bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding Patients’ Experiences and Perspectives of Tele-Prehabilitation: A Qualitative Study to Inform Service Design and Delivery
Authors: Wu Fiona , Laza-Cagigas Roberto , Rampal Tarannum
Published: August 2022

Background: Tele-prehabilitation is a behaviour change intervention that facilities the modification of unhealthy lifestyle behaviours. Understanding patients’ experiences of tele-prehabilitation provides important insights into service improvement. In this study, we aimed to describe our patients’ perceptions of tele-prehabilitation and capture their capabilities, opportunities, and motivations to participate. This was a qualitative study to inform our service design and delivery. Methods: Following purposive sampling, 22 qualitative semistructured interviews were conducted with patients in the community that had completed tele-prehabilitation. Interviews were recorded and transcribed. Deductive content analysis was used to map the identified themes against theoretical determinants of health behaviour change. Results: We conducted 22 interviews. Our patients described their overall experience of tele-prehabilitation as positive and provided important insights that impacted their capabilities, opportunities, and motivations to engage with our service. Our team provided them the capabilities and self-efficacy to engage by personalising multimodal plans and setting goals. The remote delivery of our service was a recurring positive theme in providing flexibility and widening accessibility to participation. A missed opportunity was the potential for peer support through shared experiences with other patients. Patients showed greater motivation to participate for immediate perioperative benefit compared to long-term health gains. Conclusion: Patients’ experiences and perspectives of tele-prehabilitation can be enhanced by incorporating the findings from this qualitative study into service redesign and delivery. We recommend: (1) applying holistic principles in care and goal-setting, (2) delivering a combination of home-based and in-centre programmes, and (3) engaging with patients at the start of their cancer journey when they are most motivated. In turn, this can result in more effective uptake, improve adherence to interventions, and greater satisfaction.
Cylinder Fatigue Design of Low-Speed, High-Torque Radial Piston Motor
Authors: Cheng Lifu , Chen Xinyuan , Wei Guoqian
Published: August 2022

Through the comparison of fatigue properties of components made of composite materials and high-strength structural steel materials, this study proves that composite materials can replace traditional steel materials used in the production of mechanical structural components. The focus of this study was a low-speed, high-torque radial piston motor mounted on a roadheader. According to different theories, the motor block was designed using a composite material made of carbon fiber, a classic high-strength structural steel, and an aluminum alloy. The thickness of the motor cylinder obtained by theoretical calculation was verified by finite-element numerical simulation technology, and the fatigue phenomenon caused by the time change of the piston cylinder pressure was considered. The results showed that the stress results of the numerical simulation verify the rationality of the theoretical calculation of the cylinder size. In terms of safety factors, the motor cylinder made of composite materials was close to the motor cylinder made of high-strength structural steel, and the difference between the static safety factor and fatigue safety factor was only 0.8 and 0.86. The weight of the motor cylinder made of composite material was reduced from 32 N to 7 N compared with steel material, which was about 78% lighter. This is of great significance for improving the use efficiency of equipment and reducing fuel costs.
High-Performance Ultra-Broadband Absorber for Polarized Long-Wavelength Infrared Light Trapping
Authors: Xiong Ying , Liu Xiaoyi , Zhang Jian , Wang Xiaokun , Wang Xiaoyi , Gao Jinsong , Yang Haigui
Published: August 2022

Conventional infrared polarization imaging and detection systems are normally complex, bulky, and expensive, since rare existing absorber components possess polarization selectivity, especially in the long-wavelength infrared (LWIR) range. In this study, we propose a novel high-performance metamaterial absorber with ultra-broadband high absorption and polarization selectivity in the entire LWIR atmospheric window. The absorber can realize an absorptance higher than 90% with a 4750 nm bandwidth due to different surface plasmons coupled with optical phonons. It exhibits precise polarization-selective absorption at the target wavelength; specifically, it can selectively trap TM-polarized light while restricting the absorption of TE-polarized light. In addition, the designed metamaterial exhibits remarkable spectral stability when the geometric parameters of the microstructure change, which is of great benefit in its manufacturing process. The proposed ultra-thin absorber provides a promising approach to simplify LWIR imaging and detection systems and further improve their performance.
Extract Class Refactoring Based on Cohesion and Coupling: A Greedy Approach
Authors: Alzahrani Musaad
Published: August 2022

A large class with many responsibilities is a design flaw that commonly occurs in real-world object-oriented systems during their lifespan. Such a class tends to be more difficult to comprehend, test, and change. Extract class refactoring (ECR) is the technique that is used to address this design flaw by trying to extract a set of smaller classes with better quality from the large class. Unfortunately, ECR is a costly process that takes great time and effort when it is conducted completely by hand. Thus, many approaches have been introduced in the literature that tried to automatically suggest the best set of classes that can be extracted from a large class. However, most of these approaches focus on improving the cohesion of the extracted classes yet neglect the coupling between them which can lead to the extraction of highly coupled classes. Therefore, this paper proposes a novel approach that considers the combination of the cohesion and coupling to identify the set of classes that can be extracted from a large class. The proposed approach was empirically evaluated based on real-world Blobs taken from two open-source object-oriented systems. The results of the empirical evaluation revealed that the proposed approach is potentially useful and leads to improvement in the overall quality.
Value-Based Care in Systemic Therapy: The Way Forward
Authors: Mathew Aju , Benny Steve Joseph , Boby Jeffrey Mathew , Sirohi Bhawna
Published: August 2022

