Pollmer Uta , Santala Saga-Sofia , Kontu Kaisa , Ticklen Marion
Published: March 2021

In urban transformation, no solution works without citizen support. With increasing numbers of building technologies and large-scale urban development on its way across cities, it has become vital to keep citizens informed, engaged, and content with the new changes. This paper looks at citizen engagement in Espoo (Finland) and Leipzig (Germany), and it determines whether the cities are ready for developing and implementing positive energy districts (PEDs). The authors studied the cities’ operations and current citizen engagement methods to understand how the efforts could be combined and improved. The analysis indicated that the city of Espoo already has a well-established system that continuously promotes citizen engagement at various levels, and combining the available infrastructure with company experts on citizen participation will allow Espoo to seamlessly transition towards PEDs in the near future. The city of Leipzig has a rich experience due to several national projects and participation in an earlier European project, which enabled the city to set clearer goals for the future and modify existing citizen methods. As lighthouse cities, findings from Espoo and Leipzig are also aimed at cities across Europe and beyond to boost development of PEDs together with citizens.
Enhancement of Pentachlorophenol Removal in a Historically Contaminated Soil by Adding Ascorbic Acid to H2O2/Magnetite System
Authors: Usman Muhammad , Monfort Olivier , Haderlein Stefan , Hanna Khalil
Published: March 2021

Development of new tools to improve the efficiency of iron minerals in promoting Fenton oxidation for environmental remediation is a highly promising field. Here, we examine for the first time the role of ascorbic acid (AA) in improving the magnetite (Fe3O4)-mediated Fenton oxidation to remove pentachlorophenol (PCP) in a historically contaminated soil. Experiments were performed in batch and flow-through conditions. In batch slurry experiments, the combination of Fe3O4/AA/H2O2 removed up to 95% of PCP as compared to the 43% removal by Fe3O4/H2O2. Dissolved Fe(II) measurements and Mössbauer spectroscopy highlight the role of AA in increasing the Fe(II) generation. Therefore, its presence enabled the Fe3O4 to maintain its structural Fe(II) content even after the oxidation reaction. Despite kinetic limitations in water-saturated columns, use of Fe3O4/AA/H2O2 removed about 70% of PCP contrary to the 20% PCP removal with Fe3O4/H2O2. This oxidation performance was affected by an injection flow rate or column residence time of AA and H2O2 in columns. Thus, the presence of AA significantly improved the ability of magnetite in promoting the Fenton reaction. Owing to the crucial role of AA in the Fe(II)/Fe(III) redox cycling, a mixed-valent character of magnetite makes it a potential catalyst for Fenton oxidation of organic pollutants.
The Importance of Drosophila melanogaster Research to UnCover Cellular Pathways Underlying Parkinson’s Disease
Authors: Vos Melissa , Klein Christine
Published: March 2021

Parkinson’s disease (PD) is a complex neurodegenerative disorder that is currently incurable. As a consequence of an incomplete understanding of the etiology of the disease, therapeutic strategies mainly focus on symptomatic treatment. Even though the majority of PD cases remain idiopathic (~90%), several genes have been identified to be causative for PD, facilitating the generation of animal models that are a good alternative to study disease pathways and to increase our understanding of the underlying mechanisms of PD. Drosophila melanogaster has proven to be an excellent model in these studies. In this review, we will discuss the different PD models in flies and key findings identified in flies in different affected pathways in PD. Several molecular changes have been identified, of which mitochondrial dysfunction and a defective endo-lysosomal pathway emerge to be the most relevant for PD pathogenesis. Studies in flies have significantly contributed to our knowledge of how disease genes affect and interact in these pathways enabling a better understanding of the disease etiology and providing possible therapeutic targets for the treatment of PD, some of which have already resulted in clinical trials.
Functions of Dendritic Cells and Its Association with Intestinal Diseases
Authors: Yang Ze-Jun , Wang Bo-Ya , Wang Tian-Tian , Wang Fei-Fei , Guo Yue-Xin , Hua Rong-Xuan , Shang Hong-Wei , Lu Xin , Xu Jing-Dong
Published: March 2021