The rising cost of cancer care has shed light on an important aspect of healthcare delivery. Financial toxicity of therapy must be considered in clinical practice and policy-making. One way to mitigate the impact of financial toxicity of cancer care is by focusing on an approach of healthcare delivery that aims to deliver value to the patient. Should value of therapy be one of the most important determinants of cancer care? If so, how do we measure it? How can we implement it in routine clinical practice? In this viewpoint, we discuss value-based care in systemic therapy in oncology. Strategies to improve the quality of care by incorporating value-based approaches are discussed: use of composite tools to assess the value of drugs, alternative dosing strategies, and the use of Health Technology Assessment in regulatory procedures. We propose that there must be a greater emphasis on value of therapy in determining its use and its cost.
Diversity and Functional Relevance of Canopy Arthropods in Central Europe
Authors: Floren Andreas , Linsenmair Karl Eduard , Müller Tobias
Published: August 2022

Although much is known about the ecology and functional importance of canopy arthropods in temperate forests, few studies have tried to assess the overall diversity and investigate the composition and dynamics of tree-specific communities. This has impeded a deeper understanding of the functioning of forests, and of how to maintain system services. Here, we present the first comprehensive data of whole arthropod communities, collected by insecticidal knockdown (fogging) from 1159 trees in 18 study areas in Central Europe during the last 25 years. The data includes 3,253,591 arthropods from 32 taxa (order, suborder, family) collected on 24 tree species from 18 genera. Fogging collects free-living, ectophytic arthropods in approximately the same number as they occur in the trees. To our knowledge, these are the most comprehensive data available today on the taxonomic composition of arboreal fauna. Assigning all arthropods to their feeding guild provided a proxy of their functional importance. The data showed that the canopy communities were regularly structured, with a clear dominance hierarchy comprised of eight ‘major taxa’ that represented 87% of all arthropods. Despite significant differences in the proportions of taxa on deciduous and coniferous trees, the composition of the guilds was very similar. The individual tree genera, on the other hand, showed significant differences in guild composition, especially when different study areas and years were compared, whereas tree-specific traits, such as tree height, girth in breast height or leaf cover, explained little of the overall variance. On the ordinal level, guild composition also differed significantly between managed and primary forests, with a simultaneous low within-group variability, indicating that management is a key factor determining the distribution of biodiversity and guild composition.
Activity Patterns of Stenocercus iridescens in an Ecuadorian Coastal Agroecosystem: Is Temperature Important?
Authors: Zambrano Ramón H. , Guerrero-Casado José , Centeno Víctor A. , Tortosa Francisco S.
Published: August 2022

Circadian rhythms of Neotropical lizards have been poorly studied, which represents a problem when designing ecological studies or monitoring such species based on direct observations. In this work, 1000 m-long transects were established in an agroecosystem area of the Ecuadorian coast region to study the activity patterns of Stenocercus iridescens. The number of individuals (as a response variable) was correlated with local weather conditions: temperature, precipitation, and heliophany (duration of the solar brightness). We carried out the study in both dry and rainy seasons, and during different time ranges. The time range in which the transects were performed was the most important predictor, and the activity peak was established between 16:00 h and 18:00 h. Heliophany negatively affected lizard activity, but only on the days with higher heliophany during the dry season, whereas temperature was not a significant predictor. Our results suggest that in an area where temperature is relatively constant and the solar radiation is high, particularly during the dry season, the heliophany (an indirect measure of solar radiation) can affect ectotherm activity patterns more than temperature, particularly in open habitats such as agroecosystems.
Hypothetical Reason for the Restoration of HbA1c Level for Pre-Diabetic Patients through the Recovery of Arterial Blood Flow Access to Rhomboid Fossa
Authors: Vetcher Alexandre A. , Zhukov Kirill V. , Gasparyan Bagrat A. , Shishonin Alexander Y.
Published: August 2022

We demonstrate that the recovery of cervical vertebral arterial blood flow access to the rhomboid fossa causes the restoration of HbA1c level for the patients with pre-diabetic (pre-DM) condition. This observation is in good agreement with the consideration of the human body as a dissipative structure. Such consideration is the focus of the recently announced centralized aerobic-anaerobic energy balance compensation (CAAEBC) theory. According to the theory, observed connections between high blood pressure (HBP) and the lifted level of HbA1c can be hypothetically linked through the restrictions of blood flow access to rhomboid fossa, causing the delivery of incorrect information of blood oxygen availability. Below we provide detailed information of how in this case CAAEBC theory explains the very initiation of multiple chronic diseases, starting with type 2 Diabetes Mellitus (DM).
Glucose-Dependent Insulinotropic Polypeptide Plasma Level Influences the Effect of n-3 PUFA Supplementation
Authors: Goralska Joanna , Razny Urszula , Calder Philip C. , Gruca Anna , Childs Caroline E. , Zabielski Piotr , Dembinska-Kiec Aldona , Banach Maciej , Solnica Bogdan , Malczewska-Malec Malgorzata
Published: August 2022

Elevated glucose-dependent insulinotropic peptide (GIP) levels in obesity may predict the metabolic benefits of n-3 PUFA supplementation. This placebo-controlled trial aimed to analyze fasting and postprandial GIP response to 3-month n-3 PUFA supplementation (1.8 g/d; DHA:EPA, 5:1) along with caloric restriction (1200–1500 kcal/d) in obese subjects. Compliance was confirmed by the incorporation of DHA and EPA into red blood cells (RBCs). Blood analyses of glucose, insulin, non-esterified fatty acids (NEFAs), GIP and triglycerides were performed at fasting, and during an oral glucose tolerance test and a high fat mixed-meal tolerance test. Fatty acid composition of RBC was assessed by gas chromatography and total plasma fatty acid content and composition was measured by gas–liquid chromatography. The DHA and EPA content in RBCs significantly increased due to n-3 PUFA supplementation vs. placebo (77% vs. −3%, respectively). N-3 PUFA supplementation improved glucose tolerance and decreased circulating NEFA levels (0.750 vs. 0.615 mmol/L), as well as decreasing plasma saturated (1390 vs. 1001 µg/mL) and monounsaturated (1135 vs. 790 µg/mL) fatty acids in patients with relatively high GIP levels. The effects of n-3 PUFAs were associated with the normalization of fasting (47 vs. 36 pg/mL) and postprandial GIP levels. Obese patients with elevated endogenous GIP could be a target group for n-3 PUFA supplementation in order to achieve effects that obese patients without GIP disturbances can achieve with only caloric restriction.
Restricted Phased Space Thermodynamics for Black Holes in Higher Dimensions and Higher Curvature Gravities
Authors: Kong Xiangqing , Wang Tao , Gao Zeyuan , Zhao Liu
Published: August 2022

The recently proposed restricted phase space thermodynamics is shown to be applicable to a large class of higher dimensional higher curvature gravity models coupled to Maxwell field, which are known as black hole scan models and are labeled by the spacetime dimension d and the highest order k of the Lanczos-Lovelock densities appearing in the action. Three typical example cases with (d,k)=(5,1),(5,2) and (6,2) are chosen as example cases and studied in some detail. These cases are representatives of Einstein-Hilbert, Chern-Simons and Born-Infield like gravity models. Our study indicates that the Einstein-Hilbert and Born-Infield like gravity models have similar thermodynamic behaviors, e.g., the existence of isocharge T−S phase transitions with the same critical exponents, the existence of isovoltage T−S transitions and the Hawking-Page like transitions, and the similar high temperature asymptotic behaviors for the isocharge heat capacities, etc. However, the Chern-Simons like (5,2)-model behaves quite differently. Neither isocharge nor isovoltage T−S transitions could occur and no Hawking-Page like transition is allowed. This seems to indicate that the Einstein-Hilbert and Born-Infield like models belong to the same universality class while the Chern-Simons like models do not.
Revisiting Sequential Information Bottleneck: New Implementation and Evaluation
Authors: Toledo Assaf , Venezian Elad , Slonim Noam
Published: August 2022

We introduce a modern, optimized, and publicly available implementation of the sequential Information Bottleneck clustering algorithm, which strikes a highly competitive balance between clustering quality and speed. We describe a set of optimizations that make the algorithm computation more efficient, particularly for the common case of sparse data representation. The results are substantiated by an extensive evaluation that compares the algorithm to commonly used alternatives, focusing on the practically important use case of text clustering. The evaluation covers a range of publicly available benchmark datasets and a set of clustering setups employing modern word and sentence embeddings obtained by state-of-the-art neural models. The results show that in spite of using the more basic Term-Frequency representation, the proposed implementation provides a highly attractive trade-off between quality and speed that outperforms the alternatives considered. This new release facilitates the use of the algorithm in real-world applications of text clustering.
The Effects of Technological Progress in Innovative Regions on the Labor Markets of Lagging Regions: A Theoretical Perspective
Authors: Hean Oudom
Published: August 2022

The technological effects of innovative regions on lagging regions’ labor markets have not been yet well understood, especially in the urban–rural context. I introduce a theoretical model that yields insight into the interactions between high-technology and lagging regions. While, through knowledge spillovers, urban technology can increase rural jobs, it can also reduce rural employment by raising the competitive advantage of urban firms over rural firms in product market competition. Progress in urban technology also exerts an ambiguous effect of a brain drain on the rural labor market.
Feasibility of a Vertically Integrated Teaching Strategy during a Surgical Clerkship Event—Learning Methods Matter
Authors: Fogarasi Miklos C. , Van Cott Christine , Feinn Richard S. , Hirshorn Steven A. , Lewis Eugene H. , Fernandez Susan V. , Ratchelous Lori , O’Connor Julia A. , Gruppen Larry D.
Published: August 2022