Dendritic cells (DCs), including conventional DCs (cDCs) and plasmacytoid DCs (pDCs), serve as the sentinel cells of the immune system and are responsible for presenting antigen information. Moreover, the role of DCs derived from monocytes (moDCs) in the development of inflammation has been emphasized. Several studies have shown that the function of DCs can be influenced by gut microbes including gut bacteria and viruses. Abnormal changes/reactions in intestinal DCs are potentially associated with diseases such as inflammatory bowel disease (IBD) and intestinal tumors, allowing DCs to be a new target for the treatment of these diseases. In this review, we summarized the physiological functions of DCs in the intestinal micro-environment, their regulatory relationship with intestinal microorganisms and their regulatory mechanism in intestinal diseases.
Small Activating RNAs: Towards the Development of New Therapeutic Agents and Clinical Treatments
Authors: Ghanbarian Hossein , Aghamiri Shahin , Eftekhary Mohamad , Wagner Nicole , Wagner Kay-Dietrich
Published: March 2021

Small double-strand RNA (dsRNA) molecules can activate endogenous genes via an RNA-based promoter targeting mechanism. RNA activation (RNAa) is an evolutionarily conserved mechanism present in diverse eukaryotic organisms ranging from nematodes to humans. Small activating RNAs (saRNAs) involved in RNAa have been successfully used to activate gene expression in cultured cells, and thereby this emergent technique might allow us to develop various biotechnological applications, without the need to synthesize hazardous construct systems harboring exogenous DNA sequences. Accordingly, this thematic issue aims to provide insights into how RNAa cellular machinery can be harnessed to activate gene expression leading to a more effective clinical treatment of various diseases.
Deciphering the Code: Stem Cell-Immune Function and Cardiac Regeneration
Authors: Steinhoff Gustav
Published: March 2021

The development of stem-cell-based and regenerative therapies for cardiovascular and other diseases has faced an unexpected roadblock in clinical translation [...]
Stark Width Data for Tb II, Tb III and Tb IV Spectral Lines
Authors: Dimitrijević Milan S.
Published: March 2021

A dataset of Stark widths for Tb II, Tb III and Tb IV is presented. To data obtained before, the results of new calculations for 62 Tb III lines from 5d to 6pj(6,j)o, a transition array, have been added. Calculations have been performed by using the simplified modified semiempirical method for temperatures from 5000 to 80,000 K for an electron density of 1017 cm−3. The results were also used to discuss the regularities within multiplets and a supermultiplet.
Changes in Salivary Amylase and Glucose in Diabetes: A Scoping Review
Authors: Pérez-Ros Pilar , Navarro-Flores Emmanuel , Julián-Rochina Ivan , Martínez-Arnau Francisco Miguel , Cauli Omar
Published: March 2021

Background and Objective: Diabetes mellitus (DM) is a common long-term disease which can be related with salivary amylase levels. DM has recently been associated with salivary amylase diagnostics that could further impair diagnoses in the diabetic population, as well as being an interesting alternative to traditional methods of determine glucose levels. The main advantage of this method is related to the fact that it is a fast diagnostic method. The DM population experiences changes to their metabolism which affects their salivary parameters, making this an alternative procedure for diagnosis and follow-up of the illness due to the non-invasive nature of salivary analyzes. The objective of this review is to summarize the evidence regarding the changes in salivary amylase and glucose levels, and their relationship with blood markers of glycemic control used in clinical settings such as blood glucose and glycated hemoglobin. The differences in salivary amylase levels depending on the method of saliva collection under fasting or non-fasting conditions. The changes in salivary amylase depends on the type of diabetes, the type of insulin treatment or the quality of glycemic control. Conclusions: Salivary amylase concentration is increased in diabetic patients in most of the studies and salivary glucose concentration in all studies in both fasting and non-fasting (post-prandial) conditions. Salivary amylase and glucose concentration represent potential non-invasive biomarkers to evaluate glycemic control and clinical management of diabetic patients, although it is necessary to evaluate the influence of potential modulating factors such as age, duration diseases, sex and the effects of pharmacological treatments in these outcomes which remained to be elucidated.
The Progress of Advanced Ultrasonography in Assessing Aortic Stiffness and the Application Discrepancy between Humans and Rodents
Authors: Wu Wenqian , Xie Mingxing , Qiu Hongyu
Published: March 2021