Sound foundational knowledge improves disease conceptualization and clinical diagnosis. Vertical integration (VI) is an appealing educational strategy to refresh relevant pre-clinical information during clinical rotations. However, an optimal learning approach for this has not yet been established. We hypothesized that a small group collaborative discussion format might serve as an appealing learning method to deliver integrated material and increase retention. During AYs 2018/2019 and 2019/2020, our multidisciplinary team utilized a Colorectal Cancer workshop incorporating pre-clinical material for Y3 students on Surgical Clerkship. In search of an optimized way to deliver vertically integrated content, we alternately presented the workshop material either in a small group (SG) case-based collaborative format or as a standard-sized group (StdG) exercise. We achieved this by testing immediate and late (4-week post-event) recall and assessing student satisfaction with the VI strategy in both physical settings (StdG and SG). A total of 93% of participants considered VI-based training worthwhile, 96% reported an increased knowledge base and 93% would welcome similar VI events in the curriculum. Significantly more SG students than StdG (52% vs. 31%, p = 0.014) enthusiastically endorsed their event and would prefer to have future VI events delivered in the format they experienced (88% for SG vs. 42% for StdG) (p < 0.0001). Combined (immediate + late) recall scores were significantly better in SG versus StdG (p = 0.007), while the rate of attrition at 4 weeks did not differ significantly (p = 0.81). VI strategy successfully reactivated pre-clinical concepts, achieving both high content retention and learner satisfaction during this workshop. Students endorsed future VI events, especially when delivered in a case-based, interactive SG setting. Although resource intensive, a VI strategy employing a small-group collaborative learning method may be considered for broader curricular use in undergraduate medical education.
Economically Disadvantaged, Incoming Readiness and School Achievement: Implications for Building High-Performing and Effective Schools
Authors: Etim James Sunday , Etim Alice , Blizard Zachary
Published: August 2022

As a result of the 2002 No Child Left Behind Act, North Carolina, like many other states, has created standards and yearly student assessments for K-12 students. Student and school yearly assessments are reported via the North Carolina School Report Cards. Based on the North Carolina School Report Cards, there are several low-performing and failing schools at all levels; schools designated by the State of North Carolina as D or F in the Report Card. This study centered on two research questions: (a) Is there a relationship between incoming readiness and school performance in NC public middle schools? (b) Is there a relationship between economically disadvantaged students and school performance in NC public middle schools? Data was collected from the North Carolina School Report Cards (SRC) datasets (NCDPI, 2019). SRCs are offered for each public school in NC. NC public schools get a report card with their individual school performance score, in addition to other pertinent information, such as teacher and student characteristics. The analysis sample contains two years of data, namely for 2018 and 2017. The dataset includes 850 observations for 425 middle schools. The analysis and results are presented as follows: First, the frequencies of particular performance grades earned by NC middle schools are presented. Second, descriptive statistics are provided and data visuals for the variables associated with the specific research questions a and b, followed by the hypotheses. Third, the hypotheses are tested with the results from the linear regression and ordered logit. Analysis showed evidence of a relationship between incoming student readiness and school performance in NC public middle schools. Larger shares of incoming students considered ready significantly predicts school performance. It is possible to find evidence of a relationship between economically disadvantaged students and school performance in NC public middle schools. Having larger shares of economically disadvantaged students significantly predicts school performance. Based on these findings, a recommendation would be that teachers and schools work to get students ready for middle school in order to improve student performance.
Digital Storytelling in Education: A Transmedia Integration Approach for the Non-Developers
Authors: Palioura Maria , Dimoulas Charalampos
Published: August 2022

The present paper focuses on digital storytelling in education, emphasizing the teachers’ needs for familiarization with the new technological conditions. A transmedia integration approach is deployed to make productive, blended learning values while utilizing the availability of tools and reusable media assets in a component-based software engineering kind of framework. The topic is inspired by social studies and humanities, which seem to be marginalized, usually failing to make effective technological facilities, benefits, and contemporary findings. It is, therefore, necessary to modernize the approach to literary things and integrate digital means into the educational process, even in cases where a sole educator on humanities and social studies lacks multidisciplinary support in multimedia authoring and software engineering. This modernization can be made possible by introducing user-friendly tools into the process, representing not just a fashion of the time but mostly a renewal trend, aiming at revitalizing the course to attract and engage learners. Undoubtedly, today’s pupils have grown up with technological means, becoming familiar with their use so their implication causes undiminished interest in most daily activities, including schooling. In this high-tech generation, it is absurd to address the transmission of knowledge and values in outdated ways. Apart from adapting to the timely students’ needs, lesson plans on transmedia storytelling practices can also satisfy tutors, triggering their inspiration and co-creation potentials. Overall, the project aims to attract the trainees’ interest with the help of digital tools, which will be embodied in the educational processes by teachers without technical know-how, while continuously adapting to the audience’s needs. Research hypothesis and questions are formed as part of the deployed human-centered interactive design, aiming at modeling best practices for teaching classical topics, such as the “Odyssey”.
Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment
Authors: Gupta Sachi , Iyer Sailesh , Agarwal Gaurav , Manoharan Poongodi , Algarni Abeer D. , Aldehim Ghadah , Raahemifar Kaamran
Published: August 2022