Aortic stiffening is a fundamental pathological alteration of atherosclerosis and other various aging-associated vascular diseases, and it is also an independent risk factor of cardiovascular morbidity and mortality. Ultrasonography is a critical non-invasive method widely used in assessing aortic structure, function, and hemodynamics in humans, playing a crucial role in predicting the pathogenesis and adverse outcomes of vascular diseases. However, its applications in rodent models remain relatively limited, hindering the progress of the research. Here, we summarized the progress of the advanced ultrasonographic techniques applied in evaluating aortic stiffness. With multiple illustrative images, we mainly characterized various ultrasound techniques in assessing aortic stiffness based on the alterations of aortic structure, hemodynamics, and tissue motion. We also discussed the discrepancy of their applications in humans and rodents and explored the potential optimized strategies in the experimental research with animal models. This updated information would help to better understand the nature of ultrasound techniques and provide a valuable prospect for their applications in assessing aortic stiffness in basic science research, particularly with small animals.
Safe Management Strategies in Clinical Forensic Autopsies of Confirmed COVID-19 Cases
Authors: Pomara Cristoforo , Salerno Monica , Sessa Francesco , Esposito Massimiliano , Barchitta Martina , Ledda Caterina , Grassi Patrizia , Liberto Aldo , Mattaliano Anna Rita , Rapisarda Venerando , Ferrante Margherita , Agodi Antonella
Published: March 2021

To date, there is poor evidence on the transmission of infection in individuals handling the bodies of deceased persons infected with SARS-CoV-2 and in particular, during autopsies. The aim of this study was to demonstrate that when appropriate strategies are adopted autopsy is a safe procedure with a minimal infection risk for all subjects involved (pathologists, technical personnel, and others) when proper strategies are adopted. We performed 16 autopsies on cadavers of persons who had died with confirmed COVID-19 with different post-mortem intervals (PMI). To confirm the presence of SARS-CoV-2 RNA, for each autopsy, 2 swabs were sampled from lungs, while to evaluate environmental contamination, 11 swabs were taken at three different times: T0 (before autopsy), T1 (at the end of the autopsy, without removing the corpse), and T2 (after cleaning and disinfecting the autopsy room). Specifically, 2 swabs were sampled on face shields used by each pathologist, and 4 swabs were collected on the autopsy table; 4 swabs were also collected from walls and 1 from floor. Lung swabs confirmed the presence of SARS-CoV-2 RNA in all cases. Environmental swabs, collected at T0 and T2 were all negative, while swabs sampled at T1 were shown to be positive. Interestingly, no association was shown between PMI length and environmental contamination. Infection control strategies for safe management of clinical forensic autopsies of bodies with suspected or confirmed COVID-19 are also described.
Arrhythmic Mitral Valve Prolapse: Introducing an Era of Multimodality Imaging-Based Diagnosis and Risk Stratification
Authors: Kukavica Deni , Guglielmo Marco , Baggiano Andrea , Muscogiuri Giuseppe , Fusini Laura , Muratori Manuela , Tamborini Gloria , Mantegazza Valentina , Trancuccio Alessandro , Arnò Carlo , Mazzanti Andrea , Pepi Mauro , Priori Silvia Giuliana , Pontone Gianluca
Published: March 2021

Mitral valve prolapse is a common cardiac condition, with an estimated prevalence between 1% and 3%. Most patients have a benign course, but ever since its initial description mitral valve prolapse has been associated to sudden cardiac death. Although the causal relationship between mitral valve prolapse and sudden cardiac death has never been clearly demonstrated, different factors have been implicated in arrhythmogenesis in patients with mitral valve prolapse. In this work, we offer a comprehensive overview of the etiology and the genetic background, epidemiology, pathophysiology, and we focus on the state-of-the-art imaging-based diagnosis of mitral valve prolapse. Going beyond the classical, well-described clinical factors, such as young age, female gender and auscultatory findings, we investigate multimodality imaging features, such as alterations of anatomy and function of the mitral valve and its leaflets, the structural and contractile anomalies of the myocardium, all of which have been associated to sudden cardiac death.
Endoscopic Ultrasound-Guided Sampling for Personalized Pancreatic Cancer Treatment
Authors: Iwasaki Eisuke , Fukuhara Seiichiro , Horibe Masayasu , Kawasaki Shintaro , Seino Takashi , Takimoto Yoichi , Tamagawa Hiroki , Machida Yujiro , Kayashima Atsuto , Noda Marin , Hayashi Hideyuki , Kanai Takanori
Published: March 2021

Pancreatic cancer is the most lethal solid malignancy, and the number of patients with pancreatic cancer is increasing. Systemic chemotherapies are often ineffective for such patients, and there is an urgent need for personalized medicine. Unlike other types of cancer, personalized treatments for pancreatic cancer are still in development. Consequently, pancreatic cancer is less sensitive to anticancer drugs and is often refractory to common treatments. Therefore, advances in personalized medicine for pancreatic cancer are necessary. This review examined advances in personalized medicine for pancreatic cancer, including the use of endoscopic ultrasound (EUS)-guided sampling. EUS-guided sampling is widely used for diagnosing pancreatic tumors and is expected to be applied to sampled tissues. Additionally, there has been an increase in clinical research using EUS-guided sampling. The combination of precision medicine using genomic testing and pharmacological profiles based on high-throughput drug sensitivity testing using patient-derived organoids is expected to revolutionize pancreatic cancer treatment.
Drone Swarms in Fire Suppression Activities: A Conceptual Framework
Authors: Ausonio Elena , Bagnerini Patrizia , Ghio Marco
Published: March 2021

The recent huge technological development of unmanned aerial vehicles (UAVs) can provide breakthrough means of fighting wildland fires. We propose an innovative forest firefighting system based on the use of a swarm of hundreds of UAVs able to generate a continuous flow of extinguishing liquid on the fire front, simulating the effect of rain. Automatic battery replacement and extinguishing liquid refill ensure the continuity of the action. We illustrate the validity of the approach in Mediterranean scrub first computing the critical water flow rate according to the main factors involved in the evolution of a fire, then estimating the number of linear meters of active fire front that can be extinguished depending on the number of drones available and the amount of extinguishing fluid carried. A fire propagation cellular automata model is also employed to study the evolution of the fire. Simulation results suggest that the proposed system can provide the flow of water required to fight low-intensity and limited extent fires or to support current forest firefighting techniques.
Simultaneous Extraction of Road and Centerline from Aerial Images Using a Deep Convolutional Neural Network
Authors: Alshaikhli Tamara , Liu Wen , Maruyama Yoshihisa
Published: March 2021

The extraction of roads and centerlines from aerial imagery is considered an important topic because it contributes to different fields, such as urban planning, transportation engineering, and disaster mitigation. Many researchers have studied this topic as a two-separated task that affects the quality of extracted roads and centerlines because of the correlation between these two tasks. Accurate road extraction enhances accurate centerline extraction if these two tasks are processed simultaneously. This study proposes a multitask learning scheme using a gated deep convolutional neural network (DCNN) to extract roads and centerlines simultaneously. The DCNN is composed of one encoder and two decoders implemented on the U-Net backbone. The decoders are assigned to extract roads and centerlines from low-resolution feature maps. Before extraction, the images are processed within an encoder to extract the spatial information from a complex, high-resolution image. The encoder consists of the residual blocks (Res-Block) connected to a bridge represented by a Res-Block, and the bridge connects the two identical decoders, which consists of stacking convolutional layers (Conv.layer). Attention gates (AGs) are added to our model to enhance the selection process for the true pixels that represent road or centerline classes. Our model is trained on a dataset of high-resolution aerial images, which is open to the public. The model succeeds in efficiently extracting roads and centerlines compared with other multitask learning models.
Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis
Authors: Zhang Wenjia , Ji Chunhan , Yu Hao , Zhao Yi , Chai Yanwei
Published: March 2021

Interpersonal and intrapersonal variabilities are two important perspectives to understand daily travel behaviors, while only a small number of studies incorporate them for understanding human dynamics. This paper employed a network analysis approach to detecting daily activity-travel patterns of 680 Beijing’s residents within a week and then used a multilevel multinomial logit model to analyze the intrapersonal variability in patterns and the socioeconomic linkages behind them. Results suggest that most activity-travel patterns have significant day-to-day intrapersonal and interpersonal variabilities. This suggests that the application of a typical day of activity-travel behaviors to measure and represent a week’s or even longer-term behaviors may be biased, due to the existence of day-to-day intrapersonal variability. This study also provides a hint for the selection of days of a week to conduct a diary survey for activity pattern mining or travel demand modeling.
Development of the Cooperative Intelligent Transport System in Thailand: A Prospective Approach
Authors: Choosakun Aroonrot , Chaiittipornwong Yaowapa , Yeom Chunho
Published: March 2021