Cloud computing is one of the most commonly used infrastructures for carrying out activities using virtual machines known as processing units. One of the most fundamental issues with cloud computing is task scheduling. The optimal determination of scheduling criteria in cloud computing is a non-deterministic polynomial-time (NP)-complete optimization problem, and several procedures to manage this problem have been suggested by researchers in the past. Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period for scheduling tasks in a heterogeneous environment. Literature shows that HEFT gives extraordinary results in terms of quality of schedule and execution time. However, in some cases, the average computation cost and selection of the first idle slot may not produce a good solution. Therefore, here we propose modified versions of the HEFT algorithm that can obtain improved results. In the rank generation phase, we implement different methodologies for calculating ranks, while in the processor selection phase, we modify the way of selecting idle slots for scheduling the tasks. This paper suggests enhanced versions of the HEFT algorithm under user-required financial constraints to minimize the makespan of a specified workflow submission on virtual machines. Our findings also suggest that enhanced versions of the HEFT algorithm perform better than the basic HEFT method in terms of lesser schedule length of the workflow problems running on various virtual machines.
SOMN_IA: Portable and Universal Device for Real-Time Detection of Driver’s Drowsiness and Distraction Levels
Authors: Flores-Monroy Jonathan , Nakano-Miyatake Mariko , Escamilla-Hernandez Enrique , Sanchez-Perez Gabriel , Perez-Meana Hector
Published: August 2022

In this paper, we propose a portable device named SOMN_IA, to detect drowsiness and distraction in drivers. The SOMN_IA can be installed inside of any type of vehicle, and it operates in real time, alerting the dangerous state caused by drowsiness and/or distraction in the driver. The SOMN_IA contains three types of alarm: light alarm, sound alarm, and the transmission of information about the driver’s dangerous state to a third party if the driver does not correct his/her dangerous state. The SOMN_IA contains a face detector and a classifier based on the convolutional neural networks (CNN), and it aids in the management of consecutive information, including isolated error correction mechanisms. All of the algorithmic parts of the SOMN_IA are analyzed and adjusted to operate in real-time in a portable device with limited computational power and memory space. The SOMN_IA requires only a buck-type converter to connect to the car battery. The SONM_IA discriminates correctly between real drowsiness and normal blinking, as well as between real dangerous distraction and a driver’s normal attention to his/her right and left. Although the real performance of the SOMN_IA is superior to the CNN classification accuracy thanks to isolated error correction, we compare the CNN classification accuracy with the previous systems.
A Personalized Respiratory Disease Exacerbation Prediction Technique Based on a Novel Spatio-Temporal Machine Learning Architecture and Local Environmental Sensor Networks
Authors: Bhowmik Rohan T. , Most Sam P.
Published: August 2022

Chronic respiratory diseases, such as the Chronic Obstructive Pulmonary Disease (COPD) and asthma, are a serious health crisis, affecting a large number of people globally and inflicting major costs on the economy. Current methods for assessing the progression of respiratory symptoms are either subjective and inaccurate, or complex and cumbersome, and do not incorporate environmental factors to track individualized risks. Lacking predictive assessments and early intervention, unexpected exacerbations often lead to hospitalizations and high medical costs. This work presents a multi-modal solution for predicting the exacerbation risks of respiratory diseases, such as COPD, based on a novel spatio-temporal machine learning architecture for real-time and accurate respiratory events detection, and tracking of local environmental and meteorological data and trends. The proposed new neural network model blends key attributes of both convolutional and recurrent neural architectures, allowing extraction of the salient spatial and temporal features encoded in respiratory sounds, thereby leading to accurate classification and tracking of symptoms. Combined with the data from environmental and meteorological sensors, and a predictive model based on retrospective medical studies, this solution can assess and provide early warnings of respiratory disease exacerbations, thereby potentially reducing hospitalization rates and medical costs.
Performance Evaluation of PV Model-Based Maximum Power Point Tracking Techniques
Authors: Ahmed Mostafa , Harbi Ibrahim , Kennel Ralph , Heldwein Marcelo Lobo , Rodríguez José , Abdelrahem Mohamed
Published: August 2022