Smart mobility is becoming an alternative technology of transportation development for today and the future. Thailand has applied the intelligent transport system (ITS) to improve traffic and transport services. The success of the project is generally dependent on collaboration between private, public, and governmental agencies in policymaking and planning, coupled with an inclusive agreement and technological knowledge in the field. This study argues that Thailand’s automatic transportation has been successful because of cooperative-ITS (C-ITS). This study explores the evidence-based cases of ITS development from six areas, Singapore, South Korea, Japan, China, the European Union, and the United States of America, to explain how the C-ITS conditions support the success of ITS. The study uses the SWOT (Strength, Weakness, Opportunity, Threat) and TOWS (Threat, Opportunity, Weakness, Strength) analysis matrix to identify influential factors from the six-area cases and compare them to Thailand. The authors identified seven components that relate to the success of Thailand’s C-ITS. These include: (1) Pragmatic policy for pilot project implementation; (2) close cooperation among stakeholders; (3) working criteria for C-ITS development; (4) architecture of standard and framework; (5) share of lessons learned about current technology; (6) capability of C-ITS deployment; and (7) a clear statement of data exchange and sharing. These findings represent both the threat and opportunity for traffic and transport improvement in Thailand through the C-ITS approach.
Smart City Ranking System: A Supporting Tool to Manage Migration Trends for Australian Cities
Authors: Tariq Muhammad Atiq Ur Rehman , Hussein Maha , Muttil Nitin
Published: March 2021

A key driver of Australia’s economic development is through promoting migration. A strong bottleneck to achieve the targets is a disproportional concentration of population in the metropolitan cities. To avoid congestion in these cities, emphasis is being given at the government level to promote the regional cities. With different city ranking systems, this study tries to identify linkage between the city ranking and people’s preference to live there. The proposed ranking system uses six components, namely, economy, mobility, environment, people, living, and governance. A comparison is done between the ranking systems by first assigning the same weightage to the six components and then assigning different weightages based on people’s preferences. This study considered 112 Australian cities, which were ranked by considering their performance based on the non-weighted and weighted parameters. Analytical Hierarchy Process is then used to assign the priorities/preferences of the components, factors, and indicators. The study also incorporates clustering technique to address the issue of missing data/information that is a typical problem with small cities where missing data is a common issue. The results of the comparison demonstrate that assigning weightage to ranking parameters makes the city ranking closer to the preference of people to live in a city. It is also recommended that the city ranking system and urban governance should have closer connection to each other. The lowest performing city ranking parameter should be given higher preferences in urban management and development plans.
Visualization and Analysis of Traffic Flow and Congestion in India
Authors: Tsuboi Tsutomu
Published: March 2021

The paper takes an analysis of traffic conditions in a developing country, namely, India. India is a country with a rapidly growing economy and a large market, and it has the second largest population in the world, which was 1.3 billion in 2018. India also suffers from environmental problems, such as air pollution and global warming that is contributed by traffic CO2 emissions from transportation. In order to analyze this problem, a particularly challenging issue in developing countries like India, is the collection of traffic data. In general, developing countries do not often have well established infrastructure such as installations of small traffic signals, they lack new road construction and public transportation, etc. This study is the first real traffic congestion analysis in India and introduces unique traffic flow analysis such as: (1) Collecting over a month of recent traffic data in a major city in India, (2) defining traffic congestion from occupancy parameter based on traffic flow theory and observation data, and (3) using geographical special analysis (GIS) for identifying traffic congestion location. These three combination analysis enables one to identify the most congested area in the city with quantitative congestion condition. This study becomes useful to other countries that have similar issues.
Ancestral Haplotype Retention and Population Expansion Determine the Complicated Population Genetic Structure of the Hilly Lineage of Neolucanus swinhoei Complex (Coleoptera, Lucanidae) on the Subtropical Taiwan Island
Authors: Tsai Cheng-Lung , Kubota Kôhei , Pham Hong-Thai , Yeh Wen-Bin
Published: March 2021

The present study demonstrates that the complicated genetic structure of the hilly lineage of the Neolucanus swinhoei complex was driven by its biological features and habitat requirements as well as hindrance by the CMR during periodical Pleistocene glaciations. The results revealed a tendency of geographical differentiation and major and sub- lineage divergences before and after the Riss glaciation, followed by stable population growth during Würm glaciation. At least four refugia were inferred for N. swinhoei during the Riss–Würm glaciations. The ancestral haplotype retention in the cytochrome oxidase subunit I (COI) gene and compensated substitution in 16S rRNA gene is a possible evolutionary scenario resulting in the inconsistent evolution pattern between COI and 16S rRNA gene coupled with the long-distance dispersal of N. swinhoei. Although the CMR did hinder the dispersal of N. swinhoei, its ancestors may have dispersed to eastern Taiwan through the northern and southern low mountains of the CMR before the Riss glaciation. Our finding suggests that the population growth in the Würm glaciation led a dispersal back to western Taiwan, which is contrast to the more common dispersal scenario from western Taiwan to eastern populations proposed in other studies.
S-N Curve Characterisation for Composite Materials and Prediction of Remaining Fatigue Life Using Damage Function
Authors: Kim Ho Sung , Huang Saijie
Published: March 2021