Maximum power point tracking (MPPT) techniques extract the ultimate power from the photovoltaic (PV) source. Therefore, it is a fundamental control algorithm in any PV configuration. The research in this area is rich and many MPPT methods have been presented in the literature. However, in the current study, we focus on the PV model-based MPPT algorithms. In this regard, the classification of this category can be mainly divided into curve fitting methods and techniques based on the mathematical model or characteristics of the PV source. The objective of the PV model-based MPPT algorithm is to allocate the position of the maximum power point (MPP). Thus, no searching efforts are required to capture that point, which makes it simple and easy to implement. Consequently, the aim of this study is to give an overview of the most commonly utilized model-based MPPT methods. Furthermore, discussion and suggestions are also addressed to highlight the gap in this area. The main methods from the literature are compared together. The comparison and evaluation are validated using an experimental hardware-in-the-loop (HIL) system, where high efficiency (more than 99%) can be obtained with a simple calculation procedure and fast convergence speed.
Suitability Classification of Retinal Fundus Images for Diabetic Retinopathy Using Deep Learning
Authors: Pinedo-Diaz German , Ortega-Cisneros Susana , Moya-Sanchez Eduardo Ulises , Rivera Jorge , Mejia-Alvarez Pedro , Rodriguez-Navarrete Francisco J. , Sanchez Abraham
Published: August 2022

Diabetic retinopathy (DR) is the primary cause of blindness in developing and developed countries. Early-stage DR detection reduces the risk of blindness in Diabetes Mellitus (DM) patients. There has been a sharp rise in the prevalence of DM in recent years, especially in low- and middle-income countries. In this context, automated artificial intelligence-based DM screening is a crucial tool to help classify the considerable amount of Retinal Fundus Images (RFI). However, retinal image quality assessment has shown to be fundamental in real-world DR screening processes to avoid out-of-distribution data, drift, and images lacking relevant anatomical information. This work analyzes the spatial domain features and image quality assessment metrics for carrying out Deep Learning (DL) classification and detecting notable features in RFI. In addition, a novel lightweight convolutional neural network is proposed specifically for binary classification at a low computational cost. The training results are comparable to state-of-the-art neural networks, which are widely used in DL applications. The implemented architecture achieves 98.6% area under the curve, and 97.66%, and 98.33% sensitivity and specificity, respectively. Moreover, the object detection model trained achieves 94.5% mean average precision. Furthermore, the proposed approach can be integrated into any automated RFI analysis system.
Fully Parallel Proposal of Naive Bayes on FPGA
Authors: Barros Wysterlânya K. P. , Barbosa Matheus T. , Dias Leonardo A. , Fernandes Marcelo A. C.
Published: August 2022

This work proposes a fully parallel hardware architecture of the Naive Bayes classifier to obtain high-speed processing and low energy consumption. The details of the proposed architecture are described throughout this work. Besides, a fixed-point implementation on a Stratix V Field Programmable Gate Array (FPGA) is presented and evaluated regarding the hardware area occupation, processing time (throughput), and dynamic power consumption. In addition, a comparative design analysis was carried out with state-of-the-art works, showing that the proposed implementation achieved a speedup of up to 104× and power savings of up to 107×-times while also reducing the hardware occupancy by up to 102×-times fewer logic cells.
Design and Analysis of Novel CO2 Conditioning Process in Ship-Based CCS
Authors: Gong Wentao , Remiezowicz Eryk , Fosbøl Philip Loldrup , von Solms Nicolas
Published: August 2022

In this work, CO2 conditioning processes for ship-based CCS sequestration are modelled using the software APSEN HYSYS V11. This study uses the captured CO2 gas from the 3D project as the feed. The feed stream contains water, H2S, and CO as contaminants. The purification processes for dehydration, desulfurization, and CO removal are reviewed. Two liquefaction approaches, the open-cycle and the closed-cycle liquefaction, are modelled and compared for transport pressures 7 and 15 bar. It is found that the energy requirement of the open-cycle process is higher than that of the closed-cycle liquefaction process. For the closed-cycle design, two refrigerants, ammonia and propane, are considered. Results show that the energy requirement of the process using ammonia is lower than that of propane. When comparing the two transport pressures, it is found that liquefaction at 15 bar requires less energy than 7 bar. On top of that, both refrigerants are unsuited for the liquefaction of CO2 at 7 bar, as their operating pressures are below 1 atm. Several optimization concepts are tested on the closed-cycle liquefaction design. The net power consumption of the closed-cycle liquefaction is reduced when CO2 is precooled using the intermediate pressure ammonia streams and the cold from the CO stripper.
The Benefit Realization Mechanism of Pumped Storage Power Plants Based on Multi-Dimensional Regulation and Leader-Follower Decision-Making
Authors: Wang Yanyue , Fang Guohua , Wang Zhenni
Published: August 2022

The roles and benefits of pumped storage are reflected in different stakeholders of the power system. The multi-dimensionality and non-linearity of pumped storage multi-stakeholder decision-making make pumped storage benefit realization a hot research topic with challenges. This paper takes pumped storage benefit sharing as the breakthrough. It adopts multiple regulation strategies and multi-level decision-making measures based on the multiple objectives of different stakeholders. A method and a framework for pumped storage benefit realization are proposed. This paper proposes the objective function system with the fairness objective at the leader level, the participation objective at the secondary leader level, and the efficiency objective at the follower level. It also constructs a three-level Leader-Follower objective model with multi-dimensional regulation and multiple values, and it develops the corresponding solution method based on Stackelberg dynamic game and interactive algorithms. The results reveal that the values of fairness, participation, and efficiency indicators of the pumped storage plant are 1.75%, 0.25%, and 9.75%, respectively, and all the indicators meet the requirements. The research results are conducive to promoting the realization of a win-win situation for different stakeholders of pumped storage, and they highlight how pumped storage plants can fulfill their functions in the power system as well as ensure its survival and development.
A Low-Cost Online Health Assessment System for Oil-Immersed Service Transformers Using Real-Time Grid Energy Monitoring
Authors: Tran Quynh T. , Roose Leon , Doan Van Binh , Nguyen Quang Ninh
Published: August 2022

In this paper, we present a low-cost health assessment system for oil-immersed service transformers using a monitoring device to measure energy in real time. By assessing the important level of transformer components, three indicators, top oil temperature, vibration, and transformer load, were selected as main indicators to investigate the service transformer’s condition. An evaluation system using Fuzzy logic method is also presented in the paper to support monitor transformer health without adding the extra cost of installing expensive sensors. Different testing scenarios with different case studies were carried out on a simulated 50 kVA oil-immersed service transformer to express the feasibility and effectiveness of this low-cost, fast response health assessment system.
Numerical Analysis on Impact of Thickness of PEM and GDL with and without MPL on Coupling Phenomena in PEFC Operated at Higher Temperature Such as 363 K and 373 K
Authors: Nishimura Akira , Toyoda Kyohei , Mishima Daiki , Ito Syogo , Hu Eric
Published: August 2022

The aim of this study is to clarify the impact of the thickness of a gas diffusion layer (GDL) and a micro porous layer (MPL) on the distributions of gas, H2O, and current density in a polymer electrolyte fuel cell (PEFC) which is operated at 363 K and 373 K and with various thicknesses of polymer electrolyte membrane (PEM) as well as a relative humidity (RH) of supply gas. These investigations are carried out by numerical simulation using the 3D model with COMSOL Multiphysics. In the case of Nafion 115, which is the thicker PEM, the change in the molar concentration of H2O from the inlet to the outlet with MPL is larger than that without MPL irrespective of the thickness of GDL, Tini and RH condition. In the case of Nafion NRE-212, which is the thinner PEM, the change in the molar concentration of H2O from the inlet to the outlet is larger with MPL than that without MPL in the case of TGP-H-060 (the thicker commercial GDL), while that is smaller with MPL than that without MPL in the case of TGP-H-030 (the thinner commercial GDL). These results exhibit the same tendency as the results of the numerical simulation on the current density.
Syntheses and Photovoltaic Properties of New Pyrazine-Based Organic Photosensitizers for Dye-Sensitized Solar Cells
Authors: Kim Mi-Ra , Pham Thanh , Choi Yeonghwan , Yang Seah , Yang Hyun-Seock , Park Sung , Kang Mijeong , Lee Songyi
Published: August 2022

Three novel pyrazine-based organic photosensitizers denoted as TPP, TPPS, and TPPF were synthesized for dye-sensitized solar cell (DSSC) studies. Chemical structures of the pyrazine-based photosensitizers were designed with pyrazine derivatives as acceptors, triphenylamine groups as donors, and the thiophene–cyanoacryl group as an auxiliary heterocyclic linkers-acceptor. Using UV-vis spectrophotometry, cyclic voltammetry, and density functional theory calculations, optical and electrochemical characteristics of these pyrazine-based photosensitizers were examined and explored in relation to photovoltaic parameters. The effects of the molecular structures of these photosensitizers on the performances of DSSCs were also investigated. The overall conversion efficiencies of DSSCs based on pyrazine-based photosensitizers were 1.31~2.64% under AM 1.5 irradiation of 100 mW/cm2. To confirm the effect of interfacial charge transfer on photovoltaic performances of DSSC based on pyrazine-based photosensitizers, interfacial charge transfer resistances were investigated by electrical impedance spectroscopy (EIS) measurements.
Review on the Status of the Research on Power-to-Gas Experimental Activities
Authors: Barbaresi Andrea , Morini Mirko , Gambarotta Agostino
Published: August 2022

In recent years, power-to-gas technologies have been gaining ground and are increasingly proving their reliability. The possibility of implementing long-term energy storage and that of being able to capture and utilize carbon dioxide are currently too important to be ignored. However, systems of this type are not yet experiencing extensive realization in practice. In this study, an overview of the experimental research projects and the research and development activities that are currently part of the power-to-gas research line is presented. By means of a bibliographical and sitographical analysis, it was possible to identify the characteristics of these projects and their distinctive points. In addition, the main research targets distinguishing these projects are presented. This provides an insight into the research direction in this regard, where a certain technological maturity has been achieved and where there is still work to be done. The projects found and analyzed amount to 87, mostly at laboratory scale. From these, what is most noticeable is that research is currently focusing heavily on improving system efficiency and integration between components.
Allometric, Growth, and Biomass Estimation Models for Acacia dealbata Link.: A Case Study in Serra da Estrela Natural Park (Portugal)
Authors: Nunes Leonel J. R. , Meireles Catarina I. R. , Gomes Carlos J. Pinto , Ribeiro Nuno M. C. Almeida
Published: August 2022