S-N curve characterisation and prediction of remaining fatigue life are studied using polyethylene terephthalate glycol-modified (PETG). A new simple method for finding a data point at the lowest number of cycles for the Kim and Zhang S-N curve model is proposed to avoid the arbitrary choice of loading rate for tensile testing. It was demonstrated that the arbitrary choice of loading rate may likely lead to an erroneous characterisation for the prediction of the remaining fatigue life. The previously proposed theoretical method for predicting the remaining fatigue life of composite materials involving the damage function was verified at a stress ratio of 0.4 for the first time. Both high to low and low to high loadings were conducted for predicting the remaining fatigue lives and a good agreement between predictions and experimental results was found. Fatigue damage consisting of cracks and whitening is described.
Design of a Lightweight Multifunctional Composite Railway Axle Utilising Coaxial Skins
Authors: Mistry Preetum J. , Johnson Michael S. , McRobie Charles A. , Jones Ivor A.
Published: March 2021

The rising economic and environmental pressures associated with the generation and consumption of energy necessitates the need for lightweighting of railway vehicles. The railway axle is a prime candidate for lightweighting of the unsprung mass. The reduction of unsprung mass correlates to reduced track damage, energy consumption and total operating costs. This paper presents the design of a lightweight multifunctional hybrid metallic-composite railway axle utilising coaxial skins. The lightweight axle assembly comprises a carbon fibre reinforced polymer composite tube with steel stub axles bonded into either end. The structural hybrid metallic-composite railway axle is surrounded by coaxial skins each performing a specific function to meet the secondary requirements. A parametric sizing study is conducted to explore the sensitivity of the design parameters of the composite tube and the stub axle interaction through the adhesive joint. The optimised design parameters of the axle consist of a; composite tube outer diameter of 225 mm, composite tube thickness of 7 mm, steel stub axle extension thickness of 10 mm and a bond overlap length of 100 mm. The optimised hybrid metallic-composite railway axle design concept has a mass of 200 kg representing a reduction of 50% over the solid steel version.
News Organizations in Colombia Building Consensus through Social Media: A Case of Digital-Native La Silla Vacía
Authors: Higgins Joyce Vanessa de Macedo
Published: March 2021

Correlation of different segments of society is a major function of mass media and works by broadening individual’s perspectives and creating common ground between these different segments Little is known about how consensus building works in the networked, digital environment or how it works in Latin America. This study explores the premise on a social media page from a digital-native news organization in Colombia, La Silla Vacía, on the salient issue of Venezuela. It found that the news organization did provide a common ground within its comments, bringing men and women closer together in consensus (rs = 0.76, n = 10, p < 0.05) of the priorities of topics relating to Venezuela (substantive attributes). The study did not find a significant correlation between the topics prioritized by the posts and the topics prioritized by the comments. Audiences focus on Venezuela in relation to the local Colombian presidential election while the news organization focused on the country in relation to refugees and the political transition happening in Venezuela.
Hot Sliding Wear of 88 wt.% TiB–Ti Composite from SHS Produced Powders
Authors: Kumar Rahul , Liu Le , Antonov Maksim , Ivanov Roman , Hussainova Irina
Published: March 2021

Titanium alloys and composites are of great interest for a wide variety of industrial applications; however, most of them suffer from poor tribological performance, especially at elevated temperatures. In this study, spark plasma sintering was utilized to produce a fully dense and thermodynamically stable TiB–Ti composite with a high content of ceramic phase (88 wt.%) from self-propagating high temperature synthesized (SHS) powders of commercially available Ti and B. Microstructural examination, thermodynamic assessments, and XRD analysis revealed the in situ formation of titanium borides with a relatively broad grain size distribution and elongated shapes of different aspect ratio. The composite exhibits a considerable hardness of 1550 HV30 combined with a good indentation fracture toughness of 8.2 MPa·m1/2. Dry sliding wear tests were performed at room and elevated temperature (800 °C) under 5 and 20 N sliding loads with the sliding speed of 0.1 m·s−1 and the sliding distance of 1000 m. A considerable decline in the coefficient of friction and wear rate was demonstrated at elevated temperature sliding. Apart from the protective nature of generated tribo-oxide layer, the development of lubricious boric acid on the surface of the composite was wholly responsible for this phenomenon. A high load bearing capacity of tribo-layer was demonstrated at 800 °C test.