Allometric, growth, and biomass estimation models for the quantification of missing parameters in trees are widely used to estimate the productivity of a stand. However, regarding species with lower economic interest, or exotic invasive species, the creation of these tools did not occur in the same way as for other species, lacking the development of relationships to allow a deeper study of these species. Thus, data were collected in a settlement of Acacia dealbata Link. in Portugal, in an area known for the current infestation of this species. After a bibliographic review, some of the identified models were tested to select those who best fit the characteristics of this stand, which were used to develop relationships that, based on the data collected, would be able to estimate parameters, such as height, volume, or mass. It was found that the models established, at least for the initial 20 years of the life of the trees, followed close to a linear model. However, the model still presents some weaknesses. For being considered an invasive species in Portugal, A. dealbata is frequently controlled, and for this reason it is very difficult to find trees older than 20 years.
Assessing Structural Complexity of Individual Scots Pine Trees by Comparing Terrestrial Laser Scanning and Photogrammetric Point Clouds
Authors: Tienaho Noora , Yrttimaa Tuomas , Kankare Ville , Vastaranta Mikko , Luoma Ville , Honkavaara Eija , Koivumäki Niko , Huuskonen Saija , Hynynen Jari , Holopainen Markus , Hyyppä Juha , Saarinen Ninni
Published: August 2022

Structural complexity of trees is related to various ecological processes and ecosystem services. To support management for complexity, there is a need to assess the level of structural complexity objectively. The fractal-based box dimension (Db) provides a holistic measure of the structural complexity of individual trees. This study aimed to compare the structural complexity of Scots pine (Pinus sylvestris L.) trees assessed with Db that was generated with point cloud data from terrestrial laser scanning (TLS) and aerial imagery acquired with an unmanned aerial vehicle (UAV). UAV imagery was converted into point clouds with structure from motion (SfM) and dense matching techniques. TLS and UAV measured Db-values were found to differ from each other significantly (TLS: 1.51 ± 0.11, UAV: 1.59 ± 0.15). UAV measured Db-values were 5% higher, and the range was wider (TLS: 0.81–1.81, UAV: 0.23–1.88). The divergence between TLS and UAV measurements was found to be explained by the differences in the number and distribution of the points and the differences in the estimated tree heights and number of boxes in the Db-method. The average point density was 15 times higher with TLS than with UAV (TLS: 494,000, UAV 32,000 points/tree), and TLS received more points below the midpoint of tree heights (65% below, 35% above), while UAV did the opposite (22% below, 78% above). Compared to the field measurements, UAV underestimated tree heights more than TLS (TLS: 34 cm, UAV: 54 cm), resulting in more boxes of Db-method being needed (4–64%, depending on the box size). Forest structure (two thinning intensities, three thinning types, and a control group) significantly affected the variation of both TLS and UAV measured Db-values. Still, the divergence between the two approaches remained in all treatments. However, TLS and UAV measured Db-values were consistent, and the correlation between them was 75%.
Quantitative Distribution and Transmission of Tea Plant Necrotic Ring Blotch Virus in Camellia sinensis
Authors: Ren Hengze , Chen Yao , Zhao Fumei , Ding Changqing , Zhang Kexin , Wang Lu , Yang Yajun , Hao Xinyuan , Wang Xinchao
Published: August 2022

Tea plant necrotic ring blotch virus (TPNRBV), which carries four positive-sense single-stranded RNA segments, causes discoloration spots and multiple necrotic ring blotches in tea trees. To understand the distribution and transmission of TPNRBV in tea trees and prevent its spread, a SYBR Green real-time quantitative polymerase chain reaction (RT-qPCR) method for detecting the four virus segments was developed. The limit of detection of RT-qPCR was 3.81, 4.73, 3.58, and 4.64 copies/μL for the four strands of TPNRBV, which was 100-fold more sensitive than conventional PCR for RNA1 detection, 10-fold for RNA2 and RNA3, and 1000-fold for RNA4 detection. Visual observation and RT-qPCR of different tea plant tissues showed that symptomatic mature leaves contained the highest TPNRBV load; the concentrations of the four RNAs in other tissues decreased or were undetectable with increasing distances from symptomatic leaves. TPNRBV did not spread efficiently through seeds, cuttings, or mechanical inoculation, but was transmitted to some tea cultivars, particularly light albinistic varieties such as ‘Zhonghuang 1’ and ‘Huangjinya’, under field conditions. Our TPNRBV detection method is useful for determining the distribution and transmission characteristics of TPNRBV and selecting tissues with the highest viral load for early diagnosis, monitoring, and management of the disease